Volatility-Adjusted Momentum Oscillator (VAMO)Concept & Rationale: This indicator combines momentum and volatility into one oscillator. The idea is that a price move accompanied by high volatility has greater significance. We use Rate of Change (ROC) for momentum and Average True Range (ATR) for volatility, multiplying them to gauge “volatility-weighted momentum.” This concept is inspired by the Weighted Momentum & Volatility Indicator, which multiplies normalized ROC and ATR values. The result is shown as a histogram oscillating around zero – rising green bars indicate bullish momentum, while falling red bars indicate bearish momentum. When the histogram crosses above or below zero, it provides clear buy/sell signals. Higher magnitude bars suggest a stronger trend move. Crypto markets often see volatility spikes preceding big moves, so VAMO aims to capture those moments when momentum and volatility align for a powerful breakout.
Key Features:
Momentum-Volatility Fusion: Measures momentum (price ROC) adjusted by volatility (ATR). Strong trends register prominently only when price change is significant and volatility is elevated.
Intuitive Histogram: Plotted as a color-coded histogram around a zero line – green bars above zero for bullish trends, red bars below zero for bearish. This makes it easy to visualize trend strength and direction at a glance.
Clear Signals: A cross above 0 signals a buy, and below 0 signals a sell. Traders can also watch for the histogram peaking and then shrinking as an early sign of a trend reversal (e.g. bars switching from growing to shrinking while still positive could mean bullish momentum is waning).
Optimized for Volatility: Because ATR is built-in, the oscillator naturally adapts to crypto volatility. In calm periods, signals will be smaller (reducing noise), whereas during volatile swings the indicator accentuates the move, helping predict big price swings.
Customization: The lookback period is adjustable. Shorter periods (e.g. 5-10) make it more sensitive for scalping, while longer periods (20+) smooth it out for swing trading.
How to Use: When VAMO bars turn green and push above zero, it indicates bullish momentum with strong volatility – a cue that price is likely to rally in the near term. Conversely, red bars below zero signal bearish pressure. For example, if a coin’s price has been flat and then VAMO spikes green above zero, it suggests an explosive upward move is brewing. Traders can enter on the zero-line cross (or on the first green bar) and consider exiting when the histogram peaks and starts shrinking (signaling momentum slowdown). In sideways markets, VAMO will hover near zero – staying out during those low-volatility periods helps avoid false signals. This indicator’s strength is catching the moment when a quiet market turns volatile in one direction, which often precedes the next few candlesticks of sustained movement.
חפש סקריפטים עבור "histogram"
Risk RewardThe Risk Reward indicator, developed by OmegaTools, is a versatile technical tool designed to help traders visualize and evaluate potential reward and risk levels in their trades. By comparing recent price action against moving averages and volatility deviations, it calculates a range-weighted assessment of upside reward and downside risk. It provides a clear, color-coded visual representation of these potential ranges, along with critical support and resistance levels to aid in trade decision-making. This indicator is ideal for traders seeking to optimize their risk-reward ratio and make informed trade management decisions.
Features
Reward and Risk Visualization: Provides a histogram showing the relative potential of upside reward versus downside risk based on current price action.
Dynamic Support and Resistance Levels: Calculates and plots key price levels based on extreme of historical volatility, helping traders to identify important price zones.
Trade Size Customization: Users can adjust the trade size, and the indicator will calculate and display the estimated risk and reward in monetary terms based on the contract value.
Adaptive Volatility Extensions: Automatically adjusts extension lines based on volume, helping traders anticipate future price ranges and potential breakouts or breakdowns.
Customizable Visuals: Allows users to personalize the color scheme for bullish and bearish scenarios, making the chart more intuitive and user-friendly.
User Guide
Trade Size (size): Adjust the trade size in units (default is 1). This parameter impacts the risk and reward calculation shown in the summary table.
Length (lnt): Set the length for the exponential moving average (EMA) and the highest/lowest price calculations. This length determines the sensitivity of the indicator.
Different Visual (down): A boolean input to adjust the method for calculating downside risk. When set to true, it uses a different visual scheme.
Bullish Color (upc): Customize the color of the bullish (upside) histogram and support levels.
Bearish Color (dnc): Customize the color of the bearish (downside) histogram and resistance levels.
Plots
First Probability: Displays a histogram representing the higher value between reward and risk. It is colored according to whether the upside or downside is greater, providing a clear signal for potential trade direction.
Second Probability: A secondary histogram plot that visualizes the lower value between reward and risk, offering an additional perspective on the trade’s risk-reward balance.
Low Level/High Level: Displays dynamic support and resistance levels based on historical price data and volatility deviations.
Extension Lines: Visualize potential future price levels using volatility-adjusted projections. These lines help traders anticipate where price could move based on current conditions.
On-Chart Labels and Risk-Reward Table:
Risk and Reward Calculations: The indicator calculates the monetary value of downside risk and upside reward based on the provided trade size, volatility measures, and price movements.
Risk/Reward Table: Displayed directly on the chart, showing the downside risk and upside reward in easy-to-understand numerical values. This helps traders quickly assess the feasibility of a trade.
How It Works:
Moving Average Comparison: The indicator first calculates the 21-period (default) exponential moving average (EMA). It then compares the current price against this moving average to determine whether the market is in a bullish or bearish phase.
Deviation Calculation: It calculates the average deviation between the price and the EMA for both bullish and bearish movements, which is used to establish dynamic support and resistance levels.
Risk-Reward Calculation: Based on the highest and lowest price levels over the set period and the calculated deviations, it determines the potential upside reward and downside risk. The reward is calculated as the distance between the current price and the upper resistance levels, while the risk is determined as the distance to the lower support levels.
Visual Representation
The indicator plots histograms representing the relative magnitude of potential reward and risk.
Support and resistance levels are dynamically plotted on the chart using circles and lines, helping traders easily spot key areas of interest.
Extension lines are drawn to visualize potential future price levels based on current volatility.
Risk/Reward Table: This feature displays the calculated monetary risk and reward based on the trade size. It updates dynamically with price changes, offering a constant reference point for traders to evaluate their trade setup.
Practical Application
Identify Entry Points: Use the dynamic support and resistance levels to identify ideal trade entry points. The histogram helps determine whether the potential reward justifies the risk.
Risk Management: The calculated downside risk provides traders with an objective view of where to place stop-loss levels, while the upside reward aids in setting profit targets.
Trade Execution: By visually assessing whether reward outweighs risk, traders can make more informed decisions on trade execution, with the risk-reward ratio clearly displayed on the chart.
Best Practices:
Use Alongside Other Indicators: While this indicator offers a powerful standalone tool for assessing risk and reward, it works best when combined with other trend or momentum indicators for confirmation.
Adjust Inputs Based on Market Conditions: Adjust the length and trade size inputs depending on the asset being traded and the time horizon, as different assets may require different sensitivity settings.
Probability Trend IndicatorUnderstanding the Indicator:
The indicator calculates the probabilities of upward and downward trends based on the percentage change in price over a specified lookback period.
It displays these probabilities in a table and plots a histogram to represent the difference between the probabilities.
The colors of the histogram bars indicate the trend direction and whether the trend is increasing or decreasing.
Setting the Lookback Period:
The indicator allows you to specify the lookback period, which determines the number of bars to consider for calculating the probabilities.
By default, the lookback period is set to 50 bars. However, you can adjust it based on your trading preferences and the timeframe you're analyzing.
Analyzing the Probabilities:
The indicator calculates the probabilities of upward and downward trends and displays them in a table on the chart.
The probabilities are presented as percentages, representing the likelihood of each type of trend occurring.
You can use these probabilities to gain insights into the potential market direction and assess the strength of the prevailing trend.
Interpreting the Histogram:
The histogram is plotted based on the difference between the probabilities of upward and downward trends, known as the oscillator value.
The histogram bars are colored to provide visual cues about the trend direction and whether the trend is gaining or losing strength.
Green bars indicate upward trends, and red bars indicate downward trends.
Lighter shades of green or red suggest increasing trends, while darker shades suggest decreasing trends.
Making Trading Decisions:
The indicator serves as a tool for assessing the probabilities of trends and can be used alongside other technical analysis methods.
You can consider the probabilities, the histogram pattern, and the overall market context to make informed trading decisions.
It's important to remember that no indicator or tool can guarantee future market movements, so prudent risk management and additional analysis are essential.
Bars In a Row Counter Pro by RRBBars In a Row Counter Pro by RagingRocketBull 2018
Version 1.0
This indicator counts bars of the same color in a sequence (dojis included) and plots the resulting counts as histogram bars
1. based on barssince, uses plot function with histogram style
2. Min/Max Threshold is the upper and lower limits for counting bars. For example, you can look only for sequences of 5 to 10 bars of the same color in a row
3. Show Histogram Beyond Threshold - you can hide/change color of the non-important histogram part that exceeds the threshold
4. Show Threshold Bands - show the upper and lower limits as levels on the indicator
5. Show Min/Max Bands - show ATH max red/green bars in a row historic levels on the indicator
6. Count Red Bars - count red bars in a sequence, show/hide red bars on a histogram (you can exclude red bars and count only green bars)
7. Count Green Bars - count green bars in a sequence, show/hide green bars on a histogram (you can exclude green bars and count only red bars)
8. Invert Red Bars - show red and green histograms together on the same axis above zero (saves space)
Feel free to use. Good Luck!
ISM Manufacturing PMIDescription
The ISM Manufacturing PMI (Purchasing Managers' Index) is a key economic indicator derived from monthly surveys of private sector companies. It provides insight into the health of the US manufacturing sector.
Above 50.0: Indicates Expansion.
Below 50.0: Indicates Contraction.
This script visualizes the ISM Manufacturing PMI using TradingView's available economic data (ECONOMICS:USBCOI), providing traders and analysts with a clear view of macroeconomic trends directly on their charts.
Key Features
Intuitive Visualization:
Dynamic Color Coding: The line turns Green during expansion (>50) and Red during contraction (<50).
Baseline Fill: Optional shading between the data line and the 50.0 baseline emphasizes the current economic state.
Histogram Mode: Toggle a histogram view to easily spot momentum shifts.
Customizable Data Source: Defaults to ECONOMICS:USBCOI but can be configured to use other tickers (e.g., FRED:NAPM) if preferred.
Smoothing: Built-in SMA, EMA, RMA, or WMA smoothing to filter out noise and see the longer-term trend.
Alerts: Set alerts for significant crossovers (Expansion/Contraction start) or extreme levels.
How to Use
Add to Chart: Apply the indicator to any chart. It works best on higher timeframes but pulls monthly data automatically.
Interpret the Trend:
Look for the line crossing the 50.0 level. A cross above suggests the manufacturing sector is growing (Bullish for economy). A cross below suggests slowing down or contraction (Bearish for economy).
Watch for extreme readings (above 60 or below 40) which often mark economic peaks or troughs.
Adjust Settings:
Style: Toggle the Line, Histogram, or Fill visibility in the settings.
Smoothing: If the raw data is too jagged, increase the "Smoothing Length" to 3 or 6 months.
Settings
PMI Ticker: Default is ECONOMICS:USBCOI.
Timeframe: Default is 1M (Monthly).
Show Line / Histogram: Toggle visualization modes.
Smoothing: Type and Length of the moving average applied to the data.
Colors: Customize the colors for Expansion (Grow), Contraction (Fall), and Neutral.
Indicator by: iCD_creator
Version: 1.0
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Updates & Support
For questions, suggestions, or bug reports, please comment below or message the author.
**Like this indicator? Leave a 👍 and share your feedback!**
Asset Liquidity Meter by Funded RelayAsset Liquidity Meter by Funded Relay
This indicator estimates the liquidity of any asset by calculating the volume traded per unit of price movement (volume / (high - low)).
Higher values generally indicate better liquidity (more volume in a smaller price range → easier to enter/exit positions with less slippage).
Lower values suggest thinner liquidity (higher risk of price impact and volatility).
