Gauti Market Maker Killzone EMA1. Identifying the Trend
Use Daily (1D) and Hourly (1H) Exponential Moving Averages (EMAs) to define the overall trend:
Bullish Trend: Both 1D and 1H EMAs are upward sloping, and the price is above these EMAs.
Bearish Trend: Both 1D and 1H EMAs are downward sloping, and the price is below these EMAs.
2. Confirmation with Higher Timeframes
Bullish Conditions:
Check 1D and 4H charts for price action above the EMA bands.
Look for price forming higher highs and higher lows or respecting support at the EMA bands.
Bearish Conditions:
Check 1D and 4H charts for price action below the EMA bands.
Look for price forming lower highs and lower lows or respecting resistance at the EMA bands.
Note: Crossover of EMAs on higher timeframes is an optional extra confirmation, but not mandatory for entry.
3. Entry Strategy
Use the 15-Minute (15M) timeframe for entries.
Entries are taken only during Killzones:
Killzones: London Open, New York Open, or other intraday key trading sessions. (Define the time ranges for these zones based on your trading hours.)
Wait for the price to touch or pull back to the EMA band during the Killzones in the direction of the overall trend:
In a bullish trend, enter long when the price touches the EMA band and shows signs of rejection or reversal.
In a bearish trend, enter short when the price touches the EMA band and shows signs of rejection or reversal.
4. Checklist for Entry
Confirm the following before entering:
1D Trend aligns with the 1H Trend.
Price Action in 1D and 4H supports the trend.
Killzone session is active.
Price is reacting to the EMA band on the 15M chart in the trend direction.
אינדיקטורים ואסטרטגיות
Psychological Levels- Rounding Numbers Psychological Levels Indicator
Overview:
The Psychological Levels Indicator automatically identifies and plots significant price levels based on psychological thresholds, which are key areas where market participants often focus their attention. These levels act as potential support or resistance zones due to human behavioral tendencies to round off numbers. This indicator dynamically adjusts the levels based on the stock's price range and ensures seamless visibility across the chart.
Key Features:
Dynamic Step Sizes:
The indicator adjusts the levels dynamically based on the stock price:
For prices below 500: Levels are spaced at 10.
For prices between 500 and 3000: Levels are spaced at 50, 100, and 1000.
For prices between 3000 and 10,000: Levels are spaced at 100 and 1000.
For prices above 10,000: Levels are spaced at 500 and 1000.
Extended Visibility:
The plotted levels are extended across the entire chart for improved visualization, ensuring traders can easily monitor these critical zones over time.
Customization Options:
Line Color: Choose the color for the levels to suit your charting style.
Line Style: Select from solid, dashed, or dotted lines.
Line Width: Adjust the thickness of the lines for better clarity.
Clean and Efficient Design:
The indicator only plots levels relevant to the visible chart range, avoiding unnecessary clutter and ensuring a clean workspace.
How It Works:
It calculates the relevant step sizes based on the price:
Smaller step sizes for lower-priced stocks.
Larger step sizes for higher-priced stocks.
Primary, secondary, and (if applicable) tertiary levels are plotted dynamically:
Primary Levels: The most granular levels based on the stock price.
Secondary Levels: Higher-order levels for broader significance.
Tertiary Levels: Additional levels for lower-priced stocks to enhance detail.
These levels are plotted across the chart, allowing traders to visualize key psychological areas effortlessly.
Use Cases:
Day Trading: Identify potential intraday support and resistance levels.
Swing Trading: Recognize key price zones where trends may pause or reverse.
Long-Term Investing: Gain insights into significant price zones for entry or exit strategies.
Hilega-Milega-RSI-EMA-WMA indicator designed by NKThis indicator is works on RSI, Price and volume to give leading Indicator to Buy or Sell.
This indicator works on all financial markets
Hilega-Milega-RSI-EMA-WMA indicator designed by Nitish Sir
For intraday trade, enter with 15 mins chart.
For positional trade, enter with 1-hour chart.
For Investment this system can be used with daily/weekly/monthly chart.
• RED line is for Volume.
• Green line is for the Price.
• Black line is for the RSI (9).
SELL Trade
1. When Volume (RED line) is above/crossed above Price (Green line) and Strength (Black line), then stock price will go down. This means we will SELL.
2. When there is a GAP in the RED line and the Green line till the time price will go down.
Exit criteria
Whenever Red line exit the shaded area of Oversold zone OR Red line cross over the Green and black line then we will exit.
In case of the SELL trade, after the entry we will monitor the trade in 5 min chart, if the candle is closed above the VWAP then exit.
If the price is crossed the 50 SMA then we will exit trade.
BUY Trade
1. When Volume (RED line) is below/crossed below Price (Green line) and Strength (Black line), then stock price will go up. This means we will BUY.
2. When there is a GAP in the RED line and the Green line till the time price will go down.
Exit criteria
Whenever Red line exit the shaded area of Overbought zone OR Red line cross over the Green and black line then we will exit.
In case of the Buy trade, after the entry we will monitor the trade candle is closed below the VWAP then exit.
If the price is crossed the 50 SMA then we will exit trade.
Multi-Indicator Signal with TableThis indicator is a versatile multi-indicator tool designed for traders who want to combine signals from various popular indicators into a single framework. It not only visualizes buy and sell signals but also provides a clear, easy-to-read table that summarizes the included indicators and their respective signal colors.
Key Features:
RSI (Relative Strength Index):
Buy Signal: RSI falls below the oversold level (default: 30).
Sell Signal: RSI rises above the overbought level (default: 70).
Signal Color: Green.
MACD (Moving Average Convergence Divergence):
Buy Signal: MACD line crosses above the signal line.
Sell Signal: MACD line crosses below the signal line.
Signal Color: Blue.
MA Crossover (Moving Average Crossover):
Buy Signal: Short EMA (default: 7) crosses above Long SMA (default: 14).
Sell Signal: Short EMA crosses below Long SMA.
Signal Color: Purple.
Stochastic Oscillator:
Buy Signal: Stochastic %K falls below 20 and crosses above %D.
Sell Signal: Stochastic %K rises above 80 and crosses below %D.
Signal Color: Yellow.
TSI (True Strength Index):
Buy Signal: TSI crosses above the zero line.
