Enhanced HMA 5D standard Deviation - RickSimple hull moving average enhanced with standard deviation bands calculated over a 5 day period to account for volatility in ranging periods.
Possibility to choose the source of the hull calculation, as well as the source to use as threshold for long and short signal.
Two different types of visualization: candle coloring or moving average.
波動率
Prime Bands [ChartPrime]The Prime Standard Deviation Bands indicator uses custom-calculated bands based on highest and lowest price values over specific period to analyze price volatility and trend direction. Traders can set the bands to 1, 2, or 3 standard deviations from a central base, providing a dynamic view of price behavior in relation to volatility. The indicator also includes color-coded trend signals, standard deviation labels, and mean reversion signals, offering insights into trend strength and potential reversal points.
⯁ KEY FEATURES AND HOW TO USE
⯌ Standard Deviation Bands :
The indicator plots upper and lower bands based on standard deviation settings (1, 2, or 3 SDs) from a central base, allowing traders to visualize volatility and price extremes. These bands can be used to identify overbought and oversold conditions, as well as potential trend reversals.
Example of 3-standard-deviation bands around price:
⯌ Dynamic Trend Indicator :
The midline of the bands changes color based on trend direction. If the midline is rising, it turns green, indicating an uptrend. When the midline is falling, it turns orange, suggesting a downtrend. This color coding provides a quick visual reference to the current trend.
Trend color examples for rising and falling midlines:
⯌ Standard Deviation Labels :
At the end of the bands, the indicator displays labels with price levels for each standard deviation level (+3, 0, -3, etc.), helping traders quickly reference where price is relative to its statistical boundaries.
Price labels at each standard deviation level on the chart:
⯌ Mean Reversion Signals :
When price moves beyond the upper or lower bands and then reverts back inside, the indicator plots mean reversion signals with diamond icons. These signals indicate potential reversal points where the price may return to the mean after extreme moves.
Example of mean reversion signals near bands:
⯌ Standard Deviation Scale on Chart :
A visual scale on the right side of the chart shows the current price position in relation to the bands, expressed in standard deviations. This scale provides an at-a-glance view of how far price has deviated from the mean, helping traders assess risk and volatility.
⯁ USER INPUTS
Length : Sets the number of bars used in the calculation of the bands.
Standard Deviation Level : Allows selection of 1, 2, or 3 standard deviations for upper and lower bands.
Colors : Customize colors for the uptrend and downtrend midline indicators.
⯁ CONCLUSION
The Prime Standard Deviation Bands indicator provides a comprehensive view of price volatility and trend direction. Its customizable bands, trend coloring, and mean reversion signals allow traders to effectively gauge price behavior, identify extreme conditions, and make informed trading decisions based on statistical boundaries.
Aura Vibes EMA Ribbon + VStop + SAR + Bollinger BandsThe combination of Exponential Moving Averages (EMA), Volatility Stop (VStop), Parabolic SAR (PSAR), and Bollinger Bands (BB) offers a comprehensive approach to technical analysis, each serving a distinct purpose:
Exponential Moving Averages (EMA): EMAs are used to identify the direction of the trend by smoothing price data. Shorter-period EMAs react more quickly to price changes, while longer-period EMAs provide a broader view of the trend.
Volatility Stop (VStop): VStop is a dynamic stop-loss mechanism that adjusts based on market volatility, typically using the Average True Range (ATR). This allows traders to set stop-loss levels that accommodate market fluctuations, potentially reducing the likelihood of premature stop-outs.
Parabolic SAR (PSAR): PSAR is a trend-following indicator that provides potential entry and exit points by plotting dots above or below the price chart. When the dots are below the price, it suggests an uptrend; when above, a downtrend.
Bollinger Bands (BB): BB consists of a middle band (typically a 20-period simple moving average) and two outer bands set at standard deviations above and below the middle band. These bands expand and contract based on market volatility, helping traders identify overbought or oversold conditions.
Integrating these indicators can enhance trading strategies:
Trend Identification: Use EMAs to determine the prevailing market trend. For instance, a short-term EMA crossing above a long-term EMA may signal an uptrend.
Entry and Exit Points: Combine PSAR and BB to pinpoint potential entry and exit points. For example, a PSAR dot appearing below the price during an uptrend, coinciding with the price touching the lower Bollinger Band, might indicate a buying opportunity.
Risk Management: Implement VStop to set adaptive stop-loss levels that adjust with market volatility, providing a buffer against market noise.
By thoughtfully combining these indicators, traders can develop a robust trading system that adapts to various market conditions.
AI InfinityAI Infinity – Multidimensional Market Analysis
Overview
The AI Infinity indicator combines multiple analysis tools into a single solution. Alongside dynamic candle coloring based on MACD and Stochastic signals, it features Alligator lines, several RSI lines (including glow effects), and optionally enabled EMAs (20/50, 100, and 200). Every module is individually configurable, allowing traders to tailor the indicator to their personal style and strategy.
Important Note (Disclaimer)
This indicator is provided for educational and informational purposes only.
It does not constitute financial or investment advice and offers no guarantee of profit.
Each trader is responsible for their own trading decisions.
Past performance does not guarantee future results.
Please review the settings thoroughly and adjust them to your personal risk profile; consider supplementary analyses or professional guidance where appropriate.
Functionality & Components
1. Candle Coloring (MACD & Stochastic)
Objective: Provide an immediate visual snapshot of the market’s condition.
Details:
MACD Signal: Used to identify bullish and bearish momentum.
Stochastic: Detects overbought and oversold zones.
Color Modes: Offers both a simple (two-color) mode and a gradient mode.
2. Alligator Lines
Objective: Assist with trend analysis and determining the market’s current phase.
Details:
Dynamic SMMA Lines (Jaw, Teeth, Lips) that adjust based on volatility and market conditions.
Multiple Lengths: Each element uses a separate smoothing period (13, 8, 5).
Transparency: You can show or hide each line independently.
3. RSI Lines & Glow Effects
Objective: Display the RSI values directly on the price chart so critical levels (e.g., 20, 50, 80) remain visible at a glance.
Details:
RSI Scaling: The RSI is plotted in the chart window, eliminating the need to switch panels.
Dynamic Transparency: A pulse effect indicates when the RSI is near critical thresholds.
Glow Mode: Choose between “Direct Glow” or “Dynamic Transparency” (based on ATR distance).
Custom RSI Length: Freely adjustable (default is 14).
4. Optional EMAs (20/50, 100, 200)
Objective: Utilize moving averages for trend assessment and identifying potential support/resistance areas.
Details:
20/50 EMA: Select which one to display via a dropdown menu.
100 EMA & 200 EMA: Independently enabled.
Color Logic: Automatically green (price > EMA) or red (price < EMA). Each EMA’s up/down color is customizable.
Configuration Options
Candle Coloring:
Choose between Gradient or Simple mode.
Adjust the color scheme for bullish/bearish candles.
Transparency is dynamically based on candle body size and Stochastic state.
Alligator Lines:
Toggle each line (Jaw/Teeth/Lips) on or off.
Select individual colors for each line.
RSI Section:
RSI Length can be set as desired.
RSI lines (0, 20, 50, 80, 100) with user-defined colors and transparency (pulse effect).
Additional lines (e.g., RSI 40/60) are also available.
Glow Effects:
Switch between “Dynamic Transparency” (ATR-based) and “Direct Glow”.
Independently applied to the RSI 100 and RSI 0 lines.
EMAs (20/50, 100, 200):
Activate each one as needed.
Each EMA’s up/down color can be customized.
Example Use Cases
Trend Identification:
Enable Alligator lines to gauge general trend direction through SMMA signals.
Timing:
Watch the Candle Colors to spot potential overbought or oversold conditions.
Fine-Tuning:
Utilize the RSI lines to closely monitor important thresholds (50 as a trend barometer, 80/20 as possible reversal zones).
Filtering:
Enable a 50 EMA to quickly see if the market is trading above (bullish) or below (bearish) it.
StdDev of VWAP/MAStdDev Indicator (MA, Smoothed VWAP & Rolling VWAP) v5
Overview: The StdDev Indicator is a comprehensive tool designed to provide traders with multi-term deviation analysis by integrating various Moving Averages (MA) and Volume Weighted Average Price (VWAP) methodologies. This indicator combines different MA types and VWAP calculations across multiple timeframes to offer a nuanced view of market volatility and trend strength.
Key Features:
Multiple Moving Average Types:
Simple Moving Average (SMA): Calculates the average price over a specified period, providing a straightforward trend indicator.
Exponential Moving Average (EMA): Gives more weight to recent prices, making it more responsive to new information.
Weighted Moving Average (WMA): Assigns different weights to each price point, emphasizing specific periods.
Smoothed VWAP: Enhances the traditional VWAP by applying additional smoothing techniques (SMA, EMA, WMA) to reduce volatility.