The indicator displays:
• Histogram: raw liquidity per bar (green = above SMA, red = below SMA)
• SMA line: smoothed liquidity trend
• Real-time info table in the top-right corner
• Built-in alert conditions
How to Use – Step by Step
1. Adding the Indicator
- Open any chart on TradingView
- Click the "Indicators" button at the top
- Search for "Asset Liquidity Meter v6" (or find it in Community Scripts / My Scripts)
- Click to add it to the chart
- It will appear in a separate pane below the price chart
2. Customizing Settings
Double-click the indicator name in the pane (or right-click → Settings):
• SMA Length (default: 14)
- Controls the smoothing period of the liquidity trend line
- Smaller values (5–10) → more responsive, good for intraday/scalping
- Larger values (20–50) → smoother trend, better for swing/position trading
• Epsilon (default: 0.00000001)
- Tiny value that prevents division-by-zero errors on flat bars (high = low)
- Almost never needs to be changed
• Colors
- High Liquidity Color: histogram bars when liquidity > SMA
- Low Liquidity Color: histogram bars when liquidity < SMA
- SMA Line Color: color of the smoothed trend line
• Show Alert Conditions in Menu
- Keep enabled (true) to see the built-in alert options when creating alerts
3. Reading & Interpreting the Indicator
• Histogram Bars (Raw Liquidity)
- Height = amount of volume per unit of price range
- Tall bars = high liquidity (market is "thick")
- Short bars = low liquidity (market is "thin")
- Green = current liquidity is stronger than the average (SMA)
- Red = current liquidity is weaker than the average
• Blue SMA Line
- Shows the average liquidity over the selected period
- Rising line → liquidity improving (more participants, easier trading)
- Falling line → liquidity decreasing (thinner market, caution advised)
• Info Table (top-right corner)
- Displays current raw liquidity, SMA value, and status ("High Liquidity" / "Low Liquidity")
- Updates in real-time on the last bar
• Zero Line (dotted gray)
- Visual reference — everything above zero is positive liquidity
4. Practical Trading Applications
• High Liquidity Zones (green bars + rising SMA)
- Favorable conditions for entering or scaling into positions
- Lower expected slippage
- Better for large orders
• Low Liquidity Zones (red bars + falling SMA)
- Higher risk of slippage and exaggerated price moves
- Consider smaller position sizes or waiting for better conditions
- Common during session opens/closes, holidays, or low-volume periods
• Crossovers
- Liquidity crossing above SMA → potential increase in market participation
- Liquidity crossing below SMA → potential drying up of interest
5. Setting Up Alerts
1. Right-click on the chart → "Add Alert"
2. In "Condition", select "Asset Liquidity Meter v6"
3. Choose one of the available alert conditions:
- Liquidity ↑ Crosses Above SMA
- Liquidity ↓ Crosses Below SMA
- Very High Liquidity (2× SMA)
- Very Low Liquidity (<30% SMA)
4. Set frequency (Once Per Bar Close is usually best)
5. Configure notification (email, popup, sound, webhook, etc.)
6. Create the alert
6. Tips for Best Results
• Works on all markets: stocks, forex, crypto, futures, indices
• Best on timeframes with meaningful volume data (5 min and higher usually give clearest signals)
• Compare liquidity across different assets or timeframes using multiple charts
• Combine with support/resistance, volume profile or order flow tools for confirmation
• Not a standalone signal — use in context with your overall strategy
Limitations & Notes
• This is an estimation based on OHLCV data — it does not show real order book depth
• Results vary significantly between centralized exchanges, brokers and instruments
• Zero-volume bars will show zero liquidity (expected behavior)
Enjoy safer and more informed trading!
Questions or suggestions? Feel free to comment below.
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.
Anchored VWAP PercentageINDICATOR: ANCHORED VWAP PERCENTAGE (AVWAP)
1. Overview
The Anchored VWAP Percentage (AVWAP) is a quantitative momentum and mean-reversion tool. It measures the percentage distance between the current price and a Volume Weighted Average Price (VWAP) that resets automatically based on specific time cycles. It allows traders to identify overextended market conditions relative to institutional value.
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2. Core Logic & Calculation
The script tracks the relationship between price and volume starting from a specific Anchor Point .
* Volume-Weighted Foundation: Unlike simple moving averages, this indicator uses the VWAP formula: sum(Volume * Price) / sum(Volume) .
* Automatic Anchoring: The starting point (Anchor) resets automatically depending on the chart timeframe (e.g., resets weekly on a 15m chart, or yearly on a Daily chart).
* Percentage Deviation: It calculates the precise gap between the price and the VWAP, plotted as an oscillator: ((Price - VWAP) / VWAP) * 100 .
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3. Adaptive Intelligence (Multi-Asset & Multi-TF)
The AVWAP is built with an internal database of 85th Percentile (P85) volatility thresholds. It recognizes that different assets have different "stretching" limits:
1. Asset-Specific Calibration: It includes optimized data for Bitcoin, Ethereum, Altcoins, Forex, and Indices .
2. Dynamic Timeframe Mapping: The anchor period and the exhaustion thresholds adjust automatically. For example:
* Intraday (1m-5m): Anchors to an 8-hour (480 min) cycle.
* Mid-Term (15m-60m): Anchors to a Weekly (W) cycle.
* Swing (Daily): Anchors to a Yearly (12M) cycle.
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4. Visual Anatomy
The indicator is designed for high-speed decision-making:
* The Histogram:
* Green: Price is trading above the VWAP (Bullish premium).
* Red: Price is trading below the VWAP (Bearish discount).
* P85 Threshold Lines:
* These lines represent the 85th percentile of historical deviations . Historically, the price stays within these boundaries 85% of the time.
* Background Highlighting: When the histogram crosses the P85 line, the background glows, signaling a Statistical Exhaustion Zone where a retracement to the mean is highly probable.
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5. How to Trade with AVWAP
* Mean Reversion: When the histogram reaches the P85 Zone , the price is "statistically overextended." This is a prime area to look for reversals or to take profits on existing trends.
* Trend Strength: If the histogram stays near the Zero Line while the price moves, the trend is supported by healthy volume.
* Value Area: The Zero Line represents the Fair Value . Buying near the Zero Line during a bullish histogram (Green) offers a high-probability entry with low risk.
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6. Technical Parameters
* Asset Selection: A dropdown to switch between Crypto, Forex, and Indices.
* Color Customization: User-defined colors for bullish and bearish sentiment.
* Precision Control: 4-decimal precision for accurate tracking of thin-margin assets like Forex.
RSI & MACD SuiteRSI & MACD Suite
A professional combination of two essential momentum indicators - Relative Strength Index (RSI) and Moving Average Convergence Divergence (MACD) - designed to provide comprehensive market analysis in a single, clean interface.
OVERVIEW
This indicator combines the power of RSI and MACD to help traders identify potential overbought/oversold conditions, momentum shifts, and trend changes. Both indicators are displayed with enhanced visual elements including gradient fills, customizable bands, and clear signal lines.
FEATURES
RSI (Relative Strength Index)
- Customizable Period: Adjustable RSI length (default: 14)
- Visual Zones: Overbought zone (above 70) with green gradient, Oversold zone (below 30) with red gradient, Background fill between bands for easy reference
- Key Levels: Clear horizontal lines at 30, 50, and 70
- Flexible Source: Choose any price source (close, open, high, low, etc.)
MACD (Moving Average Convergence Divergence)
- Customizable Parameters: Fast Length (default: 12), Slow Length (default: 26), Signal Length (default: 9)
- MA Type Selection: Choose between EMA or SMA for both oscillator and signal line
- Color-Coded Histogram: Green for bullish momentum, Red for bearish momentum
- Clear Signal Lines: Blue MACD line and orange Signal line for easy identification
ALERT CONDITIONS
The indicator includes 7 built-in alert conditions:
RSI Alerts:
1. RSI Overbought - Triggers when RSI crosses above 70
2. RSI Oversold - Triggers when RSI crosses below 30
3. RSI Midline Cross - Triggers when RSI crosses the 50 level
MACD Alerts:
4. MACD Bullish Cross - Triggers when MACD line crosses above Signal line
5. MACD Bearish Cross - Triggers when MACD line crosses below Signal line
6. MACD Histogram Bullish - Triggers when histogram crosses above zero
7. MACD Histogram Bearish - Triggers when histogram crosses below zero
CUSTOMIZATION
Clean Organization
- Inputs Tab: Separate groups for RSI and MACD settings
- Style Tab: All visual elements clearly labeled with "RSI -" or "MACD -" prefixes for easy identification
- Full Control: Customize colors, line widths, and visibility of all elements
Visual Clarity
- Professional color scheme optimized for both light and dark themes
- Gradient fills for intuitive zone identification
- Clear separation between RSI and MACD elements
SETTINGS
RSI Settings
- Length: Lookback period for RSI calculation (default: 14)
- Source: Price data to use for calculation (default: close)
MACD Settings
- Source: Price data to use for calculation (default: close)
- Fast Length: Period for fast moving average (default: 12)
- Slow Length: Period for slow moving average (default: 26)
- Signal Length: Period for signal line (default: 9)
- Oscillator MA Type: EMA or SMA for MACD calculation
- Signal MA Type: EMA or SMA for signal line
TECHNICAL DETAILS
- Pine Script Version: v6
- Indicator Type: Oscillator (subplot)
- Calculation Method: RSI uses Relative Strength Index with RMA smoothing, MACD uses Fast MA minus Slow MA with configurable MA types
- Input Validation: Built-in checks to ensure valid parameter combinations
NOTES
- Default settings are industry-standard values (RSI: 14, MACD: 12/26/9)
- All visual elements can be hidden/shown individually in the Style tab
- Alerts must be manually created by users through TradingView's alert system
- This indicator does not repaint - all signals are based on closed candles
WHO SHOULD USE THIS
- Day traders looking for momentum signals
- Swing traders identifying trend changes
- Technical analysts performing multi-indicator analysis
- Traders who want a clean, all-in-one momentum solution
DISCLAIMER
This indicator is for educational and informational purposes only. It does not constitute financial advice. Always perform your own analysis and risk assessment before making trading decisions.
Version: 1.0
Author: aaboomar
License: Mozilla Public License 2.0
Volatility State Index [Interakktive]The Volatility State Index (VSI) classifies market volatility into three behavioral states: Expansion, Decay, and Transition. It answers one question visually: Is volatility supporting price movement, withdrawing, or unstable?
Unlike traditional volatility indicators that show levels or bands, VSI diagnoses the current volatility regime so traders can adapt their approach accordingly.
█ WHAT IT DOES
• Classifies volatility into three states: Expansion (teal), Decay (grey), Transition (amber)
• Measures volatility momentum as a percentage rate-of-change
• Applies stability filtering to detect unstable/choppy conditions
• Uses persistence logic to prevent state flickering
• Exports state data for use in alerts and strategies
█ WHAT IT DOES NOT DO
• NO buy/sell signals
• NO entry/exit recommendations
• NO alerts (v1 is diagnostic only)
• NO performance claims
This is a volatility diagnostic tool, not a trading system.
█ HOW IT WORKS
The VSI processes volatility through a five-stage pipeline:
STAGE 1 — Base Volatility
Calculates ATR as the foundation for volatility measurement.
STAGE 2 — Smoothing
Applies EMA smoothing to reduce noise in the volatility series.
STAGE 3 — Volatility Momentum
Computes the percentage rate-of-change of smoothed volatility:
Volatility Momentum (%) = ((Current ATR - Previous ATR) / Previous ATR) × 100
Positive values indicate expanding volatility; negative values indicate contracting volatility.
STAGE 4 — Stability Filter
Tracks how frequently volatility momentum changes direction. Frequent sign changes indicate unstable, choppy conditions.
Stability Score = 1 - (Average Flip Rate)
Low stability forces the Transition state regardless of momentum level.
STAGE 5 — State Classification
Combines momentum thresholds and stability to determine the final state:
• Expansion: Momentum ≥ +5% (default threshold)
• Decay: Momentum ≤ -5% (default threshold)
• Transition: Between thresholds OR low stability
A persistence filter requires states to hold for multiple bars before confirming, preventing visual noise.
█ INTERPRETATION
EXPANSION (Teal)
Volatility is increasing in a sustained way. Price moves are becoming larger.
What it suggests:
• Breakouts are more likely to follow through
• Stops may need wider placement
• Trend-following approaches tend to work better
• Mean-reversion weakens
DECAY (Grey)
Volatility is decreasing. Price is compressing into tighter ranges.