Sell Signal: TSI crosses below the zero line.
Signal Color: Red.
Dynamic Signal Table:
A clean, compact table displayed at the top-right corner of the chart, summarizing the indicators and their respective signal colors for quick reference.
Customization:
All indicator parameters are fully adjustable, allowing users to fine-tune settings to match their trading strategy.
Signal colors and table design ensure a visually intuitive experience.
Usage:
This tool is ideal for traders who prefer a multi-indicator approach for generating buy/sell signals.
The combination of different indicators helps to filter out noise and increase the accuracy of trade setups.
Notes:
Signals appear only after the confirmation of the current bar to avoid false triggers.
This indicator is designed for educational purposes and should be used in conjunction with proper risk management strategies.
AiTrend Pattern Matrix for kNN Forecasting (AiBitcoinTrend)The AiTrend Pattern Matrix for kNN Forecasting (AiBitcoinTrend) is a cutting-edge indicator that combines advanced mathematical modeling, AI-driven analytics, and segment-based pattern recognition to forecast price movements with precision. This tool is designed to provide traders with deep insights into market dynamics by leveraging multivariate pattern detection and sophisticated predictive algorithms.
👽 Core Features
Segment-Based Pattern Recognition
At its heart, the indicator divides price data into discrete segments, capturing key elements like candle bodies, high-low ranges, and wicks. These segments are normalized using ATR-based volatility adjustments to ensure robustness across varying market conditions.
AI-Powered k-Nearest Neighbors (kNN) Prediction
The predictive engine uses the kNN algorithm to identify the closest historical patterns in a multivariate dictionary. By calculating the distance between current and historical segments, the algorithm determines the most likely outcomes, weighting predictions based on either proximity (distance) or averages.
Dynamic Dictionary of Historical Patterns
The indicator maintains a rolling dictionary of historical patterns, storing multivariate data for:
Candle body ranges, High-low ranges, Wick highs and lows.
This dynamic approach ensures the model adapts continuously to evolving market conditions.
Volatility-Normalized Forecasting
Using ATR bands, the indicator normalizes patterns, reducing noise and enhancing the reliability of predictions in high-volatility environments.
AI-Driven Trend Detection
The indicator not only predicts price levels but also identifies market regimes by comparing current conditions to historically significant highs, lows, and midpoints. This allows for clear visualizations of trend shifts and momentum changes.
👽 Deep Dive into the Core Mathematics
👾 Segment-Based Multivariate Pattern Analysis
The indicator analyzes price data by dividing each bar into distinct segments, isolating key components such as:
Body Ranges: Differences between the open and close prices.
High-Low Ranges: Capturing the full volatility of a bar.
Wick Extremes: Quantifying deviations beyond the body, both above and below.
Each segment contributes uniquely to the predictive model, ensuring a rich, multidimensional understanding of price action. These segments are stored in a rolling dictionary of patterns, enabling the indicator to reference historical behavior dynamically.
👾 Volatility Normalization Using ATR
To ensure robustness across varying market conditions, the indicator normalizes patterns using Average True Range (ATR). This process scales each component to account for the prevailing market volatility, allowing the algorithm to compare patterns on a level playing field regardless of differing price scales or fluctuations.
👾 k-Nearest Neighbors (kNN) Algorithm
The AI core employs the kNN algorithm, a machine-learning technique that evaluates the similarity between the current pattern and a library of historical patterns.
Euclidean Distance Calculation:
The indicator computes the multivariate distance across four distinct dimensions: body range, high-low range, wick low, and wick high. This ensures a comprehensive and precise comparison between patterns.
Weighting Schemes: The contribution of each pattern to the forecast is either weighted by its proximity (distance) or averaged, based on user settings.
👾 Prediction Horizon and Refinement
The indicator forecasts future price movements (Y_hat) by predicting logarithmic changes in the price and projecting them forward using exponential scaling. This forecast is smoothed using a user-defined EMA filter to reduce noise and enhance actionable clarity.
👽 AI-Driven Pattern Recognition
Dynamic Dictionary of Patterns: The indicator maintains a rolling dictionary of N multivariate patterns, continuously updated to reflect the latest market data. This ensures it adapts seamlessly to changing market conditions.
Nearest Neighbor Matching: At each bar, the algorithm identifies the most similar historical pattern. The prediction is based on the aggregated outcomes of the closest neighbors, providing confidence levels and directional bias.
Multivariate Synthesis: By combining multiple dimensions of price action into a unified prediction, the indicator achieves a level of depth and accuracy unattainable by single-variable models.
Visual Outputs
Forecast Line (Y_hat_line):
A smoothed projection of the expected price trend, based on the weighted contribution of similar historical patterns.
Trend Regime Bands:
Dynamic high, low, and midlines highlight the current market regime, providing actionable insights into momentum and range.
Historical Pattern Matching:
The nearest historical pattern is displayed, allowing traders to visualize similarities
👽 Applications
Trend Identification:
Detect and follow emerging trends early using dynamic trend regime analysis.
Reversal Signals:
Anticipate market reversals with high-confidence predictions based on historically similar scenarios.
Range and Momentum Trading:
Leverage multivariate analysis to understand price ranges and momentum, making it suitable for both breakout and mean-reversion strategies.
Disclaimer: This information is for entertainment purposes only and does not constitute financial advice. Please consult with a qualified financial advisor before making any investment decisions.
RShar Liquidity Zone Identifier Description of the Liquidity Zone Identifier Indicator
The **Liquidity Zone Identifier** is a TradingView indicator designed to highlight key liquidity zones on a price chart. Liquidity zones represent areas where the price is likely to encounter significant resistance or support, making them critical for technical analysis and trading decisions.
Key Features:
1. **Dynamic Resistance and Support Levels**:
- The indicator calculates the highest high and lowest low over a user-defined period (`length`) to identify potential resistance and support levels.
- Sensitivity can be adjusted using the `zoneSensitivity` parameter, which defines a percentage buffer around these levels to expand the zones.
2. **Visual Representation**:
- Resistance zones are highlighted in **red**, indicating areas where the price may face selling pressure.
- Support zones are highlighted in **green**, representing areas where the price may find buying interest.
- The zones are displayed as shaded regions using the `fill` function, making them visually distinct and easy to interpret.
