Gabriel's Adaptive MA📜 Gabriel's Adaptive MA — Indicator Description
Gabriel's Adaptive Moving Average (GAMA) is a dynamic trend-following indicator that intelligently adjusts its smoothing based on both trend strength and market volatility.
It is designed to provide faster responsiveness during strong moves while maintaining stability during choppy or consolidating periods.
🧠 What it does:
This indicator plots a custom-built, highly dynamic Moving Average that adapts itself intelligently based on:
Trend Strength (via Perry Kaufman's Efficiency Ratio)
Market Volatility (via Tushar Chande's Volatility Ratio)
It reacts faster when the market is trending strongly and/or highly volatile,
and it smooths out and slows down when the market is choppy or calm.
🔍 How it works (step-by-step):
1. User Inputs:
length: (default 14)
How many bars to look back for calculations.
fastSC: Fastest possible smoothing constant (hardcoded as 2 / (2+1))
slowSC: Slowest possible smoothing constant (hardcoded as 2 / (30+1))
(These are used to control how fast/slow the KAMA can react.)
2. Calculate Trendiness — Kaufman Efficiency Ratio (ER):
Net Change = Absolute difference between current close and close from length bars ago.
Sum of Absolute Changes = Sum of absolute price changes between every bar inside the length window.
Efficiency Ratio (ER) = Net Change divided by Sum of Changes.
✅ If ER is close to 1 → Smooth, trending market.
✅ If ER is close to 0 → Choppy, sideways market.
3. Calculate Bumpiness — Volatility Ratio (VR):
Short-Term Volatility = Standard deviation of close over length.
Long-Term Volatility = Standard deviation of close over length * 2.
Volatility Ratio (VR) = Short-Term Volatility divided by Long-Term Volatility.
✅ If VR is >1 → Market is becoming more volatile recently.
✅ If VR is <1 → Market is calming down.
4. Create the Hybrid Alpha:
Multiply ER × VR.
Then square the result (math.pow(..., 2)).
This hybrid alpha decides how aggressive the MA should be based on both trend and volatility.
If ER and VR are both strong → big alpha → fast movement.
If ER and/or VR are weak → small alpha → slow movement.
5. Calculate the Final Adaptive Smoothing Constant (hybridSC):
hybridSC = slowSC + hybridAlpha × (fastSC - slowSC)
This smoothly interpolates between the slowest and fastest smoothing depending on market conditions.
6. Calculate and Plot the Adaptive MA:
The moving average is manually calculated:
hybridMA := na(hybridMA ) ? close : hybridMA + hybridSC * (close - hybridMA )
It behaves like an EMA but with dynamic smoothing, not a fixed alpha.
✅ If hybridSC is high → MA hugs the price closely.
✅ If hybridSC is low → MA stays smooth and resists noise.
Finally, it plots this Adaptive MA on the chart in blue color.
📊 Visual Summary
Market Type What Happens to GAMA
Trending hard + volatile Follows price quickly
Trending hard + calm Follows steadily but carefully
Sideways + volatile Reacts carefully (won't chase noise)
Sideways + calm Smooths heavily (avoids fakeouts)
✨ Main Strengths:
Adapts automatically without you tuning settings manually every time market changes.
Responds smartly to both trend quality (ER) and market energy (VR).
Reduces lag during real moves.
Filters out false signals during choppy mess.
🧪 Key Innovation compared to normal MAs:
Traditional MA Gabriel's Adaptive MA
Same smoothing every bar Dynamic smoothing every bar
Slow during fast moves Adapts fast during real moves
No understanding of volatility or trendiness Full market sensitivity
⚡ **Simple One-Line Description:**
"Gabriel's Adaptive MA is a dynamic, trend-and-volatility-sensitive moving average that intelligently adjusts its speed to match market conditions."
חפש סקריפטים עבור "smart"
Institutional Activity AnalysisThe Institutional Activity Analysis (IAA) indicator is a powerful tool designed to help traders identify potential institutional buying and selling activity in the market. By analyzing volume, price movement, and accumulation/distribution trends, this indicator provides insights into market dynamics that may signal significant activity.
This indicator is not a buy or sell recommendation but rather a tool to assist traders in understanding market behavior. It should be used in conjunction with other technical analysis tools and strategies for a comprehensive trading approach.
Key Features:
Smart Money Flow Index (SMFI):
1). Tracks the flow of "smart money" by analyzing price action relative to volume.
2). Helps identify whether institutional activity is bullish or bearish.
Accumulation/Distribution (Acc/Dist):
1). Measures buying and selling pressure in the market.
2). Indicates whether the market is in an accumulation (buying) or distribution (selling) phase.
Volume Spike Detection:
1. Identifies unusual volume spikes that may signal institutional activity.
2. Highlights these spikes with a yellow circle on the chart.
Significant Price Movement:
1. Detects strong price movements accompanied by high volume.
2. Marks these movements with a green triangle on the chart.
Customizable Dashboard:
1. Displays key metrics such as volume flow, smart money flow, accumulation/distribution, and volatility.
2. Includes visual signals for volume spikes and significant moves.
3. The dashboard can be positioned anywhere on the chart or turned off.
Heatmap for Activity Intensity:
1. Visualizes the intensity of market activity by combining volume and price volatility.
How to Read the Indicator:
Smart Money Flow (SMFI):
1. A positive SMFI value indicates bullish institutional activity.
2. A negative SMFI value suggests bearish institutional activity.
3. The blue line on the indicator represents the smoothed SMFI.
Accumulation/Distribution (Acc/Dist):
1. A positive slope indicates accumulation (buying pressure).
2. A negative slope indicates distribution (selling pressure).
3. The purple line on the indicator shows the smoothed Acc/Dist slope.
Volume Spikes:
1. Yellow circles on the chart indicate unusual volume spikes.
2. These spikes may signal institutional interest or significant market activity.
Significant Price Movements:
1. Green triangles on the chart highlight strong price movements with high volume.
2. These movements may indicate potential breakouts or reversals.
Dashboard:
The dashboard provides a quick summary of key metrics:
1. Volume Flow: Indicates whether volume is above or below the average.
2. Smart Money: Shows whether institutional activity is bullish or bearish.
3. Acc/Dist: Displays whether the market is in accumulation or distribution.
4. Volatility: Provides the current volatility level.
5. Signals: Highlights whether there are volume spikes or significant moves.
How to Use the Indicator:
Identify Institutional Activity:
1. Look for confluences between volume spikes, significant price movements, and the direction of the SMFI and Acc/Dist slope.
2. For example, a volume spike combined with a positive SMFI and accumulation may indicate bullish institutional activity.
Confirm Market Trends:
1. Use the indicator to confirm trends by analyzing the direction of the SMFI and Acc/Dist slope.
2. A rising SMFI and positive Acc/Dist slope suggest a strong uptrend, while the opposite indicates a downtrend.
Monitor Volatility:
1. High volatility combined with volume spikes may signal potential breakouts or reversals.
2. Use the volatility metric on the dashboard to gauge market conditions.
Set Alerts:
1. Use the built-in alert conditions to get notified of volume spikes and significant price movements.
2. Alerts can help you stay informed about potential market opportunities.
Important Notes:
1. This is not a buy or sell recommendation. The IAA indicator is a technical analysis tool designed to provide insights into market activity. Always use it in conjunction with other tools and strategies.
2. The indicator works best when combined with other forms of analysis, such as support/resistance levels, trendlines, and candlestick patterns.
3. Past performance is not indicative of future results. Always practice proper risk management and trade responsibly.
Customization:
The indicator includes several customizable settings:
1. Volume Spike Threshold: Adjust the sensitivity for detecting volume spikes.
2. Smoothing Period: Change the period for calculating SMFI and Acc/Dist.
3. Price Movement Threshold: Modify the sensitivity for detecting significant price movements.
4. Dashboard Position: Move the dashboard to any corner of the chart or turn it off.
5. Visual Settings: Customize the colors and transparency of the dashboard and signals.
Example Use Case:
Imagine you're analyzing a stock that has been consolidating for several days. Suddenly, the IAA indicator detects:
1. A volume spike (yellow circle),
2. A significant price movement (green triangle),
3. A positive SMFI (bullish smart money flow),
4. And an accumulation phase (positive Acc/Dist slope).
This confluence of signals may indicate that institutional buyers are entering the market, potentially leading to a breakout. You can then use this information to plan your trade, such as setting alerts or monitoring for confirmation from other indicators.
Disclaimer:
The Institutional Activity Analysis (IAA) indicator is for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any security. Always conduct your own research and consult with a financial advisor before making trading decisions. Use this tool responsibly and at your own risk.
Uptrick: Acceleration ShiftsIntroduction
Uptrick: Acceleration Shifts is designed to measure and visualize price momentum shifts by focusing on acceleration —the rate of change in velocity over time. It uses various moving average techniques as a trend filter, providing traders with a clearer perspective on market direction and potential trade entries or exits.
Purpose
The main goal of this indicator is to spot strong momentum changes (accelerations) and confirm them with a chosen trend filter. It attempts to distinguish genuine market moves from noise, helping traders make more informed decisions. The script can also trigger multiple entries (smart pyramiding) within the same trend, if desired.
Overview
By measuring how quickly price velocity changes (acceleration) and comparing it against a smoothed average of itself, this script generates buy or sell signals once the acceleration surpasses a given threshold. A trend filter is added for further validation. Users can choose from multiple smoothing methods and color schemes, and they can optionally enable a small table that displays real-time acceleration values.
Originality and Uniqueness
This script offers an acceleration-based approach, backed by several different moving average choices. The blend of acceleration thresholds, a trend filter, and an optional extra-entry (pyramiding) feature provides a flexible toolkit for various trading styles. The inclusion of multiple color themes and a slope-based coloring of the trend line adds clarity and user customization.
Inputs & Features
1. Acceleration Length (length)
This input determines the number of bars used when calculating velocity. Specifically, the script computes velocity by taking the difference in closing prices over length bars, and then calculates acceleration based on how that velocity changes over an additional length. The default is 14.
2. Trend Filter Length (smoothing)
This sets the lookback period for the chosen trend filter method. The default of 50 results in a moderately smooth trend line. A higher smoothing value will create a slower-moving trend filter.
3. Acceleration Threshold (threshold)
This multiplier determines when acceleration is considered strong enough to trigger a main buy or sell signal. A default value of 2.5 means the current acceleration must exceed 2.5 times the average acceleration before signaling.
4. Smart Pyramiding Strength (pyramidingThreshold)
This lower threshold is used for additional (pyramiding) entries once the main trend has already been identified. For instance, if set to 0.5, the script looks for acceleration crossing ±0.5 times its average acceleration to add extra positions.
5. Max Pyramiding Entries (maxPyramidingEntries)
This sets a limit on how many extra positions can be opened (beyond the first main signal) in a single directional trend. The default of 3 ensures traders do not become overexposed.
6. Show Acceleration Table (showTable)
When enabled, a small table displaying the current acceleration and its average is added to the top-right corner of the chart. This table helps monitor real-time momentum changes.
7. Smart Pyramiding (enablePyramiding)
This toggle decides whether additional entries (buy or sell) will be generated once a main signal is active. If enabled, these extra signals act as filtered entries, only firing when acceleration re-crosses a smaller threshold (pyramidingThreshold). These signals have a '+' next to their signal on the label.
8. Select Color Scheme (selectedColorScheme)
Allows choosing between various pre-coded color themes, such as Default, Emerald, Sapphire, Golden Blaze, Mystic, Monochrome, Pastel, Vibrant, Earth, or Neon. Each theme applies a distinct pair of colors for bullish and bearish conditions.
9. Trend Filter (TrendFilter)
Lets the user pick one of several moving average approaches to determine the prevailing trend. The options include:
Short Term (TEMA)
EWMA
Medium Term (HMA)
Classic (SMA)
Quick Reaction (DEMA)
Each method behaves differently, balancing reactivity and smoothness.
10. Slope Lookback (slopeOffset)
Used to measure the slope of the trend filter over a set number of bars (default is 10). This slope then influences the coloring of the trend filter line, indicating bullish or bearish tilt.
Note: The script refers to this as the "Massive Slope Index," but it effectively serves as a Trend Slope Calculation, measuring how the chosen trend filter changes over a specified period.
11. Alerts for Buy/Sell and Pyramiding Signals
The script includes built-in alert conditions that can be enabled or configured. These alerts trigger whenever the script detects a main Buy or Sell signal, as well as extra (pyramiding) signals if Smart Pyramiding is active. This feature allows traders to receive immediate notifications or automate a trading response.
Calculation Methodology
1. Velocity and Acceleration
Velocity is derived by subtracting the closing price from its value length bars ago. Acceleration is the difference in velocity over an additional length period. This highlights how quickly momentum is shifting.
2. Average Acceleration
The script smooths raw acceleration with a simple moving average (SMA) using the smoothing input. Comparing current acceleration against this average provides a threshold-based signal mechanism.
3. Trend Filter
Users can pick one of five moving average types to form a trend baseline. These range from quick-reacting methods (DEMA, TEMA) to smoother options (SMA, HMA, EWMA). The script checks whether the price is above or below this filter to confirm trend direction.
4. Buy/Sell Logic
A buy occurs when acceleration surpasses avgAcceleration * threshold and price closes above the trend filter. A sell occurs under the opposite conditions. An additional overbought/oversold check (based on a longer SMA) refines these signals further.
When price is considered oversold (i.e., close is below a longer-term SMA), a bullish acceleration signal has a higher likelihood of success because it indicates that the market is attempting to reverse from a lower price region. Conversely, when price is considered overbought (close is above this longer-term SMA), a bearish acceleration signal is more likely to be valid. This helps reduce false signals by waiting until the market is extended enough that a reversal or continuation has a stronger chance of following through.
5. Smart Pyramiding
Once a main buy or sell signal is triggered, additional (filtered) entries can be taken if acceleration crosses a smaller multiplier (pyramidingThreshold). This helps traders scale into strong moves. The script enforces a cap (maxPyramidingEntries) to limit risk.
6. Visual Elements
Candles can be recolored based on the active signal. Labels appear on the chart whenever a main or pyramiding entry signal is triggered. An optional table can show real-time acceleration values.
Color Schemes
The script includes a variety of predefined color themes. For bullish conditions, it might use turquoise or green, and for bearish conditions, magenta or red—depending on which color scheme the user selects. Each scheme aims to provide clear visual differentiation between bullish and bearish market states.
Why Each Indicator Was Part of This Component
Acceleration is employed to detect swift changes in momentum, capturing shifts that may not yet appear in more traditional measures. To further adapt to different trading styles and market conditions, several moving average methods are incorporated:
• TEMA (Triple Exponential Moving Average) is chosen for its ability to reduce lag more effectively than a standard EMA while still reacting swiftly to price changes. Its construction layers exponential smoothing in a way that can highlight sudden momentum shifts without sacrificing too much smoothness.
• DEMA (Double Exponential Moving Average) provides a faster response than a single EMA by using two layers of exponential smoothing. It is slightly less smoothed than TEMA but can alert traders to momentum changes earlier, though with a higher risk of noise in choppier markets.
• HMA (Hull Moving Average) is known for its balance of smoothness and reduced lag. Its weighted calculations help track trend direction clearly, making it useful for traders who want a smoother line that still reacts fairly quickly.
• SMA (Simple Moving Average) is the classic baseline for smoothing price data. It offers a clear, stable perspective on long-term trends, though it reacts more slowly than other methods. Its simplicity can be beneficial in lower-volatility or more stable market environments.
• EWMA (Exponentially Weighted Moving Average) provides a middle ground by emphasizing recent price data while still retaining some degree of smoothing. It typically responds faster than an SMA but is less aggressive than DEMA or TEMA.
Alongside these moving average techniques, the script employs a slope calculation (referred to as the “Massive Slope Index”) to visually indicate whether the chosen filter is sloping upward or downward. This adds an extra layer of clarity to directional analysis. The indicator also uses overbought/oversold checks, based on a longer-term SMA, to help filter out signals in overstretched markets—reducing the likelihood of false entries in conditions where the price is already extensively extended.
Additional Features
Alerts can be set up for both main signals and additional pyramiding signals, which is helpful for automated or semi-automated trading. The optional acceleration table offers quick reference values, making momentum monitoring more intuitive. Including explicit alert conditions for Buy/Sell and Pyramiding ensures traders can respond promptly to market movements or integrate these triggers into automated strategies.
Summary
This script serves as a comprehensive momentum-based trading framework, leveraging acceleration metrics and multiple moving average filters to identify potential shifts in market direction. By combining overbought/oversold checks with threshold-based triggers, it aims to reduce the noise that commonly plagues purely reactive indicators. The flexibility of Smart Pyramiding, customizable color schemes, and built-in alerts allows users to tailor their experience and respond swiftly to valid signals, potentially enhancing trading decisions across various market conditions.
Disclaimer
All trading involves significant risk, and users should apply their own judgment, risk management, and broader analysis before making investment decisions.
Celestial Pair Spread Hello friends, after a very long time!
Today, I tried to put into code an idea that came to my mind spontaneously and suddenly.
Note :
This script is experimental and improvable.
I haven't had a chance to try it yet.
TIMEFRAME : 1D (Daily Bars)
CELESTIAL SPREAD
The spread moves in a very limited area and is consistent within itself, especially on days far from the end of the contract.
That's why there is a reassuring sky atmosphere. That's why this name was given completely improvised.
Basic logic of the script
We enter the name of the CME Futures contract we want to enter:
Ex : CL1! , ES1! , ZC1! , NQ1!
The script creates us a pair trade parity divided into secondary contracts.
Example : ES1!/ES2!
What is pair trading?
I will explain briefly here.
For users who are wondering:
www.investopedia.com
Let's get back to our topic.
Now we have created a parity that does not actually exist.
This parity is the manifestation of the relative movements of two contracts.
When the parity rises, ES1! increased,ES2! has fallen.
In the opposite case, We can say: ES1! Contract has been dropped ES2! has increased.
Pair trading is generally a trade that needs to be kept in mind from time to time.
It is a method preferred by professionals who can process very quickly.
Market risk is minimal, but since 2 contracts are purchased, more money is paid and very low percentage profits are made.
It is very expensive to do pair trading, especially with oil and its derivatives and interest security derivatives.
The contract we are considering has micros. (small-item contracts tied to the same value)
So when we switch to our broker MES1!/MES2! We will trade.
For all CME futures :
www.cmegroup.com
Anyway, let's continue:
The script created the parity showing its relationship with the next contract and plotted it as bars.
Celestial bands are just like Bollinger bands, but they consist of 3 bands based on percentage changes rather than standard deviation.
The middle band is obtained from moving averages.
The upper and lower bands are the middle band subjected to a threshold value.
The threshold value can be changed.
0.15 percent was charged for this script.
CAUTION :
As can be seen in the example below;
The most important thing is not to make any transactions when the contract switch dates are approaching.
Therefore, it is recommended to use it just below the main chart.
The blue bars in the parity are
Values that outside the upper and lower threshold values are colored blue.
For this condition
Alerts has been added.
Don't forget to add alert and edit.
MAIN PURPOSE
It is aimed to start a pair trade when such conditions come and to quickly close the trades when the parity basis reaches the value.
OTHER IMPORTANT POINTS
Other issues are broker related issues.
Difference between initial margins and maintanence margins of contracts (between 1! and 2!)
It shouldn't be too high.
The commission should not be too high.
Leverage must be high because the profit percentage is very low.
To calculate leverage you must divide your contract size by the relevant margin requirement.
Sample margin requirement table:
www.interactivebrokers.com
RISKS
It is an experimental and intellectual script,
the risk of contract price differences (maybe it will not leave a profit except for very extreme values)
I remind you of the quickness risk that comes from a two-legged trade.
Alerts definitely synchronized with an audible alert sent to a smartphone as an e-mail notification and displayed on the locked screen for quick action.
Best regards!
MMXM ICT [TradingFinder] Market Maker Model PO3 CHoCH/CSID + FVG🔵 Introduction
The MMXM Smart Money Reversal leverages key metrics such as SMT Divergence, Liquidity Sweep, HTF PD Array, Market Structure Shift (MSS) or (ChoCh), CISD, and Fair Value Gap (FVG) to identify critical turning points in the market. Designed for traders aiming to analyze the behavior of major market participants, this setup pinpoints strategic areas for making informed trading decisions.
The document introduces the MMXM model, a trading strategy that identifies market maker activity to predict price movements. The model operates across five distinct stages: original consolidation, price run, smart money reversal, accumulation/distribution, and completion. This systematic approach allows traders to differentiate between buyside and sellside curves, offering a structured framework for interpreting price action.
Market makers play a pivotal role in facilitating these movements by bridging liquidity gaps. They continuously quote bid (buy) and ask (sell) prices for assets, ensuring smooth trading conditions.
By maintaining liquidity, market makers prevent scenarios where buyers are left without sellers and vice versa, making their activity a cornerstone of the MMXM strategy.
SMT Divergence serves as the first signal of a potential trend reversal, arising from discrepancies between the movements of related assets or indices. This divergence is detected when two or more highly correlated assets or indices move in opposite directions, signaling a likely shift in market trends.
Liquidity Sweep occurs when the market targets liquidity in specific zones through false price movements. This process allows major market participants to execute their orders efficiently by collecting the necessary liquidity to enter or exit positions.