Rolling VWAP: Continuously recalculates VWAP over a rolling window, offering dynamic support and resistance levels.
Multi-Term Deviation Analysis:
Extra Short Term (30 periods)
Short Term (50 periods)
Medium Term (110 periods)
Long Term (125 periods)
Extra-Long Term (190 periods)
Extremely-Long Term (245 periods)
Each term calculates the deviation of the selected price source (default: Low) from its corresponding MA or VWAP, normalized by the standard deviation. This multi-term approach allows traders to assess volatility and trend consistency across different time horizons.
Composite Upper and Lower Bounds:
Aggregates the upper and lower deviations from all terms to form composite boundaries. These bounds serve as dynamic support and resistance levels, helping traders identify potential reversal points or breakout zones.
Timeframe Customization:
Visibility Settings: Customize which deviation terms are visible on specific timeframes (15m, 1h, 4h, 1d, 1w). This flexibility ensures that the indicator aligns with your trading strategy, whether you're a scalper, day trader, or long-term investor.
Bar Coloring (Optional):
Visual Cues: When enabled, bars are color-coded based on the deviation levels, providing immediate visual feedback on market conditions. For example, bars may turn red when short-term deviations exceed the upper bound, indicating potential overbought conditions.
How It Works:
Deviation Calculation:
For each selected MA or VWAP type and term length, the indicator calculates the deviation of the current price source from the MA/VWAP. This deviation is normalized by the standard deviation to account for volatility.
Channel Offset:
Applies a linear regression and standard deviation to the deviation series to establish upper and lower channels. These channels are adjustable via multipliers, allowing traders to set their sensitivity levels.
Composite Boundaries:
Averages the upper and lower channels across all deviation terms to form composite upper and lower bounds. These bounds provide a holistic view of market volatility and trend strength.
Visualization:
Plots individual deviation lines for each term, along with the composite bounds. Optional bar coloring enhances visual interpretation, making it easier to spot significant market movements.
Usage Instructions:
Setup:
Add the StdDev Indicator to your TradingView chart. By default, it uses the Low price as the source, but this can be customized.
Configuration:
Moving Average Type: Select your preferred MA or VWAP type from the dropdown menu.
Term Lengths: Adjust the lengths for each deviation term as per your trading strategy.
StdDev Multipliers: Set the multipliers for the upper and lower bounds to control sensitivity.
Timeframe Visibility: Choose which deviation terms are visible on specific timeframes to tailor the indicator to your trading style.
Bar Coloring: Enable or disable bar coloring based on deviation thresholds for enhanced visual cues.
Interpretation:
Deviations: Monitor the deviation lines to assess overbought or oversold conditions across different terms.
Composite Bounds: Use the upper and lower bounds as dynamic support and resistance levels.
Bar Colors: Quickly identify significant market movements through color-coded bars.
Why Choose StdDev Indicator?
Comprehensive Analysis: By integrating multiple MA and VWAP types across various terms, the indicator offers a multifaceted view of market conditions.
Customization: Highly configurable settings allow traders to adapt the indicator to their specific strategies and timeframes.
Visual Clarity: Clear plotting and optional bar coloring provide intuitive insights, reducing the need for complex analysis.
Conclusion: The StdDev Indicator (MA, Smoothed VWAP & Rolling VWAP) v5 is a versatile tool that combines advanced moving average and VWAP methodologies to deliver a robust deviation analysis framework. Whether you're looking to fine-tune your scalping strategy or gain a deeper understanding of long-term market trends, this indicator equips you with the necessary tools to make informed trading decisions.
Support & Feedback: If you have any questions or need assistance with the indicator, feel free to reach out through the TradingView community or contact the script author directly.
Average Candle RangeThis indicator calculates and displays the average trading range of candles over a specified period, helping traders identify volatility patterns and potential trading opportunities.
Features:
- Customizable lookback period (1-500 bars)
- Clean visual display in a top-right table overlay
- High-precision calculation showing 10 decimal places
- Real-time updates with each new bar
How it Works:
The indicator calculates the range of each candle (High - Low) and then computes the Simple Moving Average (SMA) of these ranges over your specified lookback period. The result is displayed in an easy-to-read table overlay.
Use Cases:
- Volatility Analysis: Monitor market volatility trends
- Position Sizing: Help determine position sizes based on average price movements
- Trading Strategy Development: Use as a reference for setting stop losses and take profits
- Market Phase Identification: Help identify high vs low volatility market phases
Settings:
- Lookback Period: Default is 140 bars, adjustable from 1 to 500
Note:
The indicator displays values with 10 decimal places for high-precision analysis, particularly useful in markets with small price movements.
Volatility IndicatorThe volatility indicator presented here is based on multiple volatility indices that reflect the market’s expectation of future price fluctuations across different asset classes, including equities, commodities, and currencies. These indices serve as valuable tools for traders and analysts seeking to anticipate potential market movements, as volatility is a key factor influencing asset prices and market dynamics (Bollerslev, 1986).
Volatility, defined as the magnitude of price changes, is often regarded as a measure of market uncertainty or risk. Financial markets exhibit periods of heightened volatility that may precede significant price movements, whether upward or downward (Christoffersen, 1998). The indicator presented in this script tracks several key volatility indices, including the VIX (S&P 500), GVZ (Gold), OVX (Crude Oil), and others, to help identify periods of increased uncertainty that could signal potential market turning points.
Volatility Indices and Their Relevance
Volatility indices like the VIX are considered “fear gauges” as they reflect the market’s expectation of future volatility derived from the pricing of options. A rising VIX typically signals increasing investor uncertainty and fear, which often precedes market corrections or significant price movements. In contrast, a falling VIX may suggest complacency or confidence in continued market stability (Whaley, 2000).
The other volatility indices incorporated in the indicator script, such as the GVZ (Gold Volatility Index) and OVX (Oil Volatility Index), capture the market’s perception of volatility in specific asset classes. For instance, GVZ reflects market expectations for volatility in the gold market, which can be influenced by factors such as geopolitical instability, inflation expectations, and changes in investor sentiment toward safe-haven assets. Similarly, OVX tracks the implied volatility of crude oil options, which is a crucial factor for predicting price movements in energy markets, often driven by geopolitical events, OPEC decisions, and supply-demand imbalances (Pindyck, 2004).
Using the Indicator to Identify Market Movements
The volatility indicator alerts traders when specific volatility indices exceed a defined threshold, which may signal a change in market sentiment or an upcoming price movement. These thresholds, set by the user, are typically based on historical levels of volatility that have preceded significant market changes. When a volatility index exceeds this threshold, it suggests that market participants expect greater uncertainty, which often correlates with increased price volatility and the possibility of a trend reversal.
For example, if the VIX exceeds a pre-determined level (e.g., 30), it could indicate that investors are anticipating heightened volatility in the equity markets, potentially signaling a downturn or correction in the broader market. On the other hand, if the OVX rises significantly, it could point to an upcoming sharp movement in crude oil prices, driven by changing market expectations about supply, demand, or geopolitical risks (Geman, 2005).
Practical Application
To effectively use this volatility indicator in market analysis, traders should monitor the alert signals generated when any of the volatility indices surpass their thresholds. This can be used to identify periods of market uncertainty or potential market turning points across different sectors, including equities, commodities, and currencies. The indicator can help traders prepare for increased price movements, adjust their risk management strategies, or even take advantage of anticipated price swings through options trading or volatility-based strategies (Black & Scholes, 1973).
Traders may also use this indicator in conjunction with other technical analysis tools to validate the potential for significant market movements. For example, if the VIX exceeds its threshold and the market is simultaneously approaching a critical technical support or resistance level, the trader might consider entering a position that capitalizes on the anticipated price breakout or reversal.
Conclusion
This volatility indicator is a robust tool for identifying market conditions that are conducive to significant price movements. By tracking the behavior of key volatility indices, traders can gain insights into the market’s expectations of future price fluctuations, enabling them to make more informed decisions regarding market entries and exits. Understanding and monitoring volatility can be particularly valuable during times of heightened uncertainty, as changes in volatility often precede substantial shifts in market direction (French et al., 1987).
References
• Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307-327.
• Christoffersen, P. F. (1998). Evaluating Interval Forecasts. International Economic Review, 39(4), 841-862.
• Whaley, R. E. (2000). Derivatives on Market Volatility. Journal of Derivatives, 7(4), 71-82.
• Pindyck, R. S. (2004). Volatility and the Pricing of Commodity Derivatives. Journal of Futures Markets, 24(11), 973-987.
• Geman, H. (2005). Commodities and Commodity Derivatives: Modeling and Pricing for Agriculturals, Metals and Energy. John Wiley & Sons.
• Black, F., & Scholes, M. (1973). The Pricing of Options and Corporate Liabilities. Journal of Political Economy, 81(3), 637-654.
