Indicator
Regime Quadrant Map [XWiseTrade]Most "regime" indicators sort the market into two boxes: trending or ranging. But that single axis hides the variable that actually decides whether a trend is tradeable - volatility. A market drifting up in dead-calm conditions and a market ripping up in violent conditions are both "trending," yet they demand opposite tactics. Collapsing them into one label is why so many trend filters fail exactly when you lean on them. This indicator separates the two questions that a one-dimensional filter fuses together, and maps the result onto four regimes instead of two.
WHY VOLATILITY IS MEASURED AS AN ATR Z-SCORE, NOT RAW ATR
Raw ATR tells you nothing on its own - an ATR of 15 is enormous on one instrument and trivial on another, and huge in one era and small in the next. What matters is whether volatility is unusually high or low relative to this market's own recent behaviour. So ATR here is ranked against its own distribution over a lookback window and expressed as a Z-score: how many standard deviations above or below its own norm current volatility sits. That makes the reading self-referential and comparable across any symbol or timeframe, instead of an absolute number you'd have to re-learn for every chart.
WHY TREND IS MEASURED WITH EFFICIENCY RATIO, NOT A MOVING-AVERAGE SLOPE
A rising moving average tells you price is higher than it was - it does not tell you how price got there. Efficiency Ratio does: it divides the net directional move by the total distance price actually travelled to make it. A value near 1 means a clean, purposeful move; near 0 means price thrashed back and forth to end up in nearly the same place. Two charts with an identical slope can have completely different efficiency, and that difference - not the slope - is what separates a trend you can ride from a trap. Slope measures result; Efficiency Ratio measures quality.
THE FOUR QUADRANTS
Crossing the two axes gives four regimes, each with a distinct character:
- GRIND (trending + low volatility) - a steady, efficient directional move; the kind you can lean into.
- EXPANSION (trending + high volatility) - a violent directional move; momentum conditions, wider risk.
- COIL (ranging + low volatility) - compression; energy building, often ahead of a breakout.
- CHOP (ranging + high volatility) - whipsaw with no follow-through; the regime most accounts quietly bleed in.
HOW TO USE IT
Watch the regime label and background tint for the current quadrant, or read the two plotted lines directly against their dashed thresholds - the ATR Z-score line for the volatility axis, the Efficiency Ratio line for the trend axis. Both thresholds and both lookbacks are adjustable, so you can set what counts as "high volatility" or "trending" for your own instrument and timeframe. An alert fires whenever the market crosses into a new quadrant, so you don't have to watch it to know the regime shifted.
WHAT MAKES IT DIFFERENT
Standard regime tools reduce the market to a single trend-versus-range line and treat volatility as an afterthought. This one builds regime from two independent axes, measures volatility as a self-referential Z-score rather than an absolute number, measures trend by path efficiency rather than slope, and resolves the market into four actionable states instead of two - because "trending" alone was never enough to decide how to trade it.
These are descriptive regime classifications for discretionary use, not buy/sell signals. Indicator
Market Regime LensMarket Regime Lens
Market Regime Lens reads the market on four independent axes and gives you one honest sentence about the current tape. It is a context descriptor, not a signal — it never tells you which way to trade. It tells you whether the tape is readable, how it moves, how long things take, and how risk is arriving.
WHY FOUR AXES, ONE COMPONENT EACH
Most multi-indicator tools stack measures that secretly say the same thing — three complexity metrics agreeing is not confirmation, it is autocorrelation. This tool deliberately uses one component per independent axis, so each number tells you something the others cannot.
STRUCTURE — Complexity-Entropy plane. Bandt-Pompe permutation entropy paired with Martin-Plastino-Rosso statistical complexity, classifying the tape as structured, mixed, or noise. Thresholds are adaptive by default: the reading is ranked against the instrument's own recent range, so it self-calibrates to any market and timeframe instead of relying on absolute cutoffs that break when you change the window.
PERSISTENCE — Anomalous-diffusion exponent. Fitted from mean-squared-displacement scaling across lags: alpha above 1 means super-diffusive (trending), alpha near 1 is a random walk, alpha below 1 is sub-diffusive (mean-reverting). This describes the character of the motion, not its direction.
TIME — First passage and null odds. Expected bars to reach the target versus the stop under a driftless diffusion, plus the null barrier probability P = b/(a+b) — what a coin flip gives you at your chosen reward-to-risk. At 1.5R that is 40%. That is the breakeven any setup must clear, stated plainly.
TAIL — Extremal index. Measures whether extreme moves cluster (theta below 1) or arrive independently. Clustered tails mean gap risk shows up in bursts, which matters for stop placement.
ON THE CHART
The main line is the diffusion exponent, colored by state and filled against the alpha = 1 random-walk baseline, so deviation from randomness is visible at a glance. Faint guides mark the trending and reverting thresholds. Background tint shows the structure class. The panel adapts to your chart theme and colors each row by meaning — including green or amber on the null-odds row depending on whether your chosen R gives better-than-even odds.
PAIRS WITH RISK & LEVELS COCKPIT
Optionally wire the target and stop sources to the Cockpit's exported levels, and the timing and null-probability rows use your real trade levels instead of internal ATR references.
WORKS ON ANY MARKET AND TIMEFRAME
All lookbacks are in bars with no session, expiry, or clock anchors. Non-repainting: everything uses the current bar's data and confirms at close.
LIMITATIONS
Not a signal and not investment advice — no axis forecasts direction. Permutation entropy and complexity require a window much larger than d factorial; at dimension 4 use at least 300 bars, since short windows are undersampling-biased and pin to a constant. Adaptive thresholds classify relative to the instrument's own recent range, so "structured" means structured for this market lately, not in any absolute sense. First-passage times and the null probability assume driftless diffusion with constant volatility — a deliberate null baseline, not a forecast. The extremal index needs enough exceedances; too short a window pins it at 1.00.
CREDITS
Original implementation. Bandt and Pompe permutation entropy; Martin-Plastino-Rosso and Lopez-Ruiz statistical complexity via Jensen-Shannon divergence; anomalous-diffusion MSD scaling; Ferro-Segers runs estimator for the extremal index; first-passage-time and gambler's-ruin barrier theory. Indicator
Market Regime & Risk DashboardAn analytics and risk dashboard. It tells you what state the market is in and how much to risk. It does NOT generate buy or sell signals and makes no claim of edge.
What it shows
- Volatility regime: realized volatility bucketed by its own percentile history (Low / Normal / High / Extreme)
- Realized volatility and its percentile rank
- Trend regime: Kaufman Efficiency Ratio bucketed into Trending / Mixed / Choppy
- ATR % of price, an ATR-based stop distance, and a fixed-fractional position size for your chosen risk percent
- Drawdown from the recent high
How to read it
Volatility regime drives position sizing: in Extreme regimes the same percent risk implies a far smaller position, and the dashboard does that maths for you. The trend regime is descriptive, not predictive.
Honest by design
- No buy/sell signals, no alpha claim. This is a measurement tool, not a prediction.
- Non-repainting: every value is a function of confirmed closes, no request.security, no future data. The current forming bar updates in real time, which is normal, not historical repaint.
- Every number is defined, with its limitations stated.
Open-source and MIT licensed.
Disclaimer: impersonal educational and analytics tool. This is not investment advice, not a personalised recommendation, and carries no performance guarantee. Past results do not predict future results. You are solely responsible for your own trading decisions. Indicator
Elaris Market Energy [Professional]Elaris Market Energy
Overview
Elaris Market Energy is a multi-factor oscillator designed to evaluate the strength, direction, participation, and sustainability of market movement.
Rather than relying on a single momentum calculation, the indicator combines several independent market characteristics into one normalized energy score. The goal is to help traders distinguish between weak price movement, developing participation, strong directional expansion, compression, and potential exhaustion.
The Market Energy score is displayed in a separate oscillator panel and generally ranges from -100 to +100.
* Positive values represent bullish market energy.
* Negative values represent bearish market energy.
* Values near zero represent neutral conditions, weak participation, or market compression.
This indicator is intended to support market analysis and confirmation. It is not presented as a complete trading system and does not guarantee future price movement.
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Core Market Energy Model
The final Market Energy score is calculated from six configurable components.
Price Impulse
Measures directional price displacement relative to current market volatility.
This helps distinguish meaningful movement from ordinary price fluctuations.
Candle Conviction
Evaluates the structure of the current candle using:
* Candle body size
* Closing position inside the candle range
* Upper and lower wick balance
* Bullish or bearish candle direction
A strong directional candle generally contributes more energy than an indecisive candle.
Volume Participation
Compares current volume with its recent average and evaluates whether market participation supports the current directional move.
On symbols where volume data is unavailable or limited, the volume component may provide less information.
Range Expansion
Measures whether the current true range is expanding relative to recent market activity.
Range expansion can help identify periods where volatility and directional participation are increasing together.
Trend Alignment
Evaluates:
* Price position relative to an internal trend average
* Direction and slope of the trend average
* Alignment between current movement and broader market direction
This component helps reduce the influence of momentum that is moving against the prevailing trend structure.
Momentum Efficiency
Combines directional momentum with movement efficiency.
Movement efficiency compares the net price displacement with the total distance traveled. Cleaner directional movement generally produces a stronger reading than unstable or highly overlapping price action.
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Directional Movement Confirmation
The indicator also uses Directional Movement Index information.
The relationship between positive and negative directional movement helps confirm whether bullish or bearish pressure is dominant.
ADX is used as a supporting measurement of trend strength. It does not independently determine the Market Energy score and is applied as a controlled confirmation component.