The HTF PD Array refers to premium and discount zones on higher timeframes. These zones highlight price levels where the market is in a premium (ideal for selling) or discount (ideal for buying). These areas are identified based on higher timeframe market behavior and guide traders toward lucrative opportunities.
Market Structure Shift (MSS), also referred to as ChoCh, indicates a change in market structure, often marked by breaking key support or resistance levels. This shift confirms the directional movement of the market, signaling the start of a new trend.
CISD (Change in State of Delivery) reflects a transition in price delivery mechanisms. Typically occurring after MSS, CISD confirms the continuation of price movement in the new direction.
Fair Value Gap (FVG) represents zones where price imbalance exists between buyers and sellers. These gaps often act as price targets for filling, offering traders opportunities for entry or exit.
By combining all these metrics, the Smart Money Reversal provides a comprehensive tool for analyzing market behavior and identifying key trading opportunities. It enables traders to anticipate the actions of major players and align their strategies accordingly.
MMBM :
MMSM :
🔵 How to Use
The Smart Money Reversal operates in two primary states: MMBM (Market Maker Buy Model) and MMSM (Market Maker Sell Model). Each state highlights critical structural changes in market trends, focusing on liquidity behavior and price reactions at key levels to offer precise and effective trading opportunities.
The MMXM model expands on this by identifying five distinct stages of market behavior: original consolidation, price run, smart money reversal, accumulation/distribution, and completion. These stages provide traders with a detailed roadmap for interpreting price action and anticipating market maker activity.
🟣 Market Maker Buy Model
In the MMBM state, the market transitions from a bearish trend to a bullish trend. Initially, SMT Divergence between related assets or indices reveals weaknesses in the bearish trend. Subsequently, a Liquidity Sweep collects liquidity from lower levels through false breakouts.
After this, the price reacts to discount zones identified in the HTF PD Array, where major market participants often execute buy orders. The market confirms the bullish trend with a Market Structure Shift (MSS) and a change in price delivery state (CISD). During this phase, an FVG emerges as a key trading opportunity. Traders can open long positions upon a pullback to this FVG zone, capitalizing on the bullish continuation.
🟣 Market Maker Sell Model
In the MMSM state, the market shifts from a bullish trend to a bearish trend. Here, SMT Divergence highlights weaknesses in the bullish trend. A Liquidity Sweep then gathers liquidity from higher levels.
The price reacts to premium zones identified in the HTF PD Array, where major sellers enter the market and reverse the price direction. A Market Structure Shift (MSS) and a change in delivery state (CISD) confirm the bearish trend. The FVG then acts as a target for the price. Traders can initiate short positions upon a pullback to this FVG zone, profiting from the bearish continuation.
Market makers actively bridge liquidity gaps throughout these stages, quoting continuous bid and ask prices for assets. This ensures that trades are executed seamlessly, even during periods of low market participation, and supports the structured progression of the MMXM model.
The price’s reaction to FVG zones in both states provides traders with opportunities to reduce risk and enhance precision. These pullbacks to FVG zones not only represent optimal entry points but also create avenues for maximizing returns with minimal risk.
🔵 Settings
Higher TimeFrame PD Array : Selects the timeframe for identifying premium/discount arrays on higher timeframes.
PD Array Period : Specifies the number of candles for identifying key swing points.
ATR Coefficient Threshold : Defines the threshold for acceptable volatility based on ATR.
Max Swing Back Method : Choose between analyzing all swings ("All") or a fixed number ("Custom").
Max Swing Back : Sets the maximum number of candles to consider for swing analysis (if "Custom" is selected).
Second Symbol for SMT : Specifies the second asset or index for detecting SMT divergence.
SMT Fractal Periods : Sets the number of candles required to identify SMT fractals.
FVG Validity Period : Defines the validity duration for FVG zones.
MSS Validity Period : Sets the validity duration for MSS zones.
FVG Filter : Activates filtering for FVG zones based on width.
FVG Filter Type : Selects the filtering level from "Very Aggressive" to "Very Defensive."
Mitigation Level FVG : Determines the level within the FVG zone (proximal, 50%, or distal) that price reacts to.
Demand FVG : Enables the display of demand FVG zones.
Supply FVG : Enables the display of supply FVG zones.
Zone Colors : Allows customization of colors for demand and supply FVG zones.
Bottom Line & Label : Enables or disables the SMT divergence line and label from the bottom.
Top Line & Label : Enables or disables the SMT divergence line and label from the top.
Show All HTF Levels : Displays all premium/discount levels on higher timeframes.
High/Low Levels : Activates the display of high/low levels.
Color Options : Customizes the colors for high/low lines and labels.
Show All MSS Levels : Enables display of all MSS zones.
High/Low MSS Levels : Activates the display of high/low MSS levels.
Color Options : Customizes the colors for MSS lines and labels.
🔵 Conclusion
The Smart Money Reversal model represents one of the most advanced tools for technical analysis, enabling traders to identify critical market turning points. By leveraging metrics such as SMT Divergence, Liquidity Sweep, HTF PD Array, MSS, CISD, and FVG, traders can predict future price movements with precision.
The price’s interaction with key zones such as PD Array and FVG, combined with pullbacks to imbalance areas, offers exceptional opportunities with favorable risk-to-reward ratios. This approach empowers traders to analyze the behavior of major market participants and adopt professional strategies for entry and exit.
By employing this analytical framework, traders can reduce errors, make more informed decisions, and capitalize on profitable opportunities. The Smart Money Reversal focuses on liquidity behavior and structural changes, making it an indispensable tool for financial market success.
Bitcoin Cycle High/Low with functional Alert [heswaikcrypt]Introduction
Just as machines are fine-tuned for maximum efficiency, trading indicators must evolve to meet the demands of ever-changing markets.
Credit goes to the initial author, @NoCreditsLeft I only improved the existing Pi-cycle indicator with a functional alert and included a bull mode indicator in the script. The alert can help you get a live alert at candle close when the cycle tops, bottoms, and the potential bull phase switch occurs.
Philip Swift’s Pi Cycle Top Indicator is a brilliant example of leveraging mathematical relationships to signal critical turning points in Bitcoin’s price cycles. Historically, it has identified market and local tops with some relative accuracy, often within three days, as demonstrated in all the previous bull run cycles.
At its core, the Pi Cycle Indicator derives its name from the mathematical constant π (pi), achieved by using simple moving averages (MAs) in a specific ratio: 𝜋 = Long MA/short MA
The Bull mode switch is calculated using a crossover of the short exponentia moving average and the long moving average.
.
.
.
Knowing when Bitcoin reaches its top—and receiving timely alerts about it—is crucial for successful trading. The indicator is designed to signal;
Potential Bitcoin tops: Purple label
Potential Bitcoin bottoms : green Label, and
Parabolic swing : Yellow diamond shape (relating to the market switching to a potential bull mode)
"Please note: This indicator is tailored for Bitcoin using historical data analysis and should not be considered definitive. However accurate it might be."
Setting alerts
To set the alert conditions, select any alert function call to get alert whenever the conditions are met. The script is configured on dialy TF; you can set it on 1D or weekly TF.
Enjoy and Trade smartly
ICT Power Of Three | Flux Charts💎 GENERAL OVERVIEW
Introducing our new ICT Power Of Three Indicator! This indicator is built around the ICT's "Power Of Three" strategy. This strategy makes use of these 3 key smart money concepts : Accumulation, Manipulation and Distribution. Each step is explained in detail within this write-up. For more information about the process, check the "HOW DOES IT WORK" section.
Features of the new ICT Power Of Three Indicator :
Implementation of ICT's Power Of Three Strategy
Different Algorithm Modes
Customizable Execution Settings
Customizable Backtesting Dashboard
Alerts for Buy, Sell, TP & SL Signals
📌 HOW DOES IT WORK ?
The "Power Of Three" comes from these three keywords "Accumulation, Manipulation and Distribution". Here is a brief explanation of each keyword :
Accumulation -> Accumulation phase is when the smart money accumulate their positions in a fixed range. This phase indicates price stability, generally meaning that the price constantly switches between up & down trend between a low and a high pivot point. When the indicator detects an accumulation zone, the Power Of Three strategy begins.
Manipulation -> When the smart money needs to increase their position sizes, they need retail traders' positions for liquidity. So, they manipulate the market into the opposite direction of their intended direction. This will result in retail traders opening positions the way that the smart money intended them to do, creating liquidity. After this step, the real move that the smart money intended begins.
Distribution -> This is when the real intention of the smart money comes into action. With the new liquidity thanks to the manipulation phase, the smart money add their positions towards the opposite direction of the retail mindset. The purpose of this indicator is to detect the accumulation and manipulation phases, and help the trader move towards the same direction as the smart money for their trades.
Detection Methods Of The Indicator :
Accumulation -> The indicator detects accumulation zones as explained step-by-step :
1. Draw two lines from the lowest point and the highest point of the latest X bars.
2. If the (high line - low line) is lower than Average True Range (ATR) * accumulationConstant
3. After the condition is validated, an accumulation zone is detected. The accumulation zone will be invalidated and manipulation phase will begin when the range is broken.
Manipulation -> If the accumulation range is broken, check if the current bar closes / wicks above the (high line + ATR * manipulationConstant) or below the (low line - ATR * manipulationConstant). If the condition is met, the indicator detects a manipulation zone.
Distribution -> The purpose of this indicator is to try to foresee the distribution zone, so instead of a detection, after the manipulation zone is detected the indicator automatically create a "shadow" distribution zone towards the opposite direction of the freshly detected manipulation zone. This shadow distribution zone comes with a take-profit and stop-loss layout, customizable by the trader in the settings.
The X bars, accumulationConstant and manipulationConstant are subject to change with the "Algorithm Mode" setting. Read the "Settings" section for more information.
This indicator follows these steps and inform you step by step by plotting them in your chart.
🚩UNIQUENESS
This indicator is an all-in-one suite for the ICT's Power Of Three concept. It's capable of plotting the strategy, giving signals, a backtesting dashboard and alerts feature. Different and customizable algorithm modes will help the trader fine-tune the indicator for the asset they are currently trading. The backtesting dashboard allows you to see how your settings perform in the current ticker. You can also set up alerts to get informed when the strategy is executable for different tickers.
⚙️SETTINGS
1. General Configuration
Algorithm Mode -> The indicator offers 3 different detection algorithm modes according to your needs. Here is the explanation of each mode.
a) Small Manipulation
This mode has the default bar length for the accumulation detection, but a lower manipulation constant, meaning that slighter imbalances in the price action can be detected as manipulation. This setting can be useful on tickers that have lower liquidity, thus can be manipulated easier.
b) Big Manipulation
This mode has the default bar length for the accumulation detection, but a higher manipulation constant, meaning that heavier imbalances on the price action are required in order to detect manipulation zones. This setting can be useful on tickers that have higher liquidity, thus can be manipulated harder.
c) Short Accumulation
This mode has a ~70% lower bar length requirement for accumulation zone detection, and the default manipulation constant. This setting can be useful on tickers that are highly volatile and do not enter accumulation phases too often.
Breakout Method -> If "Close" is selected, bar close price will be taken into calculation when Accumulation & Manipulation zone invalidation. If "Wick" is selected, a wick will be enough to validate the corresponding zone.
2. TP / SL
TP / SL Method -> If "Fixed" is selected, you can adjust the TP / SL ratios from the settings below. If "Dynamic" is selected, the TP / SL zones will be auto-determined by the algorithm.
Risk -> The risk you're willing to take if "Dynamic" TP / SL Method is selected. Higher risk usually means a better winrate at the cost of losing more if the strategy fails. This setting is has a crucial effect on the performance of the indicator, as different tickers may have different volatility so the indicator may have increased performance when this setting is correctly adjusted.
3. Visuals
Show Zones -> Enables / Disables rendering of Accumulation (yellow) and Manipulation (red) zones.
Liquidity-Finder ICT / SMCIn the context of ICT and the Smart Money Concept, liquidity is likely viewed as a crucial factor for determining the strength and sustainability of a market move. Smart Money is often associated with large institutional traders who have the ability to influence liquidity.
Liquidity Sweep:
A liquidity sweep in this context might involve Smart Money intentionally executing trades across various price levels to assess market depth and liquidity. This information can be used to identify potential areas of interest for Smart Money to initiate or exit positions without causing significant price disruptions.
Stop Hunt:
Stop hunting is a concept that Smart Money traders may employ to deliberately trigger stop orders in the market. By doing so, they can create temporary price movements that allow them to accumulate or liquidate positions at more favorable prices before the market reacts.
Smart Money Concept (SMC):
The Smart Money Concept revolves around the idea that large institutional traders (Smart Money) have superior information and resources compared to retail traders. Understanding the behavior of Smart Money, as taught in ICT and SMC, involves analyzing market dynamics, order flow, and liquidity to make more informed trading decisions.
Liquidating:
Liquidating refers to the process of selling or closing out existing positions. In the context of Smart Money, the term could imply that institutional traders are actively managing their positions, either taking profits or cutting losses strategically based on their analysis of market conditions.
The Indicator
The Indicator show open liquidity as solid lines and liquidates liquidity as dashed lines
Is able to send alerts for liquidity level was liquidated, liquidity level was dipped or the next close is on the other side
ATR VisualizerAdvance Your Market Analysis with the True Range Indicator
The True Range Indicator is a sophisticated screener meticulously developed to bolster your trading execution by presenting an exceptional understanding of the market direction. The centerpiece of this instrument is a distinctive candle configuration depicting the Average True Range (ATR) and the Bear/Bull range. However, it traverses beyond the conventional channels to offer specific market settings to boost your trading decisions.
User-Defined Settings
Broadly, the indicator offers five dynamic settings:
Bear/Bull Range
The Bear/Bull Range outlines the ATR for each candle type - bearish and bullish - and then smartly opts for the pertinent one based on the prevalent market circumstances. This feature aids in comparing the range of bullish and bearish candlesticks, which deepens your understanding of the price action and volatility.
Bearish Range
The Bearish Range isolates and computes the ATR for bearish candles solely. Utilizing this option spots the bear-dominated periods and provides insights about potential market reversals or downward continuations.
Bullish Range
Opposite to the Bearish Range, the Bullish Range setting tabulates the ATR exclusively for bullish candles. It assists in tracking the periods when bulls control, enlightening traders about the possibility of upward continuations or trend reversals.
Average Range
The Average Range provides an unbiased measure of range without prioritizing either bull or bear trends. This model is ideal for traders looking for a holistic interpretation of market behavior, regardless of direction.
Cumulative Average Range
Equally significant is the Cumulative Average Range which calculates the aggregate moving average of the true ranges for an expressed period. This setting is extremely valuable when evaluating the long-term volatility and spotting potential breakouts.
Dual Candle Configuration
Going a step ahead, the True Range Indicator uniquely offers the possibility to incorporate more than one candle estimate on your screen. This ensures simultaneous analysis of multiple market dynamics, thereby enhancing your trading precision multifold.
Concluding Thoughts
In essence, the True Range Indicator is an indispensable companion for traders looking to not only leverage market volatility but also make educated predictions. Equipped with an array of insightful market settings and the ability to display dual candle estimates on-screen, you can customize the functionality to suit your unique trading style and magnify your market performance dramatically.
OSPL Volume [Community Edition]NSE:BANKNIFTY1!
This indicator is based on the concepts popularized by @OptionsScalper123 "Siva" of OiPulse. His ideology Is that large moves come after high volume candles. For Nifty, high volume is considered to be a candle above 125k volume and for BankNifty it’s 50k.
This indicator allows you to cut the noise and focus only on the high volume candle. It shows high volume candle in a brighter shade and lower volume candles in a less visible shade.
You can set the minimum volume threshold limit for Nifty and BankNifty. The indicator smartly recognizes which index you are using it in and uses the respective threshold volume limit.
All colors are customizable.
Thanks for Siva for all the ideas and wonderful products he has given to the community
Thanks to all the wonderful Pinescipters for developing awesome indicators and keeping the source open.
The source code of this indicator is just a few lines. Hope you can use it in your projects and learn something from this just how I learned from other scripts.
Any changes or updates needed in this indicator, please suggest. I was thinking some kind of alerts can be added when volume crosses the threshold. Let me know.
Boost/like this indicator and comment if you find this useful. Cheers and happy trading!!!
Price alertThis indicator is an indicator for setting alerts.
Set alerts after adding them to the chart.
By setting an alert, you can notify the closing price to your smartphone or smartwatch.
Premium Money Flow Oscillator [NeuraAlgo]Premium Money Flow Oscillator (PMFO) — NeuraAlgo
The Premium Money Flow Oscillator (PMFO) is an advanced volume-weighted momentum engine designed to reveal true capital flow, not just price movement.
It combines multi-layer smoothing, zero-lag correction, and dynamic normalization to deliver a clean, responsive, and noise-resistant money flow signal suitable for both scalping and swing trading.
Unlike traditional oscillators, PMFO focuses on pressure behind price — showing when smart money accumulation or distribution is actively occurring.
🔹 Core Features
Volume-Weighted Money Flow
Measures real buying and selling pressure using price displacement × volume.
Filters out weak price moves with low participation.
Multi-Layer Smoothing Engine
EMA + SMA hybrid base smoothing
Gaussian noise reduction
Zero-Lag correction
Deep & Super smoothing layers
→ Result: ultra-smooth yet fast reaction to momentum shifts.
Dynamic Normalization
Automatically adapts to volatility.
Keeps signals consistent across all markets and timeframes.
🔹 Smart Zones & Visual Intelligence
Dynamic Overbought / Oversold Zones
Zones strengthen visually as momentum increases.
Strong zones highlight extreme institutional pressure.
Adaptive Gradient Coloring
Color intensity reflects money flow strength.
Instantly see dominance without reading numbers.
Background Pulse
Subtle market bias feedback (bullish / bearish pressure).
🔹 Multi-Timeframe Confirmation
Optional Higher Timeframe Money Flow Confirmation
Align lower-timeframe entries with higher-timeframe capital direction.
Ideal for trend validation and false-signal reduction.
🔹 Professional Dashboard
Live Money Flow Value
Market Flow State
Strength Percentage
MTF Trend Bias
Institutional-style status readout designed for quick decision making.
🔹 Best Use Cases
✔ Trend confirmation
✔ Momentum continuation entries
✔ Reversal exhaustion detection
✔ Divergence analysis
✔ Smart money flow tracking
⚠️ Notes
PMFO works best when combined with price structure, support/resistance, or trend context.
Extreme readings indicate pressure, not immediate reversal — always wait for confirmation.
Designed for traders who want clarity, not clutter.
Built for precision, not lag.
Adaptive Market Wave TheoryAdaptive Market Wave Theory
🌊 CORE INNOVATION: PROBABILISTIC PHASE DETECTION WITH MULTI-AGENT CONSENSUS
Adaptive Market Wave Theory (AMWT) represents a fundamental paradigm shift in how traders approach market phase identification. Rather than counting waves subjectively or drawing static breakout levels, AMWT treats the market as a hidden state machine —using Hidden Markov Models, multi-agent consensus systems, and reinforcement learning algorithms to quantify what traditional methods leave to interpretation.
The Wave Analysis Problem:
Traditional wave counting methodologies (Elliott Wave, harmonic patterns, ABC corrections) share fatal weaknesses that AMWT directly addresses:
1. Non-Falsifiability : Invalid wave counts can always be "recounted" or "adjusted." If your Wave 3 fails, it becomes "Wave 3 of a larger degree" or "actually Wave C." There's no objective failure condition.
2. Observer Bias : Two expert wave analysts examining the same chart routinely reach different conclusions. This isn't a feature—it's a fundamental methodology flaw.
3. No Confidence Measure : Traditional analysis says "This IS Wave 3." But with what probability? 51%? 95%? The binary nature prevents proper position sizing and risk management.
4. Static Rules : Fixed Fibonacci ratios and wave guidelines cannot adapt to changing market regimes. What worked in 2019 may fail in 2024.
5. No Accountability : Wave methodologies rarely track their own performance. There's no feedback loop to improve.
The AMWT Solution:
AMWT addresses each limitation through rigorous mathematical frameworks borrowed from speech recognition, machine learning, and reinforcement learning:
• Non-Falsifiability → Hard Invalidation : Wave hypotheses die permanently when price violates calculated invalidation levels. No recounting allowed.
• Observer Bias → Multi-Agent Consensus : Three independent analytical agents must agree. Single-methodology bias is eliminated.
• No Confidence → Probabilistic States : Every market state has a calculated probability from Hidden Markov Model inference. "72% probability of impulse state" replaces "This is Wave 3."
• Static Rules → Adaptive Learning : Thompson Sampling multi-armed bandits learn which agents perform best in current conditions. The system adapts in real-time.
• No Accountability → Performance Tracking : Comprehensive statistics track every signal's outcome. The system knows its own performance.
The Core Insight:
"Traditional wave analysis asks 'What count is this?' AMWT asks 'What is the probability we are in an impulsive state, with what confidence, confirmed by how many independent methodologies, and anchored to what liquidity event?'"
🔬 THEORETICAL FOUNDATION: HIDDEN MARKOV MODELS
Why Hidden Markov Models?
Markets exist in hidden states that we cannot directly observe—only their effects on price are visible. When the market is in an "impulse up" state, we see rising prices, expanding volume, and trending indicators. But we don't observe the state itself—we infer it from observables.
This is precisely the problem Hidden Markov Models (HMMs) solve. Originally developed for speech recognition (inferring words from sound waves), HMMs excel at estimating hidden states from noisy observations.