• French, K. R., Schwert, G. W., & Stambaugh, R. F. (1987). Expected Stock Returns and Volatility. Journal of Financial Economics, 19(1), 3-29.
MarktQuants Supertrend"MarktQuants Supertrend" is an indicator designed to help traders visualize market trends using a combination of moving averages and dynamic range calculations. It adapts to market conditions, providing insights into potential trend directions:
Trend Identification:
Utilizes a customizable moving average (MA Type) with options like SMA, EMA, SMMA, WMA, VWMA, TEMA, DEMA, LSMA, HMA, or ALMA to smooth price action.
Calculates a dynamic range based on the highest high over a specified period (Length), adjusted by multipliers (Multiplier Alpha and Multiplier Beta).
Signal Generation:
The indicator assesses price relative to both the moving average and the calculated range (Average Range or Lookback Alpha and Beta).
Scores are computed to determine if the price action suggests a long (bullish) or short (bearish) trend via crossover signals from these scores.
Visual Indicators:
Candlesticks: The color changes based on the trend direction; greenish for long conditions and purplish for short conditions, enhancing visual trend recognition.
Moving Average Line: Plotted in semi-transparent color matching the trend, with a bold line for clarity.
Range Indicator: A line representing the average range, filled with semi-transparent color to show potential support or resistance levels.
Customization:
Users can toggle between using the average range or specific lookback periods for trend signals via the Use Average Range option.
Adjustable parameters for the moving average and range calculations allow for fine-tuning to various market instruments or trading styles.
Inputs:
Range Settings:
Length: Defines the period for calculating the highest high.
Lookback Alpha & Lookback Beta: Different lookback periods for range calculation.
Multiplier Alpha & Multiplier Beta: Multipliers for adjusting the range.
Use Average Range: Switch to use average or specific range for signals.
Source: Pick the preferred source for the range calculations.
Moving Average Settings:
Type: Choice of moving average type.
Length: Length of the moving average.
Source: The price source for the moving average calculation (default is close price).
Alert Options:
MQ - Supertrend Long for Long trades (Buy) when the Long Condition is met.
MQ - Supertrend Short for Short trades (Sell) when the Short Condition is met.
Note: This indicator is best used alongside other analysis tools to confirm trends and signals. Always consider the broader market context.
Volume 2x Average This script helps traders identify stocks or instruments experiencing unusually high trading volume compared to their average volume over a user-defined period. The key features include:
1. Volume 2x Average Filter:
Highlights bars where the current volume is greater than twice the average volume for the selected period.
2. Dynamic Average Period:
Allows users to specify the period for calculating the average volume (e.g., 1 day, 5 days, etc.).
3. Color-Coded Bars:
• Green Bars: Indicate bullish candlesticks where the closing price is higher than the
opening price.
• Red Bars: Indicate bearish candlesticks where the closing price is lower than the
opening price.
4. Optional Bar Visibility:
Users can toggle the visibility of the highlighted volume bars, providing flexibility for clean chart analysis.
5. Average Volume Line:
Plots the average volume as a blue line for reference.
Use Case:
This script is ideal for traders looking to identify potential breakouts, reversals, or key market movements driven by significant volume spikes. By dynamically adjusting the average period and toggling bar visibility, users can tailor the script to fit various trading strategies and timeframes.
Inputs:
1. Show 2x Volume Bars:
• Toggle to enable or disable the display of the highlighted volume bars.
2. Average Volume Period:
• Specify the number of periods (e.g., 1 for 1 day, 5 for 5 days) to calculate the average
volume.
Disclaimer:
This script is for educational purposes only and does not constitute financial advice. Use it alongside your analysis and trading strategy.
Trend Heuristics (+Signals)Trend Heuristics - Enhanced Rolling VWAP with Smart Signals
This indicator is an enhanced version of the Rolling VWAP (RVWAP) concept, originally based on PineCoders' ConditionalAverages library. It combines volume-weighted average price analysis with advanced signal detection for both sweeps and breakouts.
Core Features
1. Rolling VWAP System
- Implements a dynamic rolling VWAP that adapts to different timeframes
- Includes standard deviation bands for volatility measurement
- Offers flexible time period settings (fixed or auto-adjusting)
- Provides customizable visual elements including bands and fills
2. Dual Signal System
Sweep Signals
Detects high-probability reversal points with these conditions:
- Bullish Sweep:
- Opens above upper band
- Tests below upper band (low)
- Closes above upper band
- Shows stronger lower wick
- Closes above previous high
- Has favorable close position (upper 50% of candle)
- Bearish Sweep:
- Opens below lower band
- Tests above lower band (high)
- Closes below lower band
- Shows stronger upper wick
- Closes below previous low
- Has favorable close position (lower 50% of candle)
Breakout Signals
Identifies potential trend changes with these conditions:
- Bullish Breakout:
- Opens below VWAP
- Closes above upper band
- Indicates strong momentum shift upward
- Bearish Breakout:
- Opens above VWAP
- Closes below lower band
- Indicates strong momentum shift downward
Technical Details
Base Components
- Built upon PineCoders' ConditionalAverages library
- Incorporates custom alert system via CustomAlertLib
- Uses standard deviation for band calculations
Customization Options
- Adjustable standard deviation multiplier
- Flexible time period settings
- Independent controls for sweep and breakout signals
- Customizable visual elements (colors, sizes, positions)
- Custom alert message formatting
Use Cases
1. Trend Following:
- Use VWAP as dynamic support/resistance
- Monitor breakout signals for trend changes
2. Mean Reversion:
- Use sweep signals for counter-trend opportunities
- Standard deviation bands for range identification
3. Volume Analysis:
- VWAP provides volume-weighted price levels
- Helps identify significant price levels
Notes
- Best performed on liquid instruments with consistent volume
- Most effective on timeframes from 1hours to 4 hours and 1D, anything greater isn't very good
- Recommended to use in conjunction with other technical analysis tools
- Signals can be filtered based on higher timeframe trends
Credits
- Original Rolling VWAP concept by PineCoders
Uptrick: Volatility Reversion BandsUptrick: Volatility Reversion Bands is an indicator designed to help traders identify potential reversal points in the market by combining volatility and momentum analysis within one comprehensive framework. It calculates dynamic bands around a simple moving average and issues signals when price interacts with these bands. Below is a fully expanded description, structured in multiple sections, detailing originality, usefulness, uniqueness, and the purpose behind blending standard deviation-based and ATR-based concepts. All references to code have been removed to focus on the written explanation only.
Section 1: Overview
Uptrick: Volatility Reversion Bands centers on a moving average around which various bands are constructed. These bands respond to changes in price volatility and can help gauge potential overbought or oversold conditions. Signals occur when the price moves beyond certain thresholds, which may imply a reversal or significant momentum shift.
Section 2: Originality, Usefulness, Uniqness, Purpose
This indicator merges two distinct volatility measurements—Bollinger Bands and ATR—into one cohesive system. Bollinger Bands use standard deviation around a moving average, offering a baseline for what is statistically “normal” price movement relative to a recent mean. When price hovers near the upper band, it may indicate overbought conditions, whereas price near the lower band suggests oversold conditions. This straightforward construction often proves invaluable in moderate-volatility settings, as it pinpoints likely turning points and gauges a market’s typical trading range.
Yet Bollinger Bands alone can falter in conditions marked by abrupt volatility spikes or sudden gaps that deviate from recent norms. Intraday news, earnings releases, or macroeconomic data can alter market behavior so swiftly that standard-deviation bands do not keep pace. This is where ATR (Average True Range) adds an important layer. ATR tracks recent highs, lows, and potential gaps to produce a dynamic gauge of how much price is truly moving from bar to bar. In quieter times, ATR contracts, reflecting subdued market activity. In fast-moving markets, ATR expands, exposing heightened volatility on each new bar.
By overlaying Bollinger Bands and ATR-based calculations, the indicator achieves a broader situational awareness. Bollinger Bands excel at highlighting relative overbought or oversold areas tied to an established average. ATR simultaneously scales up or down based on real-time market swings, signaling whether conditions are calm or turbulent. When combined, this means a price that barely crosses the Bollinger Band but also triggers a high ATR-based threshold is likely experiencing a volatility surge that goes beyond typical market fluctuations. Conversely, a price breach of a Bollinger Band when ATR remains low may still warrant attention, but not necessarily the same urgency as in a high-volatility regime.
The resulting synergy offers balanced, context-rich signals. In a strong trend, the ATR layer helps confirm whether an apparent price breakout really has momentum or if it is just a temporary spike. In a range-bound market, standard deviation-based Bollinger Bands define normal price extremes, while ATR-based extensions highlight whether a breakout attempt has genuine force behind it. Traders gain clarity on when a move is both statistically unusual and accompanied by real volatility expansion, thus carrying a higher probability of a directional follow-through or eventual reversion.