3. **Customizable Inputs**:
- **Zone Length** (`length`): Determines the number of candles considered for calculating highs and lows.
- **Zone Sensitivity** (`zoneSensitivity`): Sets the percentage margin around the calculated levels to define the liquidity zones.
- **Zone Colors**: Users can customize the colors for resistance and support zones to suit their preferences.
- **Toggle Fill**: The `showFill` option allows users to enable or disable shaded zone visualization.
4. **Alerts for Trading Opportunities**:
- Alerts are triggered when:
- The price enters the **resistance zone** (current high is greater than or equal to the resistance zone).
- The price enters the **support zone** (current low is less than or equal to the support zone).
- These alerts help traders stay informed of critical market movements without constantly monitoring the chart.
#### How It Works:
1. **Calculation of Zones**:
- The highest high and lowest low over the specified `length` are calculated to define the primary levels.
- A buffer zone is added around these levels based on the `zoneSensitivity` percentage, creating a margin of interaction for price movements.
2. **Plotting the Zones**:
- The top and bottom boundaries of the resistance and support zones are plotted as lines.
- The area between these boundaries is shaded using the `fill` function to enhance visualization.
3. **Alerts for Key Events**:
- Traders are notified when price action interacts with the zones, enabling quick decision-making.
#### Use Case:
The Liquidity Zone Identifier is ideal for:
- Identifying areas of potential price reversal or consolidation.
- Spotting high-probability trading setups near resistance and support zones.
- Complementing other technical indicators in a trading strategy.
By effectively highlighting critical price levels, this indicator provides traders with a powerful tool to navigate the markets with greater precision.
Option vs Index Performance**Indicator Name:** Option vs Index Performance
**Description:**
This indicator helps traders analyze the relative performance of options compared to their underlying index (e.g., Nifty 50). It evaluates and highlights zones based on two key metrics:
1. **Bar-to-Bar Performance:** Compares the percentage movement of the option price against the index movement on a bar-by-bar basis.
- **Green Zone**: Option outperforms the index.
- **Yellow Zone**: Option moves in sync with the index.
- **Red Zone**: Option underperforms the index.
2. **Swing Alignment:** Tracks the swing structure of the index (higher highs, higher lows) and compares it with the option chart. The indicator checks if the option's swings align with or deviate from the index's swing pattern.
The final output combines both conditions, providing clear visual zones below the chart:
- **Green**: Overperformance and alignment with the index.
- **Yellow**: Neutral performance or partial alignment.
- **Red**: Underperformance or misalignment with the index.
Use this tool on option charts to quickly identify opportunities and assess whether the option's movement is in line with the broader market trend.
Ticker Tape with Multiple Inputs# Ticker Tape
A customizable multi-symbol price tracker that displays real-time price information in a scrolling ticker format, similar to financial news tickers.
This indicator is inspired from Tradingciew's default tickertape indicator with changes in the way inputs are given.
### Overview
This indicator allows you to monitor up to 15 different symbols simultaneously across any supported exchanges on TradingView. It displays essential price information including current price, price change, and percentage change in an easy-to-read format at the bottom of your chart.
### Features
• Monitor up to 15 different symbols simultaneously
• Support for any exchange available on TradingView
• Real-time price updates
• Color-coded price changes (green for increase, red for decrease)
• Smooth scrolling animation (can be disabled)
• Customizable scroll speed and position offset
### Input Parameters
#### Ticker Tape Controls
• Running: Enable/disable the scrolling animation
• Offset: Adjust the starting position of the ticker tape
#### Symbol Settings
• Exchange (1-15): Enter the exchange name (e.g., NSE, BINANCE, NYSE)
• Symbol (1-15): Enter the symbol name (e.g., BANKNIFTY, RELIANCE, BTCUSDT)
### Display Format
For each symbol, the ticker shows:
1. Symbol Name
2. Current Price
3. Price Change (Absolute and Percentage)
### Example Usage
Input Settings:
Exchange 1: NSE
Symbol 1: BANKNIFTY
Exchange 2: NSE
Symbol 2: RELIANCE
The ticker tape will display:
`NIFTY BANK 46750.00 +350.45 (0.75%) | RELIANCE 2456.85 -12.40 (-0.50%) |`
### Use Cases
1. Multi-Market Monitoring: Track different markets simultaneously without switching between charts
2. Portfolio Tracking: Monitor all your positions in real-time
### Tips for Best Use
1. Group related symbols together for easier monitoring
2. Use the offset parameter to position important symbols in your preferred viewing area
3. Disable scrolling if you prefer a static display
4. Leave exchange field empty for default exchange symbols
### Notes
• Price updates occur in real-time during market hours
• Color coding helps quickly identify price direction
• The indicator adapts to any chart timeframe
• Empty input pairs are automatically skipped
### Performance Considerations
The indicator is optimized for efficiency, but monitoring too many high-frequency symbols might impact chart performance. It's recommended to use only the symbols you actively need to monitor.
Version: 2.0 Stock_Cloud
Last Updated: December 2024
Financial Conditions Composite Z-Score1. Inputs and Data Sources
The script pulls data for the following financial metrics using TradingView's request.security function:
CBOE:VIX (Volatility Index): A measure of market volatility.
MOVE Index: A measure of bond market volatility (or Treasury volatility).
BAMLH0A0HYM2 (High-Yield Spread): The spread between high-yield corporate bonds and Treasury yields.
BAMLC0A0CM (Credit Spread): The spread for investment-grade corporate bonds.
Each of these metrics represents a key aspect of financial conditions:
VIX: Equity market risk.
MOVE: Bond market risk.
High-Yield Spread and Credit Spread: Perception of risk in corporate debt.
2. Z-Score Calculation
A z-score standardizes each metric to show how far it deviates from its average over a specified period (lookback = 160, or 160 days):
Positive z-scores indicate the metric is higher than average.
Negative z-scores indicate the metric is lower than average.
The formula for the z-score:
Z-Score = Metric − Mean
Standard Deviation Z-Score = Standard Deviation Metric−Mean
3. Combined Z-Score
The script combines the four individual z-scores into a single Composite Z-Score, equally weighted across the metrics:
Combined Z-Score = (Z VIX + Z MOVE + Z High-Yield Spread + Z Credit Spread) / 4
This Combined Z-Score provides an overall measure of financial conditions:
Positive combined z-scores indicate tighter or riskier financial conditions.