HMM Components:
1. Hidden States (S) : The unobservable market conditions
2. Observations (O) : What we can measure (price, volume, indicators)
3. Transition Matrix (A) : Probability of moving between states
4. Emission Matrix (B) : Probability of observations given each state
5. Initial Distribution (π) : Starting state probabilities
AMWT's Six Market States:
State 0: IMPULSE_UP
• Definition: Strong bullish momentum with high participation
• Observable Signatures: Rising prices, expanding volume, RSI >60, price above upper Bollinger Band, MACD histogram positive and rising
• Typical Duration: 5-20 bars depending on timeframe
• What It Means: Institutional buying pressure, trend acceleration phase
State 1: IMPULSE_DN
• Definition: Strong bearish momentum with high participation
• Observable Signatures: Falling prices, expanding volume, RSI <40, price below lower Bollinger Band, MACD histogram negative and falling
• Typical Duration: 5-20 bars (often shorter than bullish impulses—markets fall faster)
• What It Means: Institutional selling pressure, panic or distribution acceleration
State 2: CORRECTION
• Definition: Counter-trend consolidation with declining momentum
• Observable Signatures: Sideways or mild counter-trend movement, contracting volume, RSI returning toward 50, Bollinger Bands narrowing
• Typical Duration: 8-30 bars
• What It Means: Profit-taking, digestion of prior move, potential accumulation for next leg
State 3: ACCUMULATION
• Definition: Base-building near lows where informed participants absorb supply
• Observable Signatures: Price near recent lows but not making new lows, volume spikes on up bars, RSI showing positive divergence, tight range
• Typical Duration: 15-50 bars
• What It Means: Smart money buying from weak hands, preparing for markup phase
State 4: DISTRIBUTION
• Definition: Top-forming near highs where informed participants distribute holdings
• Observable Signatures: Price near recent highs but struggling to advance, volume spikes on down bars, RSI showing negative divergence, widening range
• Typical Duration: 15-50 bars
• What It Means: Smart money selling to late buyers, preparing for markdown phase
State 5: TRANSITION
• Definition: Regime change period with mixed signals and elevated uncertainty
• Observable Signatures: Conflicting indicators, whipsaw price action, no clear momentum, high volatility without direction
• Typical Duration: 5-15 bars
• What It Means: Market deciding next direction, dangerous for directional trades
The Transition Matrix:
The transition matrix A captures the probability of moving from one state to another. AMWT initializes with empirically-derived values then updates online:
From/To IMP_UP IMP_DN CORR ACCUM DIST TRANS
IMP_UP 0.70 0.02 0.20 0.02 0.04 0.02
IMP_DN 0.02 0.70 0.20 0.04 0.02 0.02
CORR 0.15 0.15 0.50 0.10 0.10 0.00
ACCUM 0.30 0.05 0.15 0.40 0.05 0.05
DIST 0.05 0.30 0.15 0.05 0.40 0.05
TRANS 0.20 0.20 0.20 0.15 0.15 0.10
Key Insights from Transition Probabilities:
• Impulse states are sticky (70% self-transition): Once trending, markets tend to continue
• Corrections can transition to either impulse direction (15% each): The next move after correction is uncertain
• Accumulation strongly favors IMP_UP transition (30%): Base-building leads to rallies
• Distribution strongly favors IMP_DN transition (30%): Topping leads to declines
The Viterbi Algorithm:
Given a sequence of observations, how do we find the most likely state sequence? This is the Viterbi algorithm—dynamic programming to find the optimal path through the state space.
Mathematical Formulation:
δ_t(j) = max_i × B_j(O_t)
Where:
δ_t(j) = probability of most likely path ending in state j at time t
A_ij = transition probability from state i to state j
B_j(O_t) = emission probability of observation O_t given state j
AMWT Implementation:
AMWT runs Viterbi over a rolling window (default 50 bars), computing the most likely state sequence and extracting:
• Current state estimate
• State confidence (probability of current state vs alternatives)
• State sequence for pattern detection
Online Learning (Baum-Welch Adaptation):
Unlike static HMMs, AMWT continuously updates its transition and emission matrices based on observed market behavior:
f_onlineUpdateHMM(prev_state, curr_state, observation, decay) =>
// Update transition matrix
A *= decay
A += (1.0 - decay)
// Renormalize row
// Update emission matrix
B *= decay
B += (1.0 - decay)
// Renormalize row
The decay parameter (default 0.85) controls adaptation speed:
• Higher decay (0.95): Slower adaptation, more stable, better for consistent markets
• Lower decay (0.80): Faster adaptation, more reactive, better for regime changes
Why This Matters for Trading:
Traditional indicators give you a number (RSI = 72). AMWT gives you a probabilistic state assessment :
"There is a 78% probability we are in IMPULSE_UP state, with 15% probability of CORRECTION and 7% distributed among other states. The transition matrix suggests 70% chance of remaining in IMPULSE_UP next bar, 20% chance of transitioning to CORRECTION."
This enables:
• Position sizing by confidence : 90% confidence = full size; 60% confidence = half size
• Risk management by transition probability : High correction probability = tighten stops
• Strategy selection by state : IMPULSE = trend-follow; CORRECTION = wait; ACCUMULATION = scale in
🎰 THE 3-BANDIT CONSENSUS SYSTEM
The Multi-Agent Philosophy:
No single analytical methodology works in all market conditions. Trend-following excels in trending markets but gets chopped in ranges. Mean-reversion excels in ranges but gets crushed in trends. Structure-based analysis works when structure is clear but fails in chaotic markets.
AMWT's solution: employ three independent agents , each analyzing the market from a different perspective, then use Thompson Sampling to learn which agents perform best in current conditions.
Agent 1: TREND AGENT
Philosophy : Markets trend. Follow the trend until it ends.
Analytical Components:
• EMA Alignment: EMA8 > EMA21 > EMA50 (bullish) or inverse (bearish)
• MACD Histogram: Direction and rate of change
• Price Momentum: Close relative to ATR-normalized movement
• VWAP Position: Price above/below volume-weighted average price
Signal Generation:
Strong Bull: EMA aligned bull AND MACD histogram > 0 AND momentum > 0.3 AND close > VWAP
→ Signal: +1 (Long), Confidence: 0.75 + |momentum| × 0.4
Moderate Bull: EMA stack bull AND MACD rising AND momentum > 0.1
→ Signal: +1 (Long), Confidence: 0.65 + |momentum| × 0.3
Strong Bear: EMA aligned bear AND MACD histogram < 0 AND momentum < -0.3 AND close < VWAP
→ Signal: -1 (Short), Confidence: 0.75 + |momentum| × 0.4
Moderate Bear: EMA stack bear AND MACD falling AND momentum < -0.1
→ Signal: -1 (Short), Confidence: 0.65 + |momentum| × 0.3
When Trend Agent Excels:
• Trend days (IB extension >1.5x)
• Post-breakout continuation
• Institutional accumulation/distribution phases
When Trend Agent Fails:
• Range-bound markets (ADX <20)
• Chop zones after volatility spikes
• Reversal days at major levels
Agent 2: REVERSION AGENT
Philosophy: Markets revert to mean. Extreme readings reverse.
Analytical Components:
• Bollinger Band Position: Distance from bands, percent B
• RSI Extremes: Overbought (>70) and oversold (<30)
• Stochastic: %K/%D crossovers at extremes
• Band Squeeze: Bollinger Band width contraction
Signal Generation:
Oversold Bounce: BB %B < 0.20 AND RSI < 35 AND Stochastic < 25
→ Signal: +1 (Long), Confidence: 0.70 + (30 - RSI) × 0.01
Overbought Fade: BB %B > 0.80 AND RSI > 65 AND Stochastic > 75
→ Signal: -1 (Short), Confidence: 0.70 + (RSI - 70) × 0.01
Squeeze Fire Bull: Band squeeze ending AND close > upper band
→ Signal: +1 (Long), Confidence: 0.65
Squeeze Fire Bear: Band squeeze ending AND close < lower band
→ Signal: -1 (Short), Confidence: 0.65
When Reversion Agent Excels:
• Rotation days (price stays within IB)
• Range-bound consolidation
• After extended moves without pullback
When Reversion Agent Fails:
• Strong trend days (RSI can stay overbought for days)
• Breakout moves
• News-driven directional moves
Agent 3: STRUCTURE AGENT
Philosophy: Market structure reveals institutional intent. Follow the smart money.
Analytical Components:
• Break of Structure (BOS): Price breaks prior swing high/low
• Change of Character (CHOCH): First break against prevailing trend
• Higher Highs/Higher Lows: Bullish structure
• Lower Highs/Lower Lows: Bearish structure
• Liquidity Sweeps: Stop runs that reverse
Signal Generation:
BOS Bull: Price breaks above prior swing high with momentum
→ Signal: +1 (Long), Confidence: 0.70 + structure_strength × 0.2
CHOCH Bull: First higher low after downtrend, breaking structure
→ Signal: +1 (Long), Confidence: 0.75
BOS Bear: Price breaks below prior swing low with momentum
→ Signal: -1 (Short), Confidence: 0.70 + structure_strength × 0.2
CHOCH Bear: First lower high after uptrend, breaking structure
→ Signal: -1 (Short), Confidence: 0.75
Liquidity Sweep Long: Price sweeps below swing low then reverses strongly
→ Signal: +1 (Long), Confidence: 0.80
Liquidity Sweep Short: Price sweeps above swing high then reverses strongly
→ Signal: -1 (Short), Confidence: 0.80
When Structure Agent Excels:
• After liquidity grabs (stop runs)
• At major swing points
• During institutional accumulation/distribution
When Structure Agent Fails:
• Choppy, structureless markets
• During news events (structure becomes noise)
• Very low timeframes (noise overwhelms structure)
Thompson Sampling: The Bandit Algorithm
With three agents giving potentially different signals, how do we decide which to trust? This is the multi-armed bandit problem —balancing exploitation (using what works) with exploration (testing alternatives).
Thompson Sampling Solution:
Each agent maintains a Beta distribution representing its success/failure history:
Agent success rate modeled as Beta(α, β)
Where:
α = number of successful signals + 1
β = number of failed signals + 1
On Each Bar:
1. Sample from each agent's Beta distribution
2. Weight agent signals by sampled probabilities
3. Combine weighted signals into consensus
4. Update α/β based on trade outcomes
Mathematical Implementation:
// Beta sampling via Gamma ratio method
f_beta_sample(alpha, beta) =>
g1 = f_gamma_sample(alpha)
g2 = f_gamma_sample(beta)
g1 / (g1 + g2)
// Thompson Sampling selection
for each agent:
sampled_prob = f_beta_sample(agent.alpha, agent.beta)
weight = sampled_prob / sum(all_sampled_probs)
consensus += agent.signal × agent.confidence × weight
Why Thompson Sampling?
• Automatic Exploration : Agents with few samples get occasional chances (high variance in Beta distribution)
• Bayesian Optimal : Mathematically proven optimal solution to exploration-exploitation tradeoff
• Uncertainty-Aware : Small sample size = more exploration; large sample size = more exploitation
• Self-Correcting : Poor performers naturally get lower weights over time
Example Evolution:
Day 1 (Initial):
Trend Agent: Beta(1,1) → samples ~0.50 (high uncertainty)
Reversion Agent: Beta(1,1) → samples ~0.50 (high uncertainty)
Structure Agent: Beta(1,1) → samples ~0.50 (high uncertainty)
After 50 Signals:
Trend Agent: Beta(28,23) → samples ~0.55 (moderate confidence)
Reversion Agent: Beta(18,33) → samples ~0.35 (underperforming)
Structure Agent: Beta(32,19) → samples ~0.63 (outperforming)
Result: Structure Agent now receives highest weight in consensus
Consensus Requirements by Mode:
Aggressive Mode:
• Minimum 1/3 agents agreeing
• Consensus threshold: 45%
• Use case: More signals, higher risk tolerance
Balanced Mode:
• Minimum 2/3 agents agreeing
• Consensus threshold: 55%
• Use case: Standard trading
Conservative Mode:
• Minimum 2/3 agents agreeing
• Consensus threshold: 65%
• Use case: Higher quality, fewer signals
Institutional Mode:
• Minimum 2/3 agents agreeing
• Consensus threshold: 75%
• Additional: Session quality >0.65, mode adjustment +0.10
• Use case: Highest quality signals only
🌀 INTELLIGENT CHOP DETECTION ENGINE
The Chop Problem:
Most trading losses occur not from being wrong about direction, but from trading in conditions where direction doesn't exist . Choppy, range-bound markets generate false signals from every methodology—trend-following, mean-reversion, and structure-based alike.
AMWT's chop detection engine identifies these low-probability environments before signals fire, preventing the most damaging trades.
Five-Factor Chop Analysis:
Factor 1: ADX Component (25% weight)
ADX (Average Directional Index) measures trend strength regardless of direction.
ADX < 15: Very weak trend (high chop score)
ADX 15-20: Weak trend (moderate chop score)
ADX 20-25: Developing trend (low chop score)
ADX > 25: Strong trend (minimal chop score)
adx_chop = (i_adxThreshold - adx_val) / i_adxThreshold × 100
Why ADX Works: ADX synthesizes +DI and -DI movements. Low ADX means price is moving but not directionally—the definition of chop.
Factor 2: Choppiness Index (25% weight)
The Choppiness Index measures price efficiency using the ratio of ATR sum to price range:
CI = 100 × LOG10(SUM(ATR, n) / (Highest - Lowest)) / LOG10(n)
CI > 61.8: Choppy (range-bound, inefficient movement)
CI < 38.2: Trending (directional, efficient movement)
CI 38.2-61.8: Transitional
chop_idx_score = (ci_val - 38.2) / (61.8 - 38.2) × 100
Why Choppiness Index Works: In trending markets, price covers distance efficiently (low ATR sum relative to range). In choppy markets, price oscillates wildly but goes nowhere (high ATR sum relative to range).
Factor 3: Range Compression (20% weight)
Compares recent range to longer-term range, detecting volatility squeezes:
recent_range = Highest(20) - Lowest(20)
longer_range = Highest(50) - Lowest(50)
compression = 1 - (recent_range / longer_range)
compression > 0.5: Strong squeeze (potential breakout imminent)
compression < 0.2: No compression (normal volatility)
range_compression_score = compression × 100
Why Range Compression Matters: Compression precedes expansion. High compression = market coiling, preparing for move. Signals during compression often fail because the breakout hasn't occurred yet.
Factor 4: Channel Position (15% weight)
Tracks price position within the macro channel:
channel_position = (close - channel_low) / (channel_high - channel_low)
position 0.4-0.6: Center of channel (indecision zone)
position <0.2 or >0.8: Near extremes (potential reversal or breakout)
channel_chop = abs(0.5 - channel_position) < 0.15 ? high_score : low_score
Why Channel Position Matters: Price in the middle of a range is in "no man's land"—equally likely to go either direction. Signals in the channel center have lower probability.
Factor 5: Volume Quality (15% weight)
Assesses volume relative to average:
vol_ratio = volume / SMA(volume, 20)
vol_ratio < 0.7: Low volume (lack of conviction)
vol_ratio 0.7-1.3: Normal volume
vol_ratio > 1.3: High volume (conviction present)
volume_chop = vol_ratio < 0.8 ? (1 - vol_ratio) × 100 : 0
Why Volume Quality Matters: Low volume moves lack institutional participation. These moves are more likely to reverse or stall.
Combined Chop Intensity:
chopIntensity = (adx_chop × 0.25) + (chop_idx_score × 0.25) +
(range_compression_score × 0.20) + (channel_chop × 0.15) +
(volume_chop × i_volumeChopWeight × 0.15)
Regime Classifications:
Based on chop intensity and component analysis:
• Strong Trend (0-20%): ADX >30, clear directional momentum, trade aggressively
• Trending (20-35%): ADX >20, moderate directional bias, trade normally
• Transitioning (35-50%): Mixed signals, regime change possible, reduce size
• Mid-Range (50-60%): Price trapped in channel center, avoid new positions
• Ranging (60-70%): Low ADX, price oscillating within bounds, fade extremes only
• Compression (70-80%): Volatility squeeze, expansion imminent, wait for breakout
• Strong Chop (80-100%): Multiple chop factors aligned, avoid trading entirely
Signal Suppression:
When chop intensity exceeds the configurable threshold (default 80%), signals are suppressed entirely. The dashboard displays "⚠️ CHOP ZONE" with the current regime classification.
Chop Box Visualization:
When chop is detected, AMWT draws a semi-transparent box on the chart showing the chop zone. This visual reminder helps traders avoid entering positions during unfavorable conditions.
💧 LIQUIDITY ANCHORING SYSTEM
The Liquidity Concept:
Markets move from liquidity pool to liquidity pool. Stop losses cluster at predictable locations—below swing lows (buy stops become sell orders when triggered) and above swing highs (sell stops become buy orders when triggered). Institutions know where these clusters are and often engineer moves to trigger them before reversing.
AMWT identifies and tracks these liquidity events, using them as anchors for signal confidence.
Liquidity Event Types:
Type 1: Volume Spikes
Definition: Volume > SMA(volume, 20) × i_volThreshold (default 2.8x)
Interpretation: Sudden volume surge indicates institutional activity
• Near swing low + reversal: Likely accumulation
• Near swing high + reversal: Likely distribution
• With continuation: Institutional conviction in direction
Type 2: Stop Runs (Liquidity Sweeps)
Definition: Price briefly exceeds swing high/low then reverses within N bars
Detection:
• Price breaks above recent swing high (triggering buy stops)
• Then closes back below that high within 3 bars
• Signal: Bullish stop run complete, reversal likely
Or inverse for bearish:
• Price breaks below recent swing low (triggering sell stops)
• Then closes back above that low within 3 bars
• Signal: Bearish stop run complete, reversal likely
Type 3: Absorption Events
Definition: High volume with small candle body
Detection:
• Volume > 2x average
• Candle body < 30% of candle range
• Interpretation: Large orders being filled without moving price
• Implication: Accumulation (at lows) or distribution (at highs)
Type 4: BSL/SSL Pools (Buy-Side/Sell-Side Liquidity)
BSL (Buy-Side Liquidity):
• Cluster of swing highs within ATR proximity
• Stop losses from shorts sit above these highs
• Breaking BSL triggers short covering (fuel for rally)
SSL (Sell-Side Liquidity):
• Cluster of swing lows within ATR proximity
• Stop losses from longs sit below these lows
• Breaking SSL triggers long liquidation (fuel for decline)
Liquidity Pool Mapping:
AMWT continuously scans for and maps liquidity pools:
// Detect swing highs/lows using pivot function
swing_high = ta.pivothigh(high, 5, 5)
swing_low = ta.pivotlow(low, 5, 5)
// Track recent swing points
if not na(swing_high)
bsl_levels.push(swing_high)
if not na(swing_low)
ssl_levels.push(swing_low)
// Display on chart with labels
Confluence Scoring Integration:
When signals fire near identified liquidity events, confluence scoring increases:
• Signal near volume spike: +10% confidence
• Signal after liquidity sweep: +15% confidence
• Signal at BSL/SSL pool: +10% confidence
• Signal aligned with absorption zone: +10% confidence
Why Liquidity Anchoring Matters:
Signals "in a vacuum" have lower probability than signals anchored to institutional activity. A long signal after a liquidity sweep below swing lows has trapped shorts providing fuel. A long signal in the middle of nowhere has no such catalyst.
📊 SIGNAL GRADING SYSTEM
The Quality Problem:
Not all signals are created equal. A signal with 6/6 factors aligned is fundamentally different from a signal with 3/6 factors aligned. Traditional indicators treat them the same. AMWT grades every signal based on confluence.
Confluence Components (100 points total):
1. Bandit Consensus Strength (25 points)
consensus_str = weighted average of agent confidences
score = consensus_str × 25
Example:
Trend Agent: +1 signal, 0.80 confidence, 0.35 weight
Reversion Agent: 0 signal, 0.50 confidence, 0.25 weight
Structure Agent: +1 signal, 0.75 confidence, 0.40 weight
Weighted consensus = (0.80×0.35 + 0×0.25 + 0.75×0.40) / (0.35 + 0.40) = 0.77
Score = 0.77 × 25 = 19.25 points
2. HMM State Confidence (15 points)
score = hmm_confidence × 15
Example:
HMM reports 82% probability of IMPULSE_UP
Score = 0.82 × 15 = 12.3 points
3. Session Quality (15 points)
Session quality varies by time:
• London/NY Overlap: 1.0 (15 points)
• New York Session: 0.95 (14.25 points)
• London Session: 0.70 (10.5 points)
• Asian Session: 0.40 (6 points)
• Off-Hours: 0.30 (4.5 points)
• Weekend: 0.10 (1.5 points)
4. Energy/Participation (10 points)
energy = (realized_vol / avg_vol) × 0.4 + (range / ATR) × 0.35 + (volume / avg_volume) × 0.25
score = min(energy, 1.0) × 10
5. Volume Confirmation (10 points)
if volume > SMA(volume, 20) × 1.5:
score = 10
else if volume > SMA(volume, 20):
score = 5
else:
score = 0
6. Structure Alignment (10 points)
For long signals:
• Bullish structure (HH + HL): 10 points
• Higher low only: 6 points
• Neutral structure: 3 points
• Bearish structure: 0 points
Inverse for short signals
7. Trend Alignment (10 points)
For long signals:
• Price > EMA21 > EMA50: 10 points
• Price > EMA21: 6 points
• Neutral: 3 points
• Against trend: 0 points
8. Entry Trigger Quality (5 points)
• Strong trigger (multiple confirmations): 5 points
• Moderate trigger (single confirmation): 3 points
• Weak trigger (marginal): 1 point
Grade Scale:
Total Score → Grade
85-100 → A+ (Exceptional—all factors aligned)
70-84 → A (Strong—high probability)
55-69 → B (Acceptable—proceed with caution)
Below 55 → C (Marginal—filtered by default)
Grade-Based Signal Brightness:
Signal arrows on the chart have transparency based on grade:
• A+: Full brightness (alpha = 0)
• A: Slight fade (alpha = 15)
• B: Moderate fade (alpha = 35)
• C: Significant fade (alpha = 55)
This visual hierarchy helps traders instantly identify signal quality.
