Tide Tracker ZonesTide Tracker Zones – Advanced Trend & Pullback Visualizer
Overview
Tide Tracker Zones is a sophisticated trading tool designed for traders who require clarity, precision, and actionable insights in real time. The indicator converts price action into dynamic trend zones, allowing users to instantly recognize market direction, potential reversals, and low-risk entry opportunities. By visualizing the market in this way, traders can focus on execution rather than deciphering complex charts.
Unlike static indicators, Tide Tracker Zones adapts to market volatility, providing a clear picture of bullish and bearish pressure across multiple timeframes. Its visual design, including color-coded trend zones, a prominent guide line, and carefully placed signals, ensures that market behavior is easy to interpret, making it suitable for scalping, swing trading, and longer-term strategies alike.
How It Works
The indicator relies on dynamic upper and lower bands derived from recent price ranges and a configurable multiplier. These bands expand during volatile periods and contract when price action stabilizes, creating flexible zones that reflect the dominant market tide.
A guide line tracks the active band, serving as a continuous reference for trend direction. Unlike traditional moving averages, the guide line does not clutter the chart but instead provides a subtle, intuitive indication of whether the market is in a bullish or bearish phase. Background shading reinforces this trend visually, highlighting bullish zones in one color and bearish zones in another, so the prevailing market flow is immediately clear.
The system continuously evaluates price relative to the bands to determine trend direction and detect potential reversals. When price crosses a band and flips the trend, the guide line updates, and signals are generated, providing traders with actionable information without overwhelming the chart.
Signals and Pullbacks
Tide Tracker Zones offers visual cues that make entry points more obvious and less speculative. Trend reversal arrows are plotted when the market changes direction: BUY arrows indicate a shift from bearish to bullish, and SELL arrows indicate a shift from bullish to bearish.
The indicator also highlights first pullbacks within an active trend. These pullback dots mark low-risk opportunities to enter a trend in progress, filtered to ensure that only the most relevant signals are displayed. The system uses ATR-based spacing to place arrows and dots vertically on the chart, preventing visual clutter and ensuring readability even during periods of high volatility.
Color-coded zones enhance situational awareness. Bullish zones are displayed in a customizable orange, while bearish zones are shown in green. Transparency is dynamically adjusted to maintain chart clarity while still providing a clear indication of trend strength.
Strategy Integration
Tide Tracker Zones can be used effectively for both trend-following and pullback strategies. Traders may enter positions in the direction of the guide line and colored zone, using trend reversal arrows for confirmation. First pullback dots offer tactical entries with reduced risk, allowing traders to enter a trend after a brief retracement.
Stop-loss levels can be placed just beyond the opposing trend zone, while take-profit targets may be determined using the width of the bands to account for market volatility. The indicator adapts seamlessly across multiple timeframes. Higher timeframes provide context and filter noise, while lower timeframes allow traders to refine entry timing. This makes it a versatile tool for scalping, swing trading, or longer-term positions.
Advanced Techniques
For traders seeking greater precision, Tide Tracker Zones can be combined with volume or momentum indicators to validate signals. Observing the sequence of trend arrows and pullback dots allows users to develop a systematic approach to entries and exits. Monitoring the width and behavior of the bands over time can also provide insights into periods of expanding or contracting volatility, helping traders anticipate market shifts.
Adjustments to the spread length and multiplier allow the indicator to be tuned for different assets and market conditions. By understanding the interaction between the guide line, trend zones, and pullback signals, traders can create a robust framework for decision-making, reducing guesswork and improving consistency.
Why Use Tide Tracker Zones
Tide Tracker Zones provides instant clarity and actionable insight in any market. Its dynamic zones and guide line give a clear visual understanding of trend direction, while trend reversal arrows and pullback dots highlight potential entry points. Unlike traditional indicators, it adapts to volatility and changing conditions, making it reliable across multiple asset classes and timeframes.
By combining trend detection, pullback analysis, and intuitive visual guidance, Tide Tracker Zones equips traders with a complete framework for disciplined, confident trading, transforming complex price action into a visual map of opportunity.
Trend
SigmoidCycle Oscillator [LuminoAlgo]Purpose:
The SineCycle Oscillator measures price momentum using sigmoid function mathematics (S-curve transformation) borrowed from neural network theory. It generates an oscillator that fluctuates around 1.0, identifying momentum shifts and potential reversal points.
Mathematical Foundation:
This indicator applies the sigmoid logistic function concept: y = 1/(1+e^-x) , which creates an S-shaped curve. In financial markets context, this transformation:
- Maps price changes to a bounded range (-1 to +1)
- Provides non-linear sensitivity (high near zero, low at extremes)
- Naturally filters outliers without lag penalty
Calculation Process:
1. Statistical Normalization: Price deviations are measured from a moving average baseline and scaled by recent volatility (standard deviation over N periods)
2. Sigmoid Transformation: Normalized values undergo S-curve transformation, which weights small movements linearly but compresses large movements logarithmically
3. Dual Timeframe Analysis:
• Short window: User-defined period (N)
• Long window: Double period (2N)
• Ratio calculation: Short sigmoid average ÷ Long sigmoid average
4. Volatility-Weighted Smoothing: Final values use exponential smoothing where the smoothing factor adjusts based on the coefficient of variation (volatility/mean ratio)
What Makes This Different:
Unlike linear momentum oscillators (RSI, Stochastic) that use fixed mathematical relationships, the sigmoid transformation creates variable sensitivity zones. This mimics how professional traders mentally weight price movements.
Trading Application:
Signal Types:
- Momentum: Green (>1.0) = bullish, Red (<1.0) = bearish
- Reversals: 1.0 line crosses with volume confirmation
- Divergence: Price makes new high/low, oscillator doesn't
- Exhaustion: Extended readings (>1.2 or <0.8) suggest overextension
Optimal Conditions:
- Works best: Trending markets with clear swings
- Avoid: Low volume, ranging markets under 1% daily movement
- Timeframes: 4H and above for reliability
Parameter Guidelines:
- Length 8-10: Day trading (expect more whipsaws)
- Length 14-20: Swing trading (balanced signals)
- Length 25-30: Position trading (fewer, stronger signals)
Limitations:
- Lag increases with higher length settings
- Can give false signals during news-driven spikes
- Requires additional confirmation in choppy markets
Trading Framework:
Based on momentum persistence theory - assumes trends continue until sigmoid curve flattens (indicating momentum exhaustion). The mathematical model captures both mean reversion (extreme readings) and trend following (mid-range readings) characteristics.
VWAP For Loop [BackQuant]VWAP For Loop
What this tool does—in one sentence
A volume-weighted trend gauge that anchors VWAP to a calendar period (day/week/month/quarter/year) and then scores the persistence of that VWAP trend with a simple for-loop “breadth” count; the result is a clean, threshold-driven oscillator plus an optional VWAP overlay and alerts.
Plain-English overview
Instead of judging raw price alone, this indicator focuses on anchored VWAP —the market’s average price paid during your chosen institutional period. It then asks a simple question across a configurable set of lookback steps: “Is the current anchored VWAP higher than it was i bars ago—or lower?” Each “yes” adds +1, each “no” adds −1. Summing those answers creates a score that reflects how consistently the volume-weighted trend has been rising or falling. Extreme positive scores imply persistent, broad strength; deeply negative scores imply persistent weakness. Crossing predefined thresholds produces objective long/short events and color-coded context.
Under the hood
• Anchoring — VWAP using hlc3 × volume resets exactly when the selected period rolls:
Day → session change, Week → new week, Month → new month, Quarter/Year → calendar quarter/year.
