Curved Trend Channels (Zeiierman)█ Overview
Curved Trend Channels (Zeiierman) is a next-generation trend visualization tool engineered to adapt dynamically to both linear and non-linear market behavior. It introduces a novel curvature-based channeling system that grows over time during trending conditions, mirroring the natural acceleration of price trends, while simultaneously leveraging adaptive range filtering and dual-layer candle trend logic.
This tool is ideal for traders seeking smooth yet reactive dynamic channels that evolve with market structure. Whether used in curved mode or traditional slope mode, it provides exceptional clarity on trend transitions, volatility compression, and breakout development.
█ How It Works
⚪ Adaptive Range Filter Foundation
The core of the system is a volatility-based range filter that determines the underlying structure of the bands:
Pre-Smoothing of High/Low Data – Highs and lows are smoothed using a selectable moving average (SMA, EMA, HMA, KAMA, etc.) before calculating the volatility range.
Volatility Envelope – The range is scaled using a fixed factor (2.618) and further adjusted by a Band Multiplier to form the primary envelope around price.
Smoothed Volatility Curve – Final bands are stabilized using a long lookback, ensuring clean visual structure and trend clarity.
⚪ Curved Channel Logic
In Curved Mode, the trend channel grows over time when the trend direction remains unchanged:
Base Step Size (× ATR) – Sets the minimum unit of slope change.
Growth per Bar (× ATR) – Defines the acceleration rate of the channel slope with time.
Trend Persistence Recognition – The longer a trend persists, the more pronounced the slope becomes, mimicking real market accelerations.
This dynamic, time-dependent logic enables the channel to "curve" upward or downward, tracking long-standing trends with increasing confidence.
⚪ Trend Slope
As an alternative to curved logic, traders can activate a regular Trend slope using:
Slope Length – Determines how quickly the trend line adapts to price shifts.
Multiplicative Factor – Amplifies the sensitivity of the slope, useful in fast-moving markets or lower timeframes.
⚪ Candle Trend Confirmation
A robust second-layer trend detection method, the Candle Trend System evaluates directional pressure by analyzing smoothed price action:
Multi-tier Smoothing – Trend lines are derived from short-, medium-, and long-term candle movement.
█ How to Use
⚪ Trend Identification
When the Trend Line direction and Candle Colors are in agreement, this indicates strong, persistent directional conviction. Use these moments to enter with trend confirmation and manage risk more confidently.
⚪ Retest
During ongoing trends, the price will often pull back into the dynamic channel. Look for:
Support/resistance interactions at the upper or lower bands.
█ Settings
Scaled Volatility Length – Controls the historical depth used to stabilize the volatility bands.
Smoothing Type – Choose from HMA, KAMA, VIDYA, FRAMA, Super Smoother, etc. to match your asset and trading style.
Volatility MA Length – Smoothing length for the calculated range; shorter = more reactive.
High/Low Smoother Length – Additional smoothing to reduce noise from spikes or false pivots.
Band Multiplier – Widens or tightens the band range based on personal preference.
Enable Curved Channel – Toggle between curved or regular trend slope behavior.
Base Step (× ATR) – The starting point for curved slope progression.
Growth per Bar (× ATR) – How much the slope accelerates per bar during a sustained trend.
Slope – Reactivity of the standard trend line to price movements.
Multiplicative Factor – Sensitivity adjustment for HyperTrend slope.
Candle Trend Length – Lookback period for trend determination from candle structure.
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Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Indicator
Consolidation Range with Signals (Zeiierman)█ Overview
Consolidation Range with Signals (Zeiierman) is a precision tool for identifying and trading market consolidation zones, where price contracts into tight ranges before significant movement. It provides dynamic range detection using either ADX-based trend strength or volatility compression metrics, and offers built-in take profit and stop loss signals based on breakout dynamics.
Whether you trade breakouts, range reversals, or trend continuation setups, this indicator visualizes the balance between supply and demand with clearly defined mid-bands, breakout zones, and momentum-sensitive TP/SL placements.
█ How It Works
⚪ Multi-Method Range Detection
ADX Mode
Uses the Average Directional Index (ADX) to detect low-trend-strength environments. When ADX is below your selected threshold, price is considered to be in consolidation.
Volatility Mode
This mode detects consolidation by identifying periods of volatility compression. It evaluates whether the following metrics are simultaneously below their respective historical rolling averages:
Standard Deviation
Variance
Average True Range (ATR)
⚪ Dynamic Range Band System
Once a range is confirmed, the system builds a dynamic band structure using a volatility-based filter and price-jump logic:
Middle Line (Trend Filter): Reacts to price imbalance using adaptive jump logic.
Upper & Lower Bands: Calculated by expanding from the middle line using a configurable multiplier.
This creates a clean, visual box that reflects current consolidation conditions and adapts as price fluctuates within or escapes the zone.
⚪ SL/TP Signal Engine
On detection of a breakout from the range, the indicator generates up to 3 Take Profit levels and one Stop Loss, based on the breakout direction:
All TP/SL levels are calculated using the filtered base range and multipliers.
Cooldown logic ensures signals are not spammed bar-to-bar.
Entries are visualized with colored lines and labeled levels.
This feature is ideal for traders who want automated risk and reward reference points for range breakout plays.
█ How to Use
⚪ Breakout Traders
Use the SL/TP signals when the price breaks above or below the range bands, especially after extended sideways movement. You can customize how far TP1, TP2, and TP3 sit from the entry using your own risk/reward profile.
⚪ Mean Reversion Traders
Use the bands to locate high-probability reversion zones. These serve as reference zones for scalping or fade entries within stable consolidation phases.
█ Settings
Range Detection Method – Choose between ADX or Volatility compression to define range criteria.
Range Period – Determines how many bars are used to compute trend/volatility.
Range Multiplier – Scales the width of the consolidation zone.
SL/TP System – Optional levels that project TP1/TP2/TP3 and SL from the base price using multipliers.
Cooldown – Prevents repeated SL/TP signals from triggering too frequently.
ADX Threshold & Smoothing – Adjusts sensitivity of trend strength detection.
StdDev / Variance / ATR Multipliers – Fine-tune compression detection logic.
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Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Indicator
Dynamic Range Filter with Trend Candlesticks (Zeiierman)█ Overview
Dynamic Range Filter with Trend Candlesticks (Zeiierman) is a volatility-responsive trend engine that adapts in real-time to market structure, offering a clean and intelligent visualization of directional bias. It blends dynamic range calculation with customizable smoothing techniques and layered trend confirmation logic, making it ideal for traders who rely on clear trend direction, structural range analysis, and momentum-based candlestick signals.
By measuring scaled volatility over configurable lengths and applying advanced moving average techniques, this indicator filters out market noise while preserving true directional intent. Complementing this, a dual-trend system (range-based and candle-based) enhances clarity and responsiveness, particularly during shifting market conditions.