What it suggests:
• Breakouts are more likely to fail
• Ranges tend to hold
• Trend-following underperforms
• Mean-reversion strengthens
TRANSITION (Amber)
Volatility behavior is unclear or unstable. This is NOT neutral — it is uncertainty.
What it suggests:
• Mixed signals — one bar huge, next bar dead
• Higher whipsaw risk
• Reduced conviction in either direction
• Consider waiting for clarity
The key insight: Amber is a warning, not a middle ground. It appears when volatility cannot decide what it wants to do.
█ VISUAL DESIGN
The indicator uses a state-first histogram design:
• Histogram height shows volatility momentum percentage
• Histogram color shows the classified state
• Zero line provides visual anchor
• Optional momentum line for confirmation
• Optional background tint (default OFF for clean charts)
The visual hierarchy prioritizes instant state recognition. A trader should understand the volatility environment in under one second without reading numbers.
█ INPUTS
Core Settings
• ATR Length: Base volatility measurement period (default: 14)
• Smoothing Length: EMA smoothing applied to ATR (default: 10)
• Momentum Length: Rate-of-change lookback (default: 10)
State Classification
• Expansion Threshold (%): Momentum above this = Expansion (default: 5.0)
• Decay Threshold (%): Momentum below this = Decay (default: -5.0)
• Persistence Bars: Bars required to confirm state change (default: 3)
• Stability Lookback: Window for stability calculation (default: 20)
• Stability Threshold: Below this = forced Transition (default: 0.5)
Visual Settings
• Show State Histogram: Toggle main display (default: ON)
• Show Momentum Line: Thin confirmation line (default: OFF)
• Show Zero Line: Baseline reference (default: ON)
• Show Background Tint: Subtle state coloring (default: OFF)
█ DATA WINDOW EXPORTS
When enabled, the following values are exported:
• ATR (Raw)
• ATR (Smoothed)
• Volatility Momentum (%)
• Stability Score (0-1)
• State (-1/0/1): Decay = -1, Transition = 0, Expansion = 1
• Is Expansion (0/1)
• Is Decay (0/1)
• Is Transition (0/1)
These exports allow VSI to be used as a filter in Pine Script strategies or alert conditions.
█ ORIGINALITY
While ATR and volatility indicators are common, VSI is original because it:
1. Classifies volatility into behavioral states rather than showing raw levels
2. Applies momentum analysis to volatility itself (rate-of-change of ATR)
3. Uses stability filtering to detect genuinely unstable conditions
4. Implements persistence logic to prevent state flickering
5. Provides a state-first visual design optimized for instant recognition
VSI is state-first: it classifies volatility regimes (Expansion/Decay/Transition) rather than plotting volatility level alone, using momentum and stability to reduce false regime reads.
This is not a modified ATR or Bollinger Band — it is a volatility regime classifier.
█ SUITABLE MARKETS
Works on: Stocks, Futures, Forex, Crypto
Timeframes: All timeframes — state classification adapts accordingly
Best on: Instruments with consistent volatility patterns
█ RELATED
• Market Efficiency Ratio — measures price path efficiency
• Effort-Result Divergence — compares volume effort to price result
█ DISCLAIMER
This indicator is for educational purposes only. It does not constitute financial advice. Past performance does not guarantee future results. Always conduct your own analysis before making trading decisions.
Open Interest Z-Score [BackQuant]Open Interest Z-Score
A standardized pressure gauge for futures positioning that turns multi venue open interest into a Z score, so you can see how extreme current positioning is relative to its own history and where leverage is stretched, decompressing, or quietly re loading.
What this is
This indicator builds a single synthetic open interest series by aggregating futures OI across major derivatives venues, then standardises that aggregated OI into a rolling Z score. Instead of looking at raw OI or a simple change, you get a normalized signal that says "how many standard deviations away from normal is positioning right now", with optional smoothing, reference bands, and divergence detection against price.
You can render the Z score in several plotting modes:
Line for a clean, classic oscillator.
Colored line that encodes both sign and momentum of OI Z.
Oscillator histogram that makes impulses and compressions obvious.
The script also includes:
Aggregated open interest across Binance, Bybit, OKX, Bitget, Kraken, HTX, and Deribit, using multiple contract suffixes where applicable.
Choice of OI units, either coin based or converted to USD notional.
Standard deviation reference lines and adaptive extreme bands.
A flexible smoothing layer with multiple moving average types.
Automatic detection of regular and hidden divergences between price and OI Z.
Alerts for zero line and ±2 sigma crosses.
Aggregated open interest source
At the core is the same multi venue OI aggregation engine as in the OI RSI tool, adapted from NoveltyTrade's work and extended for this use case. The indicator:
Anchors on the current chart symbol and its base currency.
Loops over a set of exchanges, gated by user toggles:
Binance.
Bybit.
OKX.
Bitget.
Kraken.
HTX.
Deribit.
For each exchange, loops over several contract suffixes such as USDT.P, USD.P, USDC.P, USD.PM to cover the common perp and margin styles.
Requests OI candles for each exchange plus suffix pair into a small custom OI type that carries open, high, low and close of open interest.
Converts each OI stream into a common unit via the sw method:
In COIN mode, OI is normalized relative to the coin.
In USD mode, OI is scaled by price to approximate notional.
Exchange specific scaling factors are applied where needed to match contract multipliers.
Accumulates all valid OI candles into a single combined OI "candle" by summing open, high, low and close across venues.
The result is oiClose , a synthetic close for aggregated OI that represents cross venue positioning. If there is no valid OI data for the symbol after this process, the script throws a clear runtime error so you know the market is unsupported rather than quietly plotting nonsense.
How the Z score is computed
Once the aggregated OI close is available, the indicator computes a rolling Z score over a configurable lookback:
Define subject as the aggregated OI close.
Compute a rolling mean of this subject with EMA over Z Score Lookback Period .
Compute a rolling standard deviation over the same length.
Subtract the mean from the current OI and divide by the standard deviation.
This gives a raw Z score:
oi_z_raw = (subject − mean) ÷ stdDev .
Instead of plotting this raw value directly, the script passes it through a smoothing layer:
You pick a Smoothing Type and Smoothing Period .
Choices include SMA, HMA, EMA, WMA, DEMA, RMA, linear regression, ALMA, TEMA, and T3.
The helper ma function applies the chosen smoother to the raw Z score.
The result is oi_z , a smoothed Z score of aggregated open interest. A separate EMA with EMA Period is then applied on oi_z to create a signal line ma that can be used for crossovers and trend reads.
Plotting modes
The Plotting Type input controls how this Z score is rendered:
1) Line
In line mode:
The smoothed OI Z score is plotted as a single line using Base Line Color .
The EMA overlay is optionally plotted if Show EMA is enabled.
This is the cleanest view when you want to treat OI Z like a standard oscillator, watching for zero line crosses, swings, and divergences.
2) Colored Line
Colored line mode adds conditional color logic to the Z score:
If the Z score is above zero and rising, it is bright green, representing positive and strengthening positioning pressure.
If the Z score is above zero and falling, it shifts to a cooler cyan, representing positive but weakening pressure.
If the Z score is below zero and falling, it is bright red, representing negative and strengthening pressure (growing net de risking or shorting).
If the Z score is below zero and rising, it is dark red, representing negative but recovering pressure.
This mapping makes it easy to see not only whether OI is above or below its historical mean, but also whether that deviation is intensifying or fading.
3) Oscillator
Oscillator mode turns the Z score into a histogram:
The smoothed Z score is plotted as vertical columns around zero.
Column colors use the same conditional palette as colored line mode, based on sign and change direction.
The histogram base is zero, so bars extend up into positive Z and down into negative Z.
Oscillator mode is useful when you care about impulses in positioning, for example sharp jumps into positive Z that coincide with fast builds in leverage, or deep spikes into negative Z that show aggressive flushes.
4) None
If you only want reference lines, extreme bands, divergences, or alerts without the base oscillator, you can set plotting to None and keep the rest of the tooling active.
The EMA overlay respects plotting mode and only appears when a visible Z score line or histogram is present.
Reference lines and standard deviation levels
The Select Reference Lines input offers two styles:
Standard Deviation Levels
Plots small markers at zero.
Draws thin horizontal lines at +1, +2, −1 and −2 Z.
Acts like a classic Z score ladder, zero as mean, ±1 as normal band, ±2 as outer band.
This mode is ideal if you want a textbook statistical framing, using ±1 and ±2 sigma as standard levels for "normal" versus "extended" positioning.
Extreme Bands
Extreme bands build on the same ±1 and ±2 lines, then add:
Upper outer band between +3 and +4 Z.
Lower outer band between −3 and −4 Z.
Dynamic fill colors inside these bands:
If the Z score is positive, the upper band fill turns red with an alpha that scales with the magnitude of |Z|, capped at a chosen max strength. Stronger deviations towards +4 produce more opaque red fills.
If the Z score is negative, the lower band fill turns green with the same adaptive alpha logic, highlighting deep negative deviations.
Opposite side bands remain a faint neutral white when not in use, so they still provide structural context without shouting.
This creates a visual "danger zone" for position crowding. When the Z score enters these outer bands, open interest is many standard deviations away from its mean and you are dealing with rare but highly loaded positioning states.
Z score as a positioning pressure gauge
Because this is a Z score of aggregated open interest, it measures how unusual current positioning is relative to its own recent history, not just whether OI is rising or falling:
Z near zero means total OI is roughly in line with normal conditions for your lookback window.
Positive Z means OI is above its recent mean. The further above zero, the more "crowded" or extended positioning is.
Negative Z means OI is below its recent mean. Deep negatives often mark post flush environments where leverage has been cleared and the market is under positioned.
The smoothing options help control how much noise you want in the signal:
Short Z score lookback and short smoothing will react quickly, suited for short term traders watching intraday positioning shocks.
Longer Z score lookback with smoother MA types (EMA, RMA, T3) give a slower, more structural view of where the crowd sits over days to weeks.
Divergences between price and OI Z
The indicator includes automatic divergence detection on the Z score versus price, using pivot highs and lows:
You configure Pivot Lookback Left and Pivot Lookback Right to control swing sensitivity.
Pivots are detected on the OI Z series.
For each eligible pivot, the script compares OI Z and price at the last two pivots.
It looks for four patterns:
Regular Bullish – price makes a lower low, OI Z makes a higher low. This can indicate selling exhaustion in positioning even as price washes out. These are marked with a line and a label "ℝ" below the oscillator, in the bullish color.
Hidden Bullish – price makes a higher low, OI Z makes a lower low. This suggests continuation potential where price holds up while positioning resets. Marked with "ℍ" in the bullish color.
Regular Bearish – price makes a higher high, OI Z makes a lower high. This is a classic warning sign of trend exhaustion, where price pushes higher while OI Z fails to confirm. Marked with "ℝ" in the bearish color.
Hidden Bearish – price makes a lower high, OI Z makes a higher high. This is often seen in pullbacks within downtrends, where price retraces but positioning stretches again in the direction of the prevailing move. Marked with "ℍ" in the bearish color.
Each divergence type can be toggled globally via Show Detected Divergences . Internally, the script restricts how far back it will connect pivots, so you do not get stray signals linking very old structures to current bars.
Trading applications
Crowding and squeeze risk
Z scores are a natural way to talk about crowding:
High positive Z in aggregated OI means the market is running high leverage compared to its own norm. If price is also extended, the risk of a squeeze or sharp unwind rises.
Deep negative Z means leverage has been cleaned out. While it can be painful to sit through, this environment often sets up cleaner new trends, since there is less one sided positioning to unwind.
The extreme bands at ±3 to ±4 highlight the rare states where crowding is most intense. You can treat these events as regime markers rather than day to day noise.
Trend confirmation and fade selection
Combine Z score with price and trend:
Bull trends with positive and rising Z are supported by fresh leverage, usually more persistent.
Bull trends with flat or falling Z while price keeps grinding up can be more fragile. Divergences and extreme bands can help identify which edges you do not want to fade and which you might.
In downtrends, deep negative Z that stays pinned can mean persistent de risking. Once the Z score starts to mean revert back toward zero, it can mark the early stages of stabilization.
Event and liquidation context
Around major events, you often see:
Rapid spikes in Z as traders rush to position.
Reversal and overshoot as liquidations and forced de risking clear the book.
A move from positive extremes through zero into negative extremes as the market transitions from crowded to under exposed.