Negative combined z-scores indicate looser or less risky financial conditions.
4. Visual Elements on the Chart
A. Colorful Lines: Individual Z-Scores
Each of the four metrics is plotted as a separate line:
Red: Z-score of the VIX.
Green: Z-score of the MOVE index.
Orange: Z-score of the high-yield spread.
Purple: Z-score of the credit spread.
These lines show how each metric contributes to the overall financial conditions. For example:
A rising red line means increasing equity market volatility (risk).
A rising green line means increasing bond market volatility (risk).
B. Blue Line: Combined Z-Score
The blue line represents the Combined Z-Score. It aggregates the individual z-scores into a single measure:
A rising blue line suggests financial conditions are tightening (greater risk across markets).
A falling blue line suggests financial conditions are loosening (lower risk across markets).
C. Red and Green Background: Z-Score Regions
Red Background: When the Combined Z-Score is positive (>0), it indicates riskier or tighter financial conditions.
Green Background: When the Combined Z-Score is negative (<0), it indicates less risky or looser financial conditions.
This background coloring helps visually distinguish periods of riskier financial conditions from less risky ones.
5. Purpose of the Visualization
This indicator provides a comprehensive view of financial conditions across multiple asset classes:
Traders can use it to gauge the level of systemic market stress.
Investors can use it to assess when risk is elevated (positive z-scores) or subdued (negative z-scores).
It helps in decision-making for strategies that depend on market volatility or risk appetite.
Summary of What You See:
Colorful Lines (Red, Green, Orange, Purple): Individual z-scores for each metric (VIX, MOVE, high-yield spread, credit spread).
Blue Line: The aggregated Combined Z-Score that summarizes financial conditions.
Red and Green Background:
Red: Tight or risky financial conditions (Combined Z-Score > 0).
Green: Loose or low-risk financial conditions (Combined Z-Score < 0).
This visualization provides a multi-dimensional view of financial conditions at a glance, helping to identify periods of high or low risk in the markets.
Bollinger Bands Volatility Arrows
Explanation of Changes:
Arrow Style:
Green Up Arrow (▲): Indicates increasing volatility with a positive value.
Red Down Arrow (▼): Indicates decreasing volatility with a negative value.
Labels with Arrows:
label.new is used to create arrows with the label.style_label_up or label.style_label_down styles.
The numerical value of the volatility is displayed beside the arrow using str.tostring.
Label Position:
For increasing volatility, the green arrow is placed near the high of the candle.
For decreasing volatility, the red arrow is placed near the low of the candle.
Text Format:
Includes the arrow symbol and the volatility value (formatted to 4 decimal places).
How It Works:
You’ll see green upward arrows for increasing volatility and red downward arrows for decreasing volatility.
Each arrow includes the exact value of the Bollinger Bands width at that moment.
VWAP Trend with Standard Deviation & MidlinesThis indicator is a sophisticated VWAP (Volume Weighted Average Price) tool with multiple features:
Core Functionality:
1. Calculates a primary VWAP line that changes color based on trend direction (green when rising, red when falling)
2. Creates multiple standard deviation bands around the VWAP at customizable distances
3. Resets calculations at either:
- New York session start time (configurable, default 9:30 AM)
- Daily start time
- Can be hidden on daily/weekly/monthly timeframes if desired
Band Structure:
- Band 1 (innermost): ±1 standard deviation
- Band 2 (middle): ±2 standard deviations
- Band 3 (outermost): ±3 standard deviations
- Midlines at 0.5σ intervals between bands
- All bands can be individually enabled/disabled
Customization Options:
1. Band calculation modes:
- Standard Deviation based
- Percentage based
2. Visual settings:
- Customizable colors for all elements
- Adjustable line widths
- Optional labels with configurable size
- Optional extension lines
- Label position adjustment
3. Source data selection (default: HLC3 - High, Low, Close average)
Common Uses:
- Identifying potential support/resistance levels
- Measuring price volatility
- Spotting mean reversion opportunities
- Trading range analysis
- Trend direction confirmation
The indicator essentially creates a dynamic support/resistance structure that adapts to market volatility and volume, making it useful for both intraday and swing trading strategies.
300-Candle Weighted Average Zones w/50 EMA SignalsThis indicator is designed to deliver a more nuanced view of price dynamics by combining a custom, weighted price average with a volatility-based zone and a trend filter (in this case, a 50-period exponential moving average). The core concept revolves around capturing the overall price level over a relatively large lookback window (300 candles) but with an intentional bias toward recent market activity (the most recent 20 candles), thereby offering a balance between long-term context and short-term responsiveness. By smoothing this weighted average and establishing a “zone” of standard deviation bands around it, the indicator provides a refined visualization of both average price and its recent volatility envelope. Traders can then look for confluence with a standard trend filter, such as the 50 EMA, to identify meaningful crossover signals that may represent trend shifts or opportunities for entry and exit.
What the Indicator Does:
Weighted Price Average:
Instead of using a simple or exponential moving average, this indicator calculates a custom weighted average price over the past 300 candles. Most historical candles receive a base weight of 1.0, but the most recent 20 candles are assigned a higher weight (for example, a weight of 2.0). This weighting scheme ensures that the calculation is not simply a static lookback average; it actively emphasizes current market conditions. The effect is to generate an average line that is more sensitive to the most recent price swings while still maintaining the historical context of the previous 280 candles.
Smoothing of the Weighted Average:
Once the raw weighted average is computed, an exponential smoothing function (EMA) is applied to reduce noise and produce a cleaner, more stable average line. This smoothing helps traders avoid reacting prematurely to minor price fluctuations. By stabilizing the average line, traders can more confidently identify actual shifts in market direction.
Volatility Zone via Standard Deviation Bands:
To contextualize how far price can deviate from this weighted average, the indicator uses standard deviation. Standard deviation is a statistical measure of volatility—how spread out the price values are around the mean. By adding and subtracting one standard deviation from the smoothed weighted average, the indicator plots an upper band and a lower band, creating a zone or channel. The area between these bands is filled, often with a semi-transparent color, highlighting a volatility corridor within which price and the EMA might oscillate.