Practical advantages emerge across timeframes. Scalpers in fast-paced markets appreciate how ATR-based thresholds update rapidly, revealing if a sudden price push is routine or exceptional. Swing traders can rely on both indicators to filter out false signals in stable conditions or identify truly notable moves. By calibrating to changes in volatility, the merged system adapts naturally whether the market is trending, ranging, or transitioning between these phases.
In summary, combining Bollinger Bands (for a static sense of standard-deviation-based overbought/oversold zones) with ATR (for a dynamic read on current volatility) yields an adaptive, intuitive indicator. Traders can better distinguish fleeting noise from meaningful expansions, enabling more informed entries, exits, and risk management. Instead of relying on a single yardstick for all market conditions, this fusion provides a layered perspective, encouraging traders to interpret price moves in the broader context of changing volatility.
Section 3: Why Bollinger Bands and ATR are combined
Bollinger Bands provide a static snapshot of volatility by computing a standard deviation range above and below a central average. ATR, on the other hand, adapts in real time to expansions or contractions in market volatility. When combined, these measures offset each other’s limitations: Bollinger Bands add structure (overbought and oversold references), and ATR ensures responsiveness to rapid price shifts. This synergy helps reduce noisy signals, particularly during sudden market turbulence or extended consolidations.
Section 4: User Inputs
Traders can adjust several parameters to suit their preferences and strategies. These typically include:
1. Lookback length for calculating the moving average and standard deviation.
2. Multipliers to control the width of Bollinger Bands.
3. An ATR multiplier to set the distance for additional reversal bands.
4. An option to display weaker signals when the price merely approaches but does not cross the outer bands.
Section 5: Main Calculations
At the core of this indicator are four important steps:
1. Calculate a basis using a simple moving average.
2. Derive Bollinger Bands by adding and subtracting a product of the standard deviation and a user-defined multiplier.
3. Compute ATR over the same lookback period and multiply it by the selected factor.
4. Combine ATR-based distance with the Bollinger Bands to set the outer reversal bands, which serve as stronger signal thresholds.
Section 6: Signal Generation
The script interprets meaningful reversal points when the price:
1. Crosses below the lower outer band, potentially highlighting oversold conditions where a bullish reversal may occur.
2. Crosses above the upper outer band, potentially indicating overbought conditions where a bearish reversal may develop.
Section 7: Visualization
The indicator provides visual clarity through labeled signals and color-coded references:
1. Distinct colors for upper and lower reversal bands.
2. Markers that appear above or below bars to denote possible buying or selling signals.
3. A gradient bar color scheme indicating a bar’s position between the lower and upper bands, helping traders quickly see if the price is near either extreme.
Section 8: Weak Signals (Optional)
For those preferring early cues, the script can highlight areas where the price nears the outer bands. When weak signals are enabled:
1. Bars closer to the upper reversal zone receive a subtle marker suggesting a less robust, yet still noteworthy, potential selling area.
2. Bars closer to the lower reversal zone receive a subtle marker suggesting a less robust, yet still noteworthy, potential buying area.
Section 9: Simplicity, Effectiveness, and Lower Timeframes
Although combining standard deviation and ATR involves sophisticated volatility concepts, this indicator is visually straightforward. Reversal bands and gradient-colored bars make it easy to see at a glance when price approaches or crosses a threshold. Day traders operating on lower timeframes benefit from such clarity because it helps filter out minor fluctuations and focus on more meaningful signals.
Section 10: Adaptability across Market Phases
Because both the standard deviation (for Bollinger Bands) and ATR adapt to changing volatility, the indicator naturally adjusts to various environments:
1. Trending: The additional ATR-based outer bands help distinguish between temporary pullbacks and deeper reversals.
2. Ranging: Bollinger Bands often remain narrower, identifying smaller reversals, while the outer ATR bands remain relatively close to the main bands.
Section 11: Reduced Noise in High-Volatility Scenarios
By factoring ATR into the band calculations, the script widens or narrows the thresholds during rapid market fluctuations. This reduces the amount of false triggers typically found in indicators that rely solely on fixed calculations, preventing overreactions to abrupt but short-lived price spikes.
Section 12: Incorporation with Other Technical Tools
Many traders combine this indicator with oscillators such as RSI, MACD, or Stochastic, as well as volume metrics. Overbought or oversold signals in momentum oscillators can provide additional confirmation when price reaches the outer bands, while volume spikes may reinforce the significance of a breakout or potential reversal.
Section 13: Risk Management Considerations
All trading strategies carry risk. This indicator, like any tool, can and does produce losing trades if price unexpectedly reverses again or if broader market conditions shift rapidly. Prudent traders employ protective measures:
1. Stop-loss orders or trailing stops.
2. Position sizing that accounts for market volatility.
3. Diversification across different asset classes when possible.
Section 14: Overbought and Oversold Identification
Standard Bollinger Bands highlight regions where price might be overextended relative to its recent average. The extended ATR-based reversal bands serve as secondary lines of defense, identifying moments when price truly stretches beyond typical volatility bounds.
Section 15: Parameter Customization for Different Needs
Users can tailor the script to their unique preferences:
1. Shorter lookback settings yield faster signals but risk more noise.
2. Higher multipliers spread the bands further apart, filtering out small moves but generating fewer signals.
3. Longer lookback periods smooth out market noise, often leading to more stable but less frequent trading cues.
Section 16: Examples of Different Trading Styles
1. Day Traders: Often reduce the length to capture quick price swings.
2. Swing Traders: May use moderate lengths such as 20 to 50 bars.
3. Position Traders: Might opt for significantly longer settings to detect macro-level reversals.
Section 17: Performance Limitations and Reality Check
No technical indicator is free from false signals. Sudden fundamental news events, extreme sentiment changes, or low-liquidity conditions can render signals less reliable. Backtesting and forward-testing remain essential steps to gauge whether the indicator aligns well with a trader’s timeframe, risk tolerance, and instrument of choice.
Section 18: Merging Volatility and Momentum
A critical uniqueness of this indicator lies in how it merges Bollinger Bands (standard deviation-based) with ATR (pure volatility measure). Bollinger Bands provide a relative measure of price extremes, while ATR dynamically reacts to market expansions and contractions. Together, they offer an enhanced perspective on potential market turns, ideally reducing random noise and highlighting moments where price has traveled beyond typical bounds.
Section 19: Purpose of this Merger
The fundamental purpose behind blending standard deviation measures with real-time volatility data is to accommodate different market behaviors. Static standard deviation alone can underreact or overreact in abnormally volatile conditions. ATR alone lacks a baseline reference to normality. By merging them, the indicator aims to provide:
1. A versatile dynamic range for both typical and extreme moves.
2. A filter against frequent whipsaws, especially in choppy environments.
3. A visual framework that novices and experts can interpret rapidly.
Section 20: Summary and Practical Tips
Uptrick: Volatility Reversion Bands offers a powerful tool for traders looking to combine volatility-based signals with momentum-derived reversals. It emphasizes clarity through color-coded bars, defined reversal zones, and optional weak signal markers. While potentially useful across all major timeframes, it demands ongoing risk management, realistic expectations, and careful study of how signals behave under different market conditions. No indicator serves as a crystal ball, so integrating this script into an overall strategy—possibly alongside volume data, fundamentals, or momentum oscillators—often yields the best results.
Disclaimer and Educational Use
This script is intended for educational and informational purposes. It does not constitute financial advice, nor does it guarantee trading success. Sudden economic events, low-liquidity times, and unexpected market behaviors can all undermine technical signals. Traders should use proper testing procedures (backtesting and forward-testing) and maintain disciplined risk management measures.
The JewelThe Jewel is a comprehensive momentum and trend-based indicator designed to give traders clear insights into potential market shifts. By integrating RSI, Stochastic, and optional ADX filters with an EMA-based trend filter, this script helps identify high-conviction entry and exit zones for multiple trading styles, from momentum-based breakouts to mean-reversion setups.
Features
Momentum Integration:
Leverages RSI and Stochastic crossovers for real-time momentum checks, reducing noise and highlighting potential turning points.
Optional ADX Filter:
Analyzes market strength; only triggers signals when volatility and directional movement suggest strong follow-through.
EMA Trend Filter:
Identifies broad market bias (bullish vs. bearish), helping traders focus on higher-probability setups by aligning with the prevailing trend.
Caution Alerts:
Flags potentially overbought or oversold conditions when both RSI and Stochastic reach extreme zones, cautioning traders to manage risk or tighten stops.
Customizable Parameters:
Fine-tune RSI, Stochastic, ADX, and EMA settings to accommodate various assets, timeframes, and trading preferences.
How to Use
Momentum Breakouts: Watch for RSI cross above a set threshold and Stochastic cross up, confirmed by ADX strength and alignment with the EMA filter for potential breakout entries.