• For-loop scoring — For lag steps i = , compare today’s VWAP to VWAP .
– If VWAP > VWAP , add +1.
– Else, add −1.
The final score ∈ , where N = (end − start + 1). With defaults (1→45), N = 45.
• Signal logic (stateful)
– Long when score > upper (e.g., > 40 with N = 45 → VWAP higher than ~89% of checked lags).
– Short on crossunder of lower (e.g., dropping below −10).
– A compact state variable ( out ) holds the current regime: +1 (long), −1 (short), otherwise unchanged. This “stickiness” avoids constant flipping between bars without sufficient evidence.
Why VWAP + a breadth score?
• VWAP aggregates both price and volume—where participants actually traded.
• The breadth-style count rewards consistency of the anchored trend, not one-off spikes.
• Thresholds give you binary structure when you need it (alerts, automation), without complex math.
What you’ll see on the chart
• Sub-pane oscillator — The for-loop score line, colored by regime (long/short/neutral).
• Main-pane VWAP (optional) — Even though the indicator runs off-chart, the anchored VWAP can be overlaid on price (toggle visibility and whether it inherits trend colors).
• Threshold guides — Horizontal lines for the long/short bands (toggle).
• Cosmetics — Optional candle painting and background shading by regime; adjustable line width and colors.
Input map (quick reference)
• VWAP Anchor Period — Day, Week, Month, Quarter, Year.
• Calculation Start/End — The for-loop lag window . With 1→45, you evaluate 45 comparisons.
• Long/Short Thresholds — Default upper=40, lower=−10 (asymmetric by design; see below).
• UI/Style — Show thresholds, paint candles, background color, line width, VWAP visibility and coloring, custom long/short colors.
Interpreting the score
• Near +N — Current anchored VWAP is above most historical VWAP checkpoints in the window → entrenched strength.
• Near −N — Current anchored VWAP is below most checkpoints → entrenched weakness.
• Between — Mixed, choppy, or transitioning regimes; use thresholds to avoid reacting to noise.
Why the asymmetric default thresholds?
• Long = score > upper (40) — Demands unusually broad upside persistence before declaring “long regime.”
• Short = crossunder lower (−10) — Triggers only on downward momentum events (a fresh breach), not merely being below −10. This combination tends to:
– Capture sustained uptrends only when they’re very strong.
– Flag downside turns as they occur, rather than waiting for an extreme negative breadth.
Tuning guide
Choose an anchor that matches your horizon
– Intraday scalps : Day anchor on intraday charts.
– Swing/position : Month or Quarter anchor on 1h/4h/D charts to capture institutional cycles.
Pick the for-loop window
– Larger N (bigger end) = stronger evidence requirement, smoother oscillator.
– Smaller N = faster, more reactive score.
Set achievable thresholds
– Ensure upper ≤ N and lower ≥ −N ; if N=30, an upper of 40 can never trigger.
– Symmetric setups (e.g., +20/−20) are fine if you want balanced behavior.
Match visuals to intent
– Enabling VWAP coloring lets you see regime directly on price.
– Background shading is useful for discretionary reading; turn it off for cleaner automation displays.
Playbook examples
• Trend confirmation with disciplined entries — On Month anchor, N=45, upper=38–42: when the long regime engages, use pullbacks toward anchored VWAP on the main pane for entries, with stops just beyond VWAP or a recent swing.
• Downside transition detection — Keep lower around −8…−12 and watch for crossunders; combine with price losing anchored VWAP to validate risk-off.
• Intraday bias filter — Day anchor on a 5–15m chart, N=20–30, upper ~ 16–20, lower ~ −6…−10. Only take longs while score is positive and above a midline you define (e.g., 0), and shorts only after a genuine crossunder.
Behavior around resets (important)
Anchored VWAP is hard-reset each period. Immediately after a reset, the series can be young and comparisons to pre-reset values may span two periods. If you prefer within-period evaluation only, choose end small enough not to bridge typical period length on your timeframe, or accept that the breadth test intentionally spans regimes.
Alerts included
• VWAP FL Long — Fires when the long condition is true (score > upper and not in short).
• VWAP FL Short — Fires on crossunder of the lower threshold (event-driven).
Messages include {{ticker}} and {{interval}} placeholders for routing.
Strengths
• Simple, transparent math — Easy to reason about and validate.
• Volume-aware by construction — Decisions reference VWAP, not just price.
• Robust to single-bar noise — Needs many lags to agree before flipping state (by design, via thresholds and the stateful output).
Limitations & cautions
• Threshold feasibility — If N < upper or |lower| > N, signals will never trigger; always cross-check N.
• Path dependence — The state variable persists until a new event; if you want frequent re-evaluation, lower thresholds or reduce N.
• Regime changes — Calendar resets can produce early ambiguity; expect a few bars for the breadth to mature.
• VWAP sensitivity to volume spikes — Large prints can tilt VWAP abruptly; that behavior is intentional in VWAP-based logic.
Suggested starting profiles
• Intraday trend bias : Anchor=Day, N=25 (1→25), upper=18–20, lower=−8, paint candles ON.
• Swing bias : Anchor=Month, N=45 (1→45), upper=38–42, lower=−10, VWAP coloring ON, background OFF.
• Balanced reactivity : Anchor=Week, N=30 (1→30), upper=20–22, lower=−10…−12, symmetric if desired.
Implementation notes
• The indicator runs in a separate pane (oscillator), but VWAP itself is drawn on price using forced overlay so you can see interactions (touches, reclaim/loss).
• HLC3 is used for VWAP price; that’s a common choice to dampen wick noise while still reflecting intrabar range.
• For-loop cap is kept modest (≤50) for performance and clarity.
How to use this responsibly
Treat the oscillator as a bias and persistence meter . Combine it with your entry framework (structure breaks, liquidity zones, higher-timeframe context) and risk controls. The design emphasizes clarity over complexity—its edge is in how strictly it demands agreement before declaring a regime, not in predicting specific turns.
Summary
VWAP For Loop distills the question “How broadly is the anchored, volume-weighted trend advancing or retreating?” into a single, thresholded score you can read at a glance, alert on, and color through your chart. With careful anchoring and thresholds sized to your window length, it becomes a pragmatic bias filter for both systematic and discretionary workflows.
Scalp Sense AI# Scalp Sense AI (No Repaint)
**Adaptive trend & reversal detector with an AI-driven score, multi-timeframe confirmations, robust volume filters, and a purpose-built Scalping Mode.**
Signals are generated **only on bar close** (no repaint), include structured alert payloads for webhooks, and come with optional ATR-based TP/SL visualization for study and validation.
---
## What it is (in one paragraph)
**Scalp Sense AI** combines classic market structure (DI/ADX, EMA, SMA, Keltner, ATR) with a continuous **AI Score** that fuses RSI normalization, EMA distance (in ATR units), and DI edge into a single, volatility-aware signal. It adaptively gates **trend** and **reversal** entries, applies **HTF confirmation** without lookahead, and enforces **guard rails** (e.g., strong-trend reversal blocking) unless a high-confidence AI override and volume confirmation are present. **Scalping Mode** compresses reaction times and adds micro price-action cues (wick rejections, micro-EMA crosses, small engulfing) to surface more—but disciplined—opportunities.
---
## Non-Repainting Design
* All signals, markers, state, and alerts are computed **after bar close** using `barstate.isconfirmed`.
* HTF data are requested with `lookahead_off`.
* No “future-peeking” constructs are used.