█ How It Works
⚪ Scaled Volatility Band Calculation
At the core lies a volatility engine that constructs adaptive range bands around price using smoothed high/low calculations. The bands are dynamically adjusted using:
High/Low Smoothing – Applies a moving average to the raw high and low data before calculating the range.
Scaled Range Volatility – A 2.618 multiplier scales the distance between smoothed highs and lows, forming a responsive volatility envelope.
Band Multiplier – Controls how wide the upper/lower range bands extend from the mean.
This filtering process minimizes false signals and highlights only structurally meaningful moves.
⚪ Multi-Type Smoothing Engine
Users can choose from a wide array of smoothing algorithms for trend construction, including:
HMA (default), SMA, EMA, RMA
KAMA – Adapts to market volatility using efficiency ratios.
VIDYA – Momentum-sensitive smoothing using CMO logic.
FRAMA – Dynamically adjusts to fractal dimension in price.
Super Smoother – Ideal for eliminating aliasing in range signals.
This provides the trader with fine-tuned control over reactivity vs. smoothness.
⚪ Trend Detection (Dual Engine)
The indicator includes two independent trend tracking systems:
Main Trend Filter – Based on adaptive volatility band shifts.
Candle Trend Filter – A second-tier confirmation using smoothed candle data, ideal for directional candles and confirmation entries.
█ How to Use
⚪ Trend Confirmation
Use the Trend Line and colored candlesticks for high-probability entries in the trend direction. The more trend layers that align, the higher the confidence.
⚪ Reversal Zones
When the price reaches the outer bands or fails to break them, look for candle color shifts or a crossover in the range to anticipate possible reversals or consolidations.
█ Settings
Scaled Volatility Length – Controls the lookback used to stabilize the base volatility band.
MA Type & Length – Choose and fine-tune the smoothing method (HMA, EMA, KAMA, etc.)
High/Low Smoother – Pre-smoothing for structural high/low banding.
Band Multiplier – Adjusts the width of the dynamic bands.
Trend Length (Candles) – Length used for candle-based trend confirmation.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Indicator
Dynamic Volume Clusters with Retest Signals (Zeiierman)█ Overview
The Dynamic Volume Clusters with Retest Signals indicator is designed to detect key Volume Clusters and provide Retest Signals. This tool is specifically engineered for traders looking to capitalize on volume-based trends, reversals, and key price retest points.
The indicator seamlessly combines volume analysis, dynamic cluster calculations, and retest signal logic to present a comprehensive trading framework. It adapts to market conditions, identifying clusters of volume activity and signaling when the price retests critical zones.
█ How It Works
⚪ Volume Cluster Detection
The indicator dynamically calculates volume clusters by analyzing the highest and lowest price points within a specified lookback period.
Cluster Logic:
Bright Lines (Strong Red/Green):
These indicate that the price has frequently revisited these levels, creating a dense cluster.
Such areas serve as support or resistance, where significant historical trading has occurred, often acting as barriers to price movement.
Traders should consider these levels as potential reversal zones or consolidation points.
Faded or Darker Lines:
These lines indicate areas where the price has less historical activity, suggesting weaker clustering.
These zones have less market memory and are more likely to break, supporting trend continuation and rapid price movement.
⚪ Candle Color Logic (Market Memory)
Blue Candles (High Cluster Density):
Candles turn blue when the price has revisited a particular area many times.
This signals a highly clustered zone, likely to act as a barrier, creating consolidation or range phases.
These areas indicate strong market memory, potentially rejecting price attempts to break through.
Green or Red Candles (Low Cluster Density):
Once the price breaks out of these dense clusters, the candles turn green (bullish) or red (bearish).
This suggests the price has moved into a less clustered territory, where the path forward is clearer and trends are likely to extend without immediate resistance.
⚪ Retest Signal Logic
The indicator identifies critical retest points where the price crosses a cluster boundary and then reverses. These points are essential for traders looking to catch continuation or reversal setups.
⚪ Dynamic Price Clustering
The indicator dynamically adapts the clustering logic based on price movement and volume shifts.
Uses a dynamic moving average (VPMA) to maintain adaptive cluster levels.
Integrates a Kalman Filter for smoothing, reducing noise, and improving trend clarity.
Automatically updates as new data is received, keeping the clusters relevant in real-time.
█ How to Use
⚪ Trend Following & Reversal Detection
Use Retest signals to identify potential trend continuation or reversal points.
⚪ Trading Volume Clusters and Market Memory
Identify Key Zones:
Focus on bright, saturated cluster lines (strong red or green) as they indicate high market memory, where price has spent significant time in the past.
These zones are likely to exhibit a more choppy market. Apply range or mean reversion strategies.
Spot Potential Breakouts:
Faded or darker cluster lines indicate areas of low market memory, where the price has moved quickly and spent less time.
Use these areas to identify possible trend setups, as they represent lower resistance to price movement.
⚪ Interpreting Candle Colors for Market Phases
Blue Candles (High Cluster Density):
When candles turn blue, it signals that the price has revisited this area multiple times, creating a dense cluster.
These zones often trap price movement, leading to consolidations or range phases.
Use these areas as caution zones, where price can slow down or reverse.
Green or Red Candles (Low Cluster Density):
Once the price breaks out of these clustered zones, the candles turn green (bullish) or red (bearish), indicating lower market memory.
This signals a trend initiation with less immediate resistance, ideal for momentum and breakout trades.
Use these signals to identify emerging trends and ride the momentum.
█ Settings
Range Lookback Period: Sets the number of bars for calculating the range.
Zone Width (% of Range): Determines how wide the volume clusters are relative to the calculated range.
Volume Line Colors: Customize the appearance of bullish and bearish lines.
Retest Signals: Toggle the appearance of Triangle Up/Down retest markers.
Minimum Bars for Retest: Define the minimum number of bars required before a retest is valid.
Maximum Bars for Retest: Set the maximum number of bars within which a retest can occur.
Price Cluster Period: Adjusts the sensitivity of the dynamic clustering logic.
Cluster Confirmation: Controls how tightly the clusters respond to price action.
Price Cluster Start/Peak: Sets the minimum and maximum touches required to fully form a cluster.
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Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Indicator
Indicator
[GYTS-CE] Market Regime Detector🧊 Market Regime Detector (Community Edition)
🌸 Part of GoemonYae Trading System (GYTS) 🌸
🌸 --------- INTRODUCTION --------- 🌸
💮 What is the Market Regime Detector?
The Market Regime Detector is an advanced, consensus-based indicator that identifies the current market state to increase the probability of profitable trades. By distinguishing between trending (bullish or bearish) and cyclic (range-bound) market conditions, this detector helps you select appropriate tactics for different environments. Instead of forcing a single strategy across all market conditions, our detector allows you to adapt your approach based on real-time market behaviour.