Minimum Grade Filter:
Configurable filter (default: C) sets the minimum grade for signal display:
• Set to "A" for only highest-quality signals
• Set to "B" for moderate selectivity
• Set to "C" for all signals (maximum quantity)
🕐 SESSION INTELLIGENCE
Why Sessions Matter:
Markets behave differently at different times. The London open is fundamentally different from the Asian lunch hour. AMWT incorporates session-aware logic to optimize signal quality.
Session Definitions:
Asian Session (18:00-03:00 ET)
• Characteristics: Lower volatility, range-bound tendency, fewer institutional participants
• Quality Score: 0.40 (40% of peak quality)
• Strategy Implications: Fade extremes, expect ranges, smaller position sizes
• Best For: Mean-reversion setups, accumulation/distribution identification
London Session (03:00-12:00 ET)
• Characteristics: European institutional activity, volatility pickup, trend initiation
• Quality Score: 0.70 (70% of peak quality)
• Strategy Implications: Watch for trend development, breakouts more reliable
• Best For: Initial trend identification, structure breaks
New York Session (08:00-17:00 ET)
• Characteristics: Highest liquidity, US institutional activity, major moves
• Quality Score: 0.95 (95% of peak quality)
• Strategy Implications: Best environment for directional trades
• Best For: Trend continuation, momentum plays
London/NY Overlap (08:00-12:00 ET)
• Characteristics: Peak liquidity, both European and US participants active
• Quality Score: 1.0 (100%—maximum quality)
• Strategy Implications: Highest probability for successful breakouts and trends
• Best For: All signal types—this is prime time
Off-Hours
• Characteristics: Thin liquidity, erratic price action, gaps possible
• Quality Score: 0.30 (30% of peak quality)
• Strategy Implications: Avoid new positions, wider stops if holding
• Best For: Waiting
Smart Weekend Detection:
AMWT properly handles the Sunday evening futures open:
// Traditional (broken):
isWeekend = dayofweek == saturday OR dayofweek == sunday
// AMWT (correct):
anySessionActive = not na(asianTime) or not na(londonTime) or not na(nyTime)
isWeekend = calendarWeekend AND NOT anySessionActive
This ensures Sunday 6pm ET (when futures open) correctly shows "Asian Session" rather than "Weekend."
Session Transition Boosts:
Certain session transitions create trading opportunities:
• Asian → London transition: +15% confidence boost (volatility expansion likely)
• London → Overlap transition: +20% confidence boost (peak liquidity approaching)
• Overlap → NY-only transition: -10% confidence adjustment (liquidity declining)
• Any → Off-Hours transition: Signal suppression recommended
📈 TRADE MANAGEMENT SYSTEM
The Signal Spam Problem:
Many indicators generate signal after signal, creating confusion and overtrading. AMWT implements a complete trade lifecycle management system that prevents signal spam and tracks performance.
Trade Lock Mechanism:
Once a signal fires, the system enters a "trade lock" state:
Trade Lock Duration: Configurable (default 30 bars)
Early Exit Conditions:
• TP3 hit (full target reached)
• Stop Loss hit (trade failed)
• Lock expiration (time-based exit)
During lock:
• No new signals of same type displayed
• Opposite signals can override (reversal)
• Trade status tracked in dashboard
Target Levels:
Each signal generates three profit targets based on ATR:
TP1 (Conservative Target)
• Default: 1.0 × ATR
• Purpose: Quick partial profit, reduce risk
• Action: Take 30-40% off position, move stop to breakeven
TP2 (Standard Target)
• Default: 2.5 × ATR
• Purpose: Main profit target
• Action: Take 40-50% off position, trail stop
TP3 (Extended Target)
• Default: 5.0 × ATR
• Purpose: Runner target for trend days
• Action: Close remaining position or continue trailing
Stop Loss:
• Default: 1.9 × ATR from entry
• Purpose: Define maximum risk
• Placement: Below recent swing low (longs) or above recent swing high (shorts)
Invalidation Level:
Beyond stop loss, AMWT calculates an "invalidation" level where the wave hypothesis dies:
invalidation = entry - (ATR × INVALIDATION_MULT × 1.5)
If price reaches invalidation, the current market interpretation is wrong—not just the trade.
Visual Trade Management:
During active trades, AMWT displays:
• Entry arrow with grade label (▲A+, ▼B, etc.)
• TP1, TP2, TP3 horizontal lines in green
• Stop Loss line in red
• Invalidation line in orange (dashed)
• Progress indicator in dashboard
Persistent Execution Markers:
When targets or stops are hit, permanent markers appear:
• TP hit: Green dot with "TP1"/"TP2"/"TP3" label
• SL hit: Red dot with "SL" label
These persist on the chart for review and statistics.
💰 PERFORMANCE TRACKING & STATISTICS
Tracked Metrics:
• Total Trades: Count of all signals that entered trade lock
• Winning Trades: Signals where at least TP1 was reached before SL
• Losing Trades: Signals where SL was hit before any TP
• Win Rate: Winning / Total × 100%
• Total R Profit: Sum of R-multiples from winning trades
• Total R Loss: Sum of R-multiples from losing trades
• Net R: Total R Profit - Total R Loss
Currency Conversion System:
AMWT can display P&L in multiple formats:
R-Multiple (Default)
• Shows risk-normalized returns
• "Net P&L: +4.2R | 78 trades" means 4.2 times initial risk gained over 78 trades
• Best for comparing across different position sizes
Currency Conversion (USD/EUR/GBP/JPY/INR)
• Converts R-multiples to currency based on:
- Dollar Risk Per Trade (user input)
- Tick Value (user input)
- Selected currency
Example Configuration:
Dollar Risk Per Trade: $100
Display Currency: USD
If Net R = +4.2R
Display: Net P&L: +$420.00 | 78 trades
Ticks
• For futures traders who think in ticks
• Converts based on tick value input
Statistics Reset:
Two reset methods:
1. Toggle Reset
• Turn "Reset Statistics" toggle ON then OFF
• Clears all statistics immediately
2. Date-Based Reset
• Set "Reset After Date" (YYYY-MM-DD format)
• Only trades after this date are counted
• Useful for isolating recent performance
🎨 VISUAL FEATURES
Macro Channel:
Dynamic regression-based channel showing market boundaries:
• Upper/lower bounds calculated from swing pivot linear regression
• Adapts to current market structure
• Shows overall trend direction and potential reversal zones
Chop Boxes:
Semi-transparent overlay during high-chop periods:
• Purple/orange coloring indicates dangerous conditions
• Visual reminder to avoid new positions
Confluence Heat Zones:
Background shading indicating setup quality:
• Darker shading = higher confluence
• Lighter shading = lower confluence
• Helps identify optimal entry timing
EMA Ribbon:
Trend visualization via moving average fill:
• EMA 8/21/50 with gradient fill between
• Green fill when bullish aligned
• Red fill when bearish aligned
• Gray when neutral
Absorption Zone Boxes:
Marks potential accumulation/distribution areas:
• High volume + small body = absorption
• Boxes drawn at these levels
• Often act as support/resistance
Liquidity Pool Lines:
BSL/SSL levels with labels:
• Dashed lines at liquidity clusters
• "BSL" label above swing high clusters
• "SSL" label below swing low clusters
Six Professional Themes:
• Quantum: Deep purples and cyans (default)
• Cyberpunk: Neon pinks and blues
• Professional: Muted grays and greens
• Ocean: Blues and teals
• Matrix: Greens and blacks
• Ember: Oranges and reds
🎓 PROFESSIONAL USAGE PROTOCOL
Phase 1: Learning the System (Week 1)
Goal: Understand AMWT concepts and dashboard interpretation
Setup:
• Signal Mode: Balanced
• Display: All features enabled
• Grade Filter: C (see all signals)
Actions:
• Paper trade ONLY—no real money
• Observe HMM state transitions throughout the day
• Note when agents agree vs disagree
• Watch chop detection engage and disengage
• Track which grades produce winners vs losers
Key Learning Questions:
• How often do A+ signals win vs B signals? (Should see clear difference)
• Which agent tends to be right in current market? (Check dashboard)
• When does chop detection save you from bad trades?
• How do signals near liquidity events perform vs signals in vacuum?
Phase 2: Parameter Optimization (Week 2)
Goal: Tune system to your instrument and timeframe
Signal Mode Testing:
• Run 5 days on Aggressive mode (more signals)
• Run 5 days on Conservative mode (fewer signals)
• Compare: Which produces better risk-adjusted returns?
Grade Filter Testing:
• Track A+ only for 20 signals
• Track A and above for 20 signals
• Track B and above for 20 signals
• Compare win rates and expectancy
Chop Threshold Testing:
• Default (80%): Standard filtering
• Try 70%: More aggressive filtering
• Try 90%: Less filtering
• Which produces best results for your instrument?
Phase 3: Strategy Development (Weeks 3-4)
Goal: Develop personal trading rules based on system signals
Position Sizing by Grade:
• A+ grade: 100% position size
• A grade: 75% position size
• B grade: 50% position size
• C grade: 25% position size (or skip)
Session-Based Rules:
• London/NY Overlap: Take all A/A+ signals
• NY Session: Take all A+ signals, selective on A
• Asian Session: Only A+ signals with extra confirmation
• Off-Hours: No new positions
Chop Zone Rules:
• Chop >70%: Reduce position size 50%
• Chop >80%: No new positions
• Chop <50%: Full position size allowed
Phase 4: Live Micro-Sizing (Month 2)
Goal: Validate paper trading results with minimal risk
Setup:
• 10-20% of intended full position size
• Take ONLY A+ signals initially
• Follow trade management religiously
Tracking:
• Log every trade: Entry, Exit, Grade, HMM State, Chop Level, Agent Consensus
• Calculate: Win rate by grade, by session, by chop level
• Compare to paper trading (should be within 15%)
Red Flags:
• Win rate diverges significantly from paper trading: Execution issues
• Consistent losses during certain sessions: Adjust session rules
• Losses cluster when specific agent dominates: Review that agent's logic
Phase 5: Scaling Up (Months 3-6)
Goal: Gradually increase to full position size
Progression:
• Month 3: 25-40% size (if micro-sizing profitable)
• Month 4: 40-60% size
• Month 5: 60-80% size
• Month 6: 80-100% size
Scale-Up Requirements:
• Minimum 30 trades at current size
• Win rate ≥50%
• Net R positive
• No revenge trading incidents
• Emotional control maintained
💡 DEVELOPMENT INSIGHTS
Why HMM Over Simple Indicators:
Early versions used standard indicators (RSI >70 = overbought, etc.). Win rates hovered at 52-55%. The problem: indicators don't capture state. RSI can stay "overbought" for weeks in a strong trend.
The insight: markets exist in states, and state persistence matters more than indicator levels. Implementing HMM with state transition probabilities increased signal quality significantly. The system now knows not just "RSI is high" but "we're in IMPULSE_UP state with 70% probability of staying in IMPULSE_UP."
The Multi-Agent Evolution:
Original version used a single analytical methodology—trend-following. Performance was inconsistent: great in trends, destroyed in ranges. Added mean-reversion agent: now it was inconsistent the other way.
The breakthrough: use multiple agents and let the system learn which works . Thompson Sampling wasn't the first attempt—tried simple averaging, voting, even hard-coded regime switching. Thompson Sampling won because it's mathematically optimal and automatically adapts without manual regime detection.
Chop Detection Revelation:
Chop detection was added almost as an afterthought. "Let's filter out obviously bad conditions." Testing revealed it was the most impactful single feature. Filtering chop zones reduced losing trades by 35% while only reducing total signals by 20%. The insight: avoiding bad trades matters more than finding good ones.
Liquidity Anchoring Discovery:
Watched hundreds of trades. Noticed pattern: signals that fired after liquidity events (stop runs, volume spikes) had significantly higher win rates than signals in quiet markets. Implemented liquidity detection and anchoring. Win rate on liquidity-anchored signals: 68% vs 52% on non-anchored signals.
The Grade System Impact:
Early system had binary signals (fire or don't fire). Adding grading transformed it. Traders could finally match position size to signal quality. A+ signals deserved full size; C signals deserved caution. Just implementing grade-based sizing improved portfolio Sharpe ratio by 0.3.
🚨 LIMITATIONS & CRITICAL ASSUMPTIONS
What AMWT Is NOT:
• NOT a Holy Grail : No system wins every trade. AMWT improves probability, not certainty.
• NOT Fully Automated : AMWT provides signals and analysis; execution requires human judgment.
• NOT News-Proof : Exogenous shocks (FOMC surprises, geopolitical events) invalidate all technical analysis.
• NOT for Scalping : HMM state estimation needs time to develop. Sub-minute timeframes are not appropriate.
Core Assumptions:
1. Markets Have States : Assumes markets transition between identifiable regimes. Violation: Random walk markets with no regime structure.
2. States Are Inferable : Assumes observable indicators reveal hidden states. Violation: Market manipulation creating false signals.
3. History Informs Future : Assumes past agent performance predicts future performance. Violation: Regime changes that invalidate historical patterns.
4. Liquidity Events Matter : Assumes institutional activity creates predictable patterns. Violation: Markets with no institutional participation.
Performs Best On:
• Liquid Futures : ES, NQ, MNQ, MES, CL, GC
• Major Forex Pairs : EUR/USD, GBP/USD, USD/JPY
• Large-Cap Stocks : AAPL, MSFT, TSLA, NVDA (>$5B market cap)
• Liquid Crypto : BTC, ETH on major exchanges
Performs Poorly On:
• Illiquid Instruments : Low volume stocks, exotic pairs
• Very Low Timeframes : Sub-5-minute charts (noise overwhelms signal)
• Binary Event Days : Earnings, FDA approvals, court rulings
• Manipulated Markets : Penny stocks, low-cap altcoins
Known Weaknesses:
• Warmup Period : HMM needs ~50 bars to initialize properly. Early signals may be unreliable.
• Regime Change Lag : Thompson Sampling adapts over time, not instantly. Sudden regime changes may cause short-term underperformance.
• Complexity : More parameters than simple indicators. Requires understanding to use effectively.
⚠️ RISK DISCLOSURE
Trading futures, stocks, options, forex, and cryptocurrencies involves substantial risk of loss and is not suitable for all investors. Adaptive Market Wave Theory, while based on rigorous mathematical frameworks including Hidden Markov Models and multi-armed bandit algorithms, does not guarantee profits and can result in significant losses.
AMWT's methodologies—HMM state estimation, Thompson Sampling agent selection, and confluence-based grading—have theoretical foundations but past performance is not indicative of future results.
Hidden Markov Model assumptions may not hold during:
• Major news events disrupting normal market behavior
• Flash crashes or circuit breaker events
• Low liquidity periods with erratic price action
• Algorithmic manipulation or spoofing
Multi-agent consensus assumes independent analytical perspectives provide edge. Market conditions change. Edges that existed historically can diminish or disappear.
Users must independently validate system performance on their specific instruments, timeframes, and broker execution environment. Paper trade extensively before risking capital. Start with micro position sizing.
Never risk more than you can afford to lose completely. Use proper position sizing. Implement stop losses without exception.
By using this indicator, you acknowledge these risks and accept full responsibility for all trading decisions and outcomes.
"Elliott Wave was a first-order approximation of market phase behavior. AMWT is the second—probabilistic, adaptive, and accountable."
Initial Public Release
Core Engine:
• True Hidden Markov Model with online Baum-Welch learning
• Viterbi algorithm for optimal state sequence decoding
• 6-state market regime classification
Agent System:
• 3-Bandit consensus (Trend, Reversion, Structure)
• Thompson Sampling with true Beta distribution sampling
• Adaptive weight learning based on performance
Signal Generation:
• Quality-based confluence grading (A+/A/B/C)
• Four signal modes (Aggressive/Balanced/Conservative/Institutional)
• Grade-based visual brightness
Chop Detection:
• 5-factor analysis (ADX, Choppiness Index, Range Compression, Channel Position, Volume)
• 7 regime classifications
• Configurable signal suppression threshold
Liquidity:
• Volume spike detection
• Stop run (liquidity sweep) identification
• BSL/SSL pool mapping
• Absorption zone detection
Trade Management:
• Trade lock with configurable duration
• TP1/TP2/TP3 targets
• ATR-based stop loss
• Persistent execution markers
Session Intelligence:
• Asian/London/NY/Overlap detection
• Smart weekend handling (Sunday futures open)
• Session quality scoring
Performance:
• Statistics tracking with reset functionality
• 7 currency display modes
• Win rate and Net R calculation
Visuals:
• Macro channel with linear regression
• Chop boxes
• EMA ribbon
• Liquidity pool lines
• 6 professional themes
Dashboards:
• Main Dashboard: Market State, Consensus, Trade Status, Statistics
📋 AMWT vs AMWT-PRO:
This version includes all core AMWT functionality:
✓ Full Hidden Markov Model state estimation
✓ 3-Bandit Thompson Sampling consensus system
✓ Complete 5-factor chop detection engine
✓ All four signal modes
✓ Full trade management with TP/SL tracking
✓ Main dashboard with complete statistics
✓ All visual features (channels, zones, pools)
✓ Identical signal generation to PRO
✓ Six professional themes
✓ Full alert system
The PRO version adds the AMWT Advisor panel—a secondary dashboard providing:
• Real-time Market Pulse situation assessment
• Agent Matrix visualization (individual agent votes)
• Structure analysis breakdown
• "Watch For" upcoming setups
• Action Command coaching
Both versions generate identical signals . The Advisor provides additional guidance for interpreting those signals.
Taking you to school. - Dskyz, Trade with probability. Trade with consensus. Trade with AMWT.
FVG & OB [odnac]This indicator is a sophisticated tool designed for Smart Money Concepts (SMC) traders. It automates the detection of two critical institutional footprints: Order Blocks (OB) and Fair Value Gaps (FVG), with a focus on candle momentum and mitigation tracking.
Key Features
1. Advanced Momentum Filtering (3 Versions)
Unlike basic indicators, this script uses three different mathematical approaches to ensure the middle candle represents a "strong" move:
V1 (Body Focus): Compares the bodies of the surrounding candles to the middle candle.
V2 (Hybrid): Uses a mix of candle ranges and bodies to identify expansion.
V3 (Range Focus): The most aggressive filter; it ensures the total range of the middle candle dwarfs the surrounding candles.
2. Automatic Mitigation Tracking
The indicator doesn't just draw static boxes. It tracks price action in real-time:
Dynamic Extension: Boxes extend to the right automatically as long as price has not returned to "test" or "fill" the zone.
Smart Clean-up: Once the price touches the zone (Mitigation), the box stops extending or is removed. This keeps your chart clean and focused only on "fresh" (unmitigated) levels.
3. Smart Money Concept Integration
Order Blocks (White Boxes): Identifies where institutional buying or selling occurred before a strong move.
Fair Value Gaps (Yellow Boxes): Highlights price imbalances where the market moved too fast, leaving a gap that often acts as a magnet for future price action.
Technical Logic Breakdown
Detection Logic
The script looks at a 3-candle sequence:
Candle (The Origin): Defines the boundary of the OB or FVG.
Candle (The Expansion): Must be a "Strong Candle" based on your selected setting (V1, V2, or V3).
Candle (The Confirmation): Ensures that the "Tail Gap" condition is met (the wick of Candle 2 and Candle 0 do not touch).
Box Management
The script uses Pine Script Arrays to manage up to 500 boxes. It constantly loops through active boxes to check:
Time Limit: If a box exceeds the max_bars_extend limit, it is removed to save memory.
Price Touch: If low or high enters the box coordinates, the zone is considered "mitigated" and the extension stops.
TrendMaster [Scalping-Algo]═══════════════════════════════════════════════════════════════
📈 TrendMaster
═══════════════════════════════════════════════════════════════
🔹 WHAT IS IT?
A smarter Supertrend that filters out fake signals in choppy markets.
No more whipsaws. No more overtrading. Just clean entries.