* Result: signals do **not** change after the candle closes.
---
## How the engine works (pipeline overview)
1. **Base metrics**
* **RSI**, **EMA**, **ATR** (+ ATR SMA for regime/volatility), **SMA long & short**, **Keltner** (EMA ± ATR×mult).
* **Manual DI/ADX** for fine control (DM+, DM−, true range smoothing).
2. **Volatility regime**
* Compares ATR to its SMA and scales thresholds by √(ATR/ATR\_SMA) → robust “high\_vol” gating.
3. **Volume & flow**
* **Volume Z-score**, **OBV slope**, and **MFI** (all computed manually) to confirm impulses and filter weak reversals.
4. **Higher-Timeframe confirmation (optional)**
* Imports HTF **PDI/MDI/ADX** and **SMA** (no lookahead) to require alignment when enabled.
5. **AI Score**
* Weighted fusion of **RSI (normalized around 0)**, **EMA distance (in ATR)**, and **DI edge**.
* Smoothed; then its **mean (μ)** and **volatility (σ)** are estimated to form **adaptive bands** (hi/lo), with optional **hysteresis**.
* **Debounce** (M in N bars) avoids flicker; **bias state** persists until truly invalidated.
6. **Signal logic**
* **Trend entries** require AI bias + trend confirmations (DI/ADX/SMA, HTF if enabled), volatility OK, and **anti-breakout** filter.
* **Reversal entries** come in **core**, **early**, and **scalp** flavors (progressively more frequent), guarded by strong-trend blocks that an **AI+volume+ADX-cooling override** can bypass.
7. **Scalping Mode**
* Adaptive parameter contraction (shorter lengths), gentler guards, micro-patterns (wick/engulf/micro-EMA cross), and reduced cooldown to increase high-quality opportunities.
8. **Cooldown & state**
* One signal per side after a configurable spacing in bars; internal “last direction” avoids clustering.
9. **Visualization & alerts**
* **Triangles** for trend, **circles** for reversals (offset by ATR to avoid overlap).
* **Single-line alert payload** (BUY/SELL, reason, AI, volZ, ADX) ready for webhooks.
---
## Signals & visualization
* **Trend Long/Short** → triangle markers (above/below) when:
* AI bias aligns with trend confirmations (DI edge, ADX above threshold, price vs long SMA, optional HTF alignment).
* Volatility regime agrees; **anti-breakout** prevents entries exactly at lookback highs/lows.
* **Reversal Long/Short** → circular markers when:
* **Core**: AI near “loose” band, OBV/MFI/volZ supportive, ADX cooling, DI spread relaxed, PA confirms (crosses/div).
* **Early**: anticipatory patterns (Keltner exhaustion, simple RSI “quasi-divergence”).
* **Scalp**: micro-EMA cross, wick rejection, mini-engulfing, with relaxed guards but AI/volume still in the loop.
* **Markers appear only on the bar that actually emitted the signal** (no repaint); offsets use ATR so shapes don’t overlap.
---
## Alerts (ready for webhooks)
Enable “**Any alert() function call**” and you’ll receive compact, single-line payloads once per bar:
```
action=BUY;reason=reversal-early;ai=0.1375;volZ=0.82;adx=27.5
action=SELL;reason=trend;ai=-0.2210;volZ=0.43;adx=31.9
```
* `action`: BUY / SELL
* `reason`: `trend` | `reversal-core` | `reversal-early` | `reversal-scalp`
* `ai`: current smoothed AI Score at signal bar
* `volZ`: volume Z-score
* `adx`: current ADX
---
## Inputs (exhaustive)
### 1) Core Inputs
* **RSI Length (Base)** (`rsi_length_base`, int)
Base RSI lookback. Shorter = more reactive; longer = smoother.
* **RSI Overbought Threshold** (`rsi_overbought`, int)
Informational for context; RSI is used normalized in the AI fusion.
* **RSI Oversold Threshold** (`rsi_oversold`, int)
Informational; complements visual context.
* **EMA Length (Base)** (`ema_length_base`, int)
Primary adaptive mean; also used for Keltner mid and distance metric.
* **ATR Length (Base)** (`atr_length_base`, int)
Volatility unit for Keltner, SL/TP (debug), and regime detection.
* **ATR SMA Length** (`atr_sma_len`, int)
Smooth baseline for ATR regime; supports “high\_vol” logic.
* **ATR Multiplier Base** (`atr_mult_base`, float)
Scales volatility gating (sqrt-scaled); higher = tighter high-vol requirement.
* **Disable Volatility Filter** (`disable_volatility_check`, bool)
Bypass volatility gating if true.
* **Price Change Period (bars)** (`price_change_period_base`, int)
Simple momentum check (+/−% over N bars) used in trend validation.
* **Base Cooldown Bars Between Signals** (`signal_cooldown_base`, int ≥ 0)
Minimum bars to wait between signals (per side).
* **Trend Confirmation Bars** (`trend_confirm_bars`, int ≥ 1)
Require persistence above/below long SMA for this many bars.
* **Use Higher Timeframe Confirmation** (`use_higher_tf`, bool)
Turn on/off HTF alignment (no repaint).
* **Higher Timeframe for Confirmation** (`higher_tf`, timeframe)
E.g., “60” to confirm M15 with H1; used for HTF PDI/MDI/ADX and SMA.
* **TP as ATR Multiple** (`tp_atr_mult`, float)
For **visual debug** only (drawn after entries); not an order manager.
* **SL as ATR Multiple** (`sl_atr_mult`, float)
For visual debug only.
* **Enable Scalping Mode** (`scalping_mode`, bool)
Compresses lengths/thresholds, unlocks micro-PA modules, reduces cooldown.
* **Show Debug Lines** (`show_debug`, bool)
Plots AI bands, DI/ADX, EMA/SMA, Keltner, vol metrics, and TP/SL (debug).
### 2) AI Score & Thresholds
* **AI Score Smooth Len** (`ai_len`, int)
EMA smoothing over the raw fusion.
* **AI Volatility Window** (`ai_sigma_len`, int)
Window to estimate AI mean (μ) and standard deviation (σ).
* **K High (sigma)** (`ai_k_hi`, float)
Upper band width (σ multiplier) for strong threshold.
* **K Low (sigma)** (`ai_k_lo`, float)
Lower band width (σ multiplier) for loose threshold.
* **Debounce Window (bars)** (`ai_debounce_m`, int ≥ 1)
Rolling window length used by the confirm counter.
* **Min Bars>Thr in Window** (`ai_debounce_n`, int ≥ 1)
Minimum confirmations inside the debounce window to validate a state.
* **Use Hysteresis Thresholds** (`ai_hysteresis`, bool)
Requires crossing back past a looser band to exit bias → fewer whipsaws.
* **Weight DI Edge (0–1)** (`ai_weight_di`, float)
Importance of DI edge within the fusion.
* **Weight EMA Dist (0–1)** (`ai_weight_ema`, float)
Importance of EMA distance (in ATR units).
* **Weight RSI Norm (0–1)** (`ai_weight_rsi`, float)
Importance of normalized RSI.
* **Sensitivity (0–1)** (`sensitivity`, float)
Contracts/expands bands (higher = more sensitive).
### 3) Volume Filters
* **Volume MA Length** (`vol_ma_len`, int)
Baseline for volume Z-score.
* **Volume Z-Score Window** (`vol_z_len`, int)
Std-dev window for Z-score; larger = fewer volume “spikes”.
* **Reversal: Min Volume Z for confirm** (`vol_rev_min_z`, float)
Minimum Z required to validate reversals (adaptively relaxed in scalping).