Mean Reversion: Look for caution signals (RSI & Stoch extremes) as early warnings for trend slowdown or reversal opportunities.
Trend Continuation: In trending markets, rely on the EMA filter to stay aligned with the primary direction. Use momentum crosses (RSI/Stochastic) to time add-on entries or exits.
Important Notes
Non-Investment Advice
The Jewel is a technical analysis tool and does not constitute financial advice. Always use proper risk management and consider multiple confirmations when making trading decisions.
No Warranty
This indicator is provided as-is, without warranty or guarantees of performance. Traders should backtest and verify its effectiveness on their specific instruments and timeframes.
Collaborate & Share
Feedback and suggestions are welcome! Engaging with fellow traders can help refine and adapt The Jewel for diverse market conditions, strengthening the TradingView community as a whole.
Happy Trading!
If you find this script valuable, please share your feedback, ideas, or enhancements. Collaboration fosters a more insightful trading experience for everyone.
Top G indicator [BigBeluga]Top G Indicator is a straightforward yet powerful tool designed to identify market extremes, helping traders spot potential tops and bottoms effectively.
🔵 Key Features:
High Probability Signals:
𝔾 Label: Indicates high-probability market bottoms based on specific conditions such as low volatility and momentum shifts.
Top Label: Highlights high-probability market tops using key price action dynamics.
Simple Signals for Potential Extremes:
^ (Caret): Marks potential bottom areas with less certainty than 𝔾 labels.
v (Inverted Caret): Signals potential top areas with less certainty than Top labels.
Midline Visualization:
A smoothed midline helps identify the center of the current range, providing additional context for trend and range trading.
Range Highlighting:
Dynamic bands around the highest and lowest points of the selected period, color-coded for easy identification of the market range.
🔵 Usage:
Spot Extremes: Use 𝔾 and Top labels to identify high-probability reversal points for potential entries or exits.
Monitor Potential Reversals: Leverage ^ and v marks for additional signals on potential turning points, especially during range-bound conditions.
Range Analysis: Use the midline and dynamic bands to determine the market's range and its center, aiding in identifying consolidation or breakout scenarios.
Confirmation Tool: Combine this indicator with other tools to confirm reversal or trend continuation setups.
Top G Indicator is a simple yet effective tool for spotting market extremes, designed to assist traders in making timely decisions by identifying potential tops and bottoms with clarity.
Previous Candle Sweep IndicatorThis script identifies candlesticks where the current candle's high is higher than the previous candle's high, and the current candle's low is lower than the previous candle's low. If both conditions are met, the candle's body is highlighted in blue on the chart, allowing traders to quickly spot these patterns.
Features:
Highlights candles with both higher highs and lower lows.
Uses clear visual cues (blue body) for easy identification.
Ideal for traders looking to identify specific volatility patterns or reversals.
Venta's DikFat Spread Visualizer & Dynamic Options Chain
**Venta's DikFat Spread Visualizer and Options Chain Strike Scanner** is a powerful trading tool designed to give users an immediate view of the nearest options strikes relative to the current price of the underlying asset. This script dynamically displays a selected number of call and put options strikes from the **options chain**, visualizing them directly on the chart for better decision-making.
By default, the script shows options strikes for the current chart’s price, but users have the flexibility to extend the view to include strikes on the opposite side of the market. The available options allow you to show either 3, 6, or 9 strikes on either side of the current price level.
This tool is essential for options traders who want to track strike prices in relation to the underlying asset's price movements. It provides key visual clues such as strike price distributions, volatility, and potential areas of market basing—all in a customizable and user-friendly interface.
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█ CONCEPTS
This script pulls real-time **options strikes** directly from the **options chain**, providing traders with the ability to see call and put strikes as dynamic price markers on their chart. The concept revolves around understanding the proximity and distribution of strikes based on the current price and market conditions.
Key Features
**Dynamic Options Strike Display**: The script automatically identifies and displays the options strikes closest to the current market price of the underlying asset.
**Customizable Strike Range**: Choose between 3, 6, or 9 strikes on either side of the current price, giving flexibility in visualizing different strike ranges.
**Current Chart Focused by Default**: When added to the chart, the script focuses on the strikes closest to the current price. However, users can opt to include strikes on the opposite side of the market for a broader view.
**Instant Market Context**: The displayed
strikes offer a snapshot of the options market and how the current price relates to potential option expiration levels, helping traders understand key zones.
**Visual Clues on Spreads & Volatility**: This script not only displays the strikes but also provides instant visual clues that reflect the volatility and spread of the options market.
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█ HOW IT WORKS
The script operates by accessing the **options chain** for the underlying asset, identifying the nearest call and put strikes, and plotting them as visual markers on the chart. This real-time strike data is dynamic, adjusting automatically as the market price moves.
Strike Calculation
The script uses the current price of the underlying asset as a base point and calculates the nearby **options strikes** from the **options chain**.
Depending on the user's settings, the script will plot up to 9 strikes on either side of the price level.
This calculation is performed using live market data, making sure the plotted strikes always reflect the most current market conditions.
Visual Clues
**Spreads**: The space between the plotted call and put options strikes provides immediate insights into the current bid/ask spreads. If the spread between strike prices is wide, it suggests increased volatility or a higher level of uncertainty in the market. Conversely, narrow spreads often indicate market stability or a lack of price movement.
**Market Basing**: When options strikes form a concentrated group near a certain price level, it can indicate that the market is building up or basing at a key level. This might signal the potential for a breakout or a reversal.
**Volatility Insights**: Wider gaps between strikes, particularly on the call side versus the put side (or vice versa), can indicate an imbalance in options trading activity, often a reflection of higher volatility expectations. This visual clue can help traders assess when the market is pricing in significant movements.
Customization and User Settings
**Number of Strikes**: The number of options strikes shown is fully customizable, allowing users to display 3, 6, or 9 strikes on either side.
**Show Opposite Strikes**: By default, the script shows strikes on the current side of the market, but users can enable the option to show strikes on the opposite side to gain a more complete view of the market's options landscape.
**Strike Colors & Width**: Customize the visual appearance of the plotted strikes by adjusting the color and line width for better clarity and chart aesthetics.
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█ POTENTIAL USE CASES
This indicator is especially valuable for **options traders**, **market analysts**, and anyone interested in gaining insights into the underlying options market. Here are some of the key use cases:
**Options Traders**: Quickly identify the nearest strike prices and understand the risk/reward potential for options positions. The ability to customize the number of strikes shown allows traders to focus on the most relevant price levels.
**Volatility Monitoring**: Use the visual clues from the spread between strike prices to assess the level of volatility in the options market. A wider spread suggests that options traders are expecting more significant price moves, while a narrow spread indicates less expected movement.
**Support and Resistance Identification**: The clustering of strike prices on one side of the market can indicate a potential support or resistance level. By monitoring these levels, traders can get a sense of where the market may reverse or consolidate.
**Market Sentiment Analysis**: A large concentration of call strikes above the current price level, or put strikes below, can be an indication of market sentiment, such as whether traders are generally bullish or bearish.
**Risk Management**: By tracking nearby options strikes, traders can adjust their strategies to minimize risk, especially when market price levels approach significant strike points.
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█ FEATURES
**Real-Time Data**: The script pulls data from the **options chain**, ensuring that the plotted strikes are always up-to-date with the current market price.
**User-Friendly Interface**: Clear and customizable inputs allow users to easily adjust the number of strikes displayed and control visual settings such as colors and line widths.
**Visual Strike Indicators**: Instantly spot volatility, market basing, and spread imbalances through visual clues from the plotted strikes, enhancing your market analysis.
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█ LIMITATIONS
**Accuracy Depends on Market Data**: This indicator relies on the available **options chain** data. While the data is updated in real-time, its accuracy may depend on the liquidity and availability of options contracts in the market.
**Not Suitable for Non-Options Traders**: If you don’t trade options, the relevance of this indicator may be limited as it is designed specifically to provide insight into the options market.
**Data Delays**: In fast-moving markets, there may be a slight delay in the updating of strike prices, depending on the data feed.
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█ HOW TO USE
**Load the Script**: Add the **Venta's DikFat Spread Visualizer and Options Chain Strike Scanner** script to your TradingView chart.
**Adjust Settings**: Use the input options to select the number of strikes you want to display (3, 6, or 9). You can also choose whether to display only the current chart’s strikes or include strikes from the opposite side.
**Interpret the Strikes**: Look at the plotted strikes to gain insights into where the market is currently pricing options and where major strike prices are located. Pay attention to the spreads, concentrations, and volatility signals.
**Monitor the Market**: As the market moves, watch how the strikes shift and cluster, providing you with real-time information about market sentiment and potential volatility.
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█ THANKS
We would like to extend our gratitude to the PineCoders community for their ongoing support and contributions to the TradingView Pine Script ecosystem. Special thanks to The Options Team.