💮 The Importance of Market Regimes
Markets constantly shift between different behavioural states or "regimes":
• Bullish trending markets - characterised by sustained upward price movement
• Bearish trending markets - characterised by sustained downward price movement
• Cyclic markets - characterised by range-bound, oscillating behaviour
Each regime requires fundamentally different trading approaches. Trend-following strategies excel in trending markets but fail in cyclic ones, while mean-reversion strategies shine in cyclic markets but underperform in trending conditions. Detecting these regimes is essential for successful trading, which is why we've developed the Market Regime Detector to accurately identify market states using complementary detection methods.
🌸 --------- KEY FEATURES --------- 🌸
💮 Consensus-Based Detection
Rather than relying on a single method, our detector employs two complementary detection methodologies that analyse different aspects of market behaviour:
• Dominant Cycle Average (DCA) - analyzes price movement relative to its lookback period, a proxy for the dominant cycle
• Volatility Channel - examines price behaviour within adaptive volatility bands
These diverse perspectives are synthesised into a robust consensus that minimises false signals while maintaining responsiveness to genuine regime changes.
💮 Dominant Cycle Framework
The Market Regime Detector uses the concept of dominant cycles to establish a reference framework. You can input the dominant cycle period that best represents the natural rhythm of your market, providing a stable foundation for regime detection across different timeframes.
💮 Intuitive Parameter System
We've distilled complex technical parameters into intuitive controls that traders can easily understand:
• Adaptability - how quickly the detector responds to changing market conditions
• Sensitivity - how readily the detector identifies transitions between regimes
• Consensus requirement - how much agreement is needed among detection methods
This approach makes the detector accessible to traders of all experience levels while preserving the power of the underlying algorithms.
💮 Visual Market Feedback
The detector provides clear visual feedback about the current market regime through:
• Colour-coded chart backgrounds (purple shades for bullish, pink for bearish, yellow for cyclic)
• Colour-coded price bars
• Strength indicators showing the degree of consensus
• Customizable colour schemes to match your preferences or trading system
💮 Integration in the GYTS suite
The Market Regime Detector is compatible with the GYTS Suite , i.e. it passes the regime into the 🎼 Order Orchestrator where you can set how to trade the trending and cyclic regime.
🌸 --------- CONFIGURATION SETTINGS --------- 🌸
💮 Adaptability
Controls how quickly the Market Regime detector adapts to changing market conditions. You can see it as a low-frequency, long-term change parameter:
Very Low: Very slow adaptation, most stable but may miss regime changes
Low: Slower adaptation, more stability but less responsiveness
Normal: Balanced between stability and responsiveness
High: Faster adaptation, more responsive but less stable
Very High: Very fast adaptation, highly responsive but may generate false signals
This setting affects lookback periods and filter parameters across all detection methods.
💮 Sensitivity
Controls how sensitive the detector is to market regime transitions. This acts as a high-frequency, short-term change parameter:
Very Low: Requires substantial evidence to identify a regime change
Low: Less sensitive, reduces false signals but may miss some transitions
Normal: Balanced sensitivity suitable for most markets
High: More sensitive, detects subtle regime changes but may have more noise
Very High: Very sensitive, detects minor fluctuations but may produce frequent changes
This setting affects thresholds for regime detection across all methods.
💮 Dominant Cycle Period
This parameter allows you to specify the market's natural rhythm in bars. This represents a complete market cycle (up and down movement). Finding the right value for your specific market and timeframe might require some experimentation, but it's a crucial parameter that helps the detector accurately identify regime changes. Most of the times the cycle is between 20 and 40 bars.
💮 Consensus Mode
Determines how the signals from both detection methods are combined to produce the final market regime:
• Any Method (OR) : Signals bullish/bearish if either method detects that regime. If methods conflict (one bullish, one bearish), the stronger signal wins. More sensitive, catches more regime changes but may produce more false signals.
• All Methods (AND) : Signals only when both methods agree on the regime. More conservative, reduces false signals but might miss some legitimate regime changes.
• Weighted Decision : Balances both methods with equal weighting. Provides a middle ground between sensitivity and stability.
Each mode also calculates a continuous regime strength value that's used for colour intensity in the 'unconstrained' display mode.
💮 Display Mode
Choose how to display the market regime colours:
• Unconstrained regime: Shows the regime strength as a continuous gradient. This provides more nuanced visualisation where the intensity of the colour indicates the strength of the trend.
• Consensus only: Shows only the final consensus regime with fixed colours based on the detected regime type.
The background and bar colours will change to indicate the current market regime:
• Purple shades: Bullish trending market (darker purple indicates stronger bullish trend)
• Pink shades: Bearish trending market (darker pink indicates stronger bearish trend)
• Yellow: Cyclic (range-bound) market
💮 Custom Colour Options
The Market Regime Detector allows you to customize the colour scheme to match your personal preferences or to coordinate with other indicators:
• Use custom colours: Toggle to enable your own colour choices instead of the default scheme
• Transparency: Adjust the transparency level of all regime colours
• Bullish colours: Define custom colours for strong, medium, weak, and very weak bullish trends
• Bearish colours: Define custom colours for strong, medium, weak, and very weak bearish trends
• Cyclic colour: Define a custom colour for cyclic (range-bound) market conditions
🌸 --------- DETECTION METHODS --------- 🌸
💮 Dominant Cycle Average (DCA)
The Dominant Cycle Average method forms a key part of our detection system:
1. Theoretical Foundation :
The DCA method builds on cycle analysis and the observation that in trending markets, price consistently remains on one side of a moving average calculated using the dominant cycle period. In contrast, during cyclic markets, price oscillates around this average.
2. Calculation Process :
• We calculate a Simple Moving Average (SMA) using the specified lookback period - a proxy for the dominant cycle period
• We then analyse the proportion of time that price spends above or below this SMA over a lookback window. The theory is that the price should cross the SMA each half cycle, assuming that the dominant cycle period is correct and price follows a sinusoid.
• This lookback window is adaptive, scaling with the dominant cycle period (controlled by the Adaptability setting)
• The different values are standardised and normalised to possess more resolving power and to be more robust to noise.
3. Regime Classification :
• When the normalised proportion exceeds a positive threshold (determined by Sensitivity setting), the market is classified as bullish trending
• When it falls below a negative threshold, the market is classified as bearish trending
• When the proportion remains between these thresholds, the market is classified as cyclic
💮 Volatility Channel
The Volatility Channel method complements the DCA method by focusing on price movement relative to adaptive volatility bands:
1. Theoretical Foundation :
This method is based on the observation that trending markets tend to sustain movement outside of normal volatility ranges, while cyclic markets tend to remain contained within these ranges. By creating adaptive bands that adjust to current market volatility, we can detect when price behaviour indicates a trending or cyclic regime.