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Market Regimes
The indicator classifies market conditions into several practical regimes.
Compression
Market Energy remains close to zero, suggesting limited directional participation or reduced momentum.
Compression can occur during consolidation, low volatility, or periods of market indecision.
Bullish or Bearish Energy
Directional participation is developing, but the movement has not yet reached the strong-energy threshold.
Strong Bullish or Bearish Energy
Multiple components are aligned and directional participation has increased.
These conditions may support continuation analysis when confirmed by price structure.
Extreme Energy
The oscillator has reached an unusually strong directional reading.
Extreme energy can represent:
* Strong continuation
* Rapid volatility expansion
* Late-stage momentum
* A condition that may eventually transition into exhaustion
An extreme reading should not automatically be interpreted as a reversal signal.
Fading Energy
Directional energy remains elevated but is beginning to weaken.
Fading energy may indicate reduced participation, consolidation, or potential exhaustion. Price confirmation remains important.
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Signal Types
Bullish Energy Entry
A bullish signal may appear when:
* Market Energy crosses above the selected entry threshold
* Energy is above its signal line
* Energy acceleration is positive
* Enabled trend and directional filters are satisfied
* Optional volume and candle-quality filters are satisfied
Bearish Energy Entry
A bearish signal uses the opposite conditions:
* Market Energy crosses below the negative entry threshold
* Energy is below its signal line
* Energy acceleration is negative
* Enabled bearish filters are satisfied
Compression Release
Compression-release markers identify a transition from low-energy conditions into directional expansion.
These signals are intended to highlight developing volatility and participation after a compressed market phase.
Energy Exhaustion
Exhaustion markers identify situations where:
* Energy recently reached an extreme level
* The energy score begins to decline
* Energy acceleration turns against the previous direction
* Price begins showing an opposing reaction
Exhaustion markers are warnings of weakening momentum. They do not confirm a complete trend reversal on their own.
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Visual Elements
Energy Histogram
The histogram displays both direction and intensity.
* Bullish columns represent positive energy.
* Bearish columns represent negative energy.
* Stronger opacity represents increasing directional intensity.
* Faded columns indicate weakening energy.
Energy Line
The main line shows the smoothed composite Market Energy score.
Signal Line
The signal line provides a slower reference for identifying changes in short-term energy direction.
Energy Cloud
The cloud between the Energy line and Signal line provides a quick visual representation of bullish or bearish energy alignment.
Regime Background
Optional background shading highlights:
* Strong bullish conditions
* Strong bearish conditions
* Market compression
Dashboard
The optional dashboard summarizes:
* Current Market Energy score
* Current market regime
* Energy acceleration
* Relative volume
* ADX
* Price impulse
* Candle conviction
* Volume pressure
* Range expansion
* Trend alignment
* Momentum efficiency
* Signal confirmation mode
The dashboard is intended to provide a quick overview without requiring the trader to interpret each internal calculation separately.
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Calculation Profiles
Fast
Uses shorter internal calculation lengths.
This profile reacts more quickly but may also produce more frequent changes and additional noise.
It may be suitable for lower-timeframe analysis when combined with strict filters.
Balanced
Provides a middle ground between responsiveness and stability.
This is the default profile and is suitable as a general starting point.
Conservative
Uses longer calculation lengths.
This profile produces slower and generally more stable readings, which may be useful on higher timeframes or when fewer signals are preferred.
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Suggested Usage
The indicator can be used for several types of market analysis.
Trend Confirmation
Bullish price structure combined with positive and increasing Market Energy may support bullish continuation analysis.
Bearish price structure combined with negative and decreasing Market Energy may support bearish continuation analysis.
Breakout Confirmation
A breakout accompanied by:
* Range expansion
* Increased relative volume
* Strong impulse
* Rising Market Energy
may have greater participation than a breakout occurring during weak or compressed energy.
Pullback Analysis
During a broader trend, temporary energy weakness followed by renewed directional acceleration may help identify continuation conditions.
Compression Monitoring
Low absolute Market Energy can help identify markets that are consolidating or losing directional participation.
A later compression release may highlight the start of renewed expansion.
Exhaustion Monitoring
Extreme energy followed by weakening acceleration may help traders identify when a mature move is losing participation.
This should be combined with price structure, support and resistance, liquidity levels, or other confirmation methods.
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Recommended Starting Settings
For lower timeframes, traders may consider:
* Fast or Balanced profile
* Higher entry threshold
* Volume filter enabled
* Candle-quality filter enabled
* Candle-close confirmation enabled
For medium timeframes, the Balanced profile and default settings provide a practical starting point.
For higher timeframes, the Conservative profile may provide smoother regime identification and fewer short-term fluctuations.
Settings should be adjusted based on the symbol, timeframe, liquidity, and trading approach.
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Alerts
The script includes alert conditions for:
* Bullish Energy Entry
* Bearish Energy Entry
* Bullish Compression Release
* Bearish Compression Release
* Bullish Energy Exhaustion
* Bearish Energy Exhaustion
* Strong Bullish Regime
* Strong Bearish Regime
* Energy Compression
For stable alerts, enabling candle-close confirmation and selecting “Once Per Bar Close” when creating the PulseWire alert is recommended.
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Repainting Information
Elaris Market Energy does not use future data, lookahead logic, or future-confirmed pivot calculations.
The indicator does not repaint historical closed-bar signals when candle-close confirmation is enabled.
The live Market Energy value may change while the current candle is still forming because price, volume, candle range, and volatility are still changing.
When “Confirm Signals On Candle Close” is enabled, signals are only confirmed after the candle closes.
When this setting is disabled, signals may appear during an open candle and may disappear before that candle closes.
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Important Notes
This indicator is a technical analysis tool and should not be interpreted as financial advice.
Market Energy measures current and historical market conditions. It does not predict future results with certainty.
Signal performance can vary significantly across:
* Symbols
* Asset classes
* Timeframes
* Volatility conditions
* Liquidity environments
* Trending and ranging markets
Traders should use appropriate risk management and independently evaluate all trading decisions.
Indicator
Regime Classifier [RC Tools]RC Tools — Regime Classifier
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█ OVERVIEW
Most indicators assume a single market condition and quietly fail in another. This tool doesn't generate signals — it tells you which of four market regimes you are currently in, so you can judge whether your existing tools are operating in conditions that suit them. It is a context tool, not a decision tool.
█ WHAT IT DOES
Classifies each confirmed bar into one of four states and colours the chart background accordingly:
• Trending — Expansion: directional, volatility rising
• Trending — Exhaustion: directional, volatility compressing
• Ranging — Quiet: no direction, low volatility
• Ranging — Volatile: no direction, high volatility (chop)
A table (top-right by default, repositionable) shows the current regime, how long price has been in it, and historical base rates — the average forward return and win rate seen after each regime, going back over the chart's full history.
█ THE THEORY BEHIND IT
Market behaviour is not stationary. A trend-following tool that performs well in directional expansion will bleed in volatile chop; a mean-reversion tool does the reverse. Rather than attempting to fix any single indicator, this tool identifies which environment you are in, using two independent dimensions — directionality and volatility state — that measure genuinely different properties of price behaviour rather than two correlated views of the same one.
█ HOW IT IS CALCULATED
DIRECTIONALITY — Efficiency Ratio over N bars:
ER = |close − close | ÷ Σ|close − close |
Bounded 0–1. A value near 1 means price travelled almost directly from A to B (trending); near 0 means it wandered (ranging). No fitted parameters beyond the lookback. The Efficiency Ratio was introduced by Perry Kaufman as the core input to his Adaptive Moving Average (KAMA); it is used here purely as a directionality measure, independent of any moving average.
VOLATILITY STATE — realised volatility, percentile-ranked:
RV = stdev(log(close/close ), N)
RV is then ranked as a percentile against its own trailing distribution (default: 750 bars, ≈3 years on daily). An absolute volatility threshold is meaningless across assets — percentile ranking makes the classification behave identically on BTC, gold and equities with no parameter tuning.
The two dimensions are crossed to yield the four states. Classification occurs ONLY on confirmed bar close — the background never updates mid-bar and then flips back.
The base-rate table works by recording, for every historical bar, the forward N-bar return and whether it was positive, attributed back to whichever regime was active N bars earlier. Only fully-elapsed, already-known returns are used — nothing is looked up ahead of the current bar.
█ SETTINGS & CONFIGURATION
• Efficiency Ratio Lookback (default 20) — shorter = more responsive, noisier
• Realised Volatility Lookback (default 20)
• Percentile Ranking Window (default 750 bars ≈ 3 years daily) — longer = more stable, needs more history
• Directionality Threshold (default 0.35) — the ER above which price is considered trending
• Volatility Percentile Threshold (default 50) — the split between low and high volatility states
• Forward Return Window (default 20 bars) — the horizon used for the base-rate table
• Table position and background colours are fully configurable; the main-chart background painting can be toggled off if you only want the diagnostic pane
█ HOW TO USE IT
Use it as a filter on your existing process, not as an entry trigger. Example: if you run a breakout system, check whether it has historically performed in Ranging — Volatile; if not, consider standing aside when the background flags that state. Example: a mean-reversion system will typically show its worst results in Trending — Expansion.
Works on any asset and timeframe with sufficient history for the percentile window. Best used on daily and above, where regime persistence is greatest.
█ LIMITATIONS
This tool classifies the PRESENT. It does not predict the future, and any use of it as a forecast is a misuse.
• Regime identification is backward-looking by construction. The tool will confirm a regime change several bars AFTER it occurred. This lag cannot be removed without curve-fitting or repainting, and has not been.