The Z score makes that path obvious, especially in oscillator mode, where you see a block of high positive bars before the crash, then a slab of deep negative bars after the flush.
Settings overview
Z Score group
Plotting Type – None, Line, Colored Line, Oscillator.
Z Score Lookback Period – window used for mean and standard deviation on aggregated OI.
Smoothing Type – SMA, HMA, EMA, WMA, DEMA, RMA, linear regression, ALMA, TEMA or T3.
Smoothing Period – length for the selected moving average on the raw Z score.
Moving Average group
Show EMA – toggle EMA overlay on Z score.
EMA Period – EMA length for the signal line.
EMA Color – color of the EMA line.
Thresholds and Reference Lines group
Select Reference Lines – None, Standard Deviation Levels, Extreme Bands.
Standard deviation lines at 0, ±1, ±2 appear in both modes.
Extreme bands add filled zones at ±3 to ±4 with adaptive opacity tied to |Z|.
Extra Plotting and UI
Base Line Color – default color for the simple line mode.
Line Width – thickness of the oscillator line.
Positive Color – positive or bullish condition color.
Negative Color – negative or bearish condition color.
Divergences group
Show Detected Divergences – master toggle for divergence plotting.
Pivot Lookback Left and Pivot Lookback Right – how many bars left and right to define a pivot, controlling divergence sensitivity.
Open Interest Source group
OI Units – COIN or USD.
Exchange toggles for Binance, Bybit, OKX, Bitget, Kraken, HTX, Deribit.
Internally, all enabled exchanges and contract suffixes are aggregated into one synthetic OI series.
Alerts included
The indicator defines alert conditions for several key events:
OI Z Score Positive – Z crosses above zero, aggregated OI moves from below mean to above mean.
OI Z Score Negative – Z crosses below zero, aggregated OI moves from above mean to below mean.
OI Z Score Enters +2σ – Z enters the +2 band and above, marking extended positive positioning.
OI Z Score Enters −2σ – Z enters the −2 band and below, marking extended negative positioning.
Tie these into your strategy to be notified when leverage moves from normal to extended states.
Notes
This indicator does not rely on price based oscillators. It is a statistical lens on cross venue open interest, which makes it a complementary tool rather than a replacement for your existing price or volume signals. Use it to:
Quantify how unusual current futures positioning is compared to recent history.
Identify crowded leverage phases that can fuel squeezes.
Spot structural divergences between price and positioning.
Frame risk and opportunity around events and regime shifts.
It is not a complete trading system. Combine it with your own entries, exits and risk rules to get the most out of what the Z score is telling you about positioning pressure under the hood of the market.
RSI Profile [Kodexius]RSI Profile is an advanced technical indicator that turns the classic RSI into a distribution profile instead of a single oscillating line. Rather than only showing where the RSI is at the current bar, it displays where the RSI has spent most of its time or most of its volume over a user defined lookback period.
The script builds a histogram of RSI values between 0 and 100, splits that range into configurable bins, and then projects the result to the right side of the chart. This gives you a clear visual representation of the RSI structure, including the Point of Control (POC), the Value Area High (VAH), and the Value Area Low (VAL). The POC marks the RSI level with the highest activity, while VAH and VAL bracket the percentage based value area around it.
By combining standard RSI, a distribution profile, and value area logic, this tool lets you study RSI behavior statistically instead of only bar by bar. You can immediately see whether the current RSI reading is located inside the dominant zone, extended above it, or depressed below it, and whether the recent regime has been biased toward overbought, oversold, or neutral territory. This is particularly useful for swing traders, mean reversion systems, and anyone who wants to integrate RSI context into a more profile oriented workflow.
🔹 Features
1. RSI-Based Distribution Profile
-Builds a histogram of RSI values between 0 and 100.
-The RSI range is divided into a user-defined number of bins (e.g., 30 bins).
-Each bin represents a band of RSI values, such as 0–3.33, 3.33–6.66, ..., 96.66–100.
-For each bar in the lookback period, the script:
-Finds which bin the RSI value belongs to
Adds either:
-1.0 → if using time/frequency
-volume → if using volume-weighted RSI distribution
This creates a clear profile of where RSI has been concentrated over the chosen lookback window.
2. Time / Volume Weighting Mode
Under Profile Settings, you can choose:
-Weight by Volume = false
→ Profile is built using time spent at each RSI level (frequency).
-Weight by Volume = true
→ Profile is built using volume traded at each RSI level.
This flexibility allows you to decide whether you want:
-A pure momentum structure (time spent at each RSI)
-Or a participation-weighted structure (where higher-volume zones are emphasized)
3. Configurable Lookback & Resolution
-Profile Lookback: number of historical bars to analyze.
-Number of Bins: controls the resolution of the histogram:
Fewer bins → smoother, fewer gaps
More bins → more detail, but potentially more visual sparsity
-Profile Width (Bars): defines how wide the histogram extends into the future (visually), converted into time using average bar duration.
This provides a balance between performance, clarity, and visual density.
4. Value Area, POC, VAH, VAL
The script computes:
-POC (Point of Control)
→ The RSI bin with the highest total value (time or volume).
-Value Area (VA)
→ The range of RSI bins that contain a user-specified percentage of total activity (e.g., 70%).
-VAH & VAL
→ Upper and lower RSI boundaries of this Value Area.
These are then drawn as horizontal lines and labeled:
-POC line and label
-VAH line and label
-VAL line and label
This gives you a profile-style view similar to classical volume profile, but entirely on the RSI axis.
5. Color Coding & Visual Design
The histogram bars (boxes) are colored using a smart scheme:
-Below 30 RSI → Oversold zone, uses the Oversold Color (default: green).
-Above 70 RSI → Overbought zone, uses the Overbought Color (default: red).
-Between 30 and 70 RSI → Neutral zone, uses a gradient between:
A soft blue at lower mid levels
A soft orange at higher mid levels
Additional styling:
-POC bin is highlighted in bright yellow.
-Bins inside the Value Area → lower transparency (more solid).
-Bins outside the Value Area → higher transparency (faded).
This makes it easy to visually distinguish:
-Core RSI activity (VA)
-Extremes (oversold/overbought)
-The single dominant zone (POC)
🔹 Calculations
This section summarizes the core logic behind the script and highlights the main building blocks that power the profile.
1. Profile Structure and Bin Initialization
A custom Profile type groups together configuration, bins and drawing objects. During initialization, the script splits the 0 to 100 RSI range into evenly spaced bins, each represented by a Bin record:
method initBins(Profile p) =>
p.bins := array.new()
float step = 100.0 / p.binCount
for i = 0 to p.binCount - 1
float low = i * step
float high = (i + 1) * step
p.bins.push(Bin.new(low, high, 0.0, box(na)))
2. Filling the Profile Over the Lookback Window
On the last bar, the script clears previous drawings and walks backward through the selected lookback window. For each historical bar, it reads the RSI and volume series and feeds them into the profile:
if barstate.islast
myProfile.reset()
int start = math.max(0, bar_index - lookback)
int end = bar_index
for i = 0 to (end - start)
float r = rsi
float v = volume
if not na(r)
myProfile.add(r, v)
The add method converts each RSI value into a bin index and accumulates either a frequency count or the bar volume, depending on the chosen mode:
method add(Profile p, float rsiValue, float volumeValue) =>
int idx = int(rsiValue / (100.0 / p.binCount))
if idx >= p.binCount
idx := p.binCount - 1
if idx < 0
idx := 0
Bin targetBin = p.bins.get(idx)
float addedValue = p.useVolume ? volumeValue : 1.0
targetBin.value += addedValue
3. Finding POC and Building the Value Area
Inside the draw method, the script first scans all bins to determine the maximum value and the total sum. The bin with the highest value becomes the POC. The value area is then constructed by expanding from that center bin until the desired percentage of total activity is covered:
for in p.bins
totalVal += b.value
if b.value > maxVal
maxVal := b.value
pocIdx := i
float vaTarget = totalVal * (p.vaPercent / 100.0)
float currentVaVol = maxVal
int upIdx = pocIdx
int downIdx = pocIdx
while currentVaVol < vaTarget
float upVol = (upIdx < p.binCount - 1) ? p.bins.get(upIdx + 1).value : 0.0
float downVol = (downIdx > 0) ? p.bins.get(downIdx - 1).value : 0.0
if upVol == 0 and downVol == 0
break
if upVol >= downVol
upIdx += 1
currentVaVol += upVol
else
downIdx -= 1
currentVaVol += downVol
Hidden Impulse═══════════════════════════════════════════════════════════════════
HIDDEN IMPULSE - Multi-Timeframe Momentum Detection System
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OVERVIEW
Hidden Impulse is an advanced momentum oscillator that combines the Schaff Trend Cycle (STC) and Force Index into a comprehensive multi-timeframe trading system. Unlike standard implementations of these indicators, this script introduces three distinct trading setups with specific entry conditions, multi-timeframe confirmation, and trend filtering.
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ORIGINALITY & KEY FEATURES
This indicator is original in the following ways:
1. DUAL-TIMEFRAME STC ANALYSIS
Standard STC implementations work on a single timeframe. This script
simultaneously analyzes STC on both your trading timeframe and a higher
timeframe, providing trend context and filtering out low-probability signals.
2. FORCE INDEX INTEGRATION
The script combines STC with Force Index (volume-weighted price momentum)
to confirm the strength behind price moves. This combination helps identify
when momentum shifts are backed by genuine buying/selling pressure.
3. THREE DISTINCT TRADING SETUPS
Rather than generic overbought/oversold signals, the indicator provides
three specific, rule-based setups:
- Setup A: Classic trend-following entries with multi-timeframe confirmation
- Setup B: Divergence-based reversal entries (highest probability)
- Setup C: Mean-reversion bounce trades at extreme levels
4. INTELLIGENT FILTERING
All signals are filtered through:
- 50 EMA trend direction (prevents counter-trend trades)
- Higher timeframe STC alignment (ensures macro trend agreement)
- Force Index confirmation (validates volume support)
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HOW IT WORKS - TECHNICAL EXPLANATION
SCHAFF TREND CYCLE (STC) CALCULATION:
The STC is a cyclical oscillator that combines MACD concepts with stochastic
smoothing to create earlier and smoother trend signals.
Step 1: Calculate MACD
- Fast MA = EMA(close, Length1) — default 23
- Slow MA = EMA(close, Length2) — default 50
- MACD Line = Fast MA - Slow MA
Step 2: First Stochastic Smoothing
- Apply stochastic calculation to MACD
- Stoch1 = 100 × (MACD - Lowest(MACD, Smoothing)) / (Highest(MACD, Smoothing) - Lowest(MACD, Smoothing))
- Smooth result with EMA(Stoch1, Smoothing) — default 10
Step 3: Second Stochastic Smoothing
- Apply stochastic calculation again to the smoothed stochastic
- This creates the final STC value between 0-100
The dual stochastic smoothing makes STC more responsive than MACD while
being smoother than traditional stochastics.
FORCE INDEX CALCULATION:
Force Index measures the power behind price movements by incorporating volume:
Force Raw = (Close - Close ) × Volume
Force Index = EMA(Force Raw, Period) — default 13
Interpretation:
- Positive Force Index = Buying pressure (bulls in control)
- Negative Force Index = Selling pressure (bears in control)
- Force Index crossing zero = Momentum shift
- Divergences with price = Weakening momentum (reversal signal)
TREND FILTER:
A 50-period EMA serves as the trend filter:
- Price above EMA50 = Uptrend → Only LONG signals allowed
- Price below EMA50 = Downtrend → Only SHORT signals allowed
This prevents counter-trend trading which accounts for most losing trades.