* **OBV Slope Lookback** (`obv_slope_len`, int)
Rising/falling OBV over this window supports bull/bear confirmations.
* **MFI Length** (`mfi_len`, int)
Money Flow Index lookback (manual calculation).
### 4) Filters (Breakout / ADX / Reversal)
* **Enable Breakout Filter** (`enable_breakout_fil`, bool)
Avoid trend entries at lookback highs/lows.
* **Breakout Lookback Bars** (`breakout_lookback`, int ≥ 1)
Window for the anti-breakout guard.
* **Base ADX Length** (`adx_length_base`, int)
Lookback for DI/ADX smoothing (also adapted in Scalping Mode).
* **Base ADX Threshold** (`adx_threshold_base`, float)
Minimum ADX to validate trend context (scaled in Scalping Mode).
* **Enable Reversal Filter** (`enable_rev_filter`, bool)
Master switch for reversal logic.
* **Max ADX for Reversal** (`rev_adx_max`, float)
Hard cap: above this ADX, reversals are blocked (unless overridden by AI if allowed in Guards).
### 5) Reversal Guard (regime protection & overrides)
* **Strong Trend: ADX add-above Thr** (`guard_adx_add`, float)
Extra ADX above `adx_threshold` to mark “strong” trend.
* **Strong Trend: min DI spread** (`guard_spread_min`, float)
Minimum DI separation to consider a trend “dominant”.
* **Require ADX drop from window max (%)** (`guard_adx_drop_min_pct`, float 0–1)
ADX must drop at least this fraction from its window maximum to consider “cooling”.
* **Regime Window (bars)** (`guard_regime_len`, int ≥ 10)
Window over which ADX max is measured for the “cooling” check.
* **EMA Slope Lookback** (`guard_slope_len`, int ≥ 2)
EMA slope horizon used alongside Keltner for strong-trend identification.
* **Keltner Mult (ATR)** (`guard_kc_mult`, float)
Keltner width for strong trend bands and exhaustion checks.
* **HTF Reversal Block Mode** (`htf_block_mode`, string: `Off` | `On` | `AI-controlled`)
* `Off`: never block by HTF.
* `On`: block reversals whenever HTF is strong.
* `AI-controlled`: block **unless** AI+volume+ADX-cooling override criteria are met.
* **AI-controlled: allow AI override** (`ai_htf_override`, bool)
Enables the override mechanism in `AI-controlled` mode.
* **AI override multiplier (vs band\_hi)** (`ai_override_mult`, float)
Strength needed beyond the high band to count as “strong AI”.
* **AI override: min bars beyond strong thr** (`ai_override_min_bars`, int ≥ 1)
Debounce on the override itself.
### 6) Markers
* **Reversal Circle ATR Offset** (`rev_marker_offset_atr`, float ≥ 0)
Vertical offset for reversal circles; trend triangles use a separate (internal) offset.
### 7) Scalping Mode Tuning
* **Reversal aggressiveness (0–1)** (`scalp_rev_aggr`, float)
Higher = looser guards and stronger AI sensitivity.
* **Wick: body multiple (bull/bear)** (`scalp_wick_body_mult`, float)
Wick must be at least this multiple of body to count as rejection.
* **Wick: ATR multiple (min)** (`scalp_wick_atr_mult`, float)
Minimal wick length in ATR units.
* **Micro EMA factor (vs EMA base)** (`scalp_ema_fast_factor`, float 0.2–0.9)
Fast EMA length = base EMA × factor (rounded/int).
* **Relax breakout filter in scalping** (`scalp_breakout_relax`, bool)
Lets more trend entries through in scalping context.
### 8) ICT-style SMA (bases)
* **ICT SMA Long Length (Base)** (`sma_long_len_base`, int)
Long-term baseline for regime/trend.
* **ICT SMA Short1 Length (Base)** (`sma_short1_len_base`, int)
Short baseline for price-action crosses.
* **ICT SMA Short2 Length (Base)** (`sma_short2_len_base`, int)
Companion short baseline used in PA cross checks.
> **Adaptive “effective” values:** When **Scalping Mode** is ON, the script internally shortens multiple lengths (RSI/EMA/ATR/ADX/μσ windows, SMAs) and gently relaxes guards (ADX drop %, DI spread, volume Z, override thresholds), reduces cooldown/confirm bars, and optionally relaxes the breakout filter—so you get **more frequent but still curated** signals.
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## Plots & debug (optional)
* DI+/DI−, ADX (curr + HTF), EMA, long SMA, Keltner up/down (when strong), AI Score, AI mean, AI bands (hi/lo; low plots only when hysteresis is on), Volume MA and Z-score, and ATR-based TP/SL guide (after entries).
* These are **study aids**; the indicator does not manage trades.
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## Recommended use
* **Timeframes**:
* Scalping Mode: M1–M15.
* Standard Mode: M15–H1 (or higher).
* **Markets**: Designed for liquid FX, indices, metals, and large-cap crypto.
* **Chart type**: Standard candles recommended (Heikin-Ashi alters inputs and hence signals).
* **Alerts**: Use “Any alert() function call”. Parse the key/value payloads server-side.
---
## Good to know
* **Why some alerts don’t draw shapes retroactively**: markers are drawn **only on** the bar that emitted the signal (no repaint by design).
* **Why a reversal didn’t fire**: strong-trend guards + HTF block may have been active; check ADX, DI spread, Keltner position, EMA slope, and whether AI override criteria were met.
* **Too many / too few signals**: tune **Scalping Mode**, `signal_cooldown_base`, AI bands (`ai_k_hi/lo`, `sensitivity`), volume Z (`vol_rev_min_z`), and guards (`rev_adx_max`, `guard_*`).
---
## Disclaimer
This is an **indicator**, not a strategy or an execution system. It does not place, modify, or manage orders. Markets carry risk—validate on historical data and demo before any live decisions. No performance claims are made.
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### Version
**Scalp Sense AI v11.5** — Adaptive AI bands with hysteresis/debounce, HTF no-lookahead confirmations, guarded reversal logic with AI override, full volume suite (Z, OBV slope, MFI), anti-breakout filter, and a dedicated Scalping Mode with micro-PA cues.
Forecasting Quadratic Regression [UPDATED V6] Forecasting Quadratic Regression applies a second-degree polynomial regression model to price data, offering a non-linear alternative to traditional linear regression. By fitting a quadratic curve of the form:
y=a+bx+cx2
the indicator captures both directional trend and curvature, allowing traders to detect momentum shifts earlier than with straight-line models.
🔹 Core Features
Fits a quadratic regression curve to user-defined lookback periods
Extends the fitted curve forward to generate forecast projections
Calculates slope curvature to highlight trend acceleration or deceleration
Adapts dynamically as new bars are added
🔹 Trading Applications
Identify potential reversal zones when the curve inflects (2nd derivative sign change)
Forecast near-term mean reversion targets or extended trend continuations
Filter trades by measuring momentum curvature rather than linear slope
Visualize higher-order structure in price beyond standard regression lines
⚠️ Note: This model is statistical and assumes past curvature informs short-term future price paths. It should be combined with confirmation signals (volume, oscillators, support/resistance) to reduce false inflection points.
Zenith by JaeheeZenith (Invite-Only)
Overview
• This indicator is a trend-following, regime-aware signal tool designed to surface actionable long/short entries only when multiple, independent conditions align.
• It emphasizes trend initiation (not late trend chasing) and provides structured take-profit (TP1/TP2/TP3) cues when momentum weakens after entry.