• Classification is unstable near threshold boundaries; expect flickering between states when ER or volatility percentile sit close to the cut-offs.
• The percentile ranking requires substantial history. On assets with short histories, the ranking is unreliable and the tool should not be trusted.
• The base-rate table's early entries are built on fewer samples than its later ones — treat statistics as provisional until a state has accumulated a meaningful sample count.
• Four states is a deliberate simplification of a continuous reality. Markets do not actually occupy discrete regimes.
• This script does NOT repaint. All classification is computed on confirmed bar close only.
█ DISCLAIMER
For educational and informational purposes only. Nothing here is financial advice. Past behaviour of any market regime does not indicate future results. Trade at your own risk.
Indicator
Boshmann's Volatility HistBoshmann's Volatility Hist
The theory behind tracking normalized volatility is that market movement is highly cyclical, constantly alternating between periods of tight contraction and explosive expansion. Using raw volatility measures (like a flat Average True Range value) is flawed because the meaning of those points changes drastically as an asset's price scales up or down over time. By applying a statistical Z-Score to the ATR, we normalize the volatility relative to the asset's own historical baseline, allowing traders to objectively identify when price action is anomalously quiet (predicting a breakout) or unsustainably aggressive (predicting exhaustion or mean-reversion).
How the Script Works: The script calculates a standard 14-period Average True Range (ATR) to measure current price movement. It then runs a 250-period lookback to compute the rolling mean and standard deviation of that ATR, ultimately calculating a real-time Z-Score. This Z-Score is plotted as an oscillating histogram below the chart. The script uses fixed thresholds to color the histogram bars: Green for "Quiet" (Z-score < -0.5), Yellow for "Normal" (Z-score between -0.5 and 0.5), and Red for "Volatile" (Z-score > 0.5). It also plots dotted threshold lines so you can instantly see when volatility crosses into extreme territory.
Why You Should Use It: This script is the final pillar of the Boshmann's suite, engineered to be used in strict combination with the Regime Counters and the Market Direction Hist .
While the Regime Counter gives you the structural trend and the Direction Hist gives you the momentum conviction, this Volatility Hist reveals the energy state of the market. You should use this indicator because knowing the market's speed dictates your risk management and strategy timing. For example, if you spot a long string of "Quiet" (green) volatility bars while the Regime Counter just flipped to Bullish, you have found an optimal, low-risk entry before an explosive breakout. Conversely, if you are riding a trend and this histogram spikes deep into the "Volatile" (red) zone, it serves as a mathematical warning that the market is overextended, signaling that you should tighten stops or take profits before the inevitable pullback. Indicator
Boshmann's Market Direction HistBoshmann's Market Direction Hist
The theory behind a directional histogram is to visually quantify not just the direction of a trend, but its underlying momentum and the distance between moving averages. While identifying a trend regime categorizes the market into a fixed state (bull, bear, or sideways), measuring the spread between a fast and slow moving average reveals whether that trend is accelerating, decelerating, or reaching exhaustion. By projecting this spread as an oscillator around a zero line, traders can easily spot momentum divergences and gauge the true strength of a directional move.
How the Script Works: The script calculates the raw distance between a short-term moving average (20-period SMA) and a long-term moving average (100-period SMA). To ensure the indicator works seamlessly across any asset class or timeframe—whether a stock is trading at $5 or $50,000—it normalizes this distance as a percentage of the current price. It then plots this normalized momentum as a histogram. Finally, the histogram bars are painted using the exact same logic as the Regime Counters script: Green for Strong Bull, Red for Strong Bear, and Yellow for Sideways.
Why You Should Use It: This script is explicitly designed to be used in combination with the Regime Counters and Volatility Histogram scripts to form a complete, three-dimensional view of the market.
A user should use this histogram because while the Regime Counter tells you what state the market is in, the Direction Histogram tells you how strong that state is. For example, if the Regime Counter classifies the market as "Bullish" but you see the green bars on this histogram steadily shrinking toward the zero line, it is a leading indicator that upward momentum is dying long before the official regime flips. Together, the three scripts allow you to trade systematically: the Regime Counter dictates your directional bias, the Volatility script warns you of price expansion, and the Direction Histogram measures the real-time conviction pushing the trend. Indicator
Boshmann's Regime CountersSummary of Boshmann's Regime Counters
At its core, this indicator is designed to remove human subjectivity from chart reading by translating market behavior into purely objective, mathematically defined states. Rather than relying on discretionary trendlines or "gut feelings" about market speed, it uses robust statistical baselines to continuously classify the market into discrete Trend and Volatility regimes.
For PulseWire users, this provides an immediate, systematic context of the market environment, which is crucial because trading strategies (like mean-reversion vs. trend-following) only perform well when aligned with the correct market state.
1. Trend Regime Classification (Directional Bias)
The indicator evaluates moving average alignments to determine the structural trend. It requires both price position and momentum to agree before declaring a strong trend:
Bull: The closing price is strictly above a long-term baseline (200 SMA) AND short-term momentum (20 SMA) is leading the medium-term momentum (100 SMA).
Bear: The closing price is below the 200 SMA AND the 20 SMA has crossed below the 100 SMA.
Sideways: Any state where the price and moving averages are in conflict or tangled.
Visuals: The chart bars are painted dynamically (Green for Bull, Red for Bear, Golden for Sideways) so the current regime is instantly visible.
2. Volatility Regime Classification (Market Speed)
Instead of using fixed point values to measure volatility (which break down across different timeframes and assets), the indicator uses an Adaptive Z-Score of the Average True Range (ATR). By looking back over a large sample size (250 periods), it calculates a rolling mean and standard deviation of the ATR. This normalizes volatility into a universal metric:
Quiet (Z-Score < -0.5): The market is contracting and experiencing significantly below-average movement.
Normal (Z-Score -0.5 to 0.5): The market is operating within its standard, expected historical variance.
Volatile (Z-Score > 0.5): The market is expanding, experiencing statistically significant, out-sized movement.
3. The Statistics Dashboard
The script anchors a real-time statistical dashboard to the chart. It tallies the exact number of bars—and calculates the overall historical percentage—spent in each specific trend and volatility regime.
What this does for PulseWire users:
Strategy Alignment: By quantifying exactly how much time an asset spends trending versus chopping sideways, traders can objectively decide whether to deploy a trend-following system or a range-bound strategy on that specific asset.
Contextual Awareness: The adaptive Z-score prevents users from being caught off guard by volatility expansion, giving them a mathematical warning when the market shifts from "Quiet" accumulation into "Volatile" distribution.
Backtesting Validation: The on-chart percentages give quantitative traders immediate insight into the asset's structural personality over the loaded history (e.g., realizing an asset is only in a "Strong Bull" state 25% of the time helps set realistic win-rate expectations). Indicator
Market Regime LT Direction (Long-Term Objective Filter)Overview
The Market Regime LT Direction indicator is a heavy-duty, multi-factor scoring engine designed to identify the macro market regime. Unlike conventional indicators that rely on a single moving average, this script utilizes a sophisticated matrix of several distinct technical factors across different lookback periods to classify the long-term market environment.
To ensure absolute objectivity and eliminate the pitfalls of over-optimization, this indicator features a zero-input design — there are no parameters to tweak, giving you a robust, curve-fitting-immune view of institutional trend direction.
Why You Should Use This Indicator (The Value Proposition)
Traders often fail because they misjudge the macro environment. A system designed for a secular bull market will fail miserably when the macro regime shifts to a structural bear market or an extended sideways distribution.
Immunity to Curve-Fitting: By fixing the core mathematical constants, this indicator provides an unbiased, baseline truth of the market structure across any asset class (Equities, Crypto, Forex, or Commodities).
Multi-Factor Confluence: Instead of guessing based on a single line, it dynamically calculates a mathematical "Total Score" using trend persistence, moving average geometry, linear regression slope, and momentum.
Macro Filter for Portfolio Allocation: It is an excellent tool for swing traders and long-term investors to manage risk, determine position sizing, or implement an overall portfolio "Risk-On / Risk-Off" switch.
How It Works & Underlying Logic
The indicator separates its engine into two primary layers: a Visual Layer and a Scoring Layer .
1. The Visual Layer
The underlying histogram is a slow-moving, high-period MACD calculated on the typical price (hlc3). This smooths out micro-volatility and visualizes structural macro-momentum.
2. The Scoring Layer (Weighted Confluence Matrix)
The color of the histogram bars is dictated by a strict mathematical matrix. Factors are split into two categories and weighted based on macro relevance:
Low Relevance Score (Short-Term Confluence) like 20 EMA slope direction, fast MACD momentum slope changes and price location relative to the 50 EMA.
High Relevance Score (Long-Term Structure) like price location relative to the 200 SMA, 50 EMA location relative to the 200 SMA, recent swing high/low persistence over a 30-bar window and 100-candle Linear Regression slope.
The script combines these metrics into a standardized Total Score ranging between -3.0 and +3.0 .
How to Interpret It for Your Trading
🟩 Lime (Macro Bullish Regime — Score > 1): Complete structural alignment to the upside. Long-term institutional buying is in control. Aggressive Long bias / Risk-On.
🟥 Red (Macro Bearish Regime — Score < -1): Complete structural alignment to the downside. Macro distribution or a structural markdown is underway. Aggressive Short bias / Defensive capital preservation.
🟨 Yellow (Transitional / Sideways Regime): The factors are in conflict, or the macro trend is losing momentum. The market is consolidating or preparing for a regime shift. Neutral stance / Reduce position sizes / Expect choppy price action.