This zone is invaluable in visualizing “normal” price behavior. When the 50 EMA line and the weighted average line are both within this volatility zone, it indicates that the market’s short- to mid-term trend and its average pricing are aligned well within typical volatility bounds.
Incorporation of a 50-Period EMA:
The inclusion of a commonly used trend filter, the 50 EMA, adds another layer of context to the analysis. The 50 EMA, being a widely recognized moving average length, is often considered a baseline for intermediate trend bias. It reacts faster than a long-term average (like a 200 EMA) but is still stable enough to filter out the market “chop” seen in very short-term averages.
By overlaying the 50 EMA on this custom weighted average and the surrounding volatility zone, the trader gains a dual-dimensional perspective:
Trend Direction: If the 50 EMA is generally above the weighted average, the short-term trend is gaining bullish momentum; if it’s below, the short-term trend has a bearish tilt.
Volatility Normalization: The bands, constructed from standard deviations, provide a sense of whether the price and the 50 EMA are operating within a statistically “normal” range. If the EMA crosses the weighted average within this zone, it signals a potential trend initiation or meaningful shift, as opposed to a random price spike outside normal volatility boundaries.
Why a Trader Would Want to Use This Indicator:
Contextualized Price Level:
Standard MAs may not fully incorporate the most recent price dynamics in a large lookback window. By weighting the most recent candles more heavily, this indicator ensures that the trader is always anchored to what the market is currently doing, not just what it did 100 or 200 candles ago.
Reduced Whipsaw with Smoothing:
The smoothed weighted average line reduces noise, helping traders filter out inconsequential price movements. This makes it easier to spot genuine changes in trend or sentiment.
Visual Volatility Gauge:
The standard deviation bands create a visual representation of “normal” price movement. Traders can quickly assess if a breakout or breakdown is statistically significant or just another oscillation within the expected volatility range.
Clear Trade Signals with Confirmation:
By integrating the 50 EMA and designing signals that trigger only when the 50 EMA crosses above or below the weighted average while inside the zone, the indicator provides a refined entry/exit criterion. This avoids chasing breakouts that occur in abnormal volatility conditions and focuses on those crossovers likely to have staying power.
How to Use It in an Example Strategy:
Imagine you are a swing trader looking to identify medium-term trend changes. You apply this indicator to a chart of a popular currency pair or a leading tech stock. Over the past few days, the 50 EMA has been meandering around the weighted average line, both confined within the standard deviation zone.
Bullish Example:
Suddenly, the 50 EMA crosses decisively above the weighted average line while both are still hovering within the volatility zone. This might be your cue: you interpret this crossover as the 50 EMA acknowledging the recent upward shift in price dynamics that the weighted average has highlighted. Since it occurred inside the normal volatility range, it’s less likely to be a head-fake. You place a long position, setting an initial stop just below the lower band to protect against volatility.
If the price continues to rise and the EMA stays above the average, you have confirmation to hold the trade. As the price moves higher, the weighted average may follow, reinforcing your bullish stance.
Bearish Example:
On the flip side, if the 50 EMA crosses below the weighted average line within the zone, it suggests a subtle but meaningful change in trend direction to the downside. You might short the asset, placing your protective stop just above the upper band, expecting that the statistically “normal” level of volatility will contain the price action. If the price does break above those bands later, it’s a sign your trade may not work out as planned.
Other Indicators for Confluence:
To strengthen the reliability of the signals generated by this weighted average zone approach, traders may want to combine it with other technical studies:
Volume Indicators (e.g., Volume Profile, OBV):
Confirm that the trend crossover inside the volatility zone is supported by volume. For instance, an uptrend crossover combined with increasing On-Balance Volume (OBV) or volume spikes on up candles signals stronger buying pressure behind the price action.
Momentum Oscillators (e.g., RSI, Stochastics):
Before taking a crossover signal, check if the RSI is above 50 and rising for bullish entries, or if the Stochastics have turned down from overbought levels for bearish entries. Momentum confirmation can help ensure that the trend change is not just an isolated random event.
Market Structure Tools (e.g., Pivot Points, Swing High/Low Analysis):
Identify if the crossover event coincides with a break of a previous pivot high or low. A bullish crossover inside the zone aligned with a break above a recent swing high adds further strength to your conviction. Conversely, a bearish crossover confirmed by a breakdown below a previous swing low can make a short trade setup more compelling.
Volume-Weighted Average Price (VWAP):
Comparing where the weighted average zone lies relative to VWAP can provide institutional insight. If the bullish crossover happens while the price is also holding above VWAP, it can mean that the average participant in the market is in profit and that the trend is likely supported by strong hands.
This indicator serves as a tool to balance long-term perspective, short-term adaptability, and volatility normalization. It can be a valuable addition to a trader’s toolkit, offering enhanced clarity and precision in detecting meaningful shifts in trend, especially when combined with other technical indicators and robust risk management principles.
Implied Leverage Ratio Between Current Symbol and BTCThis script calculates and visualizes the implied leverage ratio between the current symbol and Bitcoin (BTC). The implied leverage ratio is computed by comparing the cumulative price changes of the two symbols over a defined number of candles. The results provide insights into how the current symbol performs relative to BTC in terms of bullish (upward) and bearish (downward) movements.
Features
Cumulative Up and Down Ratios:
The script calculates the cumulative price increase (up) and decrease (down) ratios for both the current symbol and BTC. These ratios are based on the percentage changes relative to each candle's opening price.
Implied Leverage Ratio:
For bullish movements, the cumulative up ratio of the current symbol is divided by BTC's cumulative up ratio.
For bearish movements, the cumulative down ratio of the current symbol is divided by BTC's cumulative down ratio.
These values reflect the implied leverage of the current symbol relative to BTC in both directions.
Customizable Comparison Symbol:
By default, the script compares the current symbol to BINANCE:BTCUSDT. However, you can specify any other symbol to tailor the analysis.
Interactive Visualization:
Green Line: Represents the ratio of cumulative up movements (current symbol vs. BTC).
Red Line: Represents the ratio of cumulative down movements (current symbol vs. BTC).
A horizontal zero line is included for reference, ensuring the chart always starts from zero.