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THE THREE TRADING SETUPS - DETAILED
SETUP A: CLASSIC MOMENTUM ENTRY
Concept: Enter when STC exits oversold/overbought zones with trend confirmation
LONG CONDITIONS:
1. Higher timeframe STC > 25 (macro trend is up)
2. Primary timeframe STC crosses above 25 (momentum turning up)
3. Force Index crosses above 0 OR already positive (volume confirms)
4. Price above 50 EMA (local trend is up)
SHORT CONDITIONS:
1. Higher timeframe STC < 75 (macro trend is down)
2. Primary timeframe STC crosses below 75 (momentum turning down)
3. Force Index crosses below 0 OR already negative (volume confirms)
4. Price below 50 EMA (local trend is down)
Best for: Trending markets, continuation trades
Win rate: Moderate (60-65%)
Risk/Reward: 1:2 to 1:3
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SETUP B: DIVERGENCE REVERSAL (HIGHEST PROBABILITY)
Concept: Identify exhaustion points where price makes new extremes but
momentum (Force Index) fails to confirm
BULLISH DIVERGENCE:
1. Price makes a lower low (LL) over 10 bars
2. Force Index makes a higher low (HL) — refuses to follow price down
3. STC is below 25 (oversold condition)
Trigger: STC starts rising AND Force Index crosses above zero
BEARISH DIVERGENCE:
1. Price makes a higher high (HH) over 10 bars
2. Force Index makes a lower high (LH) — refuses to follow price up
3. STC is above 75 (overbought condition)
Trigger: STC starts falling AND Force Index crosses below zero
Why this works: Divergences signal that the current trend is losing steam.
When volume (Force Index) doesn't confirm new price extremes, a reversal
is likely.
Best for: Reversal trading, range-bound markets
Win rate: High (70-75%)
Risk/Reward: 1:3 to 1:5
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SETUP C: QUICK BOUNCE AT EXTREMES
Concept: Catch rapid mean-reversion moves when price touches EMA50 in
extreme STC zones
LONG CONDITIONS:
1. Price touches 50 EMA from above (pullback in uptrend)
2. STC < 15 (extreme oversold)
3. Force Index > 0 (buyers stepping in)
SHORT CONDITIONS:
1. Price touches 50 EMA from below (pullback in downtrend)
2. STC > 85 (extreme overbought)
3. Force Index < 0 (sellers stepping in)
Best for: Scalping, quick mean-reversion trades
Win rate: Moderate (55-60%)
Risk/Reward: 1:1 to 1:2
Note: Use tighter stops and quick profit-taking
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HOW TO USE THE INDICATOR
STEP 1: CONFIGURE TIMEFRAMES
Primary Timeframe (STC - Primary Timeframe):
- Leave empty to use your current chart timeframe
- This is where you'll take trades
Higher Timeframe (STC - Higher Timeframe):
- Default: 30 minutes
- Recommended ratios:
* 5min chart → 30min higher TF
* 15min chart → 1H higher TF
* 1H chart → 4H higher TF
* Daily chart → Weekly higher TF
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STEP 2: ADJUST STC PARAMETERS FOR YOUR MARKET
Default (23/50/10) works well for stocks and forex, but adjust for:
CRYPTO (volatile):
- Length 1: 15
- Length 2: 35
- Smoothing: 8
(Faster response for rapid price movements)
STOCKS (standard):
- Length 1: 23
- Length 2: 50
- Smoothing: 10
(Balanced settings)
FOREX MAJORS (slower):
- Length 1: 30
- Length 2: 60
- Smoothing: 12
(Filters out noise in 24/7 markets)
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STEP 3: ENABLE YOUR PREFERRED SETUPS
Toggle setups based on your trading style:
Conservative Trader:
✓ Setup B (Divergence) — highest win rate
✗ Setup A (Classic) — only in strong trends
✗ Setup C (Bounce) — too aggressive
Trend Trader:
✓ Setup A (Classic) — primary signals
✓ Setup B (Divergence) — for entries on pullbacks
✗ Setup C (Bounce) — not suitable for trending
Scalper:
✓ Setup C (Bounce) — quick in-and-out
✓ Setup B (Divergence) — high probability scalps
✗ Setup A (Classic) — too slow
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STEP 4: READ THE SIGNALS
ON THE CHART:
Labels appear when conditions are met:
Green labels:
- "LONG A" — Setup A long entry
- "LONG B DIV" — Setup B divergence long (best signal)
- "LONG C" — Setup C bounce long
Red labels:
- "SHORT A" — Setup A short entry
- "SHORT B DIV" — Setup B divergence short (best signal)
- "SHORT C" — Setup C bounce short
IN THE INDICATOR PANEL (bottom):
- Blue line = Primary timeframe STC
- Orange dots = Higher timeframe STC (optional)
- Green/Red bars = Force Index histogram
- Dashed lines at 25/75 = Entry/Exit zones
- Background shading = Oversold (green) / Overbought (red)
INFO TABLE (top-right corner):
Shows real-time status:
- STC values for both timeframes
- Force Index direction
- Price position vs EMA
- Current trend direction
- Active signal type
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TRADING STRATEGY & RISK MANAGEMENT
ENTRY RULES:
Priority ranking (best to worst):
1st: Setup B (Divergence) — wait for these
2nd: Setup A (Classic) — in confirmed trends only
3rd: Setup C (Bounce) — scalping only
Confirmation checklist before entry:
☑ Signal label appears on chart
☑ TREND in info table matches signal direction
☑ Higher timeframe STC aligned (check orange dots or table)
☑ Force Index confirming (check histogram color)
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STOP LOSS PLACEMENT:
Setup A (Classic):
- LONG: Below recent swing low
- SHORT: Above recent swing high
- Typical: 1-2 ATR distance
Setup B (Divergence):
- LONG: Below the divergence low
- SHORT: Above the divergence high
- Typical: 0.5-1.5 ATR distance
Setup C (Bounce):
- LONG: 5-10 pips below EMA50
- SHORT: 5-10 pips above EMA50
- Typical: 0.3-0.8 ATR distance
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TAKE PROFIT TARGETS:
Conservative approach:
- Exit when STC reaches opposite level
- LONG: Exit when STC > 75
- SHORT: Exit when STC < 25
Aggressive approach:
- Hold until opposite signal appears
- Trail stop as STC moves in your favor
Partial profits:
- Take 50% at 1:2 risk/reward
- Let remaining 50% run to target
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WHAT TO AVOID:
❌ Trading Setup A in sideways/choppy markets
→ Wait for clear trend or use Setup B only
❌ Ignoring higher timeframe STC
→ Always check orange dots align with your direction
❌ Taking signals against the major trend
→ If weekly trend is down, be cautious with longs
❌ Overtrading Setup C
→ Maximum 2-3 bounce trades per session
❌ Trading during low volume periods
→ Force Index becomes unreliable
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ALERTS CONFIGURATION
The indicator includes 8 alert types:
Individual setup alerts:
- "Setup A - LONG" / "Setup A - SHORT"
- "Setup B - DIV LONG" / "Setup B - DIV SHORT" ⭐ recommended
- "Setup C - BOUNCE LONG" / "Setup C - BOUNCE SHORT"
Combined alerts:
- "ANY LONG" — fires on any long signal
- "ANY SHORT" — fires on any short signal
Recommended alert setup:
- Create "Setup B - DIV LONG" and "Setup B - DIV SHORT" alerts
- These are the highest probability signals
- Set "Once Per Bar Close" to avoid false alerts
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VISUALIZATION SETTINGS
Show Labels on Chart:
Toggle on/off the signal labels (green/red)
Disable for cleaner chart once you're familiar with the indicator
Show Higher TF STC:
Toggle the orange dots showing higher timeframe STC
Useful for visual confirmation of multi-timeframe alignment
Info Panel:
Cannot be disabled — always shows current status
Positioned top-right to avoid chart interference
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EXAMPLE TRADE WALKTHROUGH
SETUP B DIVERGENCE LONG EXAMPLE:
1. Market Context:
- Price in downtrend, below 50 EMA
- Multiple lower lows forming
- STC below 25 (oversold)
2. Divergence Formation:
- Price makes new low at $45.20
- Force Index refuses to make new low (higher low forms)
- This indicates selling pressure weakening
3. Signal Trigger:
- STC starts turning up
- Force Index crosses above zero
- Label appears: "LONG B DIV"
4. Trade Execution:
- Entry: $45.50 (current price at signal)
- Stop Loss: $44.80 (below divergence low)
- Target 1: $47.90 (STC reaches 75) — risk/reward 1:3.4
- Target 2: Opposite signal or trail stop
5. Trade Management:
- Price rallies to $47.20
- STC reaches 68 (approaching target zone)
- Take 50% profit, move stop to breakeven
- Exit remaining at $48.10 when STC crosses 75
Result: 3.7R gain
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ADVANCED TIPS
1. MULTI-TIMEFRAME CONFLUENCE
For highest probability trades, wait for:
- Primary TF signal
- Higher TF STC aligned (>25 for longs, <75 for shorts)
- Even higher TF trend in same direction (manual check)
2. VOLUME CONFIRMATION
Watch the Force Index histogram:
- Increasing bar size = Strengthening momentum
- Decreasing bar size = Weakening momentum
- Use this to gauge signal strength
3. AVOID THESE MARKET CONDITIONS
- Major news events (Force Index becomes erratic)
- Market open first 30 minutes (volatility spikes)
- Low liquidity instruments (Force Index unreliable)
- Extreme trending days (wait for pullbacks)
4. COMBINE WITH SUPPORT/RESISTANCE
Best signals occur near:
- Key horizontal levels
- Fibonacci retracements
- Previous day's high/low
- Psychological round numbers
5. SESSION AWARENESS
- Asia session: Use lower timeframes, Setup C works well
- London session: Setup A and B both effective
- New York session: All setups work, highest volume
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INDICATOR WINDOWS LAYOUT
MAIN CHART:
- Price action
- 50 EMA (green/red)
- Signal labels
- Info panel
INDICATOR WINDOW:
- STC oscillator (blue line, 0-100 scale)
- Higher TF STC (orange dots, optional)
- Force Index histogram (green/red bars)
- Reference levels (25, 50, 75)
- Background zones (green oversold, red overbought)
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PERFORMANCE OPTIMIZATION
For best results:
Backtesting:
- Test on your specific instrument and timeframe
- Adjust STC parameters if win rate < 55%
- Record which setup works best for your market
Position Sizing:
- Risk 1-2% per trade
- Setup B can use 2% risk (higher win rate)
- Setup C should use 1% risk (lower win rate)
Trade Frequency:
- Setup B: 2-5 signals per week (be patient)
- Setup A: 5-10 signals per week
- Setup C: 10+ signals per week (scalping)
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CREDITS & REFERENCES
This indicator builds upon established technical analysis concepts:
Schaff Trend Cycle:
- Developed by Doug Schaff (1996)
- Original concept published in Technical Analysis of Stocks & Commodities
- Implementation based on standard STC formula
Force Index:
- Developed by Dr. Alexander Elder
- Described in "Trading for a Living" (1993)
- Classic volume-momentum indicator
The multi-timeframe integration, three-setup system, and specific
entry conditions are original contributions of this indicator.
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DISCLAIMER
This indicator is a technical analysis tool and does not guarantee profits.
Past performance is not indicative of future results. Always:
- Use proper risk management
- Test on demo account first
- Combine with fundamental analysis
- Never risk more than you can afford to lose
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SUPPORT & QUESTIONS
If you find this indicator helpful, please:
- Leave a like and comment
- Share your feedback and results
- Report any bugs or issues
For questions about usage or optimization for specific markets,
feel free to comment below.
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MACD Positive & Negative AlertThe MACD (Moving Average Convergence Divergence) is a momentum and trend-following indicator that helps traders identify the strength and direction of a trend, spot potential reversals, and fine-tune entry/exit timing.
Core Components
- MACD Line:
The difference between the 12-period and 26-period EMA (Exponential Moving Averages). This line highlights shifts in momentum and identifies the prevailing trend direction.
- Signal Line:
A 9-period EMA of the MACD line, acting as a trigger for buy/sell signals. When the MACD line crosses above the signal line, it suggests a bullish signal; when it crosses below, it suggests a bearish one.
- Histogram:
Shows the difference between the MACD line and the signal line as a bar graph. The histogram helps traders gauge the strength of the momentum and can warn of possible reversals. A rapidly growing histogram means strengthening momentum, while a shrinking one indicates weakening momentum.
Main Uses
- Trend Identification:
A positive MACD value typically signals a bullish trend, while a negative value signals a bearish trend.
- Momentum Analysis:
Divergences between MACD and price can warn of upcoming reversals. Increasing MACD histogram bars confirm strong momentum; shrinking bars suggest consolidation or reversal.
- Signal Generation:
Crossovers between the MACD line and the signal line generate trade signals—bullish (buy) if the MACD moves above the signal, bearish (sell) if it falls below l.