• It is an indicator (not a strategy). It does not place trades, manage orders, or guarantee outcomes.
What makes it different
• Regime windowing: Signals are permitted only shortly after a regime flip and only if trend quality conditions persist (streak). This reduces signals that arrive too late in mature trends.
• Multi-filter consensus: Trend EMA slope/position, RSI state/slope, ADX/DI separation, volume expansion, and optional structure break (HH/LL) must agree before any entry is considered.
• Volatility & squeeze awareness: A TTM-style squeeze gate avoids chasing during compression unless a valid release is detected.
• Momentum-based TPs: After a valid entry, RSI divergence at confirmed pivots defines TP1→TP3 in the trend direction (price makes a new extreme while RSI momentum fails to confirm).
• Minimal repaint design: Signals and TPs are formed on confirmed pivots and bar close logic; HTF requests use lookahead_off. (See “Repainting & calculation notes.”)
How it works (signal engine)
• Trend filter:
• Baseline EMA and its slope define directional bias (price vs baseline, rising/falling baseline).
• RSI state & slope:
• RSI must be above/below its midpoint and (optionally) rising/falling to validate momentum alignment.
• Directional strength (ADX/DI):
• ADX must exceed a minimum; DI+ vs DI− alignment confirms directional pressure.
• Liquidity/participation:
• Volume must exceed its SMA×mult to avoid low-quality moves.
• Structure confirmation (optional):
• Break of recent highs/lows (windowed) helps filter range noise.
• Squeeze gate:
• During BB-inside-KC compression, entries are held back unless a valid release (KC breakout) or ATR expansion is present.
• Regime window:
• After Long/Short pass flips from 0→1, entries are allowed for a limited number of bars (window) and only after a streak (N consecutive bars meeting conditions).
• HTF alignment (optional):
• Higher-timeframe EMA trend must agree with the local setup (no lookahead).
Signals & labels
• Entry labels:
• Long Entry = “Long Entry” (below bar)
• Short Entry = “Short Entry” (above bar)
• Shapes:
• Diamonds mark entry points; optional “Macro-only” mode shows only regime-grade signals.
• Visual ribbon:
• A gradient band around the baseline provides context for volatility and bias; it does not alter signal logic.
Take-Profit framework (momentum weakening)
• After a Long Entry, the script tracks confirmed price pivot highs vs confirmed RSI pivot highs:
• TP trigger (Long): new price pivot high higher than prior, but RSI pivot high lower → bearish divergence (momentum weakening).
• Ordering: TP2 must print above TP1; TP3 must print above TP1/TP2.
• After a Short Entry, the script tracks confirmed price pivot lows vs confirmed RSI pivot lows:
• TP trigger (Short): new price pivot low lower than prior, but RSI pivot low higher → bullish divergence.
• Ordering: TP2 must print below TP1; TP3 must print below TP1/TP2.
• Why divergence?
• It captures fading momentum within an ongoing move, enabling staged partial exits without predicting tops/bottoms.
How traders typically use it
• Discretionary entries with rules:
• Confirm on bar close to avoid intrabar flips.
• Favor higher-timeframes for reliability; in practice, the 1-hour chart has been a balanced choice between responsiveness and noise.
• Risk & exits:
• Combine the indicator’s entries with independent risk management (fixed/ATR stops, volatility-scaled sizing).
• Use TP1→TP3 for partials; trail the remainder by structure/ATR or your preferred method.
Why it can add value (without hype)
• Noise rejection: By requiring simultaneous agreement across trend, momentum, participation, and compression, many low-quality whipsaws are filtered out.
• Timeliness: Limiting signal eligibility to a post-flip window seeks to capture the early phase of regime change instead of late escalations.
• Clarity: The gradient ribbon and explicit labels (“Long Entry”, “Short Entry”, “TP1–TP3”) make execution rules transparent and repeatable.
• Adaptability: Inputs (RSI length/midline, ADX/DI thresholds, squeeze, HTF alignment, structure, window/streak sizes) allow tuning for symbols/timeframes.
Best practices (recommended use)
① Confirm on bar close
• Signals can change intrabar; execute after the bar has closed.
② Validate across multiple timeframes
• Although the tool adapts to volatility, reliability improves on higher timeframes.
• In practice, the 1-hour chart has shown a stable balance between reactivity and noise.
③ Align with ribbon bias
• Trade in the same direction as the ribbon/baseline slope to reduce counter-trend exposure.
④ Combine with independent risk management
• Use stop-losses, position sizing, or ATR-based targets outside the script.
⑤ Use as confirmation, not prediction
• Treat entries as confirmation of regime change, not as a forecast of future price.
Inputs you may care about
• Trend/Structure: EMA length, slope lookback, structure window, cooldown bars.
• Momentum: RSI length/midline, rising/falling filter, ADX length/min, DI separation.
• Participation: Volume SMA length & multiplier.
• Compression: BB/KC lengths & multipliers; require-release toggle.
• Regime quality: Flip window, streak size, ATR expansion vs baseline, max extension (ATR×), optional ADX rising, optional HTF alignment.
• TP controls: Enable/disable per side, max TP count (1–3), label offset/color.
• Visuals: EMA and ribbon display, diamond sizes, optional vertical lines.
Repainting & calculation notes
• No future-bar references: The script does not use future data. HTF calls use barmerge.lookahead_off.
• Pivot confirmation: Entries and TPs use confirmed pivots (pivotRight bars later). Labels are placed at the pivot bar index once confirmed.
• Intrabar updates: Values can update before the bar closes; confirm on close for decisions.
• HTF security: Higher-timeframe values are requested without lookahead; still, HTF bars finalize only when the HTF bar closes.
Limitations & responsible use
• Not financial advice. No guarantees of profitability; markets involve risk.
• Not a strategy. It does not place, manage, or cancel orders; you must supply risk controls.
• Parameter sensitivity. Different symbols/timeframes may require tuning.
• Divergence scarcity. TP1–TP3 are divergence-based; in strong trends without momentum fade, fewer TP signals will occur.
Disclaimer
• This indicator is provided for educational and informational purposes only.
• It does not guarantee profits, predict future prices, or replace independent judgment.
• Trading involves risk, and all decisions remain solely the responsibility of the user.
• By using this tool, you acknowledge that it is intended as a study aid within TradingView, not as financial advice or an automated trading system.
Ultron Indicator BTCUSDT Ultron BTCUSDT Indicator (invite-only).
• Clear trend & reversion signals
• Next-bar execution parity and frozen TSL visuals
• Run on 4hr Binance BTCUSDT chart
• Risk sizing that uses your equity input
Usage: Add to chart → Settings → Inputs → set “Your Current Trading Equity (USD)”.
⚠️ Software tool for educational/informational use only. Not financial advice.
Past performance is not indicative of future results. You are responsible for your trades.
The Oracle by JaeheeThe Oracle
Summary
The Oracle is a volatility-adaptive trend indicator built on a smoothed range filter, persistence counters, and regime-flip logic. Signals appear only when price establishes a sustained move and flips from one regime to the other. An EMA(50)-anchored ribbon provides a flowing visual context but does not drive signals.