2. Calculation Process :
• We first calculate a smooth base channel center using a low pass filter, creating a noise-reduced centreline for price
• True Range (TR) is used to measure market volatility, which is then smoothed and scaled by the deviation factor (controlled by Sensitivity)
• Upper and lower bands are created by adding and subtracting this scaled volatility from the centreline
• Price is smoothed using an adaptive A2RMA filter, which has a very flat and stable behaviour, to reduce noise while preserving trend characteristics
• The position of this smoothed price relative to the bands is continuously monitored
3. Regime Classification :
• When smoothed price moves above the upper band, the market is classified as bullish trending
• When smoothed price moves below the lower band, the market is classified as bearish trending
• When price remains between the bands, the market is classified as cyclic
• The magnitude of price's excursion beyond the bands is used to determine trend strength
4. Adaptive Behaviour :
• The smoothing periods and deviation calculations automatically adjust based on the Adaptability setting
• The measured volatility is calculated over a period proportional to the dominant cycle, ensuring the detector works across different timeframes
• Both the center line and the bands adapt dynamically to changing market conditions, making the detector responsive yet stable
This method provides a unique perspective that complements the DCA approach, with the consensus mechanism synthesising insights from both methods.
🌸 --------- USAGE GUIDE --------- 🌸
💮 Starting with Default Settings
The default settings (Normal for Adaptability and Sensitivity, Weighted Decision for Consensus Mode) provide a balanced starting point suitable for most markets and timeframes. Begin by observing how these settings identify regimes in your preferred instruments.
💮 Finding the Optimal Dominant Cycle
The dominant cycle period is a critical parameter. Here are some approaches to finding an appropriate value:
• Start with typical values, usually something around 25 works well
• Visually identify the average distance between significant peaks and troughs
• Experiment with different values and observe which provides the most stable regime identification
• Consider using cycle-finding indicators to help identify the natural rhythm of your market
💮 Adjusting Parameters
• If you notice too many regime changes → Decrease Sensitivity or increase Consensus requirement
• If regime changes seem delayed → Increase Adaptability
• If a trending regime is not detected, the market is automatically assigned to be in a cyclic state
• If you want to see more nuanced regime transitions → Try the "unconstrained" display mode (note that this will not affect the output to other indicators)
💮 Trading Applications
Regime-Specific Strategies:
• Bullish Trending Regime - Use trend-following strategies, trail stops wider, focus on breakouts, consider holding positions longer, and emphasize buying dips
• Bearish Trending Regime - Consider shorts, tighter stops, focus on breakdown points, sell rallies, implement downside protection, and reduce position sizes
• Cyclic Regime - Apply mean-reversion strategies, trade range boundaries, apply oscillators, target definable support/resistance levels, and use profit-taking at extremes
Strategy Switching:
Create a set of rules for each market regime and switch between them based on the detector's signal. This approach can significantly improve performance compared to applying a single strategy across all market conditions.
GYTS Suite Integration:
• In the GYTS 🎼 Order Orchestrator, select the '🔗 STREAM-int 🧊 Market Regime' as the market regime source
• Note that the consensus output (i.e. not the "unconstrained" display) will be used in this stream
• Create different strategies for trending (bullish/bearish) and cyclic regimes. The GYTS 🎼 Order Orchestrator is specifically made for this.
• The output stream is actually very simple, and can possibly be used in indicators and strategies as well. It outputs 1 for bullish, -1 for bearish and 0 for cyclic regime.
🌸 --------- FINAL NOTES --------- 🌸
💮 Development Philosophy
The Market Regime Detector has been developed with several key principles in mind:
1. Robustness - The detection methods have been rigorously tested across diverse markets and timeframes to ensure reliable performance.
2. Adaptability - The detector automatically adjusts to changing market conditions, requiring minimal manual intervention.
3. Complementarity - Each detection method provides a unique perspective, with the collective consensus being more reliable than any individual method.
4. Intuitiveness - Complex technical parameters have been abstracted into easily understood controls.
💮 Ongoing Refinement
The Market Regime Detector is under continuous development. We regularly:
• Fine-tune parameters based on expanded market data
• Research and integrate new detection methodologies
• Optimise computational efficiency for real-time analysis
Your feedback and suggestions are very important in this ongoing refinement process! Indicator
Range Breakout [BigBeluga]Range Breakout is a dynamic channel-based indicator designed to identify breakout opportunities and price reactions within defined ranges. It automatically creates upper and lower bands with a midline, helping traders spot breakout zones, retests, and potential fakeouts.
🔵 Key Features:
Dynamic Channel Formation:
Automatically plots upper and lower channel bands with a midline based on ATR calculations.
Channels adjust upon breakout events or after a predefined number of bars to reflect new price ranges.
Breakout Detection:
Green circles appear when price breaks above the upper channel edge.
Red circles appear when price breaks below the lower channel edge.
A new channel is formed after each breakout, allowing traders to monitor evolving price ranges.
Retest Signals:
Upward-pointing green triangles signal a retest of the lower band, indicating potential support.
Downward-pointing red triangles indicate a retest of the upper band, suggesting possible resistance.
Filter Signals by Trends (New Feature):
Optional toggle to filter ▲ and ▼ signals based on channel breakout conditions.
When enabled:
In a bullish channel (confirmed by a green circle breakout), only ▲ signals are displayed.
In a bearish channel (confirmed by a red circle breakout), only ▼ signals are displayed.
Helps traders align retest signals with the prevailing trend for higher-quality trade setups.
Fakeout Identification:
'X' symbols appear when price breaks the upper or lower edge of the channel and quickly returns back inside.
Helps traders identify and avoid false breakouts.
🔵 Usage:
Breakout Trading: Use the green and red circle signals to identify potential breakout trades.
Retest Confirmation: Look for triangle markers to confirm retests of key levels, aiding in entry or exit decisions.
Fakeout Alerts: Utilize the 'X' signals to spot and avoid potential trap moves.
Dynamic Range Monitoring: Stay aware of changing market conditions with automatically updating channels.
Range Breakout is an essential tool for traders seeking to capitalize on range breakouts, retests, and fakeout scenarios. Its dynamic channels and clear visual signals provide a comprehensive view of market structure and potential trade setups. Indicator
Peak Reaction Zones [BigBeluga]Peak Reaction Zones is an advanced Smart Money Concept (SMC) indicator that identifies the most recent swing high and swing low zones, helping traders determine premium and discount areas for optimal trade positioning.
🔵 Key Features:
Swing High & Low Zones:
Automatically detects the latest swing high and swing low levels.
Helps traders identify key reaction points where price is likely to respond.
Premium & Discount Concept:
The high zone represents a premium area, where price is overextended and may reverse.
The low zone represents a discount area, where price is undervalued and may bounce.
The midline dynamically marks the equilibrium of the range.
Adjustable Zone Width:
Users can fine-tune the width of the zones to match their trading style.
Wider zones capture broader reaction ranges, while narrower zones focus on precise levels.
Zone Retest Signals:
Blue markers appear when price retests the lower reaction zone, signaling potential support.
Orange markers appear when price retests the upper reaction zone, indicating possible resistance.
Price Labels for Key Levels:
Displays the price value of the swing high, swing low, and midline for quick reference.
Helps traders recognize major reaction points at a glance.