Example Interpretation
- MACD Crossover:
If the MACD line crosses above the signal line, it's often considered a buy signal; a cross below is a sell signal.
- Zero Line Cross:
If the MACD histogram moves from below zero to above, this is considered a bullish momentum shift; above zero to below is a bearish move.
The MACD is most effective in trending markets and should ideally be used alongside additional indicators for robust trading decisions.
UDVR + OBV Combo — MTF (v6)The UDVR + OBV Combo is a multi-timeframe volume analysis tool that blends the Up/Down Volume Ratio with a normalized On-Balance Volume signal. It highlights when accumulation or distribution truly supports price action, adds higher-timeframe context, and shades the background when both indicators align. Use it to confirm breakouts, spot divergences, and filter trades with the backing of real volume flows.
1.Up/Down Volume Ratio (UDVR)
•Compares the rolling sum of up-volume (bars where price closed higher) vs down-volume (bars where price closed lower).
•A ratio > 1.0 = more accumulation (bullish pressure).
•A ratio < 1.0 = more distribution (bearish pressure).
•Optional histogram shows deviations from the 1.0 baseline.
•Customizable handling of equal closes (count as up, down, split, or ignore).
•Configurable lookback length and optional EMA smoothing.
2. On-Balance Volume (OBV)
•Classic cumulative OBV implemented natively (adds volume on up-bars, subtracts on down-bars).
•Normalized with a z-score so it can be compared across different symbols/timeframes.
•Includes an EMA signal line for slope detection.
•Alignment of OBV vs its EMA highlights rising or waning participation.
3. Multi-Timeframe Support
•Both UDVR and OBV can be plotted from a higher timeframe (HTF) (e.g. Daily UDVR shown on a 1h chart).
•Lets you see big-money accumulation/distribution while trading intraday.
•Shaded background when current TF and HTF agree (both bullish or both bearish).
How to read it
• Bullish confirmation = UDVR > 1 (accumulation) and OBV above EMA (rising participation).
• Bearish confirmation = UDVR < 1 (distribution) and OBV below EMA (falling participation).
• Mixed signals (e.g. UDVR > 1 but OBV falling) = caution; price may lack conviction.
• Divergences : If price makes a new high but OBV or UDVR does not, it’s a warning of weakening trend.
• Higher timeframe context : set HTF = Daily or Weekly and watch how short-term signals align with institutional flows. A long trade on the 15m chart is stronger when Daily UDVR is also above 1.
Inputs
•UDVR Lookback: number of bars for rolling volume sums.
•Smoothing EMA: smooths UDVR for stability.
•Equal Close Handling: decide how equal closes affect UDVR.
•Signal Band: optional UDVR extreme thresholds.
•Show Histogram: toggle UDVR histogram around baseline.
•Higher Timeframe UDVR: overlay Daily/Weekly UDVR on lower timeframe charts.
•OBV EMA length: slope proxy for normalized OBV.
•OBV Normalization window: controls z-score sensitivity.
•Higher Timeframe OBV: overlay higher timeframe OBV.
Alerts
•UDVR Bullish/Bearish cross at the 1.0 baseline.
•OBV slope up/down when OBV crosses its EMA.
•Alignment signals when UDVR and OBV agree (both confirm bullish or bearish conditions).
Why it’s useful
•Combines trend, momentum, and participation in one place.
•Helps avoid false breakouts by checking if volume supports the move.
•Lets you spot accumulation/distribution shifts before they show up in price.
•Gives a higher timeframe context so you’re not trading against the “big picture.”
Once applied, the indicator creates a dedicated pane below price with the following components:
UDVR Line (green/red)
• Green when UDVR > 1.0 (more up-volume than down-volume → accumulation).
• Red when UDVR < 1.0 (more down-volume → distribution).
UDVR Baseline and Bands
• Grey baseline at 1.0 = balance between buying and selling volume.
• Optional upper/lower bands (default 1.5 and 0.67) highlight extreme imbalances.
• Shaded areas between baseline and bands provide visual context for strength/weakness.
UDVR Histogram (optional)
• Columns around the baseline showing (UDVR – 1.0).
• Quick way to gauge how far above/below balance the ratio is.
Higher-Timeframe UDVR (teal line)
• Overlays the UDVR from a higher timeframe (e.g. Daily) on your intraday chart.
• Lets you see whether institutional flows support your shorter-term signals.
OBV Normalized (blue/orange line)
• Classic OBV, but normalized with a z-score so it stays readable across assets.
• Blue when OBV is above its EMA (rising participation).
• Orange when below its EMA (waning participation).
OBV EMA (grey line)
• Signal line showing the slope of OBV.
• Crosses between OBV and this line mark shifts in participation.
Higher-Timeframe OBV (purple line, optional)
• Plots OBV from a higher timeframe for additional context.
Background Shading
• Light green = both UDVR > 1 and OBV > OBV-EMA (bullish alignment).
• Light red = both UDVR < 1 and OBV < OBV-EMA (bearish alignment).
Liquidity Point LinesLiquidity Point Lines
The "Liquidity Point Lines" indicator helps traders identify potential areas of liquidity in the market by drawing lines at specific price levels where significant "liquidation events" may have occurred. These events are determined by analyzing the MACD Histogram and identifying pivot points that suggest strong movements, which are often associated with the flushing out of short or long positions.
How It Works
This indicator leverages the MACD Histogram to gauge the strength of price momentum. It then identifies pivot highs and lows within the MACD Histogram's values. When a significant pivot is detected, the indicator interprets this as a potential "liquidity point" — a price level where a substantial amount of buy or sell orders (often due to liquidations) may have been executed.
The indicator distinguishes between:
Shorts Liquidation Points (Resistance): These are identified when the MACD Histogram registers a pivot high, suggesting a strong upward movement that could have liquidated short positions. Lines are drawn at the high price of the bar where this pivot occurred.
Longs Liquidation Points (Support): Conversely, these are identified when the MACD Histogram registers a pivot low, indicating a strong downward movement that might have liquidated long positions. Lines are drawn at the low price of the bar where this pivot occurred.
Key Features and Settings
The "Liquidity Point Lines" indicator offers extensive customization to tailor its sensitivity and visual representation:
MACD Settings for Liquidity: Configure the underlying MACD calculation with adjustable Fast Length, Slow Length, Source, Signal Smoothing, and MA Types (SMA/EMA) for both the Oscillator and Signal Line.
Liquidity Points Settings:
Pivot Lookback Left/Right: Define the number of bars to look back on either side to identify a pivot in the MACD Histogram.
Dynamic Strength Thresholds: This powerful feature allows the indicator to dynamically calculate the significance of a liquidation event. When enabled, it uses the average absolute histogram value over a specified Dynamic Threshold Lookback Period and applies Small and Medium Threshold Factors to determine the strength (Small, Medium, or Large) of the liquidity point.
Fixed Strength Thresholds: If dynamic thresholds are disabled, you can set fixed numerical values for Small and Medium Histogram Thresholds to define the strength categories.
Color & Style Customization: Assign distinct colors for Small, Medium, and Large liquidation points, choose the Line Style (Solid, Dashed, Dotted), and set the Label Text Color.
Label X Offset (To Right): Adjust the horizontal position of the liquidity point labels on your chart.
Liquidity Points Management:
Max Active Liquidity Lines: Control the maximum number of liquidity lines displayed simultaneously on your chart. Older lines are automatically removed to maintain clarity, except for lines that have been "touched" (i.e., price has interacted with that liquidity level).
Visual Interpretation
Each liquidity line is colored according to the strength of the detected liquidation event, making it easy to visually assess the potential significance of the price level. Lines extend to the right, serving as ongoing reference points. When the price interacts with a liquidity line (i.e., "touches" it), the line and its corresponding label are removed, indicating that the liquidity at that level may have been absorbed.
This indicator can be a valuable tool for identifying potential support and resistance levels, understanding market reactions to "liquidation cascades," and informing your trading decisions.
CoffeeShopCrypto Supertrend Liquidity EngineMost SuperTrend indicators use fixed ATR multipliers that ignore context—forcing traders to constantly tweak settings that rarely adapt well across timeframes or assets.
This Supertrend is a nodd to and a more completion of the work
done by Olivier Seban ( @olivierseban )
This version replaces guesswork with an adaptive factor based on prior session volatility, dynamically adjusting stops to match current conditions. It also introduces liquidity-aware zones, real-time strength histograms, and a visual control panel—making your stoploss smarter, more responsive, and aligned with how the market actually moves.
📏 The Multiplier Problem & Adaptive Factor Solution
Traditional SuperTrend indicators rely on fixed ATR multipliers—often arbitrary numbers like 1.5, 2, or 3. The issue? No logical basis ties these values to actual market conditions. What works on a 5-minute Nasdaq chart fails on a daily EUR/USD chart. Traders spend hours tweaking multipliers per asset, timeframe, or volatility phase—and still end up with stoplosses that are either too tight or too loose. Worse, the market doesn’t care about your setting—it behaves according to underlying volatility, not your parameter.
This version fixes that by automating the multiplier selection entirely. It uses a 4-zone model based on the current ATR relative to the previous session’s ATR, dynamically adjusting the SuperTrend factor to match current volatility. It eliminates guesswork, adapts to the asset and timeframe, and ensures you’re always using a context-aware stoploss—one that evolves with the market instead of fighting it.
ATR EXAMPLE
Let’s say prior session ATR = 2.00
Now suppose current ATR = 0.32
This places us in Zone 1 (Very Low Volatility)
It doesn’t imply "overbought" or "oversold" — it tells you the market is moving very little, which often means:
Lower risk | Smaller stops | Smaller opportunities (and losses)
🔁 Liquidity Zones vs. Arbitrary Pullbacks
The standard SuperTrend stop loss line often looks like price “barely misses it” before continuing its trend. Traders call this "stop hunting," but what’s really happening is liquidity collection—price pulls back into a zone rich in orders before continuing. The problem? The old SuperTrend doesn’t show this zone. It only draws the outer limit, leaving no visual cue for where entries or continuation moves might realistically originate.
This script introduces 2 levels in the Liquidity Zone. One for Support and one for Stophunts, which draw dynamically between the current price and the SuperTrend line. These levels reflect where the market is most likely to revisit before resuming the trend. By visualizing the area just above the Supertrend stop loss, you can anticipate pullbacks, spot ideal re-entries, and avoid premature exits. This bridges the gap between mechanical stoploss logic and real-world liquidity behavior.
⏳ Prior Session ATR vs. Live ATR
Using real-time ATR to determine movement potential is like driving by looking in your rearview mirror. It’s reactive, not predictive. Traders often base decisions on live ATR, unaware that today’s range is still unfolding —creating volatility mismatches between what’s calculated and what actually matters. Since ATR reflects range, calculating it mid-session gives an incomplete and misleading picture of true volatility.
Instead, this system uses the ATR from the previous session , anchoring your volatility assumptions in a fully-formed price structure . It tells you how far price moved in the last full market phase—be it London, New York, or Tokyo—giving you a more reliable gauge of expected range today. This is a smarter way to estimate how far price could move rather than how far it has moved.
The Smoothing function will take the ATR, Support, Resistance, Stophunt Levels, and the Moving Avearage and smooth them by the calculation you choose.
It will also plot a moving average on your chart against closing prices by the smoothing function you choose.
🧭 Scalping vs. Trending Modes
The market moves in at least 4 phases. Trending, Ranging, Consolidation, Distribution.
Every trader has a different style —some scalp low-volatility moves during off-hours, while others ride macro trends across days. The problem with classic SuperTrend? It treats every market condition the same. A fixed system can’t possibly provide proper stoploss spacing for both a fast scalp and a long-term swing. Traders are forced to rebuild their system every time the market changes character or the session shifts.
This version solves that with a simple toggle:
Scalping or Trend Mode . With one switch, it inverts the logic of the adaptive factor to either tighten or loosen your trailing stops. During low-liquidity hours or consolidation phases, Scalping Mode offers snug stoplosses. During expansion or clear directional bias.
Trend Mode lets the trade breathe. This is flexibility built directly into the logic—not something you have to recalibrate manually.