How to Use
Add this script to your chart from the Pine Editor or the public library.
Customize the number of candles (t) to define the period over which cumulative changes are calculated.
If desired, replace the comparison symbol with another asset in the input settings.
Analyze the green and red lines to identify relative strength and implied leverage trends.
Who Can Benefit
Traders and Analysts: Gain insights into the relative performance of altcoins, stocks, or other instruments against BTC.
Leverage Seekers: Identify assets with higher or lower implied leverage compared to Bitcoin.
Market Comparisons: Understand how various assets react to market movements relative to BTC.
This tool is particularly useful for identifying potential outperformers or underperformers relative to Bitcoin and can guide strategic decisions in trading pairs or market analysis.
[blackcat] L1 Banker Move█ OVERVIEW
The Pine Script is an indicator designed to analyze market signals for institutional and short-term investors. It calculates and plots three main signals: Institutional Signal, Institutional Build, and Short-Term Investor Signal. The script uses a combination of price, volume, and moving average data to generate these signals, which can help traders identify potential buying or selling opportunities.
█ LOGICAL FRAMEWORK
The script is structured into several main sections:
1 — Input Parameters
The script does not explicitly define any input parameters, relying on default values for calculations.
2 — Custom Functions
• reference_value(values, length) : Retrieves the first non-NA value from a specified number of past values.
• calculate_institutional_and_short_term_signals(low, close, open, volume) : Calculates the institutional and short-term investor signals based on price, volume, and moving average data.
3 — Calculations
• Price and Volume Metrics: The script calculates various smoothed price changes, lowest and highest values over different periods, and volume-weighted prices.
• Moving Averages: It computes simple moving averages (SMA) and exponential moving averages (EMA) for different periods.
• RSI Calculation: The script calculates a custom RSI for different periods.
• Signal Generation: It generates the institutional and short-term investor signals based on the calculated metrics.
4 — Plotting
The script plots the three main signals on the chart using the plot function.
The flow of data and logic is as follows:
• The reference_value function is used to find reference values for calculations.
• The calculate_institutional_and_short_term_signals function performs the core calculations and returns the institutional and short-term investor signals.
• The main script calls this function and plots the results.
█ CUSTOM FUNCTIONS
1 — reference_value(values, length)
• Purpose : Retrieves the first non-NA value from a specified number of past values.
• Parameters :
• values: An array of values.
• length: The number of past values to consider.
• Return Value : The first non-NA value found or na if no valid value is found.
• Functionality : Iterates through the specified number of past values and returns the first non-NA value.
2 — calculate_institutional_and_short_term_signals(low, close, open, volume)
• Purpose : Calculates the institutional and short-term investor signals based on price, volume, and moving average data.
• Parameters :
• low: Low price series.
• close: Close price series.
• open: Open price series.
• volume: Volume series.
• Return Values :
• institutional_signal: The institutional signal.
• institutional_build: The institutional build signal.
• short_term_investor_signal: The short-term investor signal.
• Functionality :
• Computes various price and volume metrics.
• Calculates moving averages and volume-weighted prices.
• Generates the institutional and short-term investor signals based on these metrics.
█ KEY POINTS AND TECHNIQUES
1 — Advanced Pine Script Features
• Custom Functions: The script defines and uses custom functions to encapsulate complex logic.
• Conditional Statements: Extensive use of iff and if statements to control the flow of calculations.
• Looping Constructs: The for loop in reference_value function to iterate through past values.
• Exponential Moving Averages (EMA): Used to smooth out price and signal changes.
• Volume-Weighted Price (VWP): Calculated to factor in volume in price analysis.
• Custom RSI Calculation: A custom RSI formula is used, which differs from the standard RSI calculation.
2 — Optimization Techniques
• Efficient Data Handling: The reference_value function efficiently finds the first non-NA value without unnecessary computations.
• Smoothed Signals: Using EMAs to smooth out noisy signals for better trend identification.
3 — Unique Approaches
• Combination of Metrics: The script combines multiple metrics (price, volume, moving averages, and custom RSI) to generate comprehensive signals.
• Institutional Build Signal: A unique approach to detect institutional activity by comparing current price levels with historical lows and smoothed price changes.
█ EXTENDED KNOWLEDGE AND APPLICATIONS
1 — Potential Modifications
• Input Parameters: Add input parameters to allow users to customize the lengths and thresholds used in the calculations.
• Strategy Version: Convert the indicator into a strategy by adding buy/sell signals based on the generated signals.
• Additional Indicators: Integrate other technical indicators (e.g., MACD, Bollinger Bands) to enhance the signal generation process.
2 — Similar Trading Scenarios
• Institutional Activity Analysis: Use similar techniques to analyze institutional activity in other markets or assets.
• Volume Analysis: Apply the volume-weighted price and volume analysis to identify significant price movements.
• Multi-Timeframe Analysis: Extend the script to analyze signals across multiple timeframes for a more robust trading strategy.
3 — Related Pine Script Concepts
• Pine Script Functions: Understanding how to define and use custom functions effectively.
• Conditional Logic: Mastering the use of iff and if statements for complex logic.
• Looping Constructs: Familiarity with for loops for iterating through data.
• Moving Averages: Knowledge of different types of moving averages and their applications.
• Volume Analysis: Techniques for incorporating volume data into price analysis.
Bitcoin: Mayer MultipleMayer Multiple Indicator
The Mayer Multiple is a powerful tool designed to help traders assess market conditions and identify optimal buying or selling opportunities. It calculates the ratio between the current price and its 200-day simple moving average (SMA), visualizing key thresholds that indicate value zones, caution areas, and overheated markets.
Key Features:
Dynamic Market Zones: Clearly marked levels like "Smash Buy," "Boost DCA," and "Extreme Euphoria" to guide your trading decisions.
Customizable Input: Adjust the SMA length to fit your strategy.
Color-Coded Signals: Intuitive visualization of market sentiment for quick analysis.
Comprehensive Thresholds: Historical insights into price behavior with plotted reference levels based on probabilities.
This indicator is ideal for traders aiming to enhance their long-term strategies and improve decision-making in volatile markets. Use it to gain an edge in identifying potential turning points and managing risk effectively.