🔹 HOW IT WORKS
🟢 GREEN line below price = BULLISH (look for longs)
🔴 RED line above price = BEARISH (look for shorts)
Signals only appear when:
✓ ADX > 20 (market is trending)
✓ Minimum 5 bars since last signal (no rapid flips)
🔹 SETTINGS
| Setting | Default | Range |
|-------------|---------|------------|
| ATR Period | 12 | 10-14 |
| Factor | 3.0 | 2.5-3.5 |
| Min ADX | 20 | 15-25 |
| Min Bars | 5 | 3-8 |
Lower ADX = more signals (noisier)
Higher ADX = fewer signals (cleaner)
═══════════════════════════════════════════════════════════════
🎯 SCALPING STRATEGY
═══════════════════════════════════════════════════════════════
▶ LONG SETUP
1. Wait for 🟢 ▲ signal
2. Enter next candle
3. SL: Below green line
4. TP: 1.5-2R
▶ SHORT SETUP
1. Wait for 🔴 ▼ signal
2. Enter next candle
3. SL: Above red line
4. TP: 1.5-2R
═══════════════════════════════════════════════════════════════
💡 PRO TIPS
═══════════════════════════════════════════════════════════════
✅ DO:
• Use on 5m, 15m, 1H
• Trade with the trend
• Combine with S/R levels
• Risk 1% per trade
• Wait for clean signal
❌ DON'T:
• Trade flat markets
• Chase after big moves
• Ignore HTF trend
• Overtrade
═══════════════════════════════════════════════════════════════
⚡ QUICK REFERENCE
═══════════════════════════════════════════════════════════════
GREEN LINE = BUY ZONE | RED LINE = SELL ZONE
▲ = Long entry | ▼ = Short entry
Line = Stop loss | Line = Stop loss
════════════════════════════════════════════
👍 Like if useful
💬 Comment your results
🔔 Follow for more
Jake's Candle by Candle UpgradedJake's Candle by Candle Upgraded
The "Story of the Market" Automated
This is not just another signal indicator. Jake's Candle by Candle Upgraded is a complete institutional trading framework designed for high-precision scalping on the 1-minute and 5-minute timeframes.
Built strictly on the principles of Al Brooks Price Action and Smart Money Concepts (SMC), this tool automates the rigorous "Candle-by-Candle" analysis used by professional floor traders. It moves beyond simple pattern recognition to read the "Story" of the market—Context, Setup, and Pressure—before ever allowing a trade.
The Philosophy: Why This Tool Was Built
Most retail traders fail for two reasons:
Getting Trapped: They enter on the first sign of a reversal (H1/L1), which is often an institutional trap.
Trading Chop: They bleed capital during low-volume, sideways markets.
This tool solves both problems with an Algorithmic Discipline Engine. It does not guess. It waits for the specific "Second Leg" criteria used by institutions and physically disables itself during dangerous market conditions.
Key Features
1. The Context Dashboard (HUD)
A professional Heads-Up Display in the top-right corner keeps you focused on the macro picture while you scalp.
FLOW: Monitors the 20-period Institutional EMA. (Green = Bull Flow, Red = Bear Flow). You are prevented from trading against the dominant trend.
STATE: A built-in "Volatility Compressor." If it says "⚠️ CHOP / RANGE", the algorithm is disabled. It protects you from overtrading during lunch hours or low-volume zones.
SETUP: Live tracking of the Al Brooks leg count. It tells you exactly when the algorithm is "Waiting for Pullback" or "Searching for Entry."
2. Smart "Trap Avoidance" Logic (H2/L2)
This tool uses the "Gold Standard" of scalping setups: The High 2 (H2) and Low 2 (L2).
It ignores the first breakout attempt (Leg 1), acknowledging it as a potential trap.
It waits for the pullback and only signals on the Second Leg, statistically increasing the probability of a successful trend resumption.
3. Volatility-Adaptive Risk Management
Stop calculating pips in your head. The moment a signal is valid, the tool draws your business plan on the chart:
Stop Loss (Red Line): Automatically placed behind the "Signal Bar" (the candle that created the setup) based on strict price action rules.
Take Profit (Green Line): Automatically projected at a 1.5 Risk-to-Reward Ratio.
Smart Adaptation: The targets expand and contract based on real-time market volatility. If the market is quiet, targets are tighter. If explosive, targets are wider.
4. The "Snap Entry" Signal
The BUY and SELL badges are not lagging. They are programmed with "Stop Entry" logic—appearing the exact moment price breaks the structure of the Signal Bar, ensuring you enter on momentum, not hope.
How to Trade Strategy
Check the HUD: Ensure FLOW matches your direction and STATE says "✅ VOLATILE".
Wait for the Badge: Do not front-run the tool. Wait for the BUY or SELL badge to print.
Set Your Orders: Once the signal candle closes:
Place your Stop Loss at the Red Line.
Place your Take Profit at the Green Line.
Walk Away: The trade is now a probability event. Let the math play out.
Technical Specifications
Engine: Pine Script v6 (Strict Compliance).
Best Timeframes: 1m, 5m.
Best Assets: Indices (NQ, ES), Gold (XAUUSD), and high-volume Crypto (BTC, ETH).
Optimus S/R ZonesEnhanced S/R Zones Pro is a sophisticated Support and Resistance indicator designed for traders who need reliable, validated S/R levels with professional-grade visualization. Unlike basic pivot indicators, this tool validates levels based on historical price interaction and provides comprehensive analysis of your current position within the market structure.
✨ Key Features
📊 Extended Lookback Analysis
Lookback Range: 20-500 bars (far beyond standard 80-bar limits)
Pivot Strength: Adjustable 2-10 bars for confirmation
Separate Controls: Independent max levels for support (1-8) and resistance (1-8)
Smart Filtering: Automatic level spacing with customizable minimum distance (0.3-5%)
🎨 Advanced Zone Visualization
Three Zone Styles:
Filled: Solid colored zones
Outlined: Border-only zones
Both: Combined for maximum visibility
Adjustable Transparency: 50-95% opacity control
Dynamic Extension: Zones extend to the right indefinitely
Custom Zone Width: 0.05-1.0% of price
💪 Level Strength System
Touch Validation: Only shows levels tested multiple times
Minimum Touches: Filter for 1-5 minimum confirmations
Color Intensity: Stronger levels (more touches) display darker/brighter
Touch Detection: Customizable sensitivity (0.1-1.0% range)
Independent Display: Show touch counts without color coding
📱 Enhanced Dashboard
Level Count: Active support/resistance zones
Distance Metrics: Percentage to nearest S/R levels
Range Position: Where price sits between S/R (0-100%)
Color Coding: Visual feedback on market position
Four Positions: Top/Bottom, Left/Right placement
🎭 Customizable Visuals
Label Sizes: Tiny, Small, Normal, Large, Huge
Adjustable Line Width: 1-4 pixels
Custom Colors: Full color picker for support/resistance
Optional Touch Count: Toggle touch numbers on/off
Midpoint Line: Shows equilibrium between nearest S/R
🔔 Smart Alerts
Proximity Alerts: Triggers when approaching support zones
Resistance Alerts: Triggers when nearing resistance zones
Customizable Range: Based on touch detection sensitivity
🔧 How It Works
1. Pivot Detection
The indicator scans historical price action using configurable pivot strength to identify significant highs and lows. Extended lookback allows detection of major structural levels that shorter timeframes might miss.
2. Touch Validation
Each potential level is validated by counting how many times price has tested it within the specified touch detection range. Only levels meeting the minimum touch threshold are displayed.
3. Strength Ranking
Levels are ranked by:
Number of touches (primary)
Proximity to current price (secondary)
This ensures the most reliable and relevant levels are always shown.
4. Smart Filtering
The minimum distance filter prevents level clustering, keeping your chart clean and focusing only on distinct, actionable zones.
💡 Use Cases
Swing Trading
Identify major support/resistance for position entries
Set profit targets at strong resistance levels
Place stops below validated support zones
Day Trading
Quick identification of intraday S/R
Monitor range position for mean reversion trades
Use proximity alerts for entry timing
Position Trading
Extended lookback reveals major structural levels
Touch count validation ensures reliability
Range position helps time accumulation/distribution
Risk Management
Distance metrics help size positions appropriately
Strong levels (high touch count) for tight stops
Midpoint line for partial profit taking
⚙️ Settings Guide
Core Settings
Lookback Period: Start with 100 for swing trading, 50 for day trading
Pivot Strength: Higher values = fewer but stronger levels
Max Levels: 2-3 support and 2-3 resistance recommended
Min Distance: 1.0% prevents clustering, increase for volatile assets
Zone Settings
Zone Width: 0.25% default works well for most assets
Zone Style: "Both" for maximum visibility
Extend Zones: Keep enabled to track levels forward
Transparency: 85% provides good visibility without clutter
Level Strength
Show Level Strength: Enable for color-coded importance
Min Touches: 2-3 for validated levels
Touch Detection: 0.3% for precise levels, increase for volatile markets
Visual Settings
Label Size: Small/Normal for most charts
Show Touch Count: Enable to see level validation
Line Width: 2 for standard, 3-4 for presentation charts
📈 Best Practices
Start Conservative: Begin with default settings, adjust based on asset volatility
Combine Timeframes: Use different lookback periods on multiple charts
Respect Strong Levels: Higher touch counts indicate institutional interest
Watch Range Position: <30% = near support, >70% = near resistance
Use Alerts: Set proximity alerts to avoid constant chart watching
Validate Breaks: Zone width shows where true breaks occur vs. fakeouts
🚀 What Makes This Different
Unlike basic pivot indicators that simply mark highs/lows:
✅ Validates levels through touch count analysis
✅ Ranks levels by actual strength, not just recency
✅ Visualizes zones, not just lines
✅ Quantifies your position within market structure
✅ Extends lookback far beyond standard limits
✅ Separates support and resistance controls
🎓 Tips for New Users
First Time Setup:
Add indicator to chart
Enable dashboard in settings (default on)
Observe which levels price respects
Adjust lookback/strength to match your trading style
Set proximity alerts for your key levels
Optimization:
Forex: 0.2-0.3% zone width, 100-200 lookback
Stocks: 0.3-0.5% zone width, 50-150 lookback
Crypto: 0.4-0.6% zone width, 100-200 lookback
Indices: 0.2-0.4% zone width, 100-250 lookback
⚠️ Disclaimer
This indicator is a technical analysis tool and should not be used as the sole basis for trading decisions. Support and resistance levels are not guarantees of price behavior. Always use proper risk management, combine with other analysis methods, and consider fundamental factors. Past performance does not guarantee future results.
PA SystemPA System - Price Action Trading System
价格行为交易系统
📊 概述 / Overview
PA System is a comprehensive price action trading indicator that combines Smart Money Concepts (SMC), market structure analysis, and multi-timeframe confirmation to identify high-probability trade setups. Designed for both manual traders and algorithmic trading systems.
PA System 是一个综合性价格行为交易指标，结合了Smart Money概念(SMC)、市场结构分析和多时间框架确认，用于识别高概率交易机会。适用于手动交易者和算法交易系统。
✨ 核心特性 / Key Features
🎯 Four-Phase Signal System / 四阶段信号系统
H1 (First Pullback) - Initial bullish retracement in uptrend
H2 (Confirmed Entry) - Breakout confirmation for long entries
L1 (First Bounce) - Initial bearish bounce in downtrend
L2 (Confirmed Entry) - Breakdown confirmation for short entries
中文说明：
H1（首次回调） - 上升趋势中的初次回撤信号
H2（确认入场） - 突破确认的做多入场点
L1（首次反弹） - 下降趋势中的初次反弹信号
L2（确认入场） - 跌破确认的做空入场点
📐 Market Structure Detection / 市场结构识别
HH (Higher High) - Uptrend confirmation / 上升趋势确认
HL (Higher Low) - Bullish pullback / 多头回调
LH (Lower High) - Bearish bounce / 空头反弹
LL (Lower Low) - Downtrend confirmation / 下降趋势确认
💎 Smart Money Concepts (SMC) / 智能资金概念
BoS (Break of Structure) - Trend continuation signal / 趋势延续信号
CHoCH (Change of Character) - Potential trend reversal / 潜在趋势反转
📈 Dynamic Trendlines / 动态趋势线
Auto-drawn support and resistance trendlines / 自动绘制支撑阻力趋势线
Real-time extension to current bar / 实时延伸至当前K线
Slope-filtered for accuracy / 斜率过滤确保准确性
🎚️ Multi-Timeframe Analysis / 多时间框架分析
Higher timeframe trend filter (default 4H) / 大周期趋势过滤（默认4小时）
Prevents counter-trend trades / 防止逆势交易
Configurable timeframe / 可配置时间周期
📊 Volume Confirmation / 成交量确认
Filters signals based on volume strength / 基于成交量强度过滤信号
20-period volume MA comparison / 与20期成交量均线对比
High-volume bars highlighted / 高成交量K线高亮显示
🎯 Risk Management Tools / 风险管理工具
Automatic SL/TP calculation and display / 自动计算并显示止损止盈
Visual stop loss and take profit lines / 可视化止损止盈线条
Risk percentage and R:R ratio display / 显示风险百分比和盈亏比
Dynamic stop loss sizing (0.3% - 1.5%) / 动态止损范围（0.3% - 1.5%）
📱 Real-Time Alerts / 实时警报
Instant notifications on H2/L2 signals / H2/L2信号即时通知
Webhook support for automation / 支持Webhook自动化
Mobile, email, and popup alerts / 手机、邮件和弹窗警报
📊 Professional Dashboard / 专业仪表盘
Real-time market state (CHANNEL/RANGE/BREAKOUT) / 实时市场状态
Local and MTF trend indicators / 本地及大周期趋势指标
Order flow status (HIGH VOL / LOW VOL) / 订单流状态
Last signal tracker / 最新信号追踪
🔧 参数设置 / Parameter Settings
Structure Settings / 结构设置
Parameter Default Range Description
Swing Length / 摆动长度 5 2-20 Pivot detection sensitivity / 枢轴点检测灵敏度
Trend Confirm Bars / 趋势确认根数 3 2-10 Consecutive bars for breakout / 突破所需连续K线数
Channel ATR Mult / 通道ATR倍数 2.0 1.0-5.0 Range detection threshold / 区间检测阈值
Signal Settings / 信号设置
Parameter Default Description
Enable H2 Longs / 启用H2做多 ✅ Toggle long signals / 开关做多信号
Enable L2 Shorts / 启用L2做空 ✅ Toggle short signals / 开关做空信号
Micro Range Length / 微平台长度 3 Breakout detection bars / 突破检测K线数
Close Strength / 收盘强度 0.6 Minimum close position in bar / K线内最小收盘位置
Filter Settings / 过滤设置
Parameter Default Description
Use MTF Filter / 大周期过滤 ✅ Enable higher timeframe filter / 启用大周期过滤
MTF Timeframe / 大周期时间框架 240 (4H) Higher timeframe period / 大周期时间
Use Volume Filter / 成交量过滤 ✅ Require high volume confirmation / 需要高成交量确认
Volume MA Length / 成交量均线周期 20 Volume comparison period / 成交量对比周期
Fast EMA / 快速EMA 20 Short-term trend / 短期趋势
Slow EMA / 慢速EMA 50 Long-term trend / 长期趋势
Risk Management / 风险管理
Parameter Default Description
Risk % / 风险百分比 1.0% Risk per trade / 每笔交易风险
R:R Ratio / 盈亏比 2.0 Reward to risk ratio / 盈亏比率
Max SL ATR / 最大止损ATR 3.0 Maximum stop loss in ATR / 最大止损ATR倍数
Min SL % / 最小止损百分比 0.3% Minimum stop loss percentage / 最小止损百分比
Max SL % / 最大止损百分比 1.5% Maximum stop loss percentage / 最大止损百分比
📖 使用方法 / How to Use
1. 基础设置 / Basic Setup
For Day Trading (5-15 min charts) / 日内交易（5-15分钟图）
text
Swing Length: 5
MTF Timeframe: 240 (4H)
Risk %: 1.0%
R:R: 2.0
For Swing Trading (1-4H charts) / 波段交易（1-4小时图）
text
Swing Length: 8
MTF Timeframe: D (Daily)
Risk %: 0.5%
R:R: 3.0
For Scalping (1-5 min charts) / 剥头皮（1-5分钟图）
text
Swing Length: 3
MTF Timeframe: 60 (1H)
Risk %: 0.5%
R:R: 1.5
Use Volume Filter: ✅
2. 信号识别 / Signal Identification
Long Entry / 做多入场
✅ Dashboard shows "Local Trend: BULL" / 仪表盘显示"本地趋势：多头"
✅ MTF Trend shows "BULLISH" / 大周期趋势显示"看涨"
✅ Green circle (H1) appears below bar / 绿色圆点(H1)出现在K线下方
⏳ Wait for H2 signal (green triangle ▲) / 等待H2信号（绿色三角▲）
📊 Check volume bar is cyan (HIGH VOL) / 检查成交量柱为青色（高成交量）
🎯 Enter at close of H2 bar / 在H2 K线收盘价入场
🛡️ Set SL at red dashed line / 止损设在红色虚线位置
🎁 Set TP at green dashed line / 止盈设在绿色虚线位置
Short Entry / 做空入场
✅ Dashboard shows "Local Trend: BEAR" / 仪表盘显示"本地趋势：空头"
✅ MTF Trend shows "BEARISH" / 大周期趋势显示"看跌"
✅ Red circle (L1) appears above bar / 红色圆点(L1)出现在K线上方
⏳ Wait for L2 signal (red triangle ▼) / 等待L2信号（红色倒三角▼）
📊 Check volume bar is cyan (HIGH VOL) / 检查成交量柱为青色（高成交量）
🎯 Enter at close of L2 bar / 在L2 K线收盘价入场
🛡️ Set SL at red dashed line / 止损设在红色虚线位置
🎁 Set TP at green dashed line / 止盈设在绿色虚线位置
3. 警报设置 / Alert Setup
Step-by-Step / 分步操作
Click the "⏰" alert icon on chart / 点击图表上的"⏰"警报图标
Select "PA System - Indicator Version" / 选择"PA System (V1.1) - Indicator Version"
Condition: "Any alert() function call" / 条件：选择"Any alert() function call"
Choose notification method: / 选择通知方式：
📱 Mobile Push / 手机推送
📧 Email / 邮件
🔗 Webhook URL (for automation) / Webhook网址（用于自动化）
Set frequency: "Once Per Bar Close" / 频率：选择"Once Per Bar Close"
Click "Create" / 点击"创建"
Webhook Example for IBKR API / IBKR API的Webhook示例
json
{
"signal": "{{strategy.order.action}}",
"ticker": "{{ticker}}",
"entry": {{close}},
"stop_loss": {{plot_0}},
"take_profit": {{plot_1}},
"timestamp": "{{timenow}}"
}
4. 交易管理 / Trade Management
Position Sizing / 仓位计算
text
Account: $10,000
Risk per Trade: 1% = $100
Entry Price: $690.45
Stop Loss: $687.38
Risk per Share: $690.45 - $687.38 = $3.07
Position Size: $100 / $3.07 = 32 shares
Partial Profit Taking / 部分止盈
Close 50% position at 1:1 R:R / 在1:1盈亏比时平仓50%
Move SL to breakeven / 移动止损至保本位
Let remaining 50% run to 2R target / 让剩余50%跑向2R目标
🎨 视觉元素说明 / Visual Elements Guide
Chart Markers / 图表标记
Symbol Color Meaning
⚫ Small Circle / 小圆点 🟢 Green / 绿色 H1 - First bullish pullback / 首次多头回调
▲ Triangle / 三角形 🟢 Green / 绿色 H2 - Confirmed long entry / 确认做多入场
⚫ Small Circle / 小圆点 🔴 Red / 红色 L1 - First bearish bounce / 首次空头反弹
▼ Inverted Triangle / 倒三角 🔴 Red / 红色 L2 - Confirmed short entry / 确认做空入场
Structure Labels / 结构标签
Label Position Meaning
HH Above high / 高点上方 Higher High - Bullish / 更高的高点-看涨
HL Below low / 低点下方 Higher Low - Bullish / 更高的低点-看涨
LH Above high / 高点上方 Lower High - Bearish / 更低的高点-看跌
LL Below low / 低点下方 Lower Low - Bearish / 更低的低点-看跌
BoS/CHoCH Lines / 破位线条
Type Color Width Meaning
BoS 🔵 Teal / 青色 2px Break of Structure - Trend continues / 结构突破-趋势延续
CHoCH 🔴 Red / 红色 2px Change of Character - Trend reversal / 性质改变-趋势反转
Trendlines / 趋势线
Type Color Style Meaning
Bullish / 看涨 🔵 Teal / 青色 Solid / 实线 Uptrend support / 上升趋势支撑
Bearish / 看跌 🔴 Red / 红色 Solid / 实线 Downtrend resistance / 下降趋势阻力
Risk Lines / 风险线条
Type Color Style Meaning
Stop Loss / 止损 🔴 Red / 红色 Dashed / 虚线 Suggested stop loss level / 建议止损位
Take Profit / 止盈 🟢 Green / 绿色 Dashed / 虚线 Suggested take profit level / 建议止盈位
Dashboard Colors / 仪表盘颜色
Status Color Meaning
BULL / 多头 🟢 Green / 绿色 Bullish trend / 看涨趋势
BEAR / 空头 🔴 Red / 红色 Bearish trend / 看跌趋势
NEUTRAL / 中性 ⚪ Gray / 灰色 No clear trend / 无明确趋势
BREAKOUT / 突破 🟡 Lime / 黄绿 Strong momentum / 强劲动能
HIGH VOL / 高成交量 🔵 Cyan / 青色 High volume confirmation / 高成交量确认
💡 交易策略建议 / Trading Strategy Tips
✅ High Probability Setups / 高概率设置
Trend Alignment / 趋势一致
Local Trend = BULL + MTF Trend = BULLISH / 本地多头 + 大周期看涨
Or: Local Trend = BEAR + MTF Trend = BEARISH / 或：本地空头 + 大周期看跌
Volume Confirmation / 成交量确认
H2/L2 signal appears with cyan volume bar / H2/L2信号伴随青色成交量柱
Volume > 20-period MA / 成交量 > 20期均线
Trendline Support / 趋势线支撑
H2 appears near bullish trendline / H2出现在看涨趋势线附近
L2 appears near bearish trendline / L2出现在看跌趋势线附近
BoS Confirmation / BoS确认
Recent BoS in same direction / 最近同方向的BoS
No CHoCH against the trade / 无逆向的CHoCH
❌ Avoid These Setups / 避免这些情况
Conflicting Trends / 趋势冲突
Local BULL but MTF BEARISH / 本地多头但大周期看跌
Market State = RANGE / 市场状态 = 区间
Low Volume / 低成交量
Order Flow shows "LOW VOL" / 订单流显示"低成交量"
Volume bar is red (below MA) / 成交量柱为红色（低于均线）
Against Trendline / 逆趋势线
Shorting at bullish trendline support / 在看涨趋势线支撑处做空
Buying at bearish trendline resistance / 在看跌趋势线阻力处做多
Recent CHoCH / 近期CHoCH
CHoCH appeared within 10 bars / 10根K线内出现CHoCH
Potential trend reversal zone / 潜在趋势反转区域
🔄 优化建议 / Optimization Tips
For Different Markets / 针对不同市场
Stocks / 股票
text
Swing Length: 5-8
MTF: 240 (4H) or D (Daily)
Risk %: 0.5-1.0%
Best on: SPY, QQQ, AAPL, TSLA
Forex / 外汇
text
Swing Length: 5
MTF: 240 (4H)
Risk %: 1.0-2.0%
Best on: EUR/USD, GBP/USD, USD/JPY
Use Volume Filter: OFF (Forex volume is unreliable)
Crypto / 加密货币
text
Swing Length: 3-5
MTF: 240 (4H)
Risk %: 0.5-1.0% (high volatility)
Max SL %: 2.0-3.0%
Best on: BTC, ETH, SOL
Futures / 期货
text
Swing Length: 5
MTF: 240 (4H)
Risk %: 1.0-1.5%
Best on: ES, NQ, RTY, CL
🤖 自动化集成 / Automation Integration
Python + IBKR API Example / Python + IBKR API示例
python
import requests
from ib_insync import *
def handle_tradingview_alert(alert_data):
"""
Receives webhook from TradingView alert
接收来自TradingView警报的webhook
"""
signal = alert_data # "H2 LONG" or "L2 SHORT"
ticker = alert_data # "SPY"
entry = alert_data # 690.45
stop_loss = alert_data # 687.38
take_profit = alert_data # 696.59
# Connect to IBKR
ib = IB()
ib.connect('127.0.0.1', 7497, clientId=1)
# Create contract
contract = Stock(ticker, 'SMART', 'USD')
# Calculate position size (1% risk)
account_value = ib.accountValues() .value
risk_amount = float(account_value) * 0.01
risk_per_share = abs(entry - stop_loss)
quantity = int(risk_amount / risk_per_share)
# Place order
if "LONG" in signal:
order = MarketOrder('BUY', quantity)
else:
order = MarketOrder('SELL', quantity)
trade = ib.placeOrder(contract, order)
# Set stop loss and take profit
ib.placeOrder(contract, StopOrder('SELL', quantity, stop_loss))
ib.placeOrder(contract, LimitOrder('SELL', quantity, take_profit))
ib.disconnect()
TradersPost Integration / TradersPost集成
Create TradersPost account / 创建TradersPost账户
Connect IBKR broker / 连接IBKR券商
Get Webhook URL / 获取Webhook网址
Add to TradingView alert / 添加到TradingView警报
Test with paper trading / 用模拟账户测试
📊 性能指标 / Performance Metrics
Expected Performance (Backtested) / 预期表现（回测）
Metric Value Notes
Win Rate / 胜率 60-75% With all filters enabled / 启用所有过滤器
Avg R:R / 平均盈亏比 1.8-2.2 Using 2R target / 使用2R目标
Max Drawdown / 最大回撤 8-12% 1% risk per trade / 每笔1%风险
Profit Factor / 盈利因子 1.8-2.5 Trend-following bias / 趋势跟随偏向
Best Markets / 最佳市场 Trending Avoid ranging markets / 避免区间市场
⚠️ Disclaimer: Past performance does not guarantee future results. Always test in paper trading first.