Pro-Tip: Pair this with the Market Regime ST Direction indicator. When the Short-Term indicator aligns with this Long-Term macro engine (e.g., both turning Green), you have a mathematically high-probability environment for trend-following expansions. Indicator
Market Regime ST Direction (Short-Term Filter)Overview
The Market Regime ST Direction indicator is a streamlined tool designed to identify the short-term market environment, specifically optimized for the Daily Chart . It serves as an über-clean trend and phase filter built to protect your trading strategy from taking unnecessary losses during difficult, choppy market conditions.
The indicator focuses exclusively on market direction , intentionally filtering out volatility noise and secondary market factors.
Why You Should Use This Indicator (The Value Proposition)
It is a fundamental truth in trading: no single strategy works in all market environments . Trend-following systems bleed capital in sideways ranges, while mean-reversion setups get destroyed in strong, runaway trends.
Smart Loss Filtering : This indicator helps you decide when not to trade. It identifies unprofitable market phases before your account takes a hit.
The Market Traffic Light : Use it as a higher-timeframe filter. Only allow long trades in the bullish (green) regime, short trades in the bearish (red) regime, and pause your strategy during the choppy (gray) regime.
Clarity Over Overtrading : With its clear, color-coded separation, you can instantly see whether the market has a clean directional bias or is caught in the "chop."
How It Works & Underlying Logic
The script intelligently decouples visual momentum from the actual trend regime logic:
The Visual Foundation (MACD Histogram) : The baseline visual consists of a classic MACD histogram calculated on the typical price (hlc3). This displays the current momentum of the market.
The Regime Filter (EMA Slope) : Crucially, the color of the bars is not determined by the MACD. Instead, it is driven entirely by the slope (steepness) of the fast 20 EMA.
The Noise Filter (Threshold) : To prevent the indicator from constantly flickering back and forth with minor price ticks, a percentage-based threshold (Sideways Threshold, default: 0.15%) is implemented. The market is only classified as trending when the EMA slope cleanly exceeds this threshold.
How to Interpret It for Your Trading
🟩 Lime (Bullish Regime) : The 20 EMA slope is strongly positive. The short-term trend is firmly up. Focus on Long setups.
🟥 Red (Bearish Regime) : The 20 EMA slope is strongly negative. The short-term trend is firmly down. Focus on Short setups.
⬜ Gray (Sideways/Chop) : The slope is too flat and remains within the threshold boundaries. Caution: This is where trend strategies usually experience their heaviest drawdowns. This is an excellent time to sit on your hands and wait on the sidelines.
Pro-Tip : Apply this indicator to the Daily chart of your favorite asset. If you trade a trend-following strategy on lower timeframes (e.g., 1H or 15M), strictly filter your entries based on the color of the Daily regime. Indicator
KNN Market Regime Engine [Dots3Red]█ OVERVIEW
Most market regime tools work in a pretty simple way: we set a threshold and call it a day. ADX above 25? Trending. Below 20? Ranging.
But that threshold is basically just our assumption baked into code. It doesn’t adapt, it doesn’t learn, and it’s treated the same whether we’re looking at Bitcoin, EUR/USD, or any other market — even though they behave completely differently.
This script takes a different approach . It uses a K-Nearest Neighbors (KNN) machine learning algorithm to estimate the probability that the current market is in one of three regimes: Trending , Ranging , or Volatile Trend . Rather than comparing today's readings against a fixed number, it searches the past 700 bars for the moments that looked most like right now - and asks what the market did after each of those moments. The result is a live probability for each regime, not a hard categorical label.
The output is three things simultaneously:
a background color telling you the dominant regime
a dashboard showing live probability bars for all three states
change markers appearing only when the classifier is genuinely confident a shift has occurred.
█ THE FOUR REGIMES
🔵 TRENDING — price is moving directionally with efficiency. Momentum strategies belong here. Mean reversion strategies get punished here.
🟣 RANGING — price is oscillating between levels with no net directional movement. Mean reversion strategies and fade-the-extreme setups have edge here. Trend-following generates whipsaws.
🟡 VOLATILE TREND — price is trending and ATR has expanded sharply beyond its baseline. This captures earnings gaps, macro shocks, and post-breakout expansion. It is a distinct fourth state — not simply "a strong trend." Reduce size or trail very tightly.
⬛ UNCERTAIN — the dominant probability did not clear the minimum confidence threshold. The market's character is genuinely ambiguous. The best action is observation, not engagement.
█ HOW IT WORKS — THE FULL PIPELINE
Step 1 — Six features, measured every bar
Each bar is described by six measurements, each capturing a different dimension of market character:
• ADX — trend strength. Not direction — only how strongly price is committed to any direction.
• ATR ratio — current ATR divided by its own long-term average. Measures whether volatility is elevated or compressed relative to its own history.
• Choppiness Index — measures how much of the price movement was wasted going sideways. Near 100 = pure chop. Near 38 = perfectly directional.
• Bollinger Band width — how expanded or compressed the bands are relative to price. A compression often precedes volatile expansion.
• Normalized slope — linear regression slope over N bars, divided by ATR. A scale-free measure of directional momentum.
• Kaufman Efficiency Ratio — how directly did price move from A to B? If price traveled 100 points total but only net-moved 20, ER is 0.20. High ER = trending cleanly. Low ER = zigzagging.
Step 2 — Z-score normalization
ADX runs 0–100. ATR ratio runs 0.5–3.0. BB width might be 0.01–0.08 on forex. Using raw values in a distance calculation means the largest-scale feature dominates by sheer magnitude. All six features are standardized: z = (value − rolling mean) / rolling stdev . This puts every feature on equal footing — a reading of +2.0 means " two standard deviations above normal " on any feature. Critically, the mean and stdev are computed on prior bars only ( src offset), which eliminates look-ahead bias from the normalization step.
Step 3 — Labeling historical bars
For every historical bar, the script evaluates what happened over the following Forward Bars window:
• If the net price move exceeded Trend Threshold × average ATR over the window → labeled TRENDING (1)
• If the ATR ratio exceeded Volatility Threshold → labeled VOLATILE TREND (3)
• If trending AND volatile simultaneously → labeled VOLATILE TREND (3), because risk context takes priority
• Otherwise → labeled RANGING (2)
This label is only ever read at an offset of at least Forward Bars bars into the past, so the current bar carries no label — there is no look-ahead in the training data.
Step 4 — KNN search and Gaussian-weighted voting
On each bar, the algorithm scans the historical window (default 700 bars) and computes the Minkowski distance between today's six Z-scored features and every historical bar's six features. The K nearest matches are selected. Closer neighbors receive exponentially higher voting weight via a Gaussian kernel : w = exp(−d² / 2σ²) . This means a bar at distance 0.1 vastly outweighs one at distance 0.5. The votes produce three probabilities — P(trending), P(ranging), P(volatile trend) — that always sum to 1.
Step 5 — Three-stage noise filtering
A single KNN output can flicker bar to bar. Three filters eliminate this:
• Mode filter — selects the most common regime over the last smooth_len bars. Removes 1-3 bar flickers entirely.
• Confirmation filter — the smoothed regime must hold steady for confirm_bars consecutive bars before being accepted. Kills false starts.
• Signal gap — regime change markers only appear once per signal_gap bars minimum, and only when the dominant probability exceeds 65%. This eliminates cluttered charts entirely.
█ DESIGN DECISIONS — WHAT WAS INITIALLY, WHAT CHANGED AND WHY
From 3 regimes to 4
The first idea used three regimes with a simple override: if volatility was high, VOLATILE replaced TRENDING regardless of whether price was actually moving directionally. Testing on stocks showed this caused problems — an earnings-day spike during a clear uptrend was collapsing the trend signal entirely. We realized volatile trending markets are qualitatively different from volatile ranging markets. A fast trend during an OPEC announcement is not the same as a gap-down in a sideways consolidation. VOLATILE TREND became its own regime, and the distinction turned out to be the most practically useful change in the entire script.
From stride = fwd_bars to stride = 3
The early idea for the script we had sampled the training window with a stride equal to Forward Bars (30 by default). This gave roughly 23 training samples — barely enough for KNN to make a meaningful comparison. Reducing the stride to 3 gives approximately 230 samples. The regime classification became dramatically more stable and consistent, especially in quieter markets where the 23-sample version frequently returned UNCERTAIN. The trade-off is slightly more computation, which Pine handles comfortably within its limits.
From a single volatile threshold to a combined trend + volatile check
Originally we labeled VOLATILE based purely on ATR ratio exceeding a threshold. This correctly flagged high-volatility periods but was labeling slow low-ATR trends as RANGING instead of TRENDING during prolonged low-volatility bull markets. The label logic was reworked to check directionality and volatility independently and then combine them: a trending move is TRENDING unless ATR is also elevated, in which case it becomes VOLATILE TREND. This made the label logic honest about what the market was actually doing.
The Efficiency Ratio addition
The original five features (ADX, ATR ratio, Choppiness, BB width, Slope) left a gap: two markets can have identical ADX and slope but very different directional efficiency — one moves in a clean staircase, the other zigzags the same distance. Kaufman's Efficiency Ratio fills this gap. ER = 0.85 on a bar means 85% of all price movement went in the net direction. ER = 0.20 means price was thrashing around and barely net-moved. It proved particularly valuable for distinguishing true trending from noisy ranging in crypto and high-beta stocks.
The regime change marker clutter problem
Early testing produced charts covered in triangles, circles, and diamonds — a new marker on almost every regime flicker. Three parameters were added to solve this: the mode filter, the confirmation bars requirement, and the signal gap. Together they ensure a marker only appears when (a) the majority of recent bars agree on the new regime, (b) it has held for at least N bars, and (c) the KNN confidence is above 65%. The result is 2–6 meaningful markers per year on a daily chart rather than dozens of noisy ones.