🔵 Usage:
Smart Money Trading: Utilize the premium and discount concept to align trades with institutional order flow.
Zone Reactions: Watch for price tests of reaction zones and use the retest signals to confirm potential reversals.
Midline Confirmation: If price holds above or below the midline, it can indicate directional bias.
Scalping & Swing Trading: Short-term traders can look for zone rejections, while swing traders can use the levels for trend continuation setups.
Peak Reaction Zones is a must-have tool for traders looking to trade with Smart Money Concepts, allowing for precise entries and exits based on key liquidity areas and market structure. Indicator
Indicator
Adaptive Range Scalper - KetBotAIThe Adaptive Scalper is designed to dynamically adjust entry, take-profit (TP), and stop-loss (SL) levels based on the latest market price. It combines multiple tools to provide traders with actionable insights, suitable for a range of trading styles and timeframes.
How the Indicator Works
Dynamic Levels:
- Yellow Dotted Line: Represents the entry level, following the latest price dynamically.
- Green Line: The Take Profit (TP) level, calculated as a multiple of the current price, adapts in real-time.
- Red Line: The Stop Loss (SL) level, placed below the price and also dynamically adjusts.
Bollinger Bands:
Provides context for market volatility and potential overbought/oversold zones.
Narrowing bands signal consolidation, while expanding bands indicate increased volatility.
Buy and Sell Signals:
Buy Signal: Triggered when the price crosses above the lower Bollinger Band.
Sell Signal: Triggered when the price crosses below the upper Bollinger Band.
These signals help traders time entries and exits based on momentum shifts.
Risk/Reward Analysis:
Visual shading shows the favorable risk/reward zone between the stop loss and take profit levels.
Timeframe Suggestions
Short-Term Traders (Scalping):
Use on 5-minute to 15-minute charts.
Focus on high-volatility periods for quick entries and exits.
Intraday Traders:
Ideal for 30-minute to 1-hour charts.
Provides more stable signals and less noise.
Swing Traders:
Best suited for 4-hour or daily charts.
Captures broader trends with fewer signals, allowing for larger moves.
Tool Combination
Volume Profile:
Combine with volume-based tools to confirm key support/resistance zones around TP and SL levels.
Trend Indicators:
Use with Moving Averages (e.g., 20-period or 50-period) to identify the broader trend direction.
Example: Only take buy signals in an uptrend and sell signals in a downtrend.
Momentum Oscillators:
Pair with tools like RSI or MACD to avoid entering overbought/oversold conditions.
Support/Resistance Lines:
Manually mark significant levels to confirm alignment with the indicator’s TP and SL zones.
Useful Advice for Traders
Risk Management:
- Always assess the risk/reward ratio; aim for at least 1:2 (risking 1 to gain 2).
- Adjust the multiplier to match your trading style (e.g., higher multiplier for swing trades, lower for scalping).
Avoid Overtrading:
Use the indicator in conjunction with clear rules to avoid false signals during low-volatility periods.
Monitor market volatility:
Pay attention to narrowing Bollinger Bands, which signal consolidations. Avoid trading until a breakout occurs.
Test on Demo Accounts:
Practice using the indicator on a demo account to understand its behavior across different assets and timeframes.
Focus on High-Liquidity Markets:
For the best results, trade highly liquid instruments like major currency pairs, gold, or stock indices.
Summary
The Adaptive Range Indicator dynamically adjusts to market conditions, offering clear entry and exit levels. By combining it with Bollinger Bands and other tools, traders can better navigate market trends and avoid noise. It’s versatile across multiple timeframes and assets, making it a valuable addition to any trader’s toolkit.
Indicator
Indicator
Weighted Average Strength Index (WASI)Weighted Average Strength Index (WASI)
The Weighted Average Strength Index (WASI) is a variation of the standard RSI. It uses the Weighted Moving Average (WMA) instead of the Running Moving Average (RMA), making it more responsive to recent price changes. The hypothesis is that this weighted calculation might better capture momentum shifts, providing traders with more timely insights.
How to Use:
Backtest WASI on your preferred assets and timeframes to evaluate its effectiveness for your strategy.
Use for trend following or mean reversion :
- Overbought/Oversold (OB/OS) levels can signal potential mean-reversion opportunities.
- Midline (50 level) crossovers can be used for trend-following strategies.
- WASI and its moving average (MA) crossovers offer additional trend-following or reversal signals.
Parameters and Their Functions:
WASI Length: Determines the number of periods for WASI calculation. A longer length smooths the indicator but increases lag, while a shorter length makes it more sensitive. (When in doubt, go longer).
Source: The price source for the calculation (e.g., close, open, high, or low).
MA Type: Specifies the type of moving average applied to the WASI (options include SMA, EMA, WMA, HMA, and others).
MA Length: The number of periods for the moving average used on the WASI. Higher will lead to a smoother moving average.
Indicator Features:
Dynamic OB/OS Levels: Default overbought (70) and oversold (30) levels help identify potential reversal zones.
Midline Crossover: WASI crossing above or below the 50 level may indicate a trend shift.
WASI-MA Crossover: Crossovers between WASI and its moving average can signal trend-following or mean-reversion opportunities.
Disclaimer:
This indicator is a tool for analysis and should be used in conjunction with other forms of analysis or confirmation. Past performance does not guarantee future results.
Indicator
Dynamic RSI Mean Reversion StrategyDynamic RSI Mean Reversion Strategy
Overview:
This strategy uses an RSI with ATR-Adjusted OB/OS levels in order to enhance the quality of it's mean reversion trades. It also incorporates a form of trend filtering in an effort to minimize downside and maximize upside. The backtest has fewer trades, as it uses substantial filtering to enhance trade quality. As you can see, I didn't cherry pick the results, so the results aren't the most beautiful thing you'll see in your life. I did this to ensure nobody gets misled. If you need a higher frequency of trades, consider removing the trend filter or increasing the length of the EMAs used for trend detection.
Features:
Dynamic OB/OS Levels: Uses ATR to adjust overbought and oversold thresholds dynamically, making the RSI more responsive in varying volatility conditions. This approach enhances signal strength by expanding the RSI range in high volatility and tightening it in low volatility.
Mean Reversion Focus: Designed for mean reversion but incorporates a trend-following filter to reduce countertrend trades. When the RSI is high, it often indicates an uptrend, so a trend filter prevents shorting in these cases and the same goes for downtrends and longing.
Trend Filtering: A moving average cross trend filter checks for the trend direction, with the RSI signal line color-coded to reflect trend shifts. Entries occur when the RSI crosses above or below the dynamic thresholds and is not a countertrend trade.
Stop Losses: Stop losses are set based on ATR distance from the entry price, providing volatility-adjusted protection.
Note:
If you're using this strategy on assets with a higher price, remember to increase the initial capital in the strategy settings. Otherwise, the strategy won't generate any (or many) trades and you'll end up with some inaccurate results.