📉 Histogram Oscillator for Move Strength
In legacy indicators, there’s no built-in way to gauge when the move is losing power . Traders rely on price action or momentum indicators to guess if a trend is fading. But this adds clutter, lag, and often contradiction. The classic SuperTrend doesn’t offer insight into how strong or weak the current trend leg is—only whether price has crossed a line.
This version includes a Trending Liquidity Histogram —a histogram that shows whether the liquidity in the SuperTrend zone is expanding or compressing. When the bars weaken or cross toward zero, it signals liquidity exhaustion . This early warning gives you time to prep for reversals or anticipate pullbacks. It even adapts visually depending on your trading mode, showing color-coded signals for scalping vs. trending behavior. It's both a strength gauge and a trade timing tool—built into your stoploss logic.
Histogram in Scalping Mode
Histogram in Trending Mode
📊 Visual Table for Real-Time Clarity
A major issue with custom indicators is opacity —you don’t always know what settings or values are currently being used. Even worse, if your dynamic logic changes mid-trade, you may not notice unless you go digging into the code or logs. This can create confusion, especially for discretionary traders.
This SuperTrend solves it with a clean visual summary table right on your chart. It shows your current ATR value, adaptive multiplier, trailing stop level, and whether a new zone size is active. That means no surprises and no second-guessing—everything important is visible and updated in real-time.
Chebyshev-Gauss Convergence DivergenceThe Chebyshev-Gauss Convergence Divergence is a momentum indicator that leverages the Chebyshev-Gauss Moving Average (CG-MA) to provide a smoother and more responsive alternative to traditional oscillators like the MACD. For more information see the moving average script:
How it works:
It calculates a fast CG-MA and a slow CG-MA. The CG-MA uses Gauss-Chebyshev quadrature to compute a weighted average, which can offer a better trade-off between lag and smoothness compared to simple or exponential MAs.
The Oscillator line is the difference between the fast CG-MA and the slow CG-MA.
A Signal Line, which is a simple moving average of the Oscillator line, is plotted to show the average trend of the oscillator.
A Histogram is plotted, representing the difference between the Oscillator and the Signal Line. The color of the histogram bars changes to indicate whether momentum is strengthening or weakening.
How to use:
Crossovers: A buy signal can be generated when the Oscillator line crosses above the Signal line. A sell signal can be generated when it crosses below.
Zero Line: When the Oscillator crosses above the zero line, it indicates upward momentum (fast MA is above slow MA).When it crosses below zero, it indicates downward momentum.
Divergence: Like with the MACD, look for divergences between the oscillator and price action to spot potential reversals.
Histogram: The histogram provides a visual representation of the momentum. When the bars are growing, momentum is increasing. When they are shrinking, momentum is fading.
SMI-DarknessIndicator Description: SMI-Darkness
The SMI-Darkness is an indicator based on the Stochastic Momentum Index (SMI), designed to help identify the strength and direction of an asset's trend, as well as potential buy and sell signals. It displays a smoothed SMI using multiple moving average options to customize the indicator’s behavior according to the user’s trading style.
Main Features
Smoothed SMI: Calculates the traditional SMI and smooths it using a user-configurable moving average, improving signal clarity.
Signal Line: Displays a smoothed signal line to identify crossovers with the SMI, generating potential entry or exit points.
Histogram: Shows the difference between the smoothed SMI and the signal line, visually highlighting trend strength. Blue bars indicate buying strength, while yellow bars indicate selling strength.
Horizontal Lines: Includes overbought (+40) and oversold (-40) levels, plus a neutral zero level to aid interpretation.
Indicator Parameters
SMI Short Period: Sets the short period used to calculate the SMI (default 5). Lower periods make the indicator more sensitive.
SMI Signal Period: Sets the period to smooth the signal line (default 5). Adjust to control the signal line's smoothness.
Moving Average Type: Choose the moving average type to smooth the SMI and signal line. Options include:
SMA (Simple Moving Average)
SMMA (Smoothed Moving Average)
EMA (Exponential Moving Average)
WMA (Weighted Moving Average)
HMA (Hull Moving Average)
JMA (Jurik Moving Average) — Note: This is not an original or proprietary moving average but a publicly available open-source version created by TradingView users.
VWMA (Volume-Weighted Moving Average)
KAMA (Kaufman Adaptive Moving Average)
How to Use
Trend Identification: Observe the position of the smoothed SMI relative to the signal line and the histogram values.
When the histogram is positive (blue bars), momentum is bullish.
When the histogram is negative (yellow bars), momentum is bearish.
Buy and Sell Signals:
A crossover of the smoothed SMI above the signal line may indicate a buy signal.
A crossover of the smoothed SMI below the signal line may indicate a sell signal.
Overbought/Oversold Levels:
SMI values above +40 suggest potential overbought conditions, signaling caution on long positions.
Values below -40 suggest potential oversold conditions, indicating possible buying opportunities.
Customization: Adjust the parameters to balance sensitivity and noise, choosing the moving average type that best fits your trading style.
Momentum Fusion v1Momentum Fusion v1
Overview
Momentum Fusion v1 (MFusion) is a multi-oscillator indicator that combines several components to analyze market momentum and trend strength. It incorporates modified versions of classic indicators such as PVI (Positive Volume Index), NVI (Negative Volume Index), MFI (Money Flow Index), RSI, Stochastic, and Bollinger Bands Oscillator. The indicator displays a histogram that changes color based on momentum strength and includes "FUSION🔥" signal labels when extreme values are reached.
Indicator Settings
Parameters:
EMA Length – Smoothing period for the moving average (default: 255).
Smoothing Period – Internal calculation smoothing parameter (default: 15).
BB Multiplier – Standard deviation multiplier for Bollinger Bands (default: 2.0).
Show verde / marron / media lines – Toggles the display of auxiliary lines.
Show FUSION🔥 label – Enables/disables signal labels.
Indicator Components
1. PVI (Positive Volume Index)
Formula:
pvi := volume > volume ? nz(pvi ) + (close - close ) / close * sval : nz(pvi )
Description:
PVI increases when volume rises compared to the previous bar and accounts for price percentage change. The stronger the price movement with increasing volume, the higher the PVI value.
2. NVI (Negative Volume Index)
Formula:
nvi := volume < volume ? nz(nvi ) + (close - close ) / close * sval : nz(nvi )
Description:
NVI tracks price movements during declining volume. If the price rises on low volume, it may indicate a "stealth" trend.
3. Money Flow Index (MFI)
Formula:
100 - 100 / (1 + up / dn)
Description:
An oscillator measuring money flow strength. Values above 80 suggest overbought conditions, while values below 20 indicate oversold conditions.
4. Stochastic Oscillator
Formula:
k = 100 * (close - lowest(low, length)) / (highest(high, length) - lowest(low, length))
Description:
A classic stochastic oscillator showing price position relative to the selected period's range.
5. Bollinger Bands Oscillator
Formula:
(tprice - BB midline) / (upper BB - lower BB) * 100
Description:
Indicates the price position relative to Bollinger Bands in percentage terms.
Key Lines & Histogram
1. Verde (Green Line)
Calculation:
verde = marron + oscp (normalized PVI)
Interpretation:
Higher values indicate stronger bullish momentum. A FUSION🔥 signal appears when the value reaches 750+.
2. Marron (Brown Line)
Calculation:
marron = (RSI + MFI + Bollinger Osc + Stochastic / 3) / 2
Interpretation:
A composite oscillator combining multiple indicators. Higher values suggest overbought conditions.
3. Media (Red Line)
Calculation:
media = EMA of marron with smoothing period
Interpretation:
Acts as a signal line for trend confirmation.
4. Histogram
Calculation:
histo = verde - marron
Colors:
Bright green (>100) – Strong bullish momentum.
Light green (>0) – Moderate bullish momentum.
Orange (<0) – Bearish momentum.
Red (<-100) – Strong bearish momentum.
Signals & Alerts
1. FUSION🔥 (Strong Momentum)
Condition:
verde >= 750
Visualization:
A "FUSION🔥" label appears below the chart.
Alert:
Can be set to trigger notifications when the condition is met.
2. Background Aura
Condition:
verde > 850
Visualization:
The chart background turns teal, indicating extreme momentum.
Usage Recommendations
FUSION🔥 Signal – Can be used as a long entry point when confirmed by other indicators.
Histogram:
1. Green bars – Potential long entry.
2. Red/orange bars – Potential short entry.
3. Media & Marron Crossover – Can serve as an additional trend filter.
4. Suitable for a 5-15 minute time frame
Conclusion
Momentum Fusion v1 is a powerful tool for momentum analysis, combining multiple indicators into a unified system. It is suitable for:
Trend traders (catching strong movements).
Scalpers (identifying short-term impulses).
Swing traders (filtering entry points).
The indicator features customizable settings and visual signals, making it adaptable to various trading styles.
Dynamic Trade Signal Validator (DTSV)The Dynamic Trade Signal Validator (DTSV) is designed to filter false trade signals while generating reliable, frequent trade opportunities. False signals, which lead to unprofitable trades, often occur in choppy or low-momentum markets. The DTSV combines Hull Moving Average (HMA) crossovers, Average True Range (ATR) breakout confirmation, and MACD histogram momentum filtering to ensure signals align with trend, volatility, and momentum, making it ideal for day trading or swing trading across assets like stocks, forex, or cryptocurrencies.
How It Works
The DTSV uses three components to validate trade signals, balancing frequency and reliability:
HMA Crossover for Trend Direction:
Two HMAs (default: 9-period fast, 21-period slow) detect trend changes. A buy signal triggers when the fast HMA crosses above the slow HMA (bullish), and a sell signal when it crosses below (bearish). HMAs reduce lag compared to traditional MAs, enabling more responsive trend detection.
ATR Breakout Confirmation:
The 14-period ATR ensures significant price movement by requiring the bar’s range (high minus low) to exceed the ATR multiplied by 1.0 (adjustable). This confirms volatility, reducing false signals in stagnant markets.
MACD Histogram Momentum Filter:
The MACD (default: 12, 26, 9) histogram confirms momentum. Buy signals require a positive histogram (bullish momentum), and sell signals need a negative histogram (bearish momentum), ensuring directional strength.
Signal Generation
Buy signals (green triangles below bars) occur when a bullish HMA crossover, ATR breakout, and positive MACD histogram align. Sell signals (red triangles above bars) require a bearish crossover, ATR breakout, and negative histogram. This triple confirmation minimizes false trades while maintaining frequent signals.
Enhanced KLSE Banker Flow Oscillator# Enhanced KLSE Banker Flow Oscillator
## Description
The Enhanced KLSE Banker Flow Oscillator is a sophisticated technical analysis tool designed specifically for the Malaysian stock market (KLSE). This indicator analyzes price and volume relationships to identify potential smart money movements, providing early signals for market reversals and continuation patterns.
The oscillator measures the buying and selling pressure in the market with a focus on detecting institutional activity. By combining money flow calculations with volume filters and price action analysis, it helps traders identify high-probability trading opportunities with reduced noise.