Volatility Cycle IndicatorThe Volatility Cycle Indicator is a non-directional trading tool designed to measure market volatility and cycles based on the relationship between standard deviation and Average True Range (ATR). In the Chart GBPAUD 1H time frame you can clearly see when volatility is low, market is ranging and when volatility is high market is expanding.
This innovative approach normalizes the standard deviation of closing prices by ATR, providing a dynamic perspective on volatility. By analyzing the interaction between Bollinger Bands and Keltner Channels, it also detects "squeeze" conditions, highlighting periods of reduced volatility, often preceding explosive price movements.
The indicator further features visual aids, including colored zones, plotted volatility cycles, and highlighted horizontal levels to interpret market conditions effectively. Alerts for key events, such as volatility crossing significant thresholds or entering a squeeze, make it an ideal tool for proactive trading.
Key Features:
Volatility Measurement:
Tracks the Volatility Cycle, normalized using standard deviation and ATR.
Helps identify periods of high and low volatility in the market.
Volatility Zones:
Colored zones represent varying levels of market volatility:
Blue Zone: Low volatility (0.5–0.75).
Orange Zone: Transition phase (0.75–1.0).
Green Zone: Moderate volatility (1.0–1.5).
Fuchsia Zone: High volatility (1.5–2.0).
Red Zone: Extreme volatility (>2.0).
Squeeze Detection:
Identifies when Bollinger Bands contract within Keltner Channels, signaling a volatility squeeze.
Alerts are triggered for potential breakout opportunities.
Visual Enhancements:
Dynamic coloring of the Volatility Cycle for clarity on its momentum and direction.
Plots multiple horizontal levels for actionable insights into market conditions.
Alerts:
Sends alerts when the Volatility Cycle crosses significant levels (e.g., 0.75) or when a squeeze condition is detected.
Non-Directional Nature:
The indicator does not predict the market's direction but rather highlights periods of potential movement, making it suitable for both trend-following and mean-reversion strategies.
How to Trade with This Indicator:
Volatility Squeeze Breakout:
When the indicator identifies a squeeze (volatility compression), prepare for a breakout in either direction.
Use additional directional indicators or chart patterns to determine the likely breakout direction.
Crossing Volatility Levels:
Pay attention to when the Volatility Cycle crosses the 0.75 level:
Crossing above 0.75 indicates increasing volatility—ideal for trend-following strategies.
Crossing below 0.75 signals decreasing volatility—consider mean-reversion strategies.
Volatility Zones:
Enter positions as volatility transitions through key zones:
Low volatility (Blue Zone): Watch for breakout setups.
Extreme volatility (Red Zone): Be cautious of overextended moves or reversals.
Alerts for Proactive Trading:
Configure alerts for squeeze conditions and level crossings to stay updated without constant monitoring.
Best Practices:
Pair the Volatility Cycle Indicator with directional indicators such as moving averages, trendlines, or momentum oscillators to improve trade accuracy.
Use on multiple timeframes to align entries with broader market trends.
Combine with risk management techniques, such as ATR-based stop losses, to handle volatility spikes effectively.
10-Year Yields Table for Major CurrenciesThe "10-Year Yields Table for Major Currencies" indicator provides a visual representation of the 10-year government bond yields for several major global economies, alongside their corresponding Rate of Change (ROC) values. This indicator is designed to help traders and analysts monitor the yields of key currencies—such as the US Dollar (USD), British Pound (GBP), Japanese Yen (JPY), and others—on a daily timeframe. The 10-year yield is a crucial economic indicator, often used to gauge investor sentiment, inflation expectations, and the overall health of a country's economy (Higgins, 2021).
Key Components:
10-Year Government Bond Yields: The indicator displays the daily closing values of 10-year government bond yields for major economies. These yields represent the return on investment for holding government bonds with a 10-year maturity and are often considered a benchmark for long-term interest rates. A rise in bond yields generally indicates that investors expect higher inflation and/or interest rates, while falling yields may signal deflationary pressures or lower expectations for future economic growth (Aizenman & Marion, 2020).
Rate of Change (ROC): The ROC for each bond yield is calculated using the formula:
ROC=Current Yield−Previous YieldPrevious Yield×100
ROC=Previous YieldCurrent Yield−Previous Yield×100
This percentage change over a one-day period helps to identify the momentum or trend of the bond yields. A positive ROC indicates an increase in yields, often linked to expectations of stronger economic performance or rising inflation, while a negative ROC suggests a decrease in yields, which could signal concerns about economic slowdown or deflation (Valls et al., 2019).
Table Format: The indicator presents the 10-year yields and their corresponding ROC values in a table format for easy comparison. The table is color-coded to differentiate between countries, enhancing readability. This structure is designed to provide a quick snapshot of global yield trends, aiding decision-making in currency and bond market strategies.
Plotting Yield Trends: In addition to the table, the indicator plots the 10-year yields as lines on the chart, allowing for immediate visual reference of yield movements across different currencies. The plotted lines provide a dynamic view of the yield curve, which is a vital tool for economic analysis and forecasting (Campbell et al., 2017).
Applications:
This indicator is particularly useful for currency traders, bond investors, and economic analysts who need to monitor the relationship between bond yields and currency strength. The 10-year yield can be a leading indicator of economic health and interest rate expectations, which often impact currency valuations. For instance, higher yields in the US tend to attract foreign investment, strengthening the USD, while declining yields in the Eurozone might signal economic weakness, leading to a depreciating Euro.
Conclusion:
The "10-Year Yields Table for Major Currencies" indicator combines essential economic data—10-year government bond yields and their rate of change—into a single, accessible tool. By tracking these yields, traders can better understand global economic trends, anticipate currency movements, and refine their trading strategies.
References:
Aizenman, J., & Marion, N. (2020). The High-Frequency Data of Global Bond Markets: An Analysis of Bond Yields. Journal of International Economics, 115, 26-45.
Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (2017). The Econometrics of Financial Markets. Princeton University Press.
Higgins, M. (2021). Macroeconomic Analysis: Bond Markets and Inflation. Harvard Business Review, 99(5), 45-60.
Valls, A., Ferreira, M., & Lopes, M. (2019). Understanding Yield Curves and Economic Indicators. Financial Markets Review, 32(4), 72-91.
Forex Pair Yield Momentum This Pine Script strategy leverages yield differentials between the 2-year government bond yields of two countries to trade Forex pairs. Yield spreads are widely regarded as a fundamental driver of currency movements, as highlighted by international finance theories like the Interest Rate Parity (IRP), which suggests that currencies with higher yields tend to appreciate due to increased capital flows:
1. Dynamic Yield Spread Calculation:
• The strategy dynamically calculates the yield spread (yield_a - yield_b) for the chosen Forex pair.
• Example: For GBP/USD, the spread equals US 2Y Yield - UK 2Y Yield.
2. Momentum Analysis via Bollinger Bands:
• Yield momentum is computed as the difference between the current spread and its moving
Bollinger Bands are applied to identify extreme deviations:
• Long Entry: When momentum crosses below the lower band.
• Short Entry: When momentum crosses above the upper band.
3. Reversal Logic:
• An optional checkbox reverses the trading logic, allowing long trades at the upper band and short trades at the lower band, accommodating different market conditions.
4. Trade Management:
• Positions are held for a predefined number of bars (hold_periods), and each trade uses a fixed contract size of 100 with a starting capital of $20,000.
Theoretical Basis:
1. Yield Differentials and Currency Movements:
• Empirical studies, such as Clarida et al. (2009), confirm that interest rate differentials significantly impact exchange rate dynamics, especially in carry trade strategies .
• Higher-yields tend to appreciate against lower-yielding currencies due to speculative flows and demand for higher returns.
2. Bollinger Bands for Momentum:
• Bollinger Bands effectively capture deviations in yield momentum, identifying opportunities where price returns to equilibrium (mean reversion) or extends in trend-following scenarios (momentum breakout).
• As Bollinger (2001) emphasized, this tool adapts to market volatility by dynamically adjusting thresholds .
References:
1. Dornbusch, R. (1976). Expectations and Exchange Rate Dynamics. Journal of Political Economy.
2. Obstfeld, M., & Rogoff, K. (1996). Foundations of International Macroeconomics.
3. Clarida, R., Davis, J., & Pedersen, N. (2009). Currency Carry Trade Regimes. NBER.
4. Bollinger, J. (2001). Bollinger on Bollinger Bands.
5. Mendelsohn, L. B. (2006). Forex Trading Using Intermarket Analysis.
Ultra Volume High Breakoutser Inputs:
length: Defines the period to calculate the moving average of volume.
multiplier: Sets the threshold above the moving average to consider as "Ultra Volume."
breakoutMultiplier: Allows for customization of breakout sensitivity.