Shannon Entropy Volatility AnalyzerThis algorithm aims to measure market uncertainty or volatility using a Shannon entropy-based approach. 🔄📊
Entropy is a measure of disorder or unpredictability, and here we use it to evaluate the structure of price returns within a defined range of periods (window length). 🧩⏳ Thus, the goal is to detect changes to identify conditions of high or low volatility. 🔍⚡
What we seek with Shannon's formula in this algorithm is to measure market uncertainty or volatility through dynamic entropy. This measure helps us understand how unpredictable price behavior is over a given period, which is key to making informed decisions. 📈🧠
Through this formula, we calculate the level of disorder or dispersion in price returns based on their probability of occurrence, enabling us to identify moments of high or low volatility. 💡💥
Shannon Entropy Calculation 📏
• Uses probabilities to measure uncertainty in returns. 🎲
• Entropy is normalized on a scale of 0 to 100, where:
o High Entropy: Unpredictable movements (high uncertainty). ⚠️💥
•
o Low Entropy: Structured movements (low uncertainty). 📉🔒
•
• With probabilities, we measure the level of dispersion or unpredictability of returns using Shannon's entropy formula. 📊🔍
________________________________________
Indicator Usefulness 🛠️
• Identify High Volatility: When the market is unpredictable, the indicator signals "High Uncertainty." ⚡🔮
• Detect Market Stability: When the market is more predictable and structured, the indicator highlights "Low Uncertainty." 🔒🧘♂️
• Neutral Zones: Helps monitor markets without extreme conditions, enabling safer entry or exit opportunities. ⚖️🚶♂️
________________________________________
Uncertainty Zones 🌀
1. High Uncertainty: When entropy exceeds the upper threshold. 🚨🔺
2. Low Uncertainty: When entropy is below the lower threshold. 🔻💡
3. Neutral: When entropy lies between both thresholds. ⚖️🔄
________________________________________
What We Aim to Achieve with the Formula in Practice 🎯
1. Detection of Volatile Moments: Shannon’s formula helps us identify when the market is unpredictable. This is a good moment to take additional precautions, such as reducing position size or avoiding trading during high volatility phases. ⚠️📉
2. Trading Opportunities in Stable Markets: With low entropy, we can identify when the market is more predictable, favoring trend or momentum strategies with a higher chance of success. 🚀📈
3. Optimization of Risk Management: By measuring market volatility in real-time, we can adjust entry and exit strategies, tailoring risk based on the level of uncertainty detected. 🔄⚖️
________________________________________
We hope this makes it easy to interpret and use. If you have any questions or comments, please feel free to reach out to us! 📬😊
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.
Trend Condition [TradersPro]
OVERVIEW
The Trend Condition Indicator measures the strength of the bullish or bearish trend by using a ribbon pattern of exponential moving averages and scoring system. Trend cycles naturally expand and contract as a normal part of the cycle. It is the rhythm of the market. Perpetual expansion and contraction of trend.
As trend cycles develop the indicator shows a compression of the averages. These compression zones are key locations as trends typically expand from there. The expansion of trend can be up or down.
As the trend advances the ribbon effect of the indicator can be seen as each average expands with the price action. Once they have “fanned” the probability of the current trend slowing is high.
This can be used to recognize a powerful trend may be concluding. Traders can tighten stops, exit positions or utilize other prudent strategies.
CONCEPTS
Each line will display green if it is higher than the prior period and red if it is lower than the prior period. If the average is green it is considered bullish and will score one point in the bullish display. Red lines are considered bearish and will score one point in the bearish display.
The indicator can then be used at a quick glance to see the number of averages that are bullish and the number that are bearish.
A trader may use these on any tradable instrument. They can be helpful in stock portfolio management when used with an index like the S&P 500 to determine the strength of the current market trend. This may affect trade decisions like possession size, stop location and other risk factors.
Tomas' Financial Conditions Z Score"The indicator is a composite z-score comprised of the following four components (equally-weighted):
Credit spreads - ICE BofA High Yield Option Adjusted Spread (BAMLH0A0HYM2) and ICE BofA Corporate Index Option Adjusted Spread (BAMLC0A0CM)
Volatility indexes - VIX (S&P 500 implied volatility) and MOVE (US Treasury bond implied volatility)
I've got it set to a 160-day lookback period, which I think is roughly the best setting after some tinkering.
When the z-score is above zero, it throws a red signal - and when the z-score is below zero, it throws a green signal.
This indicator is a follow-on from the "traffic light financial conditions indicator" that I wrote a thread about a couple of months ago.
I moved on from that previous indicator because it is based on the Federal Reserve's NFCI, which is regularly revised, but I didn't take that into account at the time.
So not a great real-time indicator, if the signal can be subsequently revised in the opposite direction weeks later.
This new indicator is based on real-time market data, so there's no revisions, and it also updates daily, as opposed to weekly for the NFCI"
Custom EMA (v4) [MacroGlide]Custom EMA (v4) is an easy-to-use tool designed for traders who want a clear and reliable way to analyze market trends. By using multiple Exponential Moving Averages (EMAs), this indicator helps you visualize the market's direction and momentum in a straightforward way. Whether you're tracking short-term movements or looking for long-term patterns, Custom EMA makes it simple to spot trends and trading opportunities.
Key Features:
• Multi-EMA System: Plots up to four EMAs on the chart with customizable lengths and colors, providing flexibility to analyze trends over different timeframes.
• Dynamic Trend Cloud: A visually intuitive cloud is generated between the fastest and slowest EMA. The cloud changes color based on market trends:
• Green Cloud: Indicates a bullish trend when shorter EMAs are above longer EMAs.
• Red Cloud: Indicates a bearish trend when shorter EMAs are below longer EMAs.
• Highlighting Zones: Background shading helps distinguish bullish and bearish conditions, further clarifying the prevailing trend in the market.
How to Use:
• Add the Indicator: Load the indicator onto your chart and customize the EMA lengths to suit your trading style.
• Interpret the Cloud: Observe the color of the trend cloud to identify bullish (green) or bearish (red) market conditions.
• Combine with Highlighting Zones: Use the background shading in conjunction with the cloud to confirm trend strength and direction.
• Customize to Fit Your Strategy: Adjust the lengths and colors of the EMAs to align with your preferred analysis timeframe.