## Key Features
- Dual-Timeframe Analysis: Combines long-term money flow trends with short-term momentum shifts for more accurate signals
- Adaptive Volume Filtering: Automatically adjusts volume thresholds based on recent market conditions
- Advanced Divergence Detection: Identifies potential trend reversals through price-flow divergences
- Early Signal Detection: Provides anticipatory signals before major price movements occur
- Multiple Signal Types: Offers both early alerts and strong confirmation signals with clear visual markers
- Volatility Adjustment: Adapts sensitivity based on current market volatility for more reliable signals
- Comprehensive Visual Feedback: Color-coded oscillator, signal markers, and optional text labels
- Customizable Display Options: Toggle momentum histogram, early signals, and zone fills
- Organized Settings Interface: Logically grouped parameters for easier configuration
## Indicator Components
1. Main Oscillator Line: The primary banker flow line that fluctuates above and below zero
2. Early Signal Line: Secondary indicator showing potential emerging signals
3. Momentum Histogram: Visual representation of flow momentum changes
4. Zone Fills: Color-coded background highlighting positive and negative zones
5. Signal Markers: Visual indicators for entry and exit points
6. Reference Lines: Key levels for strong and early signals
7. Signal Labels: Optional text annotations for significant signals
## Signal Types
1. Strong Buy Signal (Green Arrow): Major bullish signal with high probability of success
2. Strong Sell Signal (Red Arrow): Major bearish signal with high probability of success
3. Early Buy Signal (Blue Circle): First indication of potential bullish trend
4. Early Sell Signal (Red Circle): First indication of potential bearish trend
5. Bullish Divergence (Yellow Triangle Up): Price making lower lows while flow makes higher lows
6. Bearish Divergence (Yellow Triangle Down): Price making higher highs while flow makes lower highs
## Parameters Explained
### Core Settings
- MFI Base Length (14): Primary calculation period for money flow index
- Short-term Flow Length (5): Calculation period for early signals
- KLSE Sensitivity (1.8): Multiplier for flow calculations, higher = more sensitive
- Smoothing Length (5): Smoothing period for the main oscillator line
### Volume Filter Settings
- Volume Filter % (65): Minimum volume threshold as percentage of average
- Use Adaptive Volume Filter (true): Dynamically adjusts volume thresholds
### Signal Levels
- Strong Signal Level (15): Threshold for strong buy/sell signals
- Early Signal Level (10): Threshold for early buy/sell signals
- Early Signal Threshold (0.75): Sensitivity factor for early signals
### Advanced Settings
- Divergence Lookback (34): Period for checking price-flow divergences
- Show Signal Labels (true): Toggle text labels for signals
### Visual Settings
- Show Momentum Histogram (true): Toggle the momentum histogram display
- Show Early Signal (true): Toggle the early signal line display
- Show Zone Fills (true): Toggle background color fills
## How to Use This Indicator
### Installation
1. Add the indicator to your TradingView chart
2. Default settings are optimized for KLSE stocks
3. Customize parameters if needed for specific stocks
### Basic Interpretation
- Oscillator Above Zero: Bullish bias, buying pressure dominates
- Oscillator Below Zero: Bearish bias, selling pressure dominates
- Crossing Zero Line: Potential shift in market sentiment
- Extreme Readings: Possible overbought/oversold conditions
### Advanced Interpretation
- Divergences: Early warning of trend exhaustion
- Signal Confluences: Multiple signal types appearing together increase reliability
- Volume Confirmation: Signals with higher volume are more significant
- Momentum Alignment: Histogram should confirm direction of main oscillator
### Trading Strategies
#### Trend Following Strategy
1. Identify market trend direction
2. Wait for pullbacks shown by oscillator moving against trend
3. Enter when oscillator reverses back in trend direction with a Strong signal
4. Place stop loss below/above recent swing low/high
5. Take profit at previous resistance/support levels
#### Counter-Trend Strategy
1. Look for oscillator reaching extreme levels
2. Identify divergence between price and oscillator
3. Wait for oscillator to cross Early signal threshold
4. Enter position against prevailing trend
5. Use tight stop loss (1 ATR from entry)
6. Take profit at first resistance/support level
#### Breakout Confirmation Strategy
1. Identify stock consolidating in a range
2. Wait for price to break out of range
3. Confirm breakout with oscillator crossing zero line in breakout direction
4. Enter position in breakout direction
5. Place stop loss below/above the breakout level
6. Trail stop as price advances
### Signal Hierarchy and Reliability
From highest to lowest reliability:
1. Strong Buy/Sell signals with divergence and high volume
2. Strong Buy/Sell signals with high volume
3. Divergence signals followed by Early signals
4. Strong Buy/Sell signals with normal volume
5. Early Buy/Sell signals with high volume
6. Early Buy/Sell signals with normal volume
## Complete Trading Plan Example
### KLSE Market Trading System
#### Pre-Trading Preparation
1. Review overall market sentiment (bullish, bearish, or neutral)
2. Scan for stocks showing significant banker flow signals
3. Note key support/resistance levels for watchlist stocks
4. Prioritize trade candidates based on signal strength and volume
#### Entry Rules for Long Positions
1. Banker Flow Oscillator above zero line (positive flow environment)
2. One or more of the following signals present:
- Strong Buy signal (green arrow)
- Bullish Divergence signal (yellow triangle up)
- Early Buy signal (blue circle) with confirming price action
3. Entry confirmation requirements:
- Volume above 65% of 20-day average
- Price above short-term moving average (e.g., 20 EMA)
- No immediate resistance within 3% of entry price
4. Entry on the next candle open after signal confirmation
#### Entry Rules for Short Positions
1. Banker Flow Oscillator below zero line (negative flow environment)
2. One or more of the following signals present:
- Strong Sell signal (red arrow)
- Bearish Divergence signal (yellow triangle down)
- Early Sell signal (red circle) with confirming price action
3. Entry confirmation requirements:
- Volume above 65% of 20-day average
- Price below short-term moving average (e.g., 20 EMA)
- No immediate support within 3% of entry price
4. Entry on the next candle open after signal confirmation
#### Position Sizing Rules
1. Base risk per trade: 1% of trading capital
2. Position size calculation: Capital × Risk% ÷ Stop Loss Distance
3. Position size adjustments:
- Increase by 20% for Strong signals with above-average volume
- Decrease by 20% for Early signals without confirming price action
- Standard size for all other valid signals
#### Stop Loss Placement
1. For Long Positions:
- Place stop below the most recent swing low
- Minimum distance: 1.5 × ATR(14)
- Maximum risk: 1% of trading capital
2. For Short Positions:
- Place stop above the most recent swing high
- Minimum distance: 1.5 × ATR(14)
- Maximum risk: 1% of trading capital
#### Take Profit Strategy
1. First Target (33% of position):
- 1.5:1 reward-to-risk ratio
- Move stop to breakeven after reaching first target
2. Second Target (33% of position):
- 2.5:1 reward-to-risk ratio
- Trail stop at previous day's low/high
3. Final Target (34% of position):
- 4:1 reward-to-risk ratio or
- Exit when opposing signal appears (e.g., Strong Sell for long positions)
#### Trade Management Rules
1. After reaching first target:
- Move stop to breakeven
- Consider adding to position if new confirming signal appears
2. After reaching second target:
- Trail stop using banker flow signals
- Exit remaining position when:
- Oscillator crosses zero line in opposite direction
- Opposing signal appears
- Price closes below/above trailing stop level
3. Maximum holding period:
- 20 trading days for trend-following trades
- 10 trading days for counter-trend trades
- Re-evaluate if targets not reached within timeframe
#### Risk Management Safeguards
1. Maximum open positions: 5 trades
2. Maximum sector exposure: 40% of trading capital
3. Maximum daily drawdown limit: 3% of trading capital
4. Mandatory stop trading rules:
- After three consecutive losing trades
- After reaching 5% account drawdown
- Resume after two-day cooling period and strategy review
#### Performance Tracking
1. Track for each trade:
- Signal type that triggered entry
- Oscillator reading at entry and exit
- Volume relative to average
- Price action confirmation patterns
- Holding period
- Reward-to-risk achieved
2. Review performance metrics weekly:
- Win rate by signal type
- Average reward-to-risk ratio
- Profit factor
- Maximum drawdown
3. Adjust strategy parameters based on performance:
- Increase position size for highest performing signals
- Decrease or eliminate trades based on underperforming signals
## Advanced Usage Tips
1. Combine with Support/Resistance:
- Signals are more reliable when they occur at key support/resistance levels
- Look for banker flow divergence at major price levels
2. Multiple Timeframe Analysis:
- Use the oscillator on both daily and weekly timeframes
- Stronger signals when both timeframes align
- Enter on shorter timeframe when confirmed by longer timeframe
3. Sector Rotation Strategy:
- Compare banker flow across different sectors
- Rotate capital to sectors showing strongest positive flow
- Avoid sectors with persistent negative flow
4. Volatility Adjustments:
- During high volatility periods, wait for Strong signals only
- During low volatility periods, Early signals can be more actionable
5. Optimizing Parameters:
- For more volatile stocks: Increase Smoothing Length (6-8)
- For less volatile stocks: Decrease KLSE Sensitivity (1.2-1.5)
- For intraday trading: Reduce all length parameters by 30-50%
## Fine-Tuning for Different Markets
While optimized for KLSE, the indicator can be adapted for other markets:
1. For US Stocks:
- Reduce KLSE Sensitivity to 1.5
- Increase Volume Filter to 75%
- Adjust Strong Signal Level to 18
2. For Forex:
- Increase Smoothing Length to 8
- Reduce Early Signal Threshold to 0.6
- Focus more on divergence signals than crossovers
3. For Cryptocurrencies:
- Increase KLSE Sensitivity to 2.2
- Reduce Signal Levels (Strong: 12, Early: 8)
- Use higher Volume Filter (80%)
By thoroughly understanding and properly implementing the Enhanced KLSE Banker Flow Oscillator, traders can gain a significant edge in identifying institutional money flow and making more informed trading decisions, particularly in the Malaysian stock market.
Dollar Volume DivergenceOverview
The Dollar Volume Profile and Divergence Indicator is a comprehensive tool designed to analyze both standard volume and dollar volume activity in the market. It visualizes dollar volume (calculated as close * volume) and highlights divergences between dollar volume and standard volume, providing insights into underlying market dynamics that aren't immediately visible with traditional volume analysis.
Key Features
Dollar Volume Profile:
Plots dollar volume as a histogram.
Highlights high-dollar volume bars in green (indicating significant trading activity).
Includes an optional average dollar volume line to show trends over time.
Volume-Divergence Analysis:
Calculates the difference (divergence) between dollar volume and standard volume.
Displays positive divergence (dollar volume > standard volume) in green and negative divergence (dollar volume < standard volume) in red.
Supports both histogram and boolean point visualization for divergence, offering flexibility in how the data is displayed.
Customizable Visualization:
Users can toggle between a Histogram or Boolean Points for divergence visualization.
Option to enable or disable the dollar volume profile and its average line.
Adjustable length parameter to fine-tune sensitivity for averages and divergences.
Use Cases
Volume Confirmation: Analyze whether dollar volume aligns with standard volume to confirm strong price movements.
Divergence Detection: Identify areas where dollar volume and standard volume deviate, which may signal potential reversals or exhaustion in a trend.
Market Strength Analysis: Assess the intensity of trading activity at specific price levels to determine key areas of interest.
How It Works
Dollar Volume Calculation:
Dollar volume is derived by multiplying the close price by the volume for each bar.
A moving average of dollar volume is used to determine relative activity levels.
Divergence Calculation:
The script calculates the difference between dollar volume and standard volume.
Positive values indicate that dollar volume exceeds standard volume, suggesting institutional or larger-scale trades.
Negative values highlight areas of lower dollar volume compared to standard volume.
Visualization:
The Dollar Volume Profile is displayed as a histogram, with high-dollar volume bars highlighted.
Divergences are overlaid as either a histogram or triangle markers, depending on user preference.
Average lines (optional) provide smoother trends for both dollar volume and divergence.
Customization Options
Length: Adjusts the period for moving average calculations.
Plot Style: Choose between Histogram or Boolean Points for divergence visualization.
Toggle Visibility: Enable or disable the Dollar Volume Profile and its average line for a cleaner chart.
Why Use This Indicator?
This indicator bridges the gap between traditional volume analysis and dollar volume analysis, offering deeper insights into market behavior. By combining these metrics, traders can detect nuanced patterns, validate trends, and identify divergences that may signal market turning points or continuation.
Best Practices
Use this indicator in conjunction with price action and other technical indicators for confirmation.
Look for divergences in high-dollar volume areas to detect potential trend reversals.
Analyze the interaction between the dollar volume profile and divergence histogram for a comprehensive view of market activity.
Important Notice:
Trading financial markets involves significant risk and may not be suitable for all investors. The use of technical indicators like this one does not guarantee profitable results. This indicator should not be used as a standalone analysis tool. It is essential to combine it with other forms of analysis, such as fundamental analysis, risk management strategies, and awareness of current market conditions. Always conduct thorough research or consult with a qualified financial advisor before making trading decisions. Past performance is not indicative of future results.
Disclaimer:
Trading financial instruments involves substantial risk and may not be suitable for all investors. Past performance is not indicative of future results. This indicator is provided for informational and educational purposes only and should not be considered investment advice. Always conduct your own research and consult with a licensed financial professional before making any trading decisions.
Note: The effectiveness of any technical indicator can vary based on market conditions and individual trading styles. It's crucial to test indicators thoroughly using historical data and possibly paper trading before applying them in live trading scenarios.