Recommended Use:
Test it on different assets and timeframes. I’ve found the best results with standard RSI inputs, a relatively slow ATR, and a slower MA cross for trend filtering. Thus, the defaults are set that way. If the trend metrics are too slow, you’ll filter out too many good trades while allowing crummy ones; if too fast, most trades may be filtered out. As always, this has a lot of configurability so experiment to find the balance that works for your trading style. Strategy
Z-Score RSI StrategyOverview
The Z-Score RSI Indicator is an experimental take on momentum analysis. By applying the Relative Strength Index (RSI) to a Z-score of price data, it measures how far prices deviate from their mean, scaled by standard deviation. This isn’t your traditional use of RSI, which is typically based on price data alone. Nevertheless, this unconventional approach can yield unique insights into market trends and potential reversals.
Theory and Interpretation
The RSI calculates the balance between average gains and losses over a set period, outputting values from 0 to 100. Typically, people look at the overbought or oversold levels to identify momentum extremes that might be likely to lead to a reversal. However, I’ve often found that RSI can be effective for trend-following when observing the crossover of its moving average with the midline or the crossover of the RSI with its own moving average. These crossovers can provide useful trend signals in various market conditions.
By combining RSI with a Z-score of price, this indicator estimates the relative strength of the price’s distance from its mean. Positive Z-score trends may signal a potential for higher-than-average prices in the near future (scaled by the standard deviation), while negative trends suggest the opposite. Essentially, when the Z-Score RSI indicates a trend, it reflects that the Z-score (the distance between the average and current price) is likely to continue moving in the trend’s direction. Generally, this signals a potential price movement, though it’s important to note that this could also occur if there’s a shift in the mean or standard deviation, rather than a meaningful change in price itself.
While the Z-Score RSI could be an insightful addition to a comprehensive trading system, it should be interpreted carefully. Mean shifts may validate the indicator’s predictions without necessarily indicating any notable price change, meaning it’s best used in tandem with other indicators or strategies.
Recommendations
Before putting this indicator to use, conduct thorough backtesting and avoid overfitting. The added parameters allow fine-tuning to fit various assets, but be careful not to optimize purely for the highest historical returns. Doing so may create an overly tailored strategy that performs well in backtests but fails in live markets. Keep it balanced and look for robust performance across multiple scenarios, as overfitting is likely to lead to disappointing real-world results. Strategy
Indicator
Jurik Price Bands and Range Box [BigBeluga]Jurik Price Bands and Range Box
The Jurik Price Bands and Range Box - BigBeluga indicator is an advanced technical analysis tool that combines Jurik Moving Average (JMA) based price bands with a dynamic range box. This versatile indicator is designed to help traders identify trends, potential reversal points, and price ranges over a specified period.
🔵 KEY FEATURES
● Jurik Price Bands
Utilizes Jurik Moving Average for smoother, more responsive bands
//@function Calculates Jurik Moving Average
//@param src (float) Source series
//@param len (int) Length parameter
//@param ph (int) Phase parameter
//@returns (float) Jurik Moving Average value
jma(src, len, ph) =>
var float jma = na
var float e0 = 0.0
var float e1 = 0.0
var float e2 = 0.0
phaseRatio = ph < -100 ? 0.5 : ph > 100 ? 2.5 : ph / 100 + 1.5
beta = 0.45 * (len - 1) / (0.45 * (len - 1) + 2)
alpha = math.pow(beta, phaseRatio)
e0 := (1 - alpha) * src + alpha * nz(e0 )
e1 := (src - e0) * (1 - beta) + beta * nz(e1 )
e2 := (e0 + phaseRatio * e1 - nz(jma )) * math.pow(1 - alpha, 2) + math.pow(alpha, 2) * nz(e2 )
jma := e2 + nz(jma )
jma
Consists of an upper band, lower band, and a smooth price line
Bands adapt to market volatility using Jurik MA on ATR
Helps identify potential trend reversal points and overextended market conditions
● Dynamic Range Box
Displays a box representing the price range over a specified period
Calculates high, low, and mid-range prices
Option for adaptive mid-range calculation based on average price
Provides visual representation of recent price action and volatility
● Price Position Indicator
Shows current price position relative to the mid-range
Displays percentage difference from mid-range
Color-coded for quick trend identification
● Dashboard
Displays key information including current price, range high, mid, and low
Shows trend direction based on price position relative to mid-range
Provides at-a-glance market context
🔵 HOW TO USE
● Trend Identification
Use the middle of the Range Box as the primary trend reference point
Price above the middle of the Range Box indicates an uptrend
Price below the middle of the Range Box indicates a downtrend
The bar on the right shows the percentage distance of the close from the middle of the box
This percentage indicates both trend direction and strength
Refer to the dashboard for quick trend direction confirmation
● Potential Reversal Points
Upper and lower Jurik Bands can indicate potential trend reversal points
Price reaching or exceeding these bands may suggest overextended conditions
Watch for price reaction at these levels for possible trend shifts or pullbacks
Range Box high and low can serve as additional reference points for price action
● Range Analysis
Use Range Box to gauge recent price volatility and trading range
Mid-range line can act as a pivot point for short-term price movements
Percentage difference from mid-range helps quantify price position strength
🔵 CUSTOMIZATION
The Jurik Price Bands and Range Box indicator offers several customization options:
Adjust Range Box length for different timeframe analysis
Toggle between standard and adaptive mid-range calculation
Standard:
Adaptive:
Modify Jurik MA length and deviation for band calculation
Toggle visibility of Jurik Bands
By fine-tuning these settings, traders can adapt the indicator to various market conditions and personal trading strategies.
The Jurik Price Bands and Range Box indicator provides a multi-faceted approach to market analysis, combining trend identification, potential reversal point detection, and range analysis in one comprehensive tool. The use of Jurik Moving Average offers a smoother, more responsive alternative to traditional moving averages, potentially providing more accurate signals.
This indicator can be particularly useful for traders looking to understand market context quickly, identify potential reversal points, and assess current market volatility. The combination of dynamic bands, range analysis, and the informative dashboard provides traders with a rich set of data points to inform their trading decisions.
As with all technical indicators, it's recommended to use the Jurik Price Bands and Range Box in conjunction with other forms of analysis and within the context of a well-defined trading strategy. While this indicator provides valuable insights, it should be considered alongside other factors such as overall market conditions, volume, and fundamental analysis when making trading decisions. Indicator
RSI K-Means Clustering [UAlgo]The "RSI K-Means Clustering " indicator is a technical analysis tool that combines the Relative Strength Index (RSI) with K-means clustering techniques. This approach aims to provide more nuanced insights into market conditions by categorizing RSI values into overbought, neutral, and oversold clusters.
The indicator adjusts these clusters dynamically based on historical RSI data, allowing for more adaptive and responsive thresholds compared to traditional fixed levels. By leveraging K-means clustering, the indicator identifies patterns in RSI behavior, which can help traders make more informed decisions regarding market trends and potential reversals.