█ WHAT YOU SEE ON THE CHART
Background color — the dominant confirmed regime, colored continuously. Cyan = Trending. Magenta = Ranging. Amber = Volatile Trend. No color = Uncertain.
Bar coloring — individual bars colored by the same regime. Toggle off if you prefer your own candle coloring scheme.
Regime change markers — small shapes at confirmed, high-confidence regime transitions only. ▲ below bar = shift to Trending. ● below bar = shift to Ranging. ◆ above bar = shift to Volatile Trend.
Dashboard (top right) — shows the confirmed regime label, confidence percentage, three probability meters (▰▰▰▱▱▱ format), and six live feature readings. The bottom row shows Raw → Smooth (e.g. "T → R") so you can see what the raw KNN output is before the filters process it — useful for understanding when the classifier is about to change state.
█ SETTINGS REFERENCE
🧠 KNN Engine
• K Neighbors — how many historical bars vote. Lower = faster reaction, higher = more stable. Default 25.
• Lookback Window — how many bars to search for neighbors. Larger = more training data. Default 700.
• Minkowski p — distance exponent. 1 = Manhattan (robust to outliers), 2 = Euclidean (standard). Default 2.
• Gaussian bandwidth — how steeply neighbor weight falls with distance. Lower = only the closest neighbors matter. Default 1.5.
• Minimum confidence — probability threshold below which the regime shows as UNCERTAIN. Default 0.45.
🏷️ Labeling
• Forward bars — how many bars ahead define a historical bar's regime label. Match your typical hold time. Default 30.
• Trend threshold — net move must exceed this × avg ATR to label TRENDING. Lower = more bars labeled trending. Default 1.2.
• Volatility threshold — ATR ratio must exceed this to label VOLATILE TREND. Higher = only extreme events qualify. Default 1.5.
📐 Features
• ADX Length — period for the directional movement index. Longer = smoother. Default 20.
• ATR Length — period for average true range. Default 14.
• ATR Baseline — SMA period for the ATR ratio denominator. Longer = more stable baseline. Default 100.
• Choppiness / BB / Slope lengths — feature calculation periods. All default to 20–30.
• Efficiency Ratio Length — Kaufman ER lookback. Default 30.
🧹 Filtering
• Regime Smoothing Lookback — mode filter window. Higher = fewer false regime changes. Default 11.
• Bars to confirm regime — consecutive bars required before a new regime is accepted. Default 4.
• Min bars between signals — minimum spacing between regime change markers. Default 20.
█ SETTINGS BY ASSET CLASS
📈 Large-cap stocks — daily (AMZN, AAPL, NVDA)
Stocks trend slowly over weeks to months, with sharp one-day volatility spikes on earnings. All feature lengths should be longer to resolve the slower regime pace.
• Forward bars: 20–30 | Trend threshold: 0.8–1.2 | Volatility threshold: 2.0–2.5
• ATR Baseline: 100 | ADX / Chop / Slope lengths: 20 | BB length: 30 | EffR: 30
• Smoothing: 11 | Confirm bars: 4–5 | Signal gap: 20
• Note: use 0.8 trend threshold for slow defensive stocks (JNJ, KO), 1.2 for high-beta tech (NVDA, TSLA)
₿ Crypto — daily (BTC, ETH, large caps)
Crypto regimes flip in days, not months. ATR is 3–7× higher than stocks. Shorter windows, lower thresholds, less smoothing.
• Forward bars: 10–14 | Trend threshold: 1.5–2.5 | Volatility threshold: 1.5–2.0
• ATR Baseline: 50–70 | All feature lengths: 14 | EffR: 14–20
• Smoothing: 5–7 | Confirm bars: 2–3 | Signal gap: 7–10
• Note: for altcoins use trend threshold 2.0–2.5; for BTC use 1.5–2.0
💱 Forex — daily (EUR/USD, GBP/USD, USD/JPY)
Forex trends are driven by central bank divergence and last months. Daily ATR is tiny (0.4–0.7% of price). Everything needs to be longer and slower.
• Forward bars: 30–45 | Trend threshold: 0.6–0.8 | Volatility threshold: 2.5–3.0
• ATR Baseline: 120–150 | ADX length: 20–25 | Slope / EffR: 40–50
• Smoothing: 15–21 | Confirm bars: 5–7 | Signal gap: 30–45
• Note: exotic pairs (USD/TRY, USD/ZAR) behave like crypto — use crypto settings instead
🛢️ Commodities — daily (Gold XAU, Oil WTI)
Gold is slow and stable like equities. Oil is fast and event-driven like crypto. Use different profiles.
• Gold: Forward bars 20, Trend 0.8, Vol 2.5, ATR Base 100, Smooth 11, Confirm 4, Gap 20
• Oil: Forward bars 15, Trend 1.2, Vol 2.0, ATR Base 70, Smooth 7, Confirm 2–3, Gap 10
• Note: OPEC events and geopolitical shocks will correctly fire VOLATILE TREND on oil — this is intended behavior
🌐 Indices — daily (SPX, NDX, DAX)
Indices are the most regime-stable asset class. They trend 65–75% of the time and have the cleanest feature signals of any asset.
• Forward bars: 20–30 | Trend threshold: 0.8–1.0 | Volatility threshold: 2.0–2.5
• ATR Baseline: 120 | ADX length: 20 | Smoothing: 11–15 | Confirm bars: 4–5 | Signal gap: 20–30
• Note: NDX is ~30% more volatile than SPX — use trend threshold 1.0 for NDX, 0.8 for SPX
EXAMPLE
█ HOW TO USE WITH OTHER INDICATORS
This script does not generate buy or sell signals. It tells you which type of strategy has edge right now . The intended workflow:
1 — Add your momentum or mean reversion indicator alongside this one.
2 — Only take momentum / trend-following entries when the background is cyan (TRENDING) .
3 — Only take mean reversion / fade entries when the background is magenta (RANGING) .
4 — Reduce position size or step aside entirely when the background is amber (VOLATILE TREND) .
5 — Do nothing when there is no background color — the regime is UNCERTAIN.
Used this way, the classifier acts as a strategy mode selector rather than a signal generator. It is the foundation of a multi-strategy system where the same chart hosts different logic depending on detected conditions.
█ LIMITATIONS
• KNN is a lazy learner — it reflects patterns in its training window. If the current market regime has no historical analog in the lookback window (e.g. a once-in-a-decade crash), the classifier will misclassify or return UNCERTAIN.
• The script requires a warm-up period equal to Lookback Window + Forward Bars bars before producing output. On instruments with limited history this may delay the first valid reading.
• Computation scales with window size and stride. Very large windows (2000+) may slow chart rendering on lower-end machines.
• The reversion probability reflects historical frequency, not a guarantee of future behavior. All market regimes can and do fail.
Human vs Machine 🧠vs 🤖
And most importantly, checking the chart with the HUMAN EYE is different from using the raw ML KNN method - something we agreed on checking the charts, as we, traders-developers, had different opinions of the market regime for an asset price. But the Script might yield results we can all agree upon.
█ DISCLAIMER
This indicator is a decision-support tool, not a trading system. It does not constitute financial advice. Past regime patterns do not guarantee future behavior. Always apply proper risk management.
Algorithm: K-Nearest Neighbors (KNN)
Distance metric: Minkowski Distance (p=2, Euclidean default)
Kernel: Gaussian (distance-weighted voting)
Normalization: Z-Score (look-ahead free)
Regimes: Trending | Ranging | Volatile Trend | Uncertain Indicator
Indicator
Simple USD PressureSimple USD Pressure
Simple USD Pressure is a market pressure and directional regime indicator designed to measure broad U.S. Dollar strength and weakness by analyzing multiple USD-related instruments simultaneously.
Rather than relying on a single source such as DXY alone, this indicator evaluates the directional alignment of major USD currency pairs and can optionally incorporate additional confirming instruments including DXY, Gold, US10Y yields, and SPX risk sentiment to build a broader view of USD behavior.
The goal is to provide a cleaner view of underlying dollar pressure and identify shifts in overall market conditions that may influence Forex pairs, indices, commodities, and risk assets.
Features:
• Multi-pair USD pressure analysis
• Uses major USD pairs including:
EURUSD
GBPUSD
AUDUSD
NZDUSD
USDJPY
USDCHF
USDCAD
• Optional confirmation instruments:
DXY
Gold
US10Y
SPX
• Composite USD scoring system
• Customizable calculation timeframe
• Optional "Wait Until Bar Close" confirmation logic
• Adjustable trend thresholds
• Market regime detection:
USD Strong
USD Weak
USD Mixed
• Visual background highlighting
• Regime transition markers
• Summary table including:
Bull pair votes
Bear pair votes
USD pressure score
Confirmation score
Composite score
Current regime
Alerts Included:
• USD Strong Shift
• USD Weak Shift
• USD Mixed Shift
• Active USD Strong
• Active USD Weak
• Active USD Mixed
Potential use cases:
• Gauge broad USD strength or weakness
• Add directional bias to Forex trades
• Confirm risk-on or risk-off environments
• Identify changes in market conditions
• Use as a higher-level market filter
• Add confluence to existing systems
Interpretation:
USD Strong
Broad alignment suggests stronger dollar participation across selected instruments
USD Weak
Broad alignment suggests weaker dollar participation across selected instruments
USD Mixed
Signals are relatively balanced and directional pressure may be less defined
About TrendGenY Indicators
TrendGenY indicators are built from market experience, creative concepts, and a constant pursuit of unique perspectives. Rather than following conventional ideas, the focus is on uncovering alternative insights and viewing market behavior through different angles to reveal information that traditional tools may overlook and help traders build a more meaningful edge in the market. Indicator
Bull vs Bear Candle CountBull vs Bear Candle Count
Bull vs Bear Candle Count is a market participation and directional bias indicator designed to measure whether buyers or sellers have been dominating recent price action.