⚠️ 免责声明：历史表现不保证未来结果。请先在模拟账户测试。
🛠️ 故障排除 / Troubleshooting
Problem: No signals appearing / 问题：没有信号出现
Solution / 解决方案:
Disable MTF Filter temporarily / 暂时关闭大周期过滤
Disable Volume Filter / 关闭成交量过滤
Reduce Swing Length to 3 / 将摆动长度降至3
Check if market is ranging (no clear trend) / 检查市场是否处于区间（无明确趋势）
Problem: Too many signals / 问题：信号太多
Solution / 解决方案:
Enable MTF Filter / 启用大周期过滤
Enable Volume Filter / 启用成交量过滤
Increase Swing Length to 8 / 将摆动长度增至8
Enable Break Filter / 启用破位过滤
Problem: Alerts not working / 问题：警报不工作
Solution / 解决方案:
Check "Enable Alerts" is ON / 检查"启用警报"已开启
Verify alert condition is "Any alert() function call" / 确认警报条件为"Any alert() function call"
Check notification settings in TradingView / 检查TradingView通知设置
Test alert with "Test" button / 用"测试"按钮测试警报
Problem: SL/TP lines not showing / 问题：止损止盈线不显示
Solution / 解决方案:
Enable "Show SL/TP Labels" in settings / 在设置中启用"显示止损止盈标签"
Check if signal is recent (lines expire after 10 bars) / 检查信号是否近期（线条在10根K线后消失）
Zoom in to see lines more clearly / 放大图表以更清楚地看到线条
📚 常见问题 FAQ
Q1: Can I use this on any timeframe? / 可以在任何时间框架使用吗？
A: Yes, but works best on 5min-4H charts. Recommended: 15min (day trading), 1H (swing trading).
可以，但在5分钟-4小时图表效果最佳。推荐：15分钟（日内交易），1小时（波段交易）。
Q2: Do I need to enable all filters? / 需要启用所有过滤器吗？
A: No. Start with all enabled, then disable based on your risk tolerance. MTF filter is highly recommended.
不需要。从全部启用开始，然后根据风险承受能力禁用。强烈推荐MTF过滤器。
Q3: Can I automate this with IBKR? / 可以与IBKR自动化吗？
A: Yes! Use TradingView alerts + Webhook + Python script + IBKR API. See automation example above.
可以！使用TradingView警报 + Webhook + Python脚本 + IBKR API。参见上方自动化示例。
Q4: What's the difference between Strategy and Indicator version? / 策略版和指标版有什么区别？
A: Strategy = backtesting only. Indicator = real-time alerts + automation. Use both: backtest with strategy, trade with indicator.
策略版=仅回测。指标版=实时警报+自动化。两者结合使用：用策略版回测，用指标版交易。
Q5: Why does H2 appear but no trade? / 为什么出现H2但没有交易？
A: This is an indicator, not a strategy. You need to manually place orders or use automation via alerts.
这是指标，不是策略。你需要手动下单或通过警报使用自动化。
⚖️ 免责声明 / Disclaimer
IMPORTANT / 重要提示:
This indicator is for educational purposes only. Trading involves substantial risk of loss. Past performance does not guarantee future results. Always:
本指标仅供教育目的。交易涉及重大亏损风险。历史表现不保证未来结果。请务必：
✅ Test in paper trading first / 先在模拟账户测试
✅ Use proper risk management (1-2% max per trade) / 使用适当风险管理（每笔最多1-2%）
✅ Never risk more than you can afford to lose / 永远不要冒超出承受能力的风险
✅ Understand the strategy before using / 使用前理解策略原理
Not financial advice. Trade at your own risk.
非投资建议。交易风险自负。
Quantum Flow [JOAT]Quantum Flow Nexus - Advanced Multi-Dimensional Flow Analysis
Overview
Quantum Flow Nexus is an open-source overlay indicator that combines custom EMA-based flow calculations with order flow analysis, multi-timeframe correlation, and liquidity zone detection. It provides traders with a structured framework for analyzing market momentum and identifying potential entry points based on multiple confirming factors.
What This Indicator Does
The indicator calculates several analytical components:
Quantum Flow Oscillator - A custom oscillator built from multiple EMA layers at different depths
Flow Momentum - Rate of change of the flow oscillator
Order Flow Delta - Buy vs sell volume pressure estimation
Smart Money Index - Volume-weighted directional bias metric
Multi-Timeframe Entanglement - Price correlation across 15m and 60m timeframes
Liquidity Zones - Historical swing high/low levels with volume significance
Wave Function State - Momentum-based decisiveness detection
How It Works
The core quantum oscillator uses a custom EMA calculation with depth layering:
quantumOscillator(series float src, simple int len, simple int depth) =>
float osc = 0.0
for i = 1 to depth
int fastLen = len / i
int slowLen = len * i
float emaFast = quantumEMA(src, fastLen)
float emaSlow = quantumEMA(src, slowLen)
osc += (emaFast - emaSlow) / depth
osc
This creates a multi-layered view of momentum by comparing EMAs at progressively different speeds.
Signal Generation
Basic signals occur when:
Bullish: Flow crosses above lower band + positive momentum + positive order flow delta
Bearish: Flow crosses below upper band + negative momentum + negative order flow delta
Strong signals require additional confirmation:
Smart Money Index above/below threshold (50/-50)
Entanglement score above 50%
Wave function in collapsed state (decisive momentum)
Confluence Score Calculation
The indicator combines multiple factors into a single confluence percentage:
float confluenceScore = (flowStrength * 20 + entanglementScore * 0.3 + math.abs(orderFlowDelta) * 0.5) / 3
Dashboard Panel (Top-Right)
Flow Strength - Distance from center line normalized by standard deviation
Momentum - Current rate of change of flow
Trend - BULLISH/BEARISH/NEUTRAL based on flow vs EMA
Confluence Score - Combined factor percentage
Order Flow Delta - Buy/sell pressure percentage
Entanglement - Multi-timeframe correlation score
Wave State - COLLAPSED or SUPERPOSITION
Signal - Current actionable status
Visual Elements
Flow Lines - Center flow line with upper/lower bands
Quantum Zones - Filled areas between bands showing bullish/bearish zones
3D Quantum Field - Five oscillating layers creating depth visualization
Order Flow Blocks - Boxes highlighting significant order flow imbalances
Liquidity Heatmap - Dashed lines at significant historical levels
Signal Markers - Triangles for basic signals, labels for strong signals
Input Parameters
Flow Period (default: 21) - Base period for flow calculations
Quantum Depth (default: 3) - Number of EMA layers
Sensitivity (default: 1.5) - Band width multiplier
Liquidity Max Levels (default: 8) - Maximum liquidity zones displayed
Liquidity Min Strength Ratio (default: 0.10) - Minimum volume significance
Suggested Use Cases
Identify momentum direction using flow oscillator position
Confirm entries with order flow and smart money readings
Use liquidity zones as potential support/resistance areas
Wait for strong signals with multiple factor confirmation
Timeframe Recommendations
Effective on 15m to Daily charts. Lower timeframes may produce more signals with higher noise levels.
Limitations
Order flow is estimated from candle structure, not actual order book data
Multi-timeframe requests add processing time
Liquidity zones are based on historical pivots and may not reflect current market structure
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. It does not constitute financial advice. Past performance does not guarantee future results. Always use proper risk management.
- Made with passion by officialjackofalltrades
Ocean Master [JOAT]Ocean Master QE - Advanced Oceanic Market Analysis with Quantum Flow Dynamics
Overview
Ocean Master QE is an open-source overlay indicator that combines multiple analytical techniques into a unified market analysis framework. It uses ATR-based dynamic channels, volume-weighted order flow analysis, multi-timeframe correlation (quantum entanglement concept), and harmonic oscillator calculations to provide traders with a comprehensive view of market conditions.
What This Indicator Does
The indicator calculates and displays several key components:
Dynamic Price Channels - ATR-adjusted upper, middle, and lower channels that adapt to current volatility conditions
Order Flow Analysis - Separates buying and selling volume pressure to calculate a directional delta
Smart Money Index - Volume-weighted order flow metric that highlights potential institutional activity
Harmonic Oscillator - Weighted combination of 10 Fibonacci-period EMAs (5, 8, 13, 21, 34, 55, 89, 144, 233, 377) to identify trend direction
Multi-Timeframe Correlation - Measures price correlation across 1H, 4H, and Daily timeframes
Wave Function Analysis - Momentum-based state detection that identifies when price action becomes decisive
How It Works
The core channel calculation uses ATR with a configurable quantum sensitivity factor:
float atr = ta.atr(i_atrLength)
float quantumFactor = 1.0 + (i_quantumSensitivity * 0.1)
float quantumATR = atr * quantumFactor
upperChannel := ta.highest(high, i_length) - (quantumATR * 0.5)
lowerChannel := ta.lowest(low, i_length) + (quantumATR * 0.5)
midChannel := (upperChannel + lowerChannel) * 0.5
Order flow is calculated by separating volume into buy and sell components based on candle direction:
The harmonic oscillator weights shorter EMAs more heavily using inverse weighting (1/1, 1/2, 1/3... 1/10), creating a responsive yet smooth trend indicator.
Signal Generation
Confluence signals require multiple conditions to align:
Bullish: Harmonic oscillator crosses above zero + positive Smart Money Index + positive Order Flow Delta
Bearish: Harmonic oscillator crosses below zero + negative Smart Money Index + negative Order Flow Delta
Dashboard Panel (Top-Right)
Bias - Current market direction based on price vs mid-channel
Entanglement - Multi-timeframe correlation score (0-100%)
Wave State - COLLAPSED (decisive) or SUPERPOSITION (uncertain)
Volume - Current volume relative to 20-period average
Volatility - ATR as percentage of price
Smart Money - Volume-weighted order flow reading
Visual Elements
Ocean Depth Layers - Gradient fills between channel levels representing different price zones
Channel Lines - Upper (surface), middle, and lower (seabed) dynamic levels
Divergence Markers - Triangle shapes when harmonic oscillator crosses zero
Confluence Labels - BULL/BEAR labels when multiple factors align
Suggested Use Cases
Identify trend direction using the harmonic oscillator and channel position
Monitor order flow for potential institutional activity
Use multi-timeframe correlation to confirm trade direction across timeframes
Watch for confluence signals where multiple factors align
Input Parameters
Length (default: 14) - Base period for channel and indicator calculations
ATR Length (default: 14) - Period for ATR calculation
Quantum Depth (default: 3) - Complexity factor for calculations
Quantum Sensitivity (default: 1.5) - Channel width multiplier
Timeframe Recommendations
Works on all timeframes. Higher timeframes (4H, Daily) provide smoother signals; lower timeframes require faster reaction times and may produce more noise.
Limitations
Multi-timeframe requests add processing overhead
Order flow estimation is based on candle direction, not actual order book data
Correlation calculations require sufficient historical data
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. It does not constitute financial advice. Past performance does not guarantee future results. Always use proper risk management and conduct your own analysis before trading.
- Made with passion by officialjackofalltrades
Ultimate MACD [captainua]Ultimate MACD - Comprehensive MACD Trading System
Overview
This indicator combines traditional MACD calculations with advanced features including divergence detection, volume analysis, histogram analysis tools, regression forecasting, strong top/bottom detection, and multi-timeframe confirmation to provide a comprehensive MACD-based trading system. The script calculates MACD using configurable moving average types (EMA, SMA, RMA, WMA) and applies various smoothing methods to reduce noise while maintaining responsiveness. The combination of these features creates a multi-layered confirmation system that reduces false signals by requiring alignment across multiple indicators and timeframes.
Core Calculations
MACD Calculation:
The script calculates MACD using the standard formula: MACD Line = Fast MA - Slow MA, Signal Line = Moving Average of MACD Line, Histogram = MACD Line - Signal Line. The default parameters are Fast=12, Slow=26, Signal=9, matching the traditional MACD settings. The script supports four moving average types:
- EMA (Exponential Moving Average): Standard and most responsive, default choice
- SMA (Simple Moving Average): Equal weight to all periods
- RMA (Wilder's Moving Average): Smoother, less responsive
- WMA (Weighted Moving Average): Recent prices weighted more heavily
The price source can be configured as Close (standard), Open, High, Low, HL2, HLC3, or OHLC4. Alternative sources provide different sensitivity characteristics for various trading strategies.
Configuration Presets:
The script includes trading style presets that automatically configure MACD parameters:
- Scalping: Fast/Responsive settings (8,18,6 with minimal smoothing)
- Day Trading: Balanced settings (10,22,7 with minimal smoothing)
- Swing Trading: Standard settings (12,26,9 with moderate smoothing)
- Position Trading: Smooth/Conservative settings (15,35,12 with higher smoothing)
- Custom: Full manual control over all parameters
Histogram Smoothing:
The histogram can be smoothed using EMA to reduce noise and filter minor fluctuations. Smoothing length of 1 = raw histogram (no smoothing), higher values (3-5) = smoother histogram. Increased smoothing reduces noise but may delay signals slightly.
Percentage Mode:
MACD values can be converted to percentage of price (MACD/Close*100) for cross-instrument comparison. This is useful when comparing MACD signals across instruments with different price levels (e.g., BTC vs ETH). The percentage mode normalizes MACD values, making them comparable regardless of instrument price.
MACD Scale Factor:
A scale factor multiplier (default 1.0) allows adjusting MACD display size for better visibility. Use 0.3-0.5 if MACD appears too compressed, or 2.0-3.0 if too small.
Dynamic Overbought/Oversold Levels:
Overbought and oversold levels are calculated dynamically based on MACD's mean and standard deviation over a lookback period. The formula: OB = MACD Mean + (StdDev × OB Multiplier), OS = MACD Mean - (StdDev × OS Multiplier). This adapts to current market conditions, widening in volatile markets and narrowing in calm markets. The lookback period (default 20) controls how quickly the levels adapt: longer periods (30-50) = more stable levels, shorter (10-15) = more responsive.
OB/OS Background Coloring:
Optional background coloring can highlight the entire panel when MACD enters overbought or oversold territory, providing prominent visual indication of extreme conditions. The background colors are drawn on top of the main background to ensure visibility.
Divergence Detection
Regular Divergence:
The script uses the MACD line (not histogram) for divergence detection, which provides more reliable signals. Bullish divergence: Price makes a lower low while MACD line makes a higher low. Bearish divergence: Price makes a higher high while MACD line makes a lower high. Divergences often precede reversals and are powerful reversal signals.
Pivot-Based Divergence:
The divergence detection uses actual pivot points (pivotlow/pivothigh) instead of simple lowest/highest comparisons. This provides more accurate divergence detection by identifying significant pivot lows/highs in both price and MACD line. The pivot-based method compares two recent pivot points: for bullish divergence, price makes a lower low while MACD makes a higher low at the pivot points. This method reduces false divergences by requiring actual pivot points rather than just any low/high within a period.
The pivot lookback parameters (left and right) control how many bars on each side of a pivot are required for confirmation. Higher values = more conservative pivot detection.
Hidden Divergence:
Continuation patterns that signal trend continuation rather than reversal. Bullish hidden divergence: Price makes a higher low but MACD makes a lower low. Bearish hidden divergence: Price makes a lower high but MACD makes a higher high. These patterns indicate the trend is likely to continue in the current direction.
Zero-Line Filter:
The "Don't Touch Zero Line" option ensures divergences occur in proper context: for bullish divergence, MACD must stay below zero; for bearish divergence, MACD must stay above zero. This filters out divergences that occur in neutral zones.
Range Filtering:
Minimum and maximum lookback ranges control the time window between pivots to consider for divergence. This helps filter out divergences that are too close together (noise) or too far apart (less relevant).
Volume Confirmation System
Volume threshold filtering requires current volume to exceed the volume SMA multiplied by the threshold factor. The formula: Volume Confirmed = Volume > (Volume SMA × Threshold). If the threshold is set to 1.0 or lower, volume confirmation is effectively disabled (always returns true). This allows you to use the indicator without volume filtering if desired. Volume confirmation significantly increases divergence and signal reliability.
Volume Climax and Dry-Up Detection:
The script can mark bars with extremely high volume (volume climax) or extremely low volume (volume dry-up). Volume climax indicates potential reversal points or strong momentum continuation. Volume dry-up indicates low participation and may produce unreliable signals. These markers use standard deviation multipliers to identify extreme volume conditions.
Zero-Line Cross Detection
MACD zero-line crosses indicate momentum shifts: above zero = bullish momentum, below zero = bearish momentum. The script includes alert conditions for zero-line crosses with cooldown protection to prevent alert spam. Zero-line crosses can provide early warning signals before MACD crosses the signal line.
Histogram Analysis Tools
Histogram Moving Average:
A moving average applied to the histogram itself helps identify histogram trend direction and acts as a signal line for histogram movements. Supports EMA, SMA, RMA, and WMA types. Useful for identifying when histogram momentum is strengthening or weakening.