🔶 Key Features
K-means Clustering: The indicator employs K-means clustering, an unsupervised machine learning technique, to dynamically determine overbought, neutral, and oversold levels based on historical RSI data.
User-Defined Inputs: You can customize various aspects of the indicator's behavior, including:
RSI Source: Select the data source used for RSI calculation (e.g., closing price).
RSI Length: Define the period length for RSI calculation.
Training Data Size: Specify the number of historical RSI values used for K-means clustering.
Number of K-means Iterations: Set the number of iterations performed by the K-means algorithm to refine cluster centers.
Overbought/Neutral/Oversold Levels: You can define initial values for these levels, which will be further optimized through K-means clustering.
Alerts: The indicator can generate alerts for various events, including:
Trend Crossovers: Alerts for when the RSI crosses above/below the neutral zone, signaling potential trend changes.
Overbought/Oversold: Alerts when the RSI reaches the dynamically determined overbought or oversold thresholds.
Reversals: Alerts for potential trend reversals based on RSI crossing above/below the calculated overbought/oversold levels.
RSI Classification: Alerts based on the current RSI classification (ranging, uptrend, downtrend).
🔶 Interpreting Indicator
Adjusted RSI Value: The primary plot represents the adjusted RSI value, calculated based on the relative position of the current RSI compared to dynamically adjusted overbought and oversold levels. This value provides an intuitive measure of the market's momentum. The final overbought, neutral, and oversold levels are determined by K-means clustering and are displayed as horizontal lines. These levels serve as dynamic support and resistance points, indicating potential reversal zones.
Classification Symbols : The "RSI K-Means Clustering " indicator uses specific symbols to classify the current market condition based on the position of the RSI value relative to dynamically determined clusters. These symbols provide a quick visual reference to help traders understand the prevailing market sentiment. Here's a detailed explanation of each classification symbol:
Ranging Classification ("R")
This symbol appears when the RSI value is closest to the neutral threshold compared to the overbought or oversold thresholds. It indicates a ranging market, where the price is moving sideways without a clear trend direction. In this state, neither buyers nor sellers are in control, suggesting a period of consolidation or indecision. This is often seen as a time to wait for a breakout or reversal signal before taking a position.
Up-Trend Classification ("↑")
The up-trend symbol, represented by an upward arrow, is displayed when the RSI value is closer to the overbought threshold than to the neutral or oversold thresholds. This classification suggests that the market is in a bullish phase, with buying pressure outweighing selling pressure. Traders may consider this as a signal to enter or hold long positions, as the price is likely to continue rising until the market reaches an overbought condition.
Down-Trend Classification ("↓")
The down-trend symbol, depicted by a downward arrow, appears when the RSI value is nearest to the oversold threshold. This indicates a bearish market condition, where selling pressure dominates. The market is likely experiencing a downward movement, and traders might view this as an opportunity to enter or hold short positions. This symbol serves as a warning of potential further declines, especially if the RSI continues to move toward the oversold level.
Bullish Reversal ("▲")
This signal occurs when the RSI value crosses above the oversold threshold. It indicates a potential shift from a downtrend to an uptrend, suggesting that the market may start to move higher. Traders might use this signal as an opportunity to enter long positions.
Bearish Reversal ("▼")
This signal appears when the RSI value crosses below the overbought threshold. It suggests a possible transition from an uptrend to a downtrend, indicating that the market may begin to decline. This signal can alert traders to consider entering short positions or taking profits on long positions.
These classification symbols are plotted near the adjusted RSI line, with their positions adjusted based on the standard deviation and a distance multiplier. This placement helps in visualizing the classification's strength and ensuring clarity in the indicator's presentation. By monitoring these symbols, traders can quickly assess the market's state and make more informed trading decisions.
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results. Indicator
Indicator
Range Average Retest Model [LuxAlgo]The Range Average Retest Model tool highlights setups from the range average retest entry model, a model using the retest of the average between two opposite swing points as an entry.
This tool uses long-term volatility coupled with user-defined multipliers to filter out swing areas and set take profit and stop loss levels for all trades.
Key features include:
Draw up to 165 swing areas and their associated trades
Filter out swing areas using Pivot Length , Selection Mode and Threshold parameters
Filter out trades with Maximum Distance and Minimum Distance parameters
Enable or disable swing areas and select default colors
Enable or disable overlapping trades and change the default colors for Take Profit and Stop Loss zones
🔶 USAGE
The "Range Average Retest Model" is an entry model that enters a position when the price retests the average made between two swing points. Users can determine the period of the detected swing points from the "Pivot Length" setting.
The conditions for long or short trades, regardless of whether the swing area is bullish or bearish, are as follows:
Long positions: the current bar close is below the swing area average and the last bar close was above it.
Short positions: the current bar close is above the swing area average price and the last bar close was below it.
Each trade is displayed on the chart with a line connecting it to its swing area highlighting the range average, a green area for the take profit, and a red area for the stop loss.
Both the Take Profit and Stop Loss levels are calculated by applying your own multiplier in the settings panel to the long-term volatility measure, in this case, the average true range over the last 200 bars.
Trades will remain open until they reach either the Stop Loss or Take Profit price levels.
🔹 Filtering Swing Areas
The daily chart of the Nasdaq-100 futures (NQ) with pivot length 2 and bullish selection mode: it only detects bullish swing areas, but they are smaller and more numerous.
Traders can manipulate the behavior of the swing areas from the settings panel.
The Selection mode will filter areas by bias: it will detect bullish areas, bearish areas, or both.
The Threshold parameter is applied to the long-term volatility to filter out areas where the average prices are too close together; the higher the value, the greater the difference between the average prices must be.
🔹 Trades
3-minute chart of the Nasdaq-100 futures (NQ) with pivot length 5, bearish selection mode maximum distance 4, and stop loss 2: many trades detected with very asymmetric risk/reward.
The behavior of the trades is also manipulated from the settings panel.
The maximum and minimum distance parameters specify the number of bars a trade must be away from a swing area.
The Take Profit and Stop Loss parameters are applied to the long-term volatility to obtain their respective price levels.
🔹 Overlapping Trades
Same chart as before, but with overlapping trades: messy, right?
By default the tool does not show overlapping trades, this allows for a cleaner chart.
In the settings panel traders can enable overlapping mode, in which case the tool will show all available trades.
Traders must be aware that the chart can be very crowded.
🔶 SETTINGS
🔹 Swings
Pivot Length: How many bars are used to confirm a swing point. The larger this parameter is, the larger and fewer swing areas will be detected.
Selection Mode: Swing area detection mode, detect only bullish swings, only bearish swings, or both.
Threshold: Swing area comparator. This threshold is multiplied by a measure of volatility (average true range over the last 200 bars), for a new swing area to be detected it must have an average level that is sufficiently distant from the average level of any untouched swing area, this parameter controls that distance.
🔹 Trades
Maximum distance: Maximum distance allowed between a swing area and a trade.