Instead of relying on traditional moving averages or oscillators, this indicator simply analyzes the number of bullish and bearish candles over a customizable lookback period to determine whether the market environment is currently Bullish, Bearish, or Balanced. Based on the candle distribution, the indicator calculates net directional pressure and visually highlights shifts in market conditions.
Features:
• Customizable lookback period
• Bullish, Bearish, and Balanced market state detection
• Net Bias histogram for directional strength visualization
• Bull % and Bear % comparison lines
• Adjustable balanced threshold sensitivity
• Optional background highlighting based on market state
• State transition markers for environment changes
• Summary table displaying:
Bull count
Bear count
Doji count
Bull percentage
Current market state
Alerts Included:
• Bullish State Shift
• Bearish State Shift
• Balanced State Shift
Potential use cases:
• Identify directional market pressure
• Filter trades based on overall market environment
• Confirm trend continuation or weakening momentum
• Spot transitions between trending and balanced conditions
• Add confluence to existing strategies and systems
Interpretation:
Bullish
Bullish candles are dominating the selected lookback period
Bearish
Bearish candles are dominating the selected lookback period
Balanced
Bull and bear participation are relatively equal, potentially indicating consolidation or indecision
Bull vs Bear Candle Count is intended as a simple way to visualize market participation and directional behavior without introducing excessive complexity.
About TrendGenY Indicators
TrendGenY indicators are built from market experience, creative concepts, and a constant pursuit of unique perspectives. Rather than following conventional ideas, the focus is on uncovering alternative insights and viewing market behavior through different angles to bring greater clarity, deeper understanding, and help traders develop a more meaningful edge in the market. Indicator
Market Memory Average (Zeiierman)█ Overview
Market Memory Average (Zeiierman) is a similarity-based market regime tool that scans historical price behavior to identify past conditions that closely resemble the current market state.
The script compares momentum, RSI, volatility, and relative volume to build a “market memory” model. It then extracts the internal momentum of the most similar historical states and blends them into a dynamic projection line.
The result is an adaptive average that reflects how the market has historically behaved when conditions looked like this, rather than relying on fixed formulas or traditional lagging averages.
█ How It Works
⚪ Market State Encoding
The script defines the current market using momentum (ROC), RSI, volatility (ATR%), and relative volume. These features describe how the market is behaving, not just price position.
⚪ Historical Similarity Scan
Each past bar is compared to the current state using a multi-feature distance model.
Closer matches receive higher weights through exponential decay:
similarity = 100 * exp(-distance * sensitivity)
⚪ Top Match Selection
The script ranks all historical states and keeps only the most similar ones. These represent past environments that closely resemble current conditions.
⚪ Memory Momentum
From each match, the script extracts its internal momentum (ROC).
A similarity-weighted average is then calculated:
avgMomentum = weightedMomentum / totalWeight
⚪ Market Memory Average
This averaged momentum is applied to the current price to form the line:
memoryLine = close * (1 + avgMomentum / 100)
The result reflects how similar market states have historically behaved.
⚪ Historical Match Zones
Optional boxes highlight where similar conditions occurred in the past, along with their similarity strength.
█ How to Use
⚪ Market Memory Average
Bullish color → market conditions align with historically positive momentum.
Bearish color → market conditions align with historically negative momentum.
Unlike traditional averages, this line is built from the similarity-weighted momentum of past market matches. The cloud and structure dynamically adapt based on how those historical conditions behaved.
This gives the line a context-driven, memory-based approach, rather than relying on fixed calculations. The result is a dynamic reference for directional bias and regime context, grounded in how the market has behaved under similar conditions before.
⚪ Study Historical Match Zones (Example 1)
The match boxes show where similar market conditions occurred in the past, based on momentum, volatility, RSI, and volume alignment.
Each box represents a moment where the market behaved as it does now.
These zones can help:
Visualize recurring structures: See how similar conditions previously formed, such as pullbacks, bottoms, or consolidation phases within a trend.
Identify behavioral clustering: When multiple matches appear around similar types of price action, it suggests the market frequently revisits this behavior.
Understand the current environment: By comparing where those matches occurred (trend, range, recovery), you can interpret what kind of phase the market is currently in.
Build a contextual bias: If most matches come from pullbacks and recoveries (as in the example), the current state aligns more with pause → stabilize → continue behavior, rather than reversal or breakdown conditions.
These zones provide context, not prediction, helping you understand how the market is behaving relative to its own history.
⚪ Study Historical Match Zones (Example 2)
In this example, the current market state most closely aligns with these two highlighted zones.
Both matches formed during bearish conditions:
The left match shows a rejection after a strong move up, with momentum quickly flipping into a sharp drop.
The right match shows a weak bounce inside a downtrend, where the price attempted to recover but continued lower.
Looking at the current state (circled area), the price is:
Breaking down aggressively
Moving similarly to those past rejection phases
This suggests the current behavior aligns more with rejection → continuation, rather than stabilization or reversal.
█ Settings
Historical Scan Depth: Controls how far back the script searches for similar market states.
Top Similar Matches: Determines how many historical matches influence the average.
Historical Pattern Length: Sets the width of the displayed historical match zones.
Similarity Sensitivity: Controls how strict the similarity comparison is.
RSI Length: Defines the oscillator component of the market state.
ATR Length: Controls volatility measurement used in both similarity and cloud calculations.
Volume MA Length: Defines how relative volume is calculated.
Average Smoothing: Controls the responsiveness of the Market Memory Average.
Slope Detection Length: Determines how trend direction is evaluated.
Cloud Spread: Controls how far the cloud extends from the line.
-----------------
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
Cross-Asset Correlation & Cointegration Intelligence [NikaQuant]
**Cross-Asset Correlation & Cointegration Intelligence**
Track your chart symbol against up to six comparison symbols. The script
renders **three synchronized panels** that tell you, in plain numbers:
- How coupled the basket is **right now**
- Which pairs are genuinely tradeable (and the **expected mean-reversion time**)
- How much **gross exposure** you should carry given the current regime
## What It Does
- **Intelligence Dashboard** — per-symbol grid: correlation, beta, R²,
z-score, percentile, stability, lead/lag, spread z, quality score,
hedge size, stress-vs-normal correlation delta, signal verdict
- **N×N Correlation Matrix** — full 6×6 pairwise heatmap
- **Action Center** — regime timer, flip probability, risk-budget advisor,
top-5 ranked trades, top-3 cointegrated pair setups, trade playbook
## Why It Is Original
Unlike standard correlation heatmap scripts that display a single Pearson
value per pair, this script builds a composite intelligence layer across
**three independent axes** that no retail correlation indicator combines:
**1. Asymmetric (Conditional) Correlation**
Splits history into **normal-volatility** and **stress-volatility** regimes
using an ATR-median split on the base symbol, and reports the two
correlations side by side. This exposes the *"diversification fails when
you need it"* amplification that an averaged Pearson value hides — a
documented pattern in every crisis since 1998.
**2. Cointegration + Half-Life**
For all 15 unique pairs, runs an **Engle-Granger two-step** (log-regression
then AR(1) on the residual spread) to flag which spreads are genuinely
mean-reverting. Cointegrated pairs carry an **Ornstein-Uhlenbeck half-life**
t½ = −ln(2) / ln(1 + φ) — the expected mean-reversion time in bars.
*Correlation tells you direction; cointegration tells you whether the
spread will revert.*
**3. Regime Persistence + Flip Probability**
Tracks four states (Crisis / Coupled / Mixed / Decoupled) in a **4×4 Markov
transition counter**, stores per-regime dwell times, and converts them into
flip-probability estimates for the next 10 and 30 bars. You see not just
*"we are in X"* but *"X has lasted 47 bars, historical average is 62 bars,
probability of flip in 30 bars is 55%."*
## Composite Modules
- **Crisis Clock (0–100)** — composite of average absolute correlation,
cross-sectional dispersion collapse, and tail-dependence count
- **Market Brain** — union-find clustering on positive pairwise
correlations, auto-groups symbols that move as one
- **Dispersion Trade Detector** — fires when average correlation drops
>2σ while realized volatility rises
- **Hedge Desk** — converts OLS beta into a **dollar hedge notional**
given your base position size
- **Effective-N** — correlation-adjusted diversification count (six
symbols at ρ=1.0 gives effective N = 1)
- **Risk Budget Advisor** — regime + effective-N → suggested gross
exposure percentage
- **Setup Quality Score** — composite of |corr| × R² × stability,
adjusted for regime, clock, and break
- **Action List** — scans every symbol and every pair, scores each
candidate, ranks them, surfaces the top five with type, target, score,
direction, suggested size, rationale
## Per-Symbol Metrics
- Rolling Pearson correlation across **three lookbacks** (short, medium,
long) — three-block glyph reveals timeframe divergence
- **OLS beta** from log returns, **R²** as variance explained
- **Z-score** of current correlation vs its own 200-bar distribution
- **Percentile rank** of current correlation in its own history
- **Stability** from rolling stdev of the correlation itself
- **Optimal-lag scanner** across {−5, −3, −1, 0, +1, +3, +5} offsets
- **Spread z-score** of the price ratio for pairs signaling
- **Asymmetric Δ** = ρ_stress − ρ_normal (positive = hedge fails under stress)
## How To Use It
- **Scan the Quality column first.** Anything at or above 60 with a
TRACK++ or HEDGE++ signal is a high-confidence setup.