What it does
① Calculates a smoothed volatility-based range to adapt to market conditions
② Builds a filtered price path that reduces single-bar noise
③ Tracks persistence of upward or downward filter movement with counters
④ Confirms Buy/Sell signals only on regime flips, not on single ticks
⑤ Draws a multi-phase ribbon around EMA(50) to visualize slope and bias
How it works (concept level)
① Smoothed Range: Double EMA of absolute price change, scaled by multiplier
② Filtered Price: Range filter constrains price movement to reduce noise
③ Persistence Counters: Upward/Downward counters accumulate only if the filter continues in one direction
④ Signal Logic:
• Buy = price above filter AND prior regime was short
• Sell = price below filter AND prior regime was long
• Requires a full flip of state to confirm new signals
⑤ Ribbon: EMA(50) baseline with sinusoidal offsets creates a flowing ribbon, colored by EMA slope (visual only)
Why it is useful
① Noise resistance: Avoids whipsaws by requiring persistence + state flips
② Clarity: Ribbon visually encodes background trend for quick recognition
③ Balanced design: Combines volatility adaptation, persistence, and confirmation in one framework
④ Adaptable: Works across assets and timeframes without heavy parameter tuning
How to use it
① Signal reading:
• ✧ Buy marker = confirmed transition into an upward regime
• ✧ Sell marker = confirmed transition into a downward regime
• Use bar close confirmation
② Ribbon context: Align trades with ribbon slope/color to stay with the dominant trend
③ Timeframes:
• Higher (4H, Daily) = better swing bias
• Lower (5m, 15m) = faster signals but noisier
④ Combination: Pair with ATR stops, position sizing, or volume/momentum studies for added confirmation
Limitations
① Still possible to see false flips in choppy consolidations
② Smoothing introduces slight delay in regime confirmation
③ Signals can repaint intrabar — confirm on bar close
④ Indicator only — no built-in money management or strategy logic
Best Practices (Recommended Use)
① Confirm on bar close
• Signals can change intrabar; always make decisions after the bar has closed.
② Validate across multiple timeframes
• Although the tool adapts to volatility, reliability improves on higher timeframes.
• In practice, the 1-hour chart has shown the most stable balance between reactivity and noise.
③ Align with ribbon bias
• Trade in the same direction as the ribbon slope/color to reduce countertrend exposure.
④ Combine with independent risk management
• Use stop-losses, position sizing, or ATR-based targets outside the script.
• The indicator highlights transitions, but risk control must be user-defined.
⑤ Use as confirmation, not prediction
• Treat signals as confirmation of regime change, not as a forecast of future price.
EMA Trend Regime Filter by JaeheeOverview
This indicator defines bullish/bearish regimes using a five-EMA stack and emits one signal per confirmed regime flip. Optional ATR gap gating and an ADX gate require structure and strength before a switch is confirmed. An optional, subtle center line improves readability. This is not a strategy and it does not execute trades.
Note: This tool is not the ATR-based Supertrend; it uses EMA stacking with ATR/ADX gating.
Why this combination (originality & value)
• EMA stacking provides a clear directional framework.
• ATR gap gating filters compressed/fragile stacks by requiring each adjacent EMA distance to exceed ATR × multiplier.
• A state machine limits signals to one per direction change, reducing alert fatigue.
• Confirm bars + ADX gate elevate the quality of regime recognition under directional pressure.
Together, these components interact to emphasize durable regime shifts while curbing noise typical of sideways phases.
How it works (concept)
EMA stack: Bullish when EMA1 > EMA2 > EMA3 > EMA4 > EMA5; bearish is the reverse.
ATR spacing (optional): When enabled, each EMA gap must exceed ATR × k to qualify for a flip.
Confirmation streak: Conditions must persist for confirmBars before a flip is validated.
Trend-strength gate: A flip is allowed only when ADX ≥ adxMin.
Flip & signal: On validation, a single marker/label is emitted; duplicates are suppressed.
Visual layer (optional): Subtle background/center line for context; visuals do not affect logic.
Why it’s useful
• Regime clarity: A binary bullish/bearish state reduces decision fatigue and aligns your playbook with market context.
• Counter-trend filter: In a bullish regime, counter-trend shorts are discouraged; in a bearish regime, counter-trend longs are discouraged—until the regime flips.
• Signal economy: One signal per confirmed flip helps avoid alert fatigue and over-trading.
• Volatility awareness: ATR gap gating filters compressed EMA stacks that often precede whipsaws.
• Strength confirmation: The ADX gate requires directional pressure before a switch is allowed.
Practical workflows (how it can be used)
• HTF compass (e.g., H4): Use a higher timeframe such as the 4-hour chart to set directional bias; execute on your lower timeframe with your own triggers and risk rules.
• Alignment rule: Trade in the direction of the active regime—prefer long setups during a bullish regime and short setups during a bearish regime—until a confirmed flip occurs.
• Pullback playbook: In a bullish regime, consider pullbacks to structure/MA confluence; in a bearish regime, consider rallies into resistance. Always size risk independently of the indicator.
• Parameter tuning: Adapt confirmBars, ATR × multiplier, and ADX minimum to the instrument’s volatility. Higher thresholds generally reduce noise but may delay flips.
• Alerts/automation: Set alerts on regime flips but confirm on bar close; intrabar values can update.
Context note (BTC, H4)
On higher timeframes such as the 4-hour chart, trends are often more stable. For BTC, the regime can help distinguish whether the broader market is trending up or down: when the H4 regime is bullish, favor long-side opportunities even if lower-timeframe candles retrace; when the regime turns bearish, favor short-side opportunities. This is context, not signals—entries/exits and risk management remain your responsibility.
Key inputs
• EMA lengths (1–5), Confirm Bars, Min Spacing by ATR
• ADX Length, ADX Minimum
• Visualization toggles (background opacity, center line, label/marker colors)
Alerts
• EMA REGIME LONG — fires once on a confirmed bullish regime
• EMA REGIME SHORT — fires once on a confirmed bearish regime
Notes & limitations
• Designed without future-bar references. Values can update intrabar, so confirm on close before acting on signals.
• This is an indicator for study purposes; it does not place trades.
• Parameters may require tuning across symbols/timeframes.
• Publish with a clean chart so the indicator’s output is clearly identifiable.
• Use on standard bar types (e.g., candles). Non-standard chart types can yield unrealistic behavior for signal logic.
ALMA & UT Bot Confluence StrategyALMA & UT Bot Confluence Strategy
This is a comprehensive trend-following and momentum strategy designed to identify high-probability trade setups by combining multiple layers of confirmation. It is built around an ALMA (Arnaud Legoux Moving Average) and a long-term EMA, and then enhances signal quality with the popular UT Bot indicator, a Volume Filter, and an adaptive hold mechanism.
The primary goal of this strategy is to filter out market noise, avoid low liquidity traps, and provide more robust and selective trading logic by adapting its timing to changing market volatility.
Key Features and How It Works
This strategy is not a simple crossover system. An entry signal is generated by the confluence of only a few conditions:
Underlying Trend and Signal Engine:
ALMA (Arnaud Legoux Moving Average): Provides a responsive, low-latency signal line for entries. EMA (Exponential Moving Average): A longer-term EMA acts as a primary trend filter, ensuring trades are executed only in line with the overall market trend.
Confirmation Layer:
UT Bot Confirmation: A trade is considered valid only when the UT Bot indicator provides a relevant buy or sell signal. This acts as a strong secondary confirmation, reducing false entries.
Advanced Filters for Signal Quality:
Volume Filter: This is an important safety mechanism that prevents trades from being executed in low-volume, illiquid markets where price action can be erratic and unreliable.
Momentum Filter (ADX and RSI): The strategy uses the ADX to check for sufficient market momentum and the RSI to ensure it doesn't enter overbought/oversold zones.