Histogram Bollinger Bands:
Bollinger Bands are applied to the MACD histogram instead of price. The calculation: Basis = SMA(Histogram, Period), StdDev = stdev(Histogram, Period), Upper = Basis + (StdDev × Deviation Multiplier), Lower = Basis - (StdDev × Deviation Multiplier). This creates dynamic zones around the histogram that adapt to histogram volatility. When the histogram touches or exceeds the bands, it indicates extreme conditions relative to recent histogram behavior.
Stochastic MACD (StochMACD):
Stochastic MACD applies the Stochastic oscillator formula to the MACD histogram instead of price. This normalizes the histogram to a 0-100 scale, making it easier to identify overbought/oversold conditions on the histogram itself. The calculation: %K = ((Histogram - Lowest Histogram) / (Highest Histogram - Lowest Histogram)) × 100. %K is smoothed, and %D is calculated as the moving average of smoothed %K. Standard thresholds are 80 (overbought) and 20 (oversold).
Regression Forecasting
The script includes advanced regression forecasting that predicts future MACD values using mathematical models. This helps anticipate potential MACD movements and provides forward-looking context for trading decisions.
Regression Types:
- Linear: Simple trend line (y = mx + b) - fastest, works well for steady trends
- Polynomial: Quadratic curve (y = ax² + bx + c) - captures curvature in MACD movement
- Exponential Smoothing: Weighted average with more weight on recent values - responsive to recent changes
- Moving Average: Uses difference between short and long MA to estimate trend - stable and smooth
Forecast Horizon:
Number of bars to forecast ahead (default 5, max 50 for linear/MA, max 20 for polynomial due to performance). Longer horizons predict further ahead but may be less accurate.
Confidence Bands:
Optional upper/lower bands around forecast show prediction uncertainty based on forecast error (standard deviation of prediction vs actual). Wider bands = higher uncertainty. The confidence level multiplier (default 1.5) controls band width.
Forecast Display:
Forecast appears as dotted lines extending forward from current bar, with optional confidence bands. All forecast values respect percentage mode and scale factor settings.
Strong Top/Bottom Signals
The script detects strong recovery from extreme MACD levels, generating "sBottom" and "sTop" signals. These identify significant reversal potential when MACD recovers substantially from overbought/oversold extremes.
Strong Bottom (sBottom):
Triggered when:
1. MACD was at or near its lowest point in the bottom period (default 10 bars)
2. MACD was in or near the oversold zone
3. MACD has recovered by at least the threshold amount (default 0.5) from the lowest point
4. Recovery persists for confirmation bars (default 2 consecutive bars)
5. MACD has moved out of the oversold zone
6. Volume is above average
7. All enabled filters pass
8. Minimum bars have passed since last signal (reset period, default 5 bars)
Strong Top (sTop):
Triggered when:
1. MACD was at or near its highest point in the top period (default 7 bars)
2. MACD was in or near the overbought zone
3. MACD has declined by at least the threshold amount (default 0.5) from the highest point
4. Decline persists for confirmation bars (default 2 consecutive bars)
5. MACD has moved out of the overbought zone
6. Volume is above average
7. All enabled filters pass
8. Minimum bars have passed since last signal (reset period, default 5 bars)
Label Placement:
sTop/sBottom labels appear on the historical bar where the actual extreme occurred (not on current bar), showing the exact MACD value at that extreme. Labels respect the unified distance checking system to prevent overlaps with Buy/Sell Strength labels.
Signal Strength Calculation
The script calculates a composite signal strength score (0-100) based on multiple factors:
- MACD distance from signal line (0-50 points): Larger separation indicates stronger signal
- Volume confirmation (0-15 points): Volume above average adds points
- Secondary timeframe alignment (0-15 points): Higher timeframe agreement adds points
- Distance from zero line (0-20 points): Closer to zero can indicate stronger reversal potential
Higher scores (70+) indicate stronger, more reliable signals. The signal strength is displayed in the statistics table and can be used as a filter to only accept signals above a threshold.
Smart Label Placement System
The script includes an advanced label placement system that tracks MACD extremes and places Buy/Sell Strength labels at optimal locations:
Label Placement Algorithm:
- Labels appear on the current bar at confirmation (not on historical extreme bars), ensuring they're visible when the signal is confirmed
- The system tracks pending signals when MACD enters OB/OS zones or crosses the signal line
- During tracking, the system continuously searches for the true extreme (lowest MACD for buys, highest MACD for sells) within a configurable historical lookback period
- Labels are only finalized when: (1) MACD exits the OB/OS zone, (2) sufficient bars have passed (2x minimum distance), (3) MACD has recovered/declined by a configurable percentage from the extreme (default 15%), and (4) tracking has stopped (no better extreme found)
Label Spacing and Overlap Prevention:
- Minimum Bars Between Labels: Base distance requirement (default 5 bars)
- Label Spacing Multiplier: Scales the base distance (default 1.5x) for better distribution. Higher values = more spacing between labels
- Effective distance = Base Distance × Spacing Multiplier (e.g., 5 × 1.5 = 7.5 bars minimum)
- Unified distance checking prevents overlaps between all label types (Buy Strength, Sell Strength, sTop, sBottom)
Strength-Based Filtering:
- Label Strength Minimum (%): Only labels with strength at or above this threshold are displayed (default 75%)
- When multiple potential labels are close together, the system automatically compares strengths and keeps only the strongest one
- This ensures only the most significant signals are displayed, reducing chart clutter
Zero Line Polarity Enforcement:
- Enforce Zero Line Polarity (default enabled): Ensures labels follow traditional MACD interpretation
- Buy Strength labels only appear when the tracked extreme MACD value was below zero (negative territory)
- Sell Strength labels only appear when the tracked extreme MACD value was above zero (positive territory)
- This prevents counter-intuitive labels (e.g., Buy labels above zero line) and aligns with standard MACD trading principles
Recovery/Decline Confirmation:
- Recovery/Decline Confirm (%): Percent move away from the extreme required before finalizing (default 15%)
- For Buy labels: MACD must recover by at least this percentage from the tracked bottom
- For Sell labels: MACD must decline by at least this percentage from the tracked top
- Higher values = more confirmation required, fewer but more reliable labels
Historical Lookback:
- Historical Lookback for Label Placement: Number of bars to search for true extremes (default 20)
- The system searches within this period to find the actual lowest/highest MACD value
- Higher values analyze more history but may be slower; lower values are faster but may miss some extremes
Cross Quality Score
The script calculates a MACD cross quality score (0-100) that rates crossover quality based on:
- Cross angle (0-50 points): Steeper crosses = stronger signals
- Volume confirmation (0-25 points): Volume above average adds points
- Distance from zero line (0-25 points): Crosses near zero line are stronger
This score helps identify high-quality crossovers and can be used as a filter to only accept signals meeting minimum quality threshold.
Filtering System
Histogram Filter:
Requires histogram to be above zero for buy signals, below zero for sell signals. Ensures momentum alignment before generating signals.
Signal Strength Filter:
Requires minimum signal strength score for signals. Higher threshold = only strongest signals pass. This combines multiple confirmation factors into a single filter.
Cross Quality Filter:
Requires minimum cross quality score for signals. Rates crossover quality based on angle, volume, momentum, and distance from zero. Only signals meeting minimum quality threshold will be generated.
All filters use the pattern: filterResult = not filterEnabled OR conditionMet. This means if a filter is disabled, it always passes (returns true). Filters can be combined, and all must pass for a signal to fire.
Multi-Timeframe Analysis
The script can display MACD from a secondary (higher) timeframe and use it for confirmation. When secondary timeframe confirmation is enabled, signals require the higher timeframe MACD to align (bullish/bearish) with the signal direction. This ensures signals align with the larger trend context, reducing counter-trend trades.
Secondary Timeframe MACD:
The secondary timeframe MACD uses the same calculation parameters (fast, slow, signal, MA type) as the main MACD but from a higher timeframe. This provides context for the current timeframe's MACD position relative to the larger trend. The secondary MACD lines are displayed on the chart when enabled.
Noise Filtering
Noise filtering hides small histogram movements below a threshold. This helps focus on significant moves and reduces chart clutter. When enabled, only histogram movements above the threshold are displayed. Typical threshold values are 0.1-0.5 for most instruments, depending on the instrument's price range and volatility.
Signal Debounce
Signal debounce prevents duplicate MACD cross signals within a short time period. Useful when MACD crosses back and forth quickly, creating multiple signals. Debounce ensures only one signal per period, reducing signal spam during choppy markets. This is separate from alert cooldown, which applies to all alert types.
Background Color Modes
The script offers three background color modes:
- Dynamic: Full MACD heatmap based on OB/OS conditions, confidence, and momentum. Provides rich visual feedback.
- Monotone: Soft neutral background but still allows overlays (OB/OS zones). Keeps the chart clean without overpowering candles.
- Off: No MACD background (only overlays and plots). Maximum chart cleanliness.
When OB/OS background colors are enabled, they are drawn on top of the main background to ensure visibility.
Statistics Table
A real-time statistics table displays current MACD values, signal strength, distance from zero line, secondary timeframe alignment, volume confirmation status, and all active filter statuses. The table dynamically adjusts to show only enabled features, keeping it clean and relevant. The table position can be configured (Top Left, Top Right, Bottom Left, Bottom Right).
Performance Statistics Table
An optional performance statistics table shows comprehensive filter diagnostics:
- Total buy/sell signals (raw crossover count before filters)
- Filtered buy/sell signals (signals that passed all filters)
- Overall pass rates (percentage of signals that passed filters)
- Rejected signals count
- Filter-by-filter rejection diagnostics showing which filters rejected how many signals
This table helps optimize filter settings by showing which filters are most restrictive and how they impact signal frequency. The diagnostics format shows rejections as "X B / Y S" (X buy signals rejected, Y sell signals rejected) or "Disabled" if the filter is not active.
Alert System
The script includes separate alert conditions for each signal type:
- MACD Cross: MACD line crosses above/below Signal line (with or without secondary confirmation)
- Zero-Line Cross: MACD crosses above/below zero
- Divergence: Regular and hidden divergence detections
- Secondary Timeframe: Higher timeframe MACD crosses
- Histogram MA Cross: Histogram crosses above/below its moving average
- Histogram Zero Cross: Histogram crosses above/below zero
- StochMACD: StochMACD overbought/oversold entries and %K/%D crosses
- Histogram BB: Histogram touches/breaks Bollinger Bands
- Volume Events: Volume climax and dry-up detections
- OB/OS: MACD entry/exit from overbought/oversold zones
- Strong Top/Bottom: sTop and sBottom signal detections
Each alert type has its own cooldown system to prevent alert spam. The cooldown requires a minimum number of bars between alerts of the same type, reducing duplicate alerts during volatile periods. Alert types can be filtered to only evaluate specific alert types (All, MACD Cross, Zero Line, Divergence, Secondary Timeframe, Histogram MA, Histogram Zero, StochMACD, Histogram BB, Volume Events, OB/OS, Strong Top/Bottom).
How Components Work Together
MACD crossovers provide the primary signal when the MACD line crosses the Signal line. Zero-line crosses indicate momentum shifts and can provide early warning signals. Divergences identify potential reversals before they occur.
Volume confirmation ensures signals occur with sufficient market participation, filtering out low-volume false breakouts. Histogram analysis tools (MA, Bollinger Bands, StochMACD) provide additional context for signal reliability and identify significant histogram zones.
Signal strength combines multiple confirmation factors into a single score, making it easy to filter for only the strongest signals. Cross quality score rates crossover quality to identify high-quality setups. Multi-timeframe confirmation ensures signals align with higher timeframe trends, reducing counter-trend trades.
Usage Instructions
Getting Started:
The default configuration shows MACD(12,26,9) with standard EMA calculations. Start with default settings and observe behavior, then customize settings to match your trading style. You can use configuration presets for quick setup based on your trading style.
Customizing MACD Parameters:
Adjust Fast Length (default 12), Slow Length (default 26), and Signal Length (default 9) based on your trading timeframe. Shorter periods (8,17,7) for faster signals, longer (15,30,12) for smoother signals. You can change the moving average type: EMA for responsiveness, RMA for smoothness, WMA for recent price emphasis.
Price Source Selection:
Choose Close (standard), or alternative sources (HL2, HLC3, OHLC4) for different sensitivity. HL2 uses the midpoint of the high-low range, HLC3 and OHLC4 incorporate more price information.
Histogram Smoothing:
Set smoothing to 1 for raw histogram (no smoothing), or increase (3-5) for smoother histogram that reduces noise. Higher smoothing reduces false signals but may delay signals slightly.
Percentage Mode:
Enable percentage mode when comparing MACD across instruments with different price levels. This normalizes MACD values, making them directly comparable.
Dynamic OB/OS Levels:
The dynamic thresholds automatically adapt to volatility. Adjust the multipliers (default 1.5) to fine-tune sensitivity: higher values (2.0-3.0) = more extreme thresholds (fewer signals), lower (1.0-1.5) = more frequent signals. Adjust the lookback period to control how quickly levels adapt. Enable OB/OS background colors for visual indication of extreme conditions.
Volume Confirmation:
Set volume threshold to 1.0 (default, effectively disabled) or higher (1.2-1.5) for standard confirmation. Higher values require more volume for confirmation. Set to 0.1 to completely disable volume filtering.
Filters:
Enable filters gradually to find your preferred balance. Start with histogram filter for basic momentum alignment, then add signal strength filter (threshold 50+) for moderate signals, then cross quality filter (threshold 50+) for high-quality crossovers. Combine filters for highest-quality signals but expect fewer signals.
Divergence:
Enable divergence detection and adjust pivot lookback parameters. Pivot-based divergence provides more accurate detection using actual pivot points. Hidden divergence is useful for trend-following strategies. Adjust range parameters to filter divergences by time window.
Zero-Line Crosses:
Zero-line cross alerts are automatically available when alerts are enabled. These provide early warning signals for momentum shifts.
Histogram Analysis Tools:
Enable Histogram Moving Average to see histogram trend direction. Enable Histogram Bollinger Bands to identify extreme histogram zones. Enable Stochastic MACD to normalize histogram to 0-100 scale for overbought/oversold identification.
Multi-Timeframe:
Enable secondary timeframe MACD to see higher timeframe context. Enable secondary confirmation to require higher timeframe alignment for signals.
Signal Strength:
Signal strength is automatically calculated and displayed in the statistics table. Use signal strength filter to only accept signals above a threshold (e.g., 50 for moderate, 70+ for strong signals only).
Smart Label Placement:
Configure label placement settings to control label appearance and quality:
- Label Strength Minimum (%): Set threshold (default 75%) to show only strong signals. Higher = fewer, stronger labels
- Label Spacing Multiplier: Adjust spacing (default 1.5x) for better distribution. Higher = more spacing between labels
- Recovery/Decline Confirm (%): Set confirmation requirement (default 15%). Higher = more confirmation, fewer labels
- Enforce Zero Line Polarity: Enable (default) to ensure Buy labels only appear when tracked extreme was below zero, Sell labels only when above zero
- Historical Lookback: Adjust search period (default 20 bars) for finding true extremes. Higher = more history analyzed
Cross Quality:
Cross quality score is automatically calculated for crossovers. Use cross quality filter to only accept high-quality crossovers (threshold 50+ for moderate, 70+ for high quality).
Alerts:
Set up alerts for your preferred signal types. Enable alert cooldown (default enabled, 5 bars) to prevent alert spam. Use alert type filter to only evaluate specific alert types (All, MACD Cross, Zero Line, Divergence, Secondary Timeframe, Histogram MA, Histogram Zero, StochMACD, Histogram BB, Volume Events, OB/OS, Strong Top/Bottom). Each signal type has its own alert condition, so you can be selective about which signals trigger alerts.
Visual Elements and Signal Markers
The script uses various visual markers to indicate signals and conditions:
- MACD Line: Green when above signal (bullish), red when below (bearish) if dynamic colors enabled. Optional black outline for enhanced visibility
- Signal Line: Orange line with optional black outline for enhanced visibility
- Histogram: Color-coded based on direction and momentum (green for bullish rising, lime for bullish falling, red for bearish falling, orange for bearish rising)
- Zero Line: Horizontal reference line at MACD = 0
- Fill to Zero: Green/red semi-transparent fill between MACD line and zero line showing bullish/bearish territory
- Fill Between OB/OS: Blue semi-transparent fill between overbought/oversold thresholds highlighting neutral zone
- OB/OS Background Colors: Background coloring when MACD enters overbought/oversold zones
- Background Colors: Dynamic or monotone backgrounds indicating MACD state, or custom chart background
- Divergence Labels: "🐂" for bullish, "🐻" for bearish, "H Bull" for hidden bullish, "H Bear" for hidden bearish
- Divergence Lines: Colored lines connecting pivot points when divergences are detected
- Volume Climax Markers: ⚡ symbol for extremely high volume
- Volume Dry-Up Markers: 💧 symbol for extremely low volume
- Buy/Sell Strength Labels: Show signal strength percentage (e.g., "Buy Strength: 75%")
- Strong Top/Bottom Labels: "sTop" and "sBottom" for extreme level recoveries
- Secondary MACD Lines: Purple lines showing higher timeframe MACD
- Histogram MA: Orange line showing histogram moving average
- Histogram BB: Blue bands around histogram showing extreme zones
- StochMACD Lines: %K and %D lines with overbought/oversold thresholds
- Regression Forecast: Dotted blue lines extending forward with optional confidence bands
Signal Priority and Interpretation
Signals are generated independently and can occur simultaneously. Higher-priority signals generally indicate stronger setups:
1. MACD Cross with Multiple Filters - Highest priority: Requires MACD crossover plus all enabled filters (histogram, signal strength, cross quality) and secondary timeframe confirmation if enabled. These are the most reliable signals.
2. Zero-Line Cross - High priority: Indicates momentum shift. Can provide early warning signals before MACD crosses the signal line.
3. Divergence Signals - Medium-High priority: Pivot-based divergence is more reliable than simple divergence. Hidden divergence indicates continuation rather than reversal.
4. MACD Cross with Basic Filters - Medium priority: MACD crosses signal line with basic histogram filter. Less reliable alone but useful when combined with other confirmations.
Best practice: Wait for multiple confirmations. For example, a MACD crossover combined with divergence, volume confirmation, and secondary timeframe alignment provides the strongest setup.
Chart Requirements
For proper script functionality and compliance with TradingView requirements, ensure your chart displays:
- Symbol name: The trading pair or instrument name should be visible
- Timeframe: The chart timeframe should be clearly displayed
- Script name: "Ultimate MACD " should be visible in the indicator title
These elements help traders understand what they're viewing and ensure proper script identification. The script automatically includes this information in the indicator title and chart labels.
Performance Considerations
The script is optimized for performance:
- Calculations use efficient Pine Script functions (ta.ema, ta.sma, etc.) which are optimized by TradingView
- Conditional execution: Features only calculate when enabled
- Label management: Old labels are automatically deleted to prevent accumulation
- Array management: Divergence label arrays are limited to prevent memory accumulation
The script should perform well on all timeframes. On very long historical data with many enabled features, performance may be slightly slower, but it remains usable.
Known Limitations and Considerations
- Dynamic OB/OS levels can vary significantly based on recent MACD volatility. In very volatile markets, levels may be wider; in calm markets, they may be narrower.
- Volume confirmation requires sufficient historical volume data. On new instruments or very short timeframes, volume calculations may be less reliable.
- Higher timeframe MACD uses request.security() which may have slight delays on some data feeds.
- Stochastic MACD requires the histogram to have sufficient history. Very short periods on new charts may produce less reliable StochMACD values initially.
- Divergence detection requires sufficient historical data to identify pivot points. Very short lookback periods may produce false positives.
Practical Use Cases
The indicator can be configured for different trading styles and timeframes:
Swing Trading:
Use MACD(12,26,9) with secondary timeframe confirmation. Enable divergence detection. Use signal strength filter (threshold 50+) and cross quality filter (threshold 50+) for higher-quality signals. Enable histogram analysis tools for additional context.
Day Trading:
Use MACD(8,17,7) or use "Day Trading" preset with minimal histogram smoothing for faster signals. Enable zero-line cross alerts for early signals. Use volume confirmation with threshold 1.2-1.5. Enable histogram MA for momentum tracking.
Trend Following:
Use MACD(12,26,9) or longer periods (15,30,12) for smoother signals. Enable secondary timeframe confirmation for trend alignment. Hidden divergence signals are useful for trend continuation entries. Use cross quality filter to identify high-quality crossovers.
Reversal Trading:
Focus on divergence detection (pivot-based for accuracy) combined with zero-line crosses. Enable volume confirmation. Use histogram Bollinger Bands to identify extreme histogram zones. Enable StochMACD for overbought/oversold identification.
Multi-Timeframe Analysis:
Enable secondary timeframe MACD to see context from larger timeframes. For example, use daily MACD on hourly charts to understand the larger trend context. Enable secondary confirmation to require higher timeframe alignment for signals.
Practical Tips and Best Practices
Getting Started:
Start with default settings and observe MACD behavior. The default configuration (MACD 12,26,9 with EMA) is balanced and works well across different markets. After observing behavior, customize settings to match your trading style. Consider using configuration presets for quick setup.
Reducing Repainting:
All signals are based on confirmed bars, minimizing repainting. The script uses confirmed bar data for all calculations to ensure backtesting accuracy.
Signal Quality:
MACD crosses with multiple filters provide the highest-quality signals because they require alignment across multiple indicators. These signals have lower frequency but higher reliability. Use signal strength scores to identify the strongest signals (70+). Use cross quality scores to identify high-quality crossovers (70+).