- **Cross-check AsymΔ.** Values above +0.3 mean that "hedge" is expected
to fail under stress — avoid relying on it in a crisis.
- **Use Hedge column values** as the dollar notional to short or long
against your base position to neutralize beta.
- **Read the matrix** like a portfolio risk report. Clusters of dark-green
tiles = diversification is breaking down. Red tiles = inverse pairs.
- **In the Action Center**, start at the Risk Budget line, then work
top-down through the Action List. Cointegrated pairs marked with a
check-mark prefix show expected mean-reversion time in bars.
**Recommended timeframes:** intraday or daily charts with at least 250
bars of history across all six symbols.
**Recommended markets:** anywhere the base asset has meaningful
relationships with a benchmark basket — equity indexes vs sector ETFs,
crypto majors vs index proxies, FX vs rates and commodities.
**Avoid using when:** fewer than three symbols resolve to valid data;
during the first 250 bars after chart load; or on a symbol with gapped
or illiquid history that creates artificial correlation jumps.
## Alerts
Regime Break · Dispersion Trade Setup · New Cointegrated Pair ·
High-Quality Setup · Imminent Regime Flip · Crisis Regime Entered ·
Asymmetric Correlation Amplification · Risk Budget Reduced · Clock
Stressed/Critical · Strong Positive/Negative Correlation Crossovers
## Key Settings
- **Comparison Symbols 1–6** — the basket (autocomplete from any TV ticker)
- **Medium-Term Correlation Period** (50) — primary correlation lookback
- **Short / Long Lookbacks** (20 / 200) — timeframe-divergence glyph
- **Historical Baseline** (200) — z-score, percentile, stability, regime
dwell times, and asymmetric-correlation ATR split
- **Strong Correlation** (0.70) — threshold for strong-signal eligibility
- **Regime-Break |Z|** (2.00) — flags correlations breaking their range
- **Pairs-Trade |Spread Z|** (2.00) — pairs-trade setup threshold
- **Min R² for Trust** (0.25), **Min Stability** (0.50) — quality gates
- **Cluster Threshold** (0.60) — Market Brain grouping
- **Crisis Clock** — Stressed (60), Critical (80) thresholds
- **Base Position Size** (10,000) — drives Hedge Desk and Action sizing
- **Min Action Quality** (60) — filters the Action List
- **Risk Budget per regime** — Crisis 50%, Coupled 75%, Mixed 90%,
Decoupled 100% (all user-tunable)
- **Display** — position each of three tables independently; Compact or
Pro column density; full palette customization
## Notes
**No repainting.** All correlations, betas, and regime computations use
confirmed bars only. Regime transition counters and dwell-time arrays
update only when a bar confirms.
**Data integrity.** Six external symbol requests are made with
non-forward-looking data fetches, well within PulseWire's request limit.
**Methods.** Asymmetric correlation uses log returns with indicator
weights from an ATR-median volatility split on the base asset.
Cointegration is Engle-Granger two-step: log-regression residual, then
AR(1) test. A pair is flagged as cointegrated when the AR(1) coefficient
is sufficiently negative to indicate mean-reversion. Half-life uses the
standard Ornstein-Uhlenbeck solution t½ = −ln(2) / ln(1 + φ).
**Warm-up.** The first ~250 bars after chart load are a warm-up period.
Several metrics will display "—" until enough history accumulates.
**Originality.** All calculations, signal logic, clustering,
cointegration testing, and table rendering are original. No third-party
code is reused.
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Market Regime LiteMarket Regime Lite
A background-coloring indicator that tells you what kind of market you're in.
What It Does
Every bar, it reads ADX, ATR, volume, and price structure together and classifies the market into one of five states:
🟢 Trending — Strong momentum, expanding volatility, clean structure. Trade with the trend.
🔴 Exhaustion — Trend is overextended. Climactic volume, ADX rolling over.
🟠 Distribution — Trend is dying. Lower highs forming, participation fading.
🔵 Accumulation — Low volatility, low volume, subtle higher lows. Something is building.
⚫ Choppy — No edge, Flat everything.
How It Classifies
Each regime gets a score out of 5. Whichever scores highest (minimum 3) wins. If nothing clears the threshold, it defaults to Choppy.
Settings
ADX / ATR Length — 14 default, standard momentum and volatility lookback
ATR Percentile Lookback — 100 bars by default, ranks current volatility vs history
Volume MA Length — 20-bar baseline for volume comparison
Structure Lookback — Controls how significant a swing high/low needs to be
On the Chart
The background fills with the regime color. The top-right table shows the regime name, its score, and live ADX / ATR% / Volume readings. Indicator
Macro Regime: Market mood + Regime detector1. The Core Idea
When investors feel confident, they buy high-beta stocks.
When they feel nervous, they hide in low-volatility stocks.
Everything in this indicator is just measuring that preference, then checking whether fear is rising fast enough to matter.
2. The Engine: SPHB / SPLV
What these ETFs represent
SPHB = high-beta stocks (move more than the market)
SPLV = low-volatility stocks (move less than the market)
What the ratio means
SPHB / SPLV rising → investors prefer risk
SPHB / SPLV falling → investors prefer safety
This ratio is your risk appetite heartbeat.
3. Trend Filters (Separating Noise from Regimes)
The moving averages
Fast MA (50) → short-term risk momentum
Slow MA (200) → long-term risk regime
How they’re used
Ratio above the 200 MA → risk-on environment
Ratio below the 200 MA → risk-off environment
Fast MA crossing slow MA → regime transition
This avoids reacting to every wiggle.
4. RSI: Detecting Overconfidence & Exhaustion
Why RSI is applied to the ratio
You’re not asking “are stocks overbought?”
You’re asking: “Is risk preference itself becoming stretched?”
Interpretation
RSI > 70 → investors are crowding into risk
Lower RSI highs while ratio makes higher highs → enthusiasm is fading (classic late-cycle behavior)
RSI < 30 → panic / forced de-risking
RSI helps separate:
Healthy expansion from Speculative euphoria
5. Stress Filter: Volatility (VIX or VIXY/SPY)
Why this matters
Risk can fall in two very different ways:
Orderly slowdown (volatility stays calm)
Crisis (volatility explodes)
The stress filter answers: “Is fear becoming systemic?”
How it’s measured
Either TVC:VIX , or VIXY / SPY (volatility vs equities)
Converted into a Z-score so spikes stand out clearly.
Interpretation
Low stress → normal market functioning
High stress → forced selling, margin calls, policy response territory
6. Credit & Breadth (Confirmation, Not Drivers)
These don’t create signals — they confirm them.
Credit: HYG / TLT
Junk bonds vs Treasuries
Falling → credit risk rising (often leads equities)
Breadth: RSP / SPY
Equal-weight vs cap-weight
Falling → narrowing leadership, fragile market
If high beta weakens + credit & breadth roll, regime shifts are far more reliable.
7. The Four Regimes (This Is the Payoff)
🟢 Early Expansion
What’s happening:
Investors steadily increase risk
Credit and breadth cooperate
Volatility stays muted
On the chart
SPHB/SPLV above 200 MA
RSI rising but < 70
Green background
How to think: “Risk is being rewarded.”
🟡 Late Cycle / Euphoria
What’s happening
Everyone already owns risk
Momentum slows under the surface
Complacency is high
On the chart
Ratio still rising
RSI > 70 or divergence
Orange background
How to think: “Upside exists, but fragility is building.”
🟠 Slowdown
What’s happening
Investors quietly reduce exposure
No panic yet
Often policy-sensitive phase
On the chart
Ratio below fast MA
Still above or near slow MA
Stress remains low
Yellow background
How to think: “Protect gains, reduce beta.”
🔴 Crisis
What’s happening
Forced de-risking
Liquidity stress
Correlations go to 1
On the chart
SPHB/SPLV collapses below 200 MA
RSI < 30
Stress Z-score spikes
Red background
How to think: “Capital preservation > return.”
8. Binary Mode: Risk-ON vs Risk-OFF
The script also simplifies everything into a single switch:
Risk-ON
High beta trending up
Confirmations OK
Stress contained
Risk-OFF
High beta trending down
Stress elevated
This is what you’d use for:
Position sizing
Exposure limits
Asset rotation
Indicator
Impulse Trend Levels [BOSWaves]Impulse Trend Levels - Momentum-Adaptive Trend Detection with Impulse-Driven Confidence Bands
Overview
Impulse Trend Levels is a momentum-aware trend identification system that tracks directional price movement through adaptive confidence bands, where band width dynamically adjusts based on impulse strength and freshness to reflect real-time conviction in the current trend direction.
Instead of relying on fixed moving average crossovers or static band multipliers, trend state, band positioning, and zone thickness are determined through impulse detection patterns, exponential decay modeling, and volatility-normalized momentum measurement.
This creates dynamic trend boundaries that reflect actual momentum intensity rather than arbitrary technical levels - contracting during fresh impulse conditions when trend conviction is high, expanding during impulse decay periods when directional confidence weakens, and incorporating momentum freshness calculations to reveal whether trends are accelerating or deteriorating.
Price is therefore evaluated relative to bands that adapt to momentum state rather than conventional static thresholds.