Volatility Filter (Bollinger Bands): This helps prevent entries when the price deviates too far from its average, preventing "buying at the top" or "selling at the bottom." Adaptive Timing (Dynamic Cool-Down):
Instead of a fixed waiting period between trades, this strategy uses a dynamic cooling-down period based on the ATR. It automatically waits longer during periods of high volatility (to prevent volatility) and becomes more responsive in calmer markets. How to Use This Strategy:
Long Entry (BUY): When all bullish conditions align, a green "BUY" triangle appears below the price.
Short Entry (SELL): When all bearish conditions align, a red "SELL" triangle appears above the price.
Trend Visualization: The chart background is color-coded according to UT Bot's trend direction (Green for an uptrend, Red for a downtrend), allowing for at-a-glance market analysis.
Double Exit Strategy Options
You have full control over how you exit trades:
Classic SL/TP: Use a standard Stop-Loss and Take-Profit order based on ATR (Average True Range) multipliers. UT Bot Trailing Stop (Recommended): A dynamic exit mechanism that follows the price allows your winning trades to catch up to larger trends while protecting your profits.
Disclaimer
This script is for educational purposes only and should not be construed as financial advice. Past performance is not indicative of future results. All trades involve risk. Before risking any capital, we strongly recommend extensively backtesting this strategy across your preferred assets and timeframes to understand its behavior and find settings that suit your personal trading style.
The author recommends using this strategy with Heikin-Ashi candlesticks. Using this method will significantly increase the strategy's trading success rate and profitability in backtests.
You should change the settings according to your preferred chart time range. You can find the best value for you by observing the value changes you make on the chart.
JJ Thursday Expiry Highlighter - NiftyThursday Expiry Highlighter
This indicator shades the background of all Thursday trading sessions on your chart — ideal for Nifty, Bank Nifty, and other Indian markets where the weekly options expiry typically occurs on Thursdays.
Features:
Highlights entire Thursday columns on any timeframe (intraday or daily).
Adjustable highlight color and transparency for maximum visibility without obscuring candles.
Makes expiry days stand out for quick recognition in both live trading and historical analysis.
Use Cases:
Quickly identify weekly option expiry days for planning.
Visually backtest expiry-day patterns or volatility setups.
Combine with other indicators for expiry-specific strategies.
Disclaimer:
This tool is for educational and informational purposes only. It does not provide financial advice and should not be relied upon as a sole basis for making investment decisions. Market conditions can change, and there is no guarantee of accuracy. Always do your own research and consult a licensed financial professional before trading or investing.
Up On Volume Screener [LevelUp]The Up On Volume Screener is a powerful scanner designed to identify stocks exhibiting strong bullish momentum, characterized by a higher close on the day or week accompanied by a significant spike in trading volume compared to the average. This screener allows traders to customize parameters such as moving average lengths, closing range requirements, and proximity to 52-week highs using multiples of the ATR (average true range).
By pinpointing stocks with robust buying pressure and high volume, the Up On Volume screener helps traders uncover potential breakout opportunities, early trend leaders, and stocks demonstrating relative strength, making it an essential tool for momentum, swing, and growth trading strategies.
🔹 Why Search For Up On Volume?
▪ Confirmation of Bullish Momentum: Stocks that close higher on the day/week signal buying pressure and bullish sentiment throughout the session. This helps traders and investors identify names that are attracting demand, possibly due to news, earnings, or sector strength.
▪ Volume Adds Conviction: When a stock closes up with increased volume, it suggests strong participation behind the move — not just a “head fake” or a thinly traded rally. High volume confirms that institutional players or multiple market participants are involved, which often leads to more reliable price trends.
▪ Early Stage Moves: Daily breakouts can often mark the beginning of a larger trend. Catching stocks on days they close up helps pinpoint emerging leaders and stocks transitioning from accumulation to bullish phases.
▪ Technical Strength: A bullish close (especially in the top half of the day’s price range) is a technical sign of demand. This is a favored criterion in many technical analysis strategies for swing trading, momentum trading, and even fundamental breakouts.
🔹 When Is Up On Volume Screen Most Helpful?
▪ After Market Close: Stocks that show strength and close up on high volume often show continued follow-through in the coming days/weeks.
▪ After Major News/Events: When stocks respond positively to news releases, earnings, or sector movements, searching for those that close up can help you catch momentum before it’s widely recognized.
▪ Trend Days: On days when the market is trending (not sideways or choppy), screening for stocks closing up helps you align with the strongest moves and avoid false signals.
▪ Early in Bullish Cycles: Searching for stocks closing up during the early stage of a market rally or sector rotation can help growth traders get in ahead of sustained upward moves.a
▪ Relative Strength Signals True Leadership: When most stocks decline in a weak market, those that hold firm or rise are showing clear relative strength. This means buyers are stepping in even when the broader mood is negative, often signaling institutional accumulation — these are the names likely to become tomorrow’s winners.
▪ Early Clues to New Cycles: Throughout history, the biggest winners in bull markets often began their runs during corrections and bear phases, not after the headlines turn positive. By focusing on stocks that close green on red days, you’re hunting for companies quietly building buying pressure, poised to break out when the tide turns.
▪ Faster Recoveries and Outperformance: Stocks that resist declines tend to rebound earlier and outpace the broader market once conditions improve. These resilient names frequently end up delivering outsized returns, often leading sector rallies or driving new market themes.
🔹 Screening Features - Setting Your Search Criteria
There are various search options that can be customized.
✓ Volume Gap Up %: Minimum volume percent change over the average volume.
✓ Moving Average: Set length for average volume calculations on daily and weekly timeframes.
✓ Closing Range %: Specify the preferred closing range on the day or week.
✓ Price With X ATR of 52-Week High: Filter for stocks within X ATRs of their 52-week highs.
🔹 Installation And Usage
▪ Mark this indicator as a Favorite.
▪ Use the Pine Screener to search for stocks.
▪ Save the search results to a watchlist.
▪ View the watchlist in TradingView.
🔹 Note
Some high-volume breakout scans rely on proprietary formulas. With this screener, every filter can be researched and verified - no black box! The only variables are price, volume % change, closing range and price within a specified ATR of the 52-week high.
ML Compressor Enhanced Trading Indicator# 🤖 ML Enhanced Trading Indicator - Advanced Market Analysis
## 📊 Overview
This is a comprehensive Machine Learning Enhanced Trading Indicator that combines multiple advanced analytical techniques to provide high-probability trading signals. The indicator uses artificial intelligence, pattern recognition, anomaly detection, and traditional technical analysis to identify optimal entry and exit points in the market.