Methodology:
This indicator leverages a layered EMA approach, using up to four EMAs to calculate the trend cloud and define market conditions. By comparing the relative positions of the EMAs, it identifies bullish and bearish trends and visually represents them with a color-coded cloud. The inclusion of highlighting zones enhances the trader's ability to quickly grasp market sentiment.
Originality and Usefulness:
Custom EMA (v4) sets itself apart by integrating a trend cloud that adapts dynamically to EMA positions, providing traders with a clean and intuitive way to visualize market trends. The combination of multi-EMA plotting, background shading, and trend cloud offers comprehensive insight into both short-term and long-term market movements.
Charts:
The indicator plots four customizable EMAs alongside a trend cloud that visually captures market direction. Whether you're monitoring short-term price action or identifying long-term trends, the Custom EMA (v4) provides clarity and simplicity for traders at all levels.
Enjoy the game!
IndicatorsLibrary "Indicators"
cmf(lookback, n_to_smooth)
Calculates the Chaikin's Money Flow.
Parameters:
lookback (simple int)
n_to_smooth (simple int)
Returns: float The Money Flow value.
cmma(lookback, atr_length)
Calculates the CMMA (Close Minus Moving Average) indicator.
Parameters:
lookback (simple int)
atr_length (simple int)
Returns: float The CMMA value.
macd(fast_length, slow_length, n_to_smooth)
Calculates the normalized and scaled MACD.
Parameters:
fast_length (simple int)
slow_length (simple int)
n_to_smooth (simple int)
Returns: A tuple containing .
stochK(length, n_to_smooth)
Calculates a simplified Stochastic Oscillator.
Uses: 100 * ta.sma((close - lowest_low) / (highest_high - lowest_low), n_to_smooth)
Parameters:
length (simple int)
n_to_smooth (simple int)
Returns: float The Stochastic %K value.
williamsR(length)
Calculates the Williams %R using the stochK function.
Uses: -1 * (100 - stoch(length, 1))
Parameters:
length (simple int)
Returns: float The Williams %R value.
Standard Deviation of Returns: DivergencePurpose:
The "Standard Deviation of Returns: Divergence" indicator is designed to help traders identify potential trend reversals or continuation signals by analyzing divergences between price action and the statistical volatility of returns. Divergences can signal weakening momentum in the prevailing trend, offering insight into potential buying or selling opportunities.
Key Components
1. Returns Calculation:
* The indicator uses logarithmic returns (log(close / close )) to measure relative price changes in a normalized manner.
* Log returns are more effective than simple price differences when analyzing data across varying price levels, as they account for percentage-based changes.
2. Standard Deviation of Returns:
* The script computes the standard deviation of returns over a user-defined lookback period (ta.stdev(returns, lookback)).
* Standard deviation measures the dispersion of returns around their average, effectively quantifying market volatility.
* A higher standard deviation indicates increased volatility, while lower standard deviation reflects a calmer market.
3. Price Action:
* Detects higher highs (new peaks in price) and lower lows (new troughs in price) over the lookback period.
* Price trends are compared to the behavior of the standard deviation.
4. Divergence Detection:
A divergence occurs when price action (higher highs or lower lows) is not confirmed by a corresponding movement in standard deviation:
Bullish Divergence: Price makes a lower low, but the standard deviation does not, signaling potential upward momentum.
Bearish Divergence: Price makes a higher high, but the standard deviation does not, signaling potential downward momentum.
5. Visual Cues:
The script highlights divergence regions directly on the chart:
Green Background: Indicates a bullish divergence (potential buy signal).
Red Background: Indicates a bearish divergence (potential sell signal).
How It Works
Inputs:
* The user specifies the lookback period (lookback) for calculating the standard deviation and detecting divergences.
Calculation:
* Each bar’s returns are computed and used to calculate the standard deviation over the specified lookback period.
* The indicator evaluates price highs/lows and compares these with the highest and lowest values of the standard deviation within the same lookback period.
Highlight of Divergences:
When divergences are detected:
Bullish Divergence: The background of the chart is shaded green.
Bearish Divergence: The background of the chart is shaded red.
Trading Application
Bullish Divergence:
* Occurs when the market is oversold, or downward momentum is weakening.
* Suggests a potential reversal to an uptrend, signaling a buying opportunity.
Bearish Divergence:
* Occurs when the market is overbought, or upward momentum is weakening.
* Suggests a potential reversal to a downtrend, signaling a selling opportunity.
Contextual Use:
* Use this indicator in conjunction with other technical tools like RSI, MACD, or moving averages to confirm signals.
* Effective in volatile or ranging markets to help anticipate shifts in momentum.
Summary
The "Standard Deviation of Returns: Divergence" indicator is a robust tool for spotting divergences that can signal weakening market trends. It combines statistical volatility with price action analysis to highlight key areas of potential reversals. By integrating this tool into your trading strategy, you can gain additional confirmation for entries or exits while keeping a close watch on momentum shifts.
Disclaimer: This is not a financial advise; please consult your financial advisor for personalized advice.
squeeze candles with volume Function :
This indicator was designed to detect specific candles called “squeeze”. These candles are characterized by a relatively small body (the difference between the opening and closing price) and long shadows (the distance between the high and low prices), accompanied by significant volume. They often indicate a period of increased volatility or a potential trend reversal.
Use :
Visual detection:
Candles identified as "squeeze" are highlighted in red on the chart.
An “S” icon appears above each detected squeeze candle.
Alerts:
The indicator emits an audible and visual alert when a squeeze candle with high volume is detected (if alerts are enabled).
Market analysis:
This indicator is particularly useful for identifying trading opportunities during periods when the market is showing signs of compression or impending volatility.
Customizable settings:
Minimum volume: Defines the threshold at which the volume is considered high.
Maximum body/shadow ratio: Allows you to adjust the sensitivity to detect squeeze candles (the lower the ratio, the smaller the detected candles will have in relation to their shadows).
Benefits :
Provides accurate alerts on key market candles.
Helps anticipate large movements through analysis of volume and candle characteristics.
Adaptable to different strategies thanks to adjustable parameters.
Ideal for:
Traders who want to identify areas of potential volatility or reversal signals in the market, regardless of the asset or time frame used.