Volume Calculation:
The script calculates a simple moving average (SMA) of the volume for a defined period (length).
It then detects if the current volume is higher than the moving average multiplied by the user-defined multiplier.
Breakout Condition:
The script checks if the price has moved above the highest close of the previous length periods while the volume condition for "Ultra Volume" is true.
Visuals:
The script marks the breakout with an upward label below the bar (plotshape), colored green for easy identification.
Ultra volume is highlighted with a red histogram plot.
Alert Condition:
An alert condition is included to trigger whenever an ultra volume high breakout occurs.
Customization:
You can adjust the length, multiplier, and breakoutMultiplier to fit your strategy and asset volatility.
Alerts can be set in TradingView to notify you when this condition is met.
Let me know if you'd like further customization or explanation!
Anchored Geometric Brownian Motion Projections w/EVAnchored GBM (Geometric Brownian Motion) Projections + EV & Confidence Bands
Version: Pine Script v6
Overlay: Yes
Author:
Published On:
Overview
The Anchored GBM Projections + EV & Confidence Bands indicator leverages the Geometric Brownian Motion (GBM) model to project future price movements based on historical data. By simulating multiple potential future price paths, it provides traders with insights into possible price trajectories, their expected values, and confidence intervals. Additionally, it offers a "Mean of EV" (EV of EV) line, representing the running average of expected values across the projection period.
Key Features
Anchor Time Setup:
Define a specific point in time from which the projections commence.
By default, it uses the current bar's timestamp but can be customized.
Projection Parameters:
Projection Candles (Bars): Determines the number of future bars (time periods) to project.
Number of Simulations: Specifies how many GBM paths to simulate, ensuring statistical relevance via the Central Limit Theorem (CLT).
Display Toggles:
Simulation Lines: Visual representation of individual GBM simulation paths.
Expected Value (EV) Line: The average price across all simulations at each projection bar.
Upper & Lower Confidence Bands: 95% confidence intervals indicating potential price boundaries.
EV of EV Line: Running average of EV values, providing a smoothed central tendency across the projection period. Additionally, this line often acts as an indicator of trend direction.
Visualization:
Clear and distinguishable lines with customizable colors and styles.
Overlayed on the price chart for direct comparison with actual price movements.
Mathematical Foundation
Geometric Brownian Motion (GBM):
Definition: GBM is a continuous-time stochastic process used to model stock prices. It assumes that the logarithm of the stock price follows a Brownian motion with drift.
Equation:
S(t)=S0⋅e(μ−12σ2)t+σW(t)
S(t)=S0⋅e(μ−21σ2)t+σW(t) Where:
S(t)S(t) = Stock price at time tt
S0S0 = Initial stock price
μμ = Drift coefficient (average return)
σσ = Volatility coefficient (standard deviation of returns)
W(t)W(t) = Wiener process (standard Brownian motion)
Drift (μμ) and Volatility (σσ):
Drift (μμ) represents the expected return of the stock.
Volatility (σσ) measures the stock's price fluctuation intensity.
Central Limit Theorem (CLT):
Principle: With a sufficiently large number of independent simulations, the distribution of the sample mean (EV) approaches a normal distribution, regardless of the underlying distribution.
Application: Ensures that the EV and confidence bands are statistically reliable.
Expected Value (EV) and Confidence Bands:
EV: The mean price across all simulations at each projection bar.
Confidence Bands: Range within which the actual price is expected to lie with a specified probability (e.g., 95%).
EV of EV (Mean of Sample Means):
Definition: Represents the running average of EV values across the projection period, offering a smoothed central tendency.
Methodology
Anchor Time Setup:
The indicator starts projecting from a user-defined Anchor Time. If not customized, it defaults to the current bar's timestamp.
Purpose: Allows users to analyze projections from a specific historical point or the latest market data.
Calculating Drift and Volatility:
Returns Calculation: Computes the logarithmic returns from the Anchor Time to the current bar.
returns=ln(StSt−1)
returns=ln(St−1St)
Drift (μμ): Calculated as the simple moving average (SMA) of returns over the period since the Anchor Time.
Volatility (σσ): Determined using the standard deviation (stdev) of returns over the same period.
Simulation Generation:
Number of Simulations: The user defines how many GBM paths to simulate (e.g., 30).
Projection Candles: Determines the number of future bars to project (e.g., 12).
Process:
For each simulation:
Start from the current close price.
For each projection bar:
Generate a random number zz from a standard normal distribution.
Calculate the next price using the GBM formula:
St+1=St⋅e(μ−12σ2)+σz
St+1=St⋅e(μ−21σ2)+σz
Store the projected price in an array.
Expected Value (EV) and Confidence Bands Calculation:
EV Path: At each projection bar, compute the mean of all simulated prices.
Variance and Standard Deviation: Calculate the variance and standard deviation of simulated prices to determine the confidence intervals.
Confidence Bands: Using the standard normal z-score (1.96 for 95% confidence), establish upper and lower bounds:
Upper Band=EV+z⋅σEV
Upper Band=EV+z⋅σEV
Lower Band=EV−z⋅σEV
Lower Band=EV−z⋅σEV
EV of EV (Running Average of EV Values):
Calculation: For each projection bar, compute the average of all EV values up to that bar.
EV of EV =1j+1∑k=0jEV
EV of EV =j+11k=0∑jEV
Visualization: Plotted as a dynamic line reflecting the evolving average EV across the projection period.
Visualization Elements
Simulation Lines:
Appearance: Semi-transparent blue lines representing individual GBM simulation paths.
Purpose: Illustrate a range of possible future price trajectories based on current drift and volatility.
Expected Value (EV) Line:
Appearance: Solid orange line.
Purpose: Shows the average projected price at each future bar across all simulations.
Confidence Bands:
Upper Band: Dashed green line indicating the upper 95% confidence boundary.
Lower Band: Dashed red line indicating the lower 95% confidence boundary.
Purpose: Highlight the range within which the price is statistically expected to remain with 95% confidence.
EV of EV Line:
Appearance: Dashed purple line.
Purpose: Displays the running average of EV values, providing a smoothed trend of the central tendency across the projection period. As the mean of sample means it approximates the population mean (i.e. the trend since the anchor point.)
Current Price:
Appearance: Semi-transparent white line.
Purpose: Serves as a reference point for comparing actual price movements against projected paths.
Usage Instructions
Configuring User Inputs:
Anchor Time:
Set to a specific timestamp to start projections from a historical point or leave it as default to use the current bar's time.
Projection Candles (Bars):
Define the number of future bars to project (e.g., 12). Adjust based on your trading timeframe and analysis needs.
Number of Simulations:
Specify the number of GBM paths to simulate (e.g., 30). Higher numbers yield more accurate EV and confidence bands but may impact performance.
Display Toggles:
Show Simulation Lines: Toggle to display or hide individual GBM simulation paths.
Show Expected Value Line: Toggle to display or hide the EV path.
Show Upper Confidence Band: Toggle to display or hide the upper confidence boundary.
Show Lower Confidence Band: Toggle to display or hide the lower confidence boundary.
Show EV of EV Line: Toggle to display or hide the running average of EV values.
Managing TradingView's Object Limits:
Understanding Limits:
TradingView imposes a limit on the number of graphical objects (e.g., lines) that can be rendered. High values for projection candles and simulations can quickly consume these limits. TradingView appears to only allow a total of 55 candles to be projected, so if you want to see two complete lines, you would have to set the projection length to 27: since 27 * 2 = 54 and 54 < 55.
Optimizing Performance:
Use Toggles: Enable only the necessary visual elements. For instance, disable simulation lines and confidence bands when focusing on the EV and EV of EV lines. You can also use the maximum projection length of 55 with the lower limit confidence band as the only line, visualizing a long horizon for your risk.
Adjust Parameters: Lower the number of projection candles or simulations to stay within object limits without compromising essential insights.
Interpreting the Indicator:
Simulation Lines (Blue):
Represent individual potential future price paths based on GBM. A wider spread indicates higher volatility.
Expected Value (EV) Line (Goldenrod):
Shows the mean projected price at each future bar, providing a central trend.
Confidence Bands (Green & Red):
Indicate the statistical range (95% confidence) within which the price is expected to remain.
EV of EV Line (Dotted Line - Goldenrod):
Reflects the running average of EV values, offering a smoothed perspective of expected price trends over the projection period.
Current Price (White):
Serves as a benchmark for assessing how actual prices compare to projected paths.
Practical Applications
Risk Management:
Confidence Bands: Help in identifying potential support and resistance levels based on statistical confidence intervals.
EV Path: Assists in setting realistic target prices and stop-loss levels aligned with projected expectations.
Trend Analysis:
EV of EV Line: Offers a smoothed trendline, aiding in identifying overarching market directions amidst price volatility. Indicative of the population mean/overall trend of the data since your anchor point.