Minimum distance: Minimum distance allowed between a swing area and a trade.
Take profit: The size of the take profit - this threshold is multiplied by a measure of volatility (the average true range over the last 200 bars).
Stop loss: The size of the stop-loss: this threshold is multiplied by a measure of volatility (the average true range over the last 200 bars).
Indicator
Megabar Breakout (Range & Volume & RSI)Hey there,
This strategy is based on the idea that certain events lead to what are called Megabars. Megabars are bars that have a very large range and volume. I wanted to verify whether these bars indicate the start of a trend and whether one should follow the trend.
Summary of the Code:
The code is based on three indicators: the range of the bar, the volume of the bar, and the RSI. When certain values of these indicators are met, a Megabar is identified. The direction of the Megabar indicates the direction in which we should trade.
Why do I combine these indicators?
I want to identify special bars that have the potential to mark the beginning of a breakout. Therefore, a bar needs to exhibit high volume, have a large range (huge price movement), and we also use the Relative Strength Index (RSI) to assess potential momentum. Only if all three criteria are met within one candle, do we use this as an identifier for a megabar.
Explanation of Drawings on the Chart:
As you can see, there is a green background on my chart. The green background symbolizes the time when I'm entering a trade. Only if a Megabar happens during that time, I'm ready to enter a trade. The time is between 6 AM and 4 PM CET. It's just because I prefer that time. Also, the strategy draws an error every time a Megabar happens based on VOL and Range only (not on the RSI). That makes it pretty easy to go through your chart and check the biggest bars manually. You can activate or deactivate these settings via the input data of the strategy.
When Do We Enter a Trade?
We wait for a Megabar to happen during our trading session. If the Megabar is bullish, we open a LONG trade at the opening price of the next candle. If the Megabar is bearish, we open a SHORT trade at the opening price of the next candle.
Where Do We Put Our Take Profit & Stop Loss?
The default setting is TP = 40 Pips and SL = 30 Pips. In that case, we are always trading with a risk-reward ratio of 1.33 by default. You can easily change these settings via the input data of the strategy.
Strategy Results
The criteria for Megabars were chosen by me in a way that makes Megabars something special. They are not intended to occur too frequently, as the fundamental idea of this strategy would otherwise not hold. This results in only 37 closed trades within the last 12 months. If you change the criterias for a megabar to a milder one, you will create more Megabars and therefore more trades. It's up to you. I have adapted this strategy to the 30-minute chart of the EURUSD. In the evaluation, we consider a period of 12 months, which I believe is sufficient.
My default settings for the indicators look like this:
Avg Length Vol 20
Avg Multiplier Vol 3
Avg Length Range 20
Avg Multiplier Range 4
Value SMA RSI for Long Trades 50
Value SMA RSI for Short Trades 70
IMPORTANT: The current performance overview does not display the results of these settings. Please change the settings to my default ones so that you can see how I use this strategy.
I do not recommend trading this strategy without further testing. The script is meant to reflect a basic idea and be used as a tool to identify Megabars. I have made this strategy completely public so that it can be further developed. One can take this framework and test it on different timeframes and different markets. Strategy
Monday range by MatboomThe "Monday Range" Pine Script indicator calculates and displays the lowest and highest prices during a specified trading session, focusing on Mondays. Users can configure the trading session parameters, such as start and end times and time zone. The indicator visually highlights the session range on the chart by plotting the session low and high prices and applying a background color within the session period. The customizable days of the week checkboxes allow users to choose which days the indicator should consider for analysis.
Session Configuration:
session = input.session("0000-0000", title="Trading Session")
timeZone = input.string("UTC", title="Time Zone")
monSession = input.bool(true, title="Mon ", group="Trading Session", inline="d1")
tueSession = input.bool(true, title="Tue ", group="Trading Session", inline="d1")
Users can configure the trading session start and end times and the time zone.
Checkboxes for Monday (monSession) and Tuesday (tueSession) sessions are provided.
SessionLow and SessionHigh Functions:
SessionLow(sessionTime, sessionTimeZone=syminfo.timezone) => ...
SessionHigh(sessionTime, sessionTimeZone=syminfo.timezone) => ...
Custom functions to calculate the lowest (SessionLow) and highest (SessionHigh) prices during a specified trading session.
InSession Function:
InSession(sessionTimes, sessionTimeZone=syminfo.timezone) => ...
Determines if the current bar is inside the specified trading session.
Days of Week String and Session String:
sessionDays = ""
if monSession
sessionDays += "2"
if tueSession
sessionDays += "3"
tradingSession = session + ":" + sessionDays
Constructs a string representing the selected days of the week for the session.
Fetch Session Low and High:
sessLow = SessionLow(tradingSession, timeZone)
sessHigh = SessionHigh(tradingSession, timeZone)
Calls the custom functions to obtain the session low and high prices.
Plot Session Low and High and Background Color for Session
plot(sessLow, color=color.red, title="Session Low")
plot(sessHigh, color=color.red, title="Session Low")
bgcolor(InSession(tradingSession, timeZone) ? color.new(color.aqua, 90) : na)
Indicator
Easy To Trade indicatorAbstract
This script evaluates how easy for traders to trade.
This script computes the level that the gains were distributed in many trading days.
We can use this indicator to decide the instruments and the time we trade.
Introduction
Why we think the trading markets are boring?
It is because most of the gains were concentrated in a few trading days.
We look for instruments we can buy at support and sell at resistance frequently and repeatedly.
However, it does not happen usually because it is difficult to find sellers sell at support and buyers buy at resistance.
This script is a method to measure if an instrument is difficult to trade.
If most of the gains were concentrated in a few trading days, this script says it is difficult to trade.
If gains were distributed in many trading days and we can buy low and sell high repeatedly, this script says it is easy to trade.
Therefore, this script measure how difficult for us to trade by the ratio between the area of value and the total gain.
How it works
1. Determine the instruments and time frames we are interested in.
2. Determine how many days this script evaluate the result. This number may depend on how many days from you buy in to you sell out.
3. If the instrument you choose is easy to trade, this script reports higher values.
4. If the instrument is long term bullish, the number "easy to invest" is usually higher than the number "easy to short" .
5. We can consider trade instruments which are easier to trade than others.
6. We can consider wait until the period that it is difficult to trade has past or keep believing that some instruments are easier to trade than others.
Parameters
x_src = The price for each trading day this script use. It may be open , high , low , close or their combination.
x_is_exp = Whether this script evaluate the price movement in exponential or logarithm. You are advised to answer yes if the price changes drastically.
x_period = How many days this script evaluate the result.
Conclusion
With this indicator , we have data to explain how easy or difficult an instrument is for traders . In other words , if we hear some people say the trading markets are boring or difficult for traders , we can use this indicator to verify how accurate their comments are.
With this explainable analysis , we have more knowledge about which instruments and which sessions are relative easy for us to buy low and sell high repeatedly and frequently , we can have better proceeding than buy and hold simply. Indicator
Indicator