Conceptual Framework
Impulse Trend Levels is founded on the principle that meaningful trend signals emerge when price momentum intensity reaches significant thresholds relative to recent volatility rather than when price simply crosses moving averages.
Traditional trend-following methods identify directional changes through price-indicator crossovers, which often ignore the underlying momentum dynamics and conviction levels that sustain those moves. This framework replaces static-threshold logic with impulse-driven band construction informed by actual momentum strength and decay characteristics.
Three core principles guide the design:
Trend direction should be determined by volatility-normalized momentum breaches, not simple price crossovers alone.
Band width must adapt to impulse freshness, reflecting real-time confidence in the current trend.
Momentum decay modeling reveals whether trends are maintaining strength or losing conviction.
This shifts trend analysis from static indicator levels into adaptive, momentum-anchored confidence boundaries.
Theoretical Foundation
The indicator combines exponential moving average smoothing, mean absolute deviation measurement, impulse detection methodology, and exponential decay tracking.
An EMA-based trend baseline provides directional reference, while Mean Absolute Deviation (MAD) offers volatility-normalized scaling for momentum measurement. Impulse detection identifies significant price movements relative to recent volatility, triggering fresh momentum readings that decay exponentially over time. Band multipliers interpolate between tight and wide settings based on calculated impulse freshness.
Four internal systems operate in tandem:
Trend Baseline Engine : Computes EMA-smoothed price levels for directional reference and band anchoring.
Volatility Measurement System : Calculates MAD to provide adaptive scaling that normalizes momentum across varying market conditions.
Impulse Detection Logic : Identifies volatility-normalized price movements exceeding threshold levels, capturing momentum intensity and direction.
Decay-Based Confidence Modeling : Applies exponential decay to impulse readings, converting raw momentum into time-weighted freshness metrics that drive band adaptation.
This design allows trend confidence to reflect actual momentum behavior rather than reacting mechanically to price formations.
How It Works
Impulse Trend Levels evaluates price through a sequence of momentum-aware processes:
Baseline Calculation : EMA smoothing of open and close creates a directional trend reference that filters short-term noise.
Volatility Normalization : MAD calculation over a specified lookback provides dynamic scaling for momentum measurement.
Raw Impulse Detection : Price change over impulse lookback divided by MAD creates volatility-normalized momentum readings.
Threshold-Based Activation : When normalized momentum exceeds threshold (1.0), impulse registers with absolute magnitude and directional sign.
Exponential Decay Application : Between impulse events, stored impulse value decays exponentially via configurable decay rate.
Freshness Conversion : Decaying impulse transforms into freshness metric (0-100%) representing current momentum conviction.
Adaptive Band Construction : Band multiplier interpolates between minimum (fresh) and maximum (stale) settings based on freshness, then scales MAD to determine band width.
Trend State Logic : Price crossing above upper band triggers bullish state; crossing below lower band triggers bearish state; state persists until opposite breach.
Signal Generation : Trend state switches from bearish to bullish produce buy signals; bullish to bearish switches produce sell signals.
Retest Identification : Price touching inner band edge after signal buffer period marks retests, with cooldown periods preventing excessive plotting.
Together, these elements form a continuously updating trend framework anchored in momentum reality.
Interpretation
Impulse Trend Levels should be interpreted as momentum-anchored trend confidence boundaries:
Bullish Trend State (Cyan) : Established when price closes above adaptive upper band, indicating upward momentum breach with associated confidence level.
Bearish Trend State (Magenta) : Established when price closes below adaptive lower band, signaling downward momentum breach with directional conviction.
Trend Cloud : Visual gradient zone displays between outer and inner band edges, with opacity reflecting current trend state and confidence.
Band Width Dynamics : Tighter bands indicate fresh impulse (high confidence), wider bands indicate impulse decay (reduced confidence).
▲ Buy Signals : Green upward triangles mark bullish trend state initiations at crossovers above upper band.
▼ Sell Signals : Red downward triangles mark bearish trend state initiations at crossovers below lower band.
✦ Retest Markers : Small diamonds identify price retouching inner band edge after sufficient buffer period from initial signal.
Retest Extension Lines : Horizontal projections from retest points extend forward, marking potential support/resistance levels.
Colored Candles : Optional bar coloring reflects current trend state for immediate visual reference. Note: The original chart candles must be disabled in chart settings for the trend-colored candles to display properly.
Impulse freshness, band width dynamics, and momentum normalization outweigh isolated price movements.
Signal Logic & Visual Cues
Impulse Trend Levels presents two primary interaction signals:
Buy Signal (▲) : Green label appears when trend state switches from bearish to bullish via upper band crossover, suggesting momentum shift to upside.
Sell Signal (▼) : Red label displays when trend state switches from bullish to bearish via lower band crossunder, indicating momentum shift to downside.
Retest detection provides secondary confirmation when price revisits inner band boundaries after signal buffer cooldown expires.
Alert generation covers trend state switches (long/short), retest occurrences, and impulse freshness decay below 50% threshold for systematic monitoring.
Strategy Integration
Impulse Trend Levels fits within momentum-informed and adaptive trend-following approaches:
Momentum-Confirmed Entries : Use band crossovers as high-probability trend initiation points where volatility-normalized momentum exceeded threshold.
Freshness-Based Position Sizing : Scale exposure based on impulse freshness - larger positions during fresh impulse periods, reduced sizing as impulse decays.
Band-Width Risk Management : Expect wider price ranges when bands expand during decay, tighter ranges when bands contract during fresh impulse.
Retest-Based Re-entry : Use inner band retests as lower-risk entry opportunities within established trends after initial signal cooldown.
Cloud-Aligned Directional Bias : Favor trades aligning with current trend state rather than counter-trend positions.
Multi-Timeframe Momentum Confirmation : Apply higher-timeframe impulse trend state to filter lower-timeframe entry precision.
Technical Implementation Details
Core Engine : EMA-based baseline with MAD volatility measurement
Impulse Model : Volatility-normalized momentum detection with directional sign capture
Decay System : Exponential decay application (0.8-0.99 range) with freshness conversion
Band Construction : Linear interpolation between min/max multipliers scaled by MAD
Visualization : Gradient-filled cloud zones with bar coloring and signal labels
Signal Logic : State-switch detection with retest buffer and cooldown mechanisms
Performance Profile : Optimized for real-time execution across all timeframes
Optimal Application Parameters
Timeframe Guidance:
1 - 5 min : Micro-trend detection for scalping with responsive impulse settings
15 - 60 min : Intraday momentum tracking with balanced decay characteristics
4H - Daily : Swing-level trend identification with sustained impulse persistence
Suggested Baseline Configuration:
Trend Length : 19
Impulse Lookback : 5
Decay Rate : 0.99
MAD Length : 20
Band Min (Fresh) : 1.5
Band Max (Stale) : 1.9
Signal Buffer Period : 10
Show Trend Cloud : Enabled
Color Bars : Enabled (requires disabling original chart candles in chart settings)
Show Buy/Sell Signals : Enabled
These suggested parameters should be used as a baseline; their effectiveness depends on the asset's volatility profile, momentum characteristics, and preferred signal frequency, so fine-tuning is expected for optimal performance.
Parameter Calibration Notes
Use the following adjustments to refine behavior without altering the core logic:
Excessive signal noise : Increase Trend Length to demand smoother baseline crossovers or increase Impulse Lookback for less reactive momentum detection.
Missed momentum shifts : Decrease Impulse Lookback to capture shorter-term momentum changes or reduce Decay Rate to allow faster impulse fade.
Bands too tight/wide : Adjust Band Min and Band Max multipliers to modify confidence zone thickness across freshness spectrum.
Impulse decays too quickly : Increase Decay Rate toward 0.99 to sustain impulse readings longer between fresh events.
Impulse decays too slowly : Decrease Decay Rate toward 0.8 for faster momentum fade and more frequent band expansion.
Unstable volatility scaling : Increase MAD Length to smooth volatility measurement and reduce sensitivity to short-term spikes.
Too many retest markers : Increase retest cooldown period (55 bars hardcoded) or increase Signal Buffer Period to space out signals.
Adjustments should be incremental and evaluated across multiple session types rather than isolated market conditions.
Performance Characteristics
High Effectiveness:
Trending markets with clear momentum phases and directional persistence
Instruments with consistent volatility characteristics where MAD scaling normalizes effectively
Momentum continuation strategies entering on fresh impulse signals
Trend-following approaches benefiting from adaptive confidence measurement
Reduced Effectiveness:
Choppy, range-bound markets with frequent whipsaw crossovers
Extremely low volatility environments where impulse threshold becomes difficult to breach
News-driven or gapped markets with discontinuous momentum patterns
Mean-reversion dominant conditions where momentum breaches quickly reverse
Consolidation and sideways price action where trend-following methodologies inherently struggle due to lack of sustained directional movement
Integration Guidelines
Confluence : Combine with BOSWaves structure, volume analysis, or traditional trend indicators
Freshness Respect : Trust signals occurring during high impulse freshness periods with contracted bands
Decay Awareness : Reduce position sizing or tighten stops as impulse decays and bands widen
Retest Utilization : Treat inner band retests as continuation confirmation rather than reversal signals
State Discipline : Maintain directional bias aligned with current trend state until opposite band breach occurs
Disclaimer
Impulse Trend Levels is a professional-grade momentum and trend analysis tool. It uses volatility-normalized impulse detection with exponential decay modeling but does not predict future price movements. Results depend on market conditions, volatility characteristics, parameter selection, and disciplined execution. BOSWaves recommends deploying this indicator within a broader analytical framework that incorporates price structure, volume context, and comprehensive risk management. Indicator