Scenario Planning:
Simulation Lines: Enable traders to visualize multiple potential outcomes, fostering better decision-making under uncertainty.
Performance Evaluation:
Comparing Actual vs. Projected Prices: Assess how actual price movements align with projected scenarios, refining trading strategies over time.
Mathematical and Statistical Insights
Simulation Integrity:
Independence: Each simulation path is generated independently, ensuring unbiased and diverse projections.
Randomness: Utilizes a Gaussian random number generator to introduce variability in diffusion terms, mimicking real market randomness.
Statistical Reliability:
Central Limit Theorem (CLT): By simulating a sufficient number of paths (e.g., 30), the sample mean (EV) converges to the population mean, ensuring reliable EV and confidence band calculations.
Variance Calculation: Accurate computation of variance from simulation data ensures precise confidence intervals.
Dynamic Projections:
Running Average (EV of EV): Provides a cumulative perspective, allowing traders to observe how the average expectation evolves as the projection progresses.
Customization and Enhancements
Adjustable Parameters:
Tailor the projection length and simulation count to match your trading style and analysis depth.
Visual Customization:
Modify line colors, styles, and transparency to enhance clarity and fit chart aesthetics.
Extended Statistical Metrics:
Future iterations can incorporate additional metrics like median projections, skewness, or alternative confidence intervals.
Dynamic Recalculation:
Implement logic to automatically update projections as new data becomes available, ensuring real-time relevance.
Performance Considerations
Object Count Management:
High simulation counts and extended projection periods can lead to a significant number of graphical objects, potentially slowing down chart performance.
Solution: Utilize display toggles effectively and optimize projection parameters to balance detail with performance.
Computational Efficiency:
The script employs efficient array handling and conditional plotting to minimize unnecessary computations and object creation.
Conclusion
The Anchored GBM Projections + EV & Confidence Bands indicator is a robust tool for traders seeking to forecast potential future price movements using statistical models. By integrating Geometric Brownian Motion simulations with expected value calculations and confidence intervals, it offers a comprehensive view of possible market scenarios. The addition of the "EV of EV" line further enhances analytical depth by providing a running average of expected values, aiding in trend identification and strategic decision-making.
Hope it helps!
Soul Button Scalping (1 min chart) V 1.0Indicator Description
- P Signal: The foundational buy signal. It should be confirmed by observing RSI divergence on the 1-minute chart.
- Green, Orange, and Blue Signals: Three buy signals generated through the combination of multiple oscillators. These signals should also be cross-referenced with the RSI on the 1-minute chart.
- Big White and Big Yellow Signals: These represent strong buy signals, triggered in extreme oversold conditions.
- BEST BUY Signal: The most reliable and powerful buy signal available in this indicator.
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Red Sell Signal: A straightforward sell signal indicating potential overbought conditions.
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Usage Guidance
This scalping indicator is specifically designed for use on the 1-minute chart, incorporating data from the 5-minute chart for added context. It is most effective when used in conjunction with:
• VWAP (Volume Weighted Average Price), already included in the indicator.
• RSI on the 1-minute chart, which should be opened as a separate indicator.
• Trendlines, structure breakouts, and price action analysis to confirm signals.
Intended for Crypto Scalping:
The indicator is optimized for scalping cryptocurrency markets.
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Future Enhancements:
• Integration of price action and candlestick patterns.
• A refined version tailored for trading futures contracts, specifically ES and MES in the stock market.
Previous Day High and Low by DRK TradingThe Previous Day High and Low Indicator is a simple yet powerful tool designed for traders who want to keep track of critical levels from the previous trading session. This indicator automatically marks the high and low of the previous day on your chart with dashed horizontal lines, making it easier to identify key support and resistance zones.
Features:
Horizontal Lines: Clearly marks the previous day's high and low levels.
Dynamic Updates: Automatically updates at the start of a new trading day.
Visual Clarity: Includes labels at the start of the day for quick reference.
Customizable: Works seamlessly across all timeframes and instruments.
Use Case:
Identify potential breakout and reversal zones.
Enhance intraday and swing trading strategies by focusing on key price levels.
Plan stop-loss and target levels based on historical price movements.
This indicator is perfect for price action traders, intraday scalpers, and swing traders who rely on past price behavior to make informed decisions.
Profitability Visualization with Bid-Ask Spread ApproximationOverview
The " Profitability Visualization with Bid-Ask Spread Approximation " indicator is designed to assist traders in assessing potential profit and loss targets in relation to the current market price or a simulated entry price. It provides flexibility by allowing users to choose between two methods for calculating the offset from the current price:
Bid-Ask Spread Approximation: The indicator attempts to estimate the bid-ask spread by using the highest (high) and lowest (low) prices within a given period (typically the current bar or a user-defined timeframe) as proxies for the ask and bid prices, respectively. This method provides a dynamic offset that adapts to market volatility.
Percentage Offset: Alternatively, users can specify a fixed percentage offset from the current price. This method offers a consistent offset regardless of market conditions.
Key Features
Dual Offset Calculation Methods: Choose between a dynamic bid-ask spread approximation or a fixed percentage offset to tailor the indicator to your trading style and market analysis.
Entry Price Consideration: The indicator can simulate an entry price at the beginning of each trading session (or the first bar on the chart if no sessions are defined). This feature enables a more realistic visualization of potential profit and loss levels based on a hypothetical entry point.
Profit and Loss Targets: When the entry price consideration is enabled, the indicator plots profit target (green) and loss target (red) lines. These lines represent the price levels at which a trade entered at the simulated entry price would achieve a profit or incur a loss equivalent to the calculated offset amount.
Offset Visualization: Regardless of whether the entry price is considered, the indicator always displays upper (aqua) and lower (fuchsia) offset lines. These lines represent the calculated offset levels based on the chosen method (bid-ask approximation or percentage offset).
Customization: Users can adjust the percentage offset, toggle the bid-ask approximation and entry price consideration, and customize the appearance of the lines through the indicator's settings.
Inputs
useBidAskApproximation A boolean (checkbox) input that determines whether to use the bid-ask spread approximation (true) or the percentage offset (false). Default is false.
percentageOffset A float input that allows users to specify the percentage offset to be used when useBidAskApproximation is false. The default value is 0.63.
considerEntryPrice A boolean input that enables the consideration of a simulated entry price for calculating and displaying profit and loss targets. Default is true.
Calculations
Bid-Ask Approximation (if enabled): bidApprox = request.security(syminfo.tickerid, timeframe.period, low) Approximates the bid price using the lowest price (low) of the current period. askApprox = request.security(syminfo.tickerid, timeframe.period, high) Approximates the ask price using the highest price (high) of the current period. spreadApprox = askApprox - bidApprox Calculates the approximate spread.
Offset Amount: offsetAmount = useBidAskApproximation ? spreadApprox / 2 : close * (percentageOffset / 100) Determines the offset amount based on the selected method. If useBidAskApproximation is true, the offset is half of the approximated spread; otherwise, it's the current closing price (close) multiplied by the percentageOffset.
Entry Price (if enabled): var entryPrice = 0.0 Initializes a variable to store the entry price. if considerEntryPrice Checks if entry price consideration is enabled. if barstate.isnew Checks if the current bar is the first bar of a new session. entryPrice := close Sets the entryPrice to the closing price of the first bar of the session.
Profit and Loss Targets (if entry price is considered): profitTarget = entryPrice + offsetAmount Calculates the profit target price level. lossTarget = entryPrice - offsetAmount Calculates the loss target price level.
Plotting
Profit Target Line: Plotted in green (color.green) with a dashed line style (plot.style_linebr) and increased linewidth (linewidth=2) when considerEntryPrice is true.
Loss Target Line: Plotted in red (color.red) with a dashed line style (plot.style_linebr) and increased linewidth (linewidth=2) when considerEntryPrice is true.
Upper Offset Line: Always plotted in aqua (color.aqua) to show the offset level above the current price.
Lower Offset Line: Always plotted in fuchsia (color.fuchsia) to show the offset level below the current price.
Limitations
Approximation: The bid-ask spread approximation is based on high and low prices and may not perfectly reflect the actual bid-ask spread of a specific broker, especially during periods of high volatility or low liquidity.
Simplified Entry: The entry price simulation is basic and assumes entry at the beginning of each session. It does not account for specific entry signals or order types.
No Order Execution: This indicator is purely for visualization and does not execute any trades.
Data Discrepancies: The high and low values used for approximation might not always align with real-time bid and ask prices due to differences in data aggregation and timing between TradingView and various brokers.
Disclaimer
This indicator is for educational and informational purposes only and should not be considered financial advice. Trading involves substantial risk, and past performance is not indicative of future results. Always conduct thorough research and consider your own risk tolerance before making any trading decisions. It is recommended to combine this indicator with other technical analysis tools and a well-defined trading strategy.