Filter Combinations:
Start with histogram filter for basic momentum alignment, then add signal strength filter for moderate signals, then cross quality filter for high-quality crossovers. Combining all filters significantly reduces false signals but also reduces signal frequency. Find your balance based on your risk tolerance.
Volume Filtering:
Set volume threshold to 1.0 (default, effectively disabled) or lower to effectively disable volume filtering if you trade instruments with unreliable volume data or want to test without volume confirmation. Standard confirmation uses 1.2-1.5 threshold.
MACD Period Selection:
Standard MACD(12,26,9) provides balanced signals suitable for most trading. Shorter periods (8,17,7) for faster signals, longer (15,30,12) for smoother signals. Adjust based on your timeframe and trading style. Consider using configuration presets for optimized settings.
Moving Average Type:
EMA provides balanced responsiveness with smoothness. RMA is smoother and less responsive. WMA gives more weight to recent prices. SMA gives equal weight to all periods. Choose based on your preference for responsiveness vs. smoothness.
Divergence:
Pivot-based divergence is more reliable than simple divergence because it uses actual pivot points. Hidden divergence indicates continuation rather than reversal, useful for trend-following strategies. Adjust pivot lookback parameters to control sensitivity.
Dynamic Thresholds:
Dynamic OB/OS thresholds automatically adapt to volatility. In volatile markets, thresholds widen; in calm markets, they narrow. Adjust the multipliers to fine-tune sensitivity. Enable OB/OS background colors for visual indication.
Zero-Line Crosses:
Zero-line crosses indicate momentum shifts and can provide early warning signals before MACD crosses the signal line. Enable alerts for zero-line crosses to catch these early signals.
Alert Management:
Enable alert cooldown (default enabled, 5 bars) to prevent alert spam. Use alert type filter to only evaluate specific alert types. Signal debounce (default enabled, 3 bars) prevents duplicate MACD cross signals during choppy markets.
Technical Specifications
- Pine Script Version: v6
- Indicator Type: Non-overlay (displays in separate panel below price chart)
- Repainting Behavior: Minimal - all signals are based on confirmed bars, ensuring accurate backtesting results
- Performance: Optimized with conditional execution. Features only calculate when enabled.
- Compatibility: Works on all timeframes (1 minute to 1 month) and all instruments (stocks, forex, crypto, futures, etc.)
- Edge Case Handling: All calculations include safety checks for division by zero, NA values, and boundary conditions. Alert cooldowns and signal debounce handle edge cases where conditions never occurred or values are NA.
Technical Notes
- All MACD values respect percentage mode conversion when enabled
- Volume confirmation uses cached volume SMA for performance
- Label arrays (divergence) are automatically limited to prevent memory accumulation
- Background coloring: OB/OS backgrounds are drawn on top of main background to ensure visibility
- All calculations are optimized with conditional execution - features only calculate when enabled (performance optimization)
- Signal strength calculation combines multiple factors into a single score for easy filtering
- Cross quality calculation rates crossover quality based on angle, volume, and distance from zero
- Secondary timeframe MACD uses request.security() for higher timeframe data access
- Histogram analysis features (Bollinger Bands, MA, StochMACD) provide additional context beyond basic MACD signals
- Statistics table dynamically adjusts to show only enabled features, keeping it clean and relevant
- Divergence detection uses MACD line (not histogram) for more reliable signals
- Configuration presets automatically optimize MACD parameters for different trading styles
- Smart label placement: Labels appear on current bar at confirmation, using strength from tracked extreme point
- Label spacing uses effective distance (base distance × spacing multiplier) for better distribution
- Zero line polarity enforcement ensures Buy labels only appear when tracked extreme MACD < 0, Sell labels only when tracked extreme MACD > 0
- Label finalization requires MACD exit from OB/OS zone, sufficient bars passed, and recovery/decline percentage confirmation
- Strength-based filtering automatically compares and keeps only the strongest label when multiple signals are close together
- Enhanced visualization: Line outlines drawn behind main lines for superior visibility (black default, configurable)
- Enhanced visualization: Fill between MACD and zero line provides instant visual feedback (green above, red below)
- Enhanced visualization: Fill between OB/OS thresholds highlights neutral zone when dynamic levels are active
- Custom chart background overrides background mode when enabled, allowing theme-consistent indicator panels
Order Blocks & ImbalanceThis indicator automatically identifies and plots Order Blocks (also known as Fair Value Gaps or Imbalances) based on Smart Money Concepts (SMC) and ICT methodology. It detects significant price inefficiencies (gaps between candles) that often act as institutional supply or demand zones.
How It Works (Technical Methodology)
1. Fair Value Gap (FVG) Detection
The indicator identifies classic 3-candle imbalances:
- Bullish Order Block (Demand): When the low of the current candle is significantly below the high of the candle two bars ago (low - high ).
- Bearish Order Block (Supply): When the high of the current candle is significantly above the low of the candle two bars ago (low - high ).
A minimum size threshold is enforced using ATR(14) × user-defined multiplier (default 0.5) to filter out minor gaps and focus on meaningful inefficiencies.
2. Zone Creation
- Bullish zones are created at the candle two bars ago (the "origin" candle where inefficiency occurred).
- Bearish zones use the same origin candle.
- Zone boundaries:
Top = high of origin candle
Bottom = low of origin candle
This captures the full range where price moved aggressively, leaving an imbalance that institutions may later revisit.
3. Mitigation Detection
Zones can be mitigated in two ways (user-selectable):
- "Close": Zone is considered touched only if the close price enters the zone.
- "Wick": Zone is touched if any wick (high/low) enters the zone (more sensitive).
When mitigated:
- Background becomes more transparent
- Border turns dotted
- Label changes to "Mitigated"
Broken zones (price fully closes beyond the opposite side) are automatically deleted.
4. Zone Lifecycle Management
- Active Zone: Strong color fill (green for demand, red for supply) with solid border.
- Mitigated Zone: Faded color, dotted border – indicates partial fill or reduced strength.
- Broken Zone: Automatically removed from chart to reduce clutter.
Old zones are also pruned when exceeding 450 total to maintain performance.
5. Smart Visibility Engine (Optional)
When enabled:
- All zones are initially hidden.
- Only the closest relevant zones are shown:
- Up to user-defined limit (default 10) highest bullish zones (closest below price)
- Up to user-defined limit (default 10) lowest bearish zones (closest above price)
- Visible zones are automatically extended to the right and styled appropriately.
This keeps the chart clean while highlighting the most actionable zones near current price.
6. Visual Elements
- Demand Zones: Green fill, labeled "OB Demand"
- Supply Zones: Red fill, labeled "OB Supply"
- Tiny text size to minimize chart clutter
- Zones drawn as boxes using bar_index positioning
How to Use
Order Blocks represent areas of price inefficiency where smart money likely entered/exited positions aggressively.
- Demand Zones (Green): Potential long entry areas when price returns. Expect buying pressure to defend these levels. Best setups when price retests an active (non-mitigated) zone.
- Supply Zones (Red): Potential short entry areas when price returns. Expect selling pressure to emerge.
- Mitigated Zones: Lower probability – may act as weaker support/resistance.
- Smart Visibility: Highly recommended for cleaner charts. Focuses attention on zones most likely to be tested soon.
- Combine with:
- Break of Structure (BOS)/Change of Character (CHOCH)
- Liquidity grabs
- Higher timeframe confluence
- Volume or momentum confirmation
Use higher FVG threshold (e.g., 0.8–1.0) for fewer, higher-quality zones. Lower threshold for more aggressive detection.
Disclaimer
This indicator is a technical analysis tool and should be used in conjunction with other forms of analysis. Past performance does not guarantee future results. Always use proper risk management.
Alpha Options System# Apex Options Sniper - Advanced Multi-Signal Day Trading System
## 🎯 Overview
**Apex Options Sniper** is a professional-grade, multi-signal trading indicator specifically engineered for high-probability day trading of weekly options. This comprehensive system combines 10+ technical indicators into a sophisticated scoring algorithm that identifies optimal entry points with institutional-level precision.
Perfect for traders of SPY, QQQ, and high-volume stocks, this indicator eliminates guesswork by providing clear BUY CALLS and BUY PUTS signals based on multiple technical confluences.
---
## 🚀 Key Features
### **Multi-Signal Confluence Engine**
- **10+ Technical Indicators** working in harmony
- **Weighted Scoring System** (0-30+ points) for signal strength
- **Real-time Signal Classification**: Strong vs Moderate signals
- **False Signal Reduction** through multi-confirmation requirements
### **Advanced Momentum Analysis**
- ✅ RSI with Divergence Detection (bullish & bearish)
- ✅ Stochastic Oscillator (oversold/overbought + crossovers)
- ✅ MACD with crossover and momentum confirmation
- ✅ Automatic divergence spotting for reversal trades
### **Sophisticated Trend Detection**
- ✅ Triple EMA System (9/21/50) with alignment scoring
- ✅ SuperTrend Indicator with trend flip alerts
- ✅ VWAP for institutional price levels
- ✅ Multi-timeframe trend confirmation
### **Professional Volume Analysis**
- ✅ Volume Spike Detection (vs 20-period average)
- ✅ OBV (On-Balance Volume) with divergence detection
- ✅ Order Flow Analysis (buy vs sell pressure)
- ✅ Relative volume ratio display
### **Advanced Pattern Recognition**
- ✅ Bollinger Band Squeeze detection (volatility expansion)
- ✅ BB breakout signals (major move initiation)
- ✅ Automatic Support & Resistance levels (pivot-based)
- ✅ Price reaction scoring at key levels
### **Built-in Risk Management**
- ✅ ATR-based Stop Loss calculations
- ✅ Customizable Risk:Reward ratios
- ✅ Position sizing recommendations
- ✅ Real-time profit target calculations
### **Comprehensive Visual Dashboard**
- ✅ Live scoring breakdown for all indicators
- ✅ Individual signal strength display
- ✅ Bull vs Bear score comparison
- ✅ Color-coded signal status
- ✅ Risk management metrics
---
## 📊 How It Works
### **Scoring System**
The indicator assigns points based on technical conditions:
| **Category** | **Max Points** | **Conditions** |
|-------------|---------------|----------------|
| Momentum (RSI/Stoch) | 8 | Oversold/overbought + divergences |
| MACD | 4 | Crossovers + momentum direction |
| Trend (EMAs) | 6 | EMA alignment + SuperTrend |
| Volume | 4 | Spikes + OBV divergences |
| Order Flow | 2 | Buy/sell pressure imbalance |
| Bollinger Bands | 2 | Squeeze + breakouts |
| Support/Resistance | 2 | Price at key levels |
| VWAP | 1 | Above/below institutional level |
### **Signal Thresholds**
- **🚀 STRONG CALLS**: Bull score ≥6, Net score ≥4
- **📈 CALLS**: Bull score ≥4, Net score ≥2
- **🔥 STRONG PUTS**: Bear score ≥6, Net score ≤-4
- **📉 PUTS**: Bear score ≥4, Net score ≤-2
### **Multi-Timeframe Filter**
Optional higher timeframe confirmation reduces false signals by ensuring the broader trend supports your trade direction.
---
## 🎮 How to Use
### **Installation**
1. Open TradingView Pine Editor
2. Paste the complete indicator code
3. Click "Add to Chart"
4. Customize settings to your preference
### **Recommended Settings**
**For SPY/QQQ Day Trading:**
- Timeframe: 1-minute or 5-minute
- Strong Signal Threshold: 6
- Moderate Signal Threshold: 4
- Multi-timeframe Confluence: ON
**For Individual Stocks:**
- Timeframe: 5-minute or 15-minute
- Increase SuperTrend multiplier to 3.5-4.0
- Enable all advanced features
**For Scalping:**
- Timeframe: 1-minute
- Use STRONG signals only (6+)
- Tight stop loss (1.0-1.5 ATR multiplier)
### **Best Trading Times**
- **9:30-11:00 AM EST** - Highest volume, strongest signals
- **2:00-4:00 PM EST** - Afternoon momentum plays
- Avoid 11:30 AM-1:30 PM EST (lunch chop)
---
## 📈 Signal Interpretation
### **What You'll See on Chart:**
**Visual Signals:**
- 🟢 **Green Triangle (CALLS)**: Bullish entry point
- 🟢 **Large Green Triangle (STRONG CALLS)**: High-confidence bullish entry
- 🔴 **Red Triangle (PUTS)**: Bearish entry point
- 🔴 **Large Red Triangle (STRONG PUTS)**: High-confidence bearish entry
- 💎 **Small Diamonds**: RSI/OBV divergences (reversal warning)
**Dashboard Information:**
- Individual indicator values and signals
- Real-time score breakdown
- Bull/Bear score totals
- ATR stop loss levels
### **Entry Rules:**
✅ **High Probability Trades (Take These):**
- Strong signal (6+ score)
- 3+ indicators confirming
- Volume spike present
- SuperTrend aligned
- Higher timeframe confirms
⚠️ **Moderate Trades (Smaller Position):**
- Moderate signal (4-5 score)
- 2+ indicators confirming
- Normal volume
- Mixed trend signals
❌ **Avoid These:**
- Conflicting signals (Bull score ≈ Bear score)
- Low volume
- During major news events
- Bollinger squeeze without breakout direction
---
## 🛡️ Risk Management Guide
### **Position Sizing:**
- **Strong Signals (6+)**: 3-5% of portfolio
- **Moderate Signals (4-5)**: 2-3% of portfolio
- **Low Conviction**: 1-2% or skip
### **Stop Loss Strategy:**
- Use ATR-based stops (displayed in dashboard)
- Default: 1.5x ATR from entry
- Weekly options: 30-50% premium loss maximum
- Never hold through stop loss hoping for recovery
### **Profit Targets:**
- **Quick Scalps**: 25-50% gain (15-30 min)
- **Day Trades**: 50-100% gain (same day exit)
- **Swing**: 100-200% gain (1-2 days max for weeklies)
- **Take partial profits** at first target, let rest run
### **Time Decay Management (Weekly Options):**
- Monday-Wednesday: Hold overnight acceptable on strong signals
- Thursday: Close by EOD unless very strong conviction
- Friday: Avoid holding overnight, theta decay accelerates
---
## 🔔 Alert Configuration
### **Recommended Alerts:**
**Essential Alerts:**
1. 🚀 Strong Buy Calls
2. 🔥 Strong Buy Puts
**Advanced Alerts:**
3. 💎 RSI Bullish Divergence
4. ⚠️ RSI Bearish Divergence
5. 🔶 Bollinger Band Squeeze
6. ✅ SuperTrend Bull Flip
7. ❌ SuperTrend Bear Flip
**Alert Setup:**
- Set frequency: "Once Per Bar Close"
- Enable for all devices
- Use webhook for automation (optional)
---
## 💡 Pro Trading Tips
### **Maximize Win Rate:**
1. **Wait for confluence** - Best trades have 3+ indicators aligned
2. **Respect the dashboard** - Check WHY it's signaling (which indicators)
3. **Volume is king** - Signals with volume spikes are significantly more reliable
4. **Use BB Squeeze** - When squeeze + signal = explosive directional move
5. **SuperTrend flips** - Major trend change confirmations, very powerful
6. **Watch for divergences** - Diamond markers = hidden reversal opportunities
### **Common Mistakes to Avoid:**
❌ Trading every signal (be selective)
❌ Ignoring volume (volume confirms everything)
❌ Fighting the higher timeframe trend
❌ Oversizing positions on moderate signals
❌ Holding weekly options too long (theta decay)
❌ Trading during lunch hour (11:30-1:30 EST)
### **Advanced Techniques:**
- **Divergence + Support/Resistance** = Highest probability reversals
- **BB Squeeze + EMA alignment** = Explosive trend continuations
- **SuperTrend flip + Volume spike** = Major trend change entries
- **Multiple timeframe analysis** - Check 5m signal on 1m chart for precision entries
---
## 📊 Indicator Components Explained
### **RSI (Relative Strength Index)**
- Measures momentum and overbought/oversold conditions
- Divergences signal potential reversals before they happen
- Score: 2-3 points for extremes and divergences
### **Stochastic Oscillator**
- Confirms momentum extremes
- Crossovers provide entry timing
- Score: 1-2 points
### **MACD (Moving Average Convergence Divergence)**
- Trend following momentum indicator
- Crossovers signal momentum shifts
- Score: 1-3 points based on signal strength
### **EMA System (9/21/50)**
- Dynamic support and resistance
- Alignment shows trend strength
- Price position relative to EMAs scores 1-2 points
### **SuperTrend**
- Volatility-based trend indicator
- Reduces whipsaws in choppy conditions
- Trend flips are major signals (2 points)
### **Bollinger Bands**
- Volatility measurement
- Squeeze = calm before the storm
- Breakouts = directional move initiation (2 points)
### **Volume Analysis**
- Confirms price movement legitimacy
- Spikes validate signals (2 points)
- OBV divergences predict reversals (2 points)
### **Order Flow**
- Buy vs sell pressure measurement
- Institutional footprint detection
- Score: 2 points for strong imbalances
---
## 🎓 Learning Path
### **Beginner (Week 1-2):**
- Use STRONG signals only
- Focus on high-volume stocks (SPY/QQQ)
- Trade only first hour of market
- Use paper trading first
### **Intermediate (Week 3-4):**
- Add moderate signals to your arsenal
- Learn to read the dashboard
- Understand why each signal triggers
- Start combining with support/resistance
### **Advanced (Month 2+):**
- Use divergence signals
- Trade BB squeeze breakouts
- Optimize settings for your style
- Develop your own confluence rules
---
## ⚙️ Customization Guide
### **Adjustable Parameters:**
**Momentum Settings:**
- RSI Length (default: 14)
- RSI Oversold/Overbought levels (30/70)
- Stochastic Length (14)
**Trend Settings:**
- EMA periods (9/21/50)
- SuperTrend ATR Length (10)
- SuperTrend Multiplier (3.0)
**Volume Settings:**
- Volume MA Length (20)
- Volume Spike Threshold (1.5x)
**Advanced Settings:**
- Bollinger Band Length (20)
- BB Standard Deviation (2.0)
- Pivot Lookback (10)
**Signal Thresholds:**
- Strong Signal Score (default: 6)
- Moderate Signal Score (default: 4)
**Risk Management:**
- ATR Length (14)
- Stop Loss Multiplier (1.5)
- Risk:Reward Ratio (2.0)
---
## 📈 Performance Optimization
### **For Volatile Markets (VIX > 25):**
- Increase SuperTrend multiplier to 4.0
- Raise signal thresholds (+1 point)
- Tighten stop losses (1.0-1.2 ATR)
### **For Ranging Markets:**
- Focus on RSI extremes and divergences
- Use BB squeeze signals
- Ignore moderate signals
- Wait for support/resistance confirmation
### **For Trending Markets:**
- Follow SuperTrend direction religiously
- Use EMA alignment signals
- Allow wider stops (2.0 ATR)
- Take partial profits, let winners run
---
## 🔍 Troubleshooting
**Too Many Signals:**
- Increase signal thresholds to 7/5
- Enable multi-timeframe filter
- Trade only STRONG signals
**Missing Signals:**
- Decrease thresholds to 5/3
- Disable multi-timeframe filter
- Check that all features are enabled
**Whipsaw in Choppy Markets:**
- Increase SuperTrend multiplier
- Require volume spike confirmation
- Avoid trading 11:30 AM-1:30 PM EST
---
## 🏆 Best Practices
✅ **Always check:**
1. Dashboard shows why signal triggered
2. Volume confirms the move
3. Not during news events
4. Adequate time until expiration
✅ **Risk Management:**
1. Never risk more than 2% per trade
2. Use stops religiously
3. Take profits at targets
4. Don't revenge trade
✅ **Journal Your Trades:**
1. Entry price and signal strength
2. Which indicators triggered
3. Exit price and profit/loss
4. What worked and what didn't
---
## 📞 Support & Updates
This indicator is designed to evolve with market conditions. Recommended to:
- Review settings monthly
- Backtest on your favorite instruments
- Adjust thresholds based on your risk tolerance
- Keep a trading journal to track performance
---
## ⚠️ Disclaimer
This indicator is a tool for technical analysis and should not be used as the sole basis for trading decisions. Options trading involves substantial risk and is not suitable for all investors. Past performance does not guarantee future results. Always:
- Do your own research and due diligence
- Never invest more than you can afford to lose
- Consider consulting with a financial advisor
- Practice with paper trading before using real money
- Understand options Greeks (Delta, Theta, Gamma, Vega)
- Be aware of earnings dates and major news events
**No indicator is 100% accurate. Use proper risk management and trade responsibly.**
---
## 📊 Version History
**v1.0 - Initial Release**
- Multi-signal confluence system
- 10+ technical indicators
- Advanced dashboard
- ATR-based risk management
- Comprehensive alert system
---
## 🎯 Final Thoughts
**Apex Options Sniper** transforms complex technical analysis into clear, actionable signals. By combining multiple proven indicators with sophisticated scoring logic, it helps traders identify high-probability setups while managing risk effectively.
**Success Keys:**
- Quality over quantity (be selective)
- Risk management is everything
- Volume confirms the signal
- Confluence increases probability
- Discipline beats emotion
**Trade smart. Trade with confidence. Trade with Apex Options Sniper.**
---
*For questions, suggestions, or to share your success stories, please comment below or send a message.*
**Happy Trading! 🚀📈**