## 🚀 Key Features
### 🧠 **Machine Learning Core**
- **Advanced Pattern Recognition**: Uses cosine similarity, Pearson correlation, and Spearman rank correlation to identify historical patterns
- **AI-Powered Predictions**: Implements multiple correlation methods to forecast price movements
- **Anomaly Detection**: Z-score based detection system for unusual market activities
- **Signal Confidence Scoring**: Reliability assessment for each trading signal
### 📈 **Technical Analysis Integration**
- **Multi-Timeframe RSI Analysis**: 14 and 21-period RSI with oversold/overbought detection
- **MACD Momentum**: Enhanced MACD histogram analysis for trend confirmation
- **Bollinger Bands Position**: Dynamic position tracking within BB channels
- **Volume Analysis**: Spike and dry volume detection with ratio calculations
- **Trend Strength Measurement**: EMA-based trend power analysis
### 🎯 **Perfect Zone Detection**
- **Ideal Buy Zone**: Identifies perfect buying opportunities when 7 conditions align:
- ML Score ≥ 0.60
- Bottom proximity detection
- RSI in 20-35 range
- Volume spike confirmation
- Positive price anomaly
- Bullish pattern match
- Positive MACD momentum
### 📊 **Comprehensive Display Table**
- **Real-time ML Analysis**: Complete breakdown of all indicators
- **Perfect Buy Conditions Tracker**: Visual checklist with completion percentage
- **Performance Metrics**: Win rate tracking and P&L analysis
- **Signal Strength Indicators**: Confidence levels for each signal
## 🔧 **Customizable Parameters**
### **ML Settings**
- **ML Lookback Period**: 20-500 bars (default: 100)
- **Anomaly Threshold**: 1.0-5.0 sensitivity (default: 2.0)
- **Pattern Similarity**: 0.5-0.99 matching threshold (default: 0.80)
- **AI Lookback Period**: 20-200 bars (default: 50)
### **AI Prediction Models**
- **Correlation Methods**: Spearman, Pearson, Cosine Similarity
- **Forecast Length**: 15-250 bars (default: 50)
- **Similarity Type**: Price or %Change analysis
### **Visual Options**
- **Table Position**: Top/Bottom Left/Right positioning
- **Table Size**: Small, Normal, Large options
- **Signal Display**: Toggle buy/sell signals on/off
- **AI Visualization**: Optional prediction paths and ZigZag
## 📋 **How to Use**
### **For Beginners**
1. Add the indicator to your chart
2. Look for "PERFECT BUY" signals in the table
3. Wait for completion percentage ≥ 85% for highest probability trades
4. Use the background color changes as visual confirmation
### **For Advanced Traders**
1. Analyze individual ML components in the detailed table
2. Monitor anomaly detection for unusual market conditions
3. Use pattern confidence levels for trade timing
4. Combine with your existing strategy for confirmation
### **Signal Interpretation**
- **🟢 PERFECT BUY**: All 7 conditions met - highest probability reversal
- **🟡 NEAR BOTTOM**: Close to ideal conditions - monitor closely
- **🔴 NOT READY**: Wait for better setup
- **Strong Buy/Sell Signals**: ML score-based entries with high confidence
## ⚠️ **Important Notes**
### **Risk Management**
- This indicator provides analysis and signals, not guaranteed outcomes
- Always use proper risk management and position sizing
- Consider market conditions and fundamental factors
- Backtest the strategy on your preferred timeframes and assets
### **Best Practices**
- Use multiple timeframe analysis for confirmation
- Combine with support/resistance levels
- Monitor volume confirmation for all signals
- Set appropriate stop-losses and profit targets
### **Performance Tracking**
- The indicator tracks its own performance with win rate calculations
- Monitor the "AI Prediction" accuracy percentage
- Use the P&L tracking to assess signal quality over time
## 🔄 **Updates and Improvements**
This indicator is continuously evolving with:
- Enhanced machine learning algorithms
- Improved pattern recognition capabilities
- Additional correlation methods for better accuracy
- Performance optimization for faster calculations
- New visualization features based on user feedback
## 📚 **Technical Details**
### **Machine Learning Implementation**
- **Pattern Matching**: 20-bar normalized price patterns with historical comparison
- **Correlation Analysis**: Mathematical similarity scoring between current and historical patterns
- **Anomaly Detection**: Statistical Z-score analysis across price, volume, and RSI
- **Signal Weighting**: Multi-factor scoring system with optimized weights
### **Algorithm Components**
1. **Feature Extraction**: Price, volume, momentum, volatility, and trend features
2. **Pattern Recognition**: Historical pattern database with similarity matching
3. **Anomaly Detection**: Multi-dimensional Z-score threshold analysis
4. **Signal Generation**: Weighted scoring system with confidence intervals
5. **Performance Tracking**: Real-time win rate and accuracy monitoring
### **Calculation Methods**
- **Trend Strength**: (EMA8 - EMA21) / EMA21 * 100
- **Volume Ratio**: Current Volume / 20-period SMA Volume
- **BB Position**: (Close - BB_Lower) / (BB_Upper - BB_Lower)
- **Anomaly Score**: Average of normalized Z-scores for price, volume, and RSI
## 🎨 **Visual Elements**
### **Background Colors**
- **Light Green**: Perfect buy zone detected
- **Light Red**: Perfect sell zone detected
- **Light Blue**: Near bottom proximity
- **Green/Red Transparency**: Price anomaly detection
### **Signal Shapes**
- **Green Triangle Up**: Strong buy signal
- **Red Triangle Down**: Strong sell signal
- **Aqua Diamond**: Perfect buy zone entry
- **Purple Diamond**: Perfect sell zone entry
### **Table Information**
- **ML Complete Analysis**: 16 comprehensive metrics
- **Perfect Buy Conditions**: 7-point checklist with status indicators
- **Real-time Values**: Live updating of all calculations
- **Color-coded Status**: Green (good), Yellow (moderate), Red (caution)
## 🔍 **Troubleshooting**
### **Common Issues**
- **Table Not Showing**: Enable "Show ML Table" in settings
- **No Signals Appearing**: Check "Show Buy/Sell Signals" option
- **Performance Issues**: Reduce ML Lookback Period for faster calculation
- **Too Many/Few Signals**: Adjust Anomaly Threshold sensitivity
### **Optimization Tips**
- **For Day Trading**: Use lower timeframes (1m, 5m, 15m) with reduced lookback periods
- **For Swing Trading**: Use higher timeframes (1h, 4h, 1D) with standard settings
- **For Scalping**: Enable only strong signals and reduce pattern similarity threshold
- **For Long-term**: Increase all lookback periods and use daily/weekly timeframes
## 📖 **Disclaimer**
This indicator is for educational and informational purposes only. It should not be considered as financial advice. Trading involves substantial risk of loss and is not suitable for all investors. Past performance does not guarantee future results.
### **Risk Warning**
- All trading involves risk of substantial losses
- Never risk more than you can afford to lose
- This indicator does not guarantee profitable trades
- Always use proper risk management techniques
- Consider consulting with a financial advisor
### **Liability**
The creator of this indicator is not responsible for any losses incurred from its use. Users should thoroughly test and understand the indicator before using it with real money.
### **Feature Requests**
- Suggest improvements through TradingView comments
- Report bugs with detailed descriptions
- Share successful strategies using the indicator
- Contribute to community discussions
## 🏆 **Credits and Acknowledgments**
This indicator builds upon various open-source libraries and mathematical concepts:
- TradingView ZigZag library for visualization
- Statistical correlation methods from academic research
- Machine learning concepts adapted for financial markets
- Community feedback and testing contributions
## 📈 **Performance Metrics**
The indicator includes built-in performance tracking:
- **Win Rate Calculation**: Percentage of profitable signals
- **Signal Accuracy**: ML prediction vs actual price movement
- **Drawdown Tracking**: Current unrealized P&L from last signal
- **Completion Percentage**: How many perfect conditions are met
## 🔬 **Mathematical Foundation**
### **Correlation Calculations**
- **Pearson**: Measures linear correlation between patterns
- **Spearman**: Rank-based correlation for non-linear relationships
- **Cosine Similarity**: Vector-based similarity for pattern matching
### **Statistical Methods**
- **Z-Score**: (Value - Mean) / Standard Deviation
- **Pattern Normalization**: Price / Price
- **Volatility Percentile**: Historical ranking of current volatility
- **Momentum Calculation**: Price change over multiple periods
## 🎯 **Trading Strategies**
### **Conservative Approach**
- Wait for Perfect Buy Zone (85%+ completion)
- Use higher timeframes for confirmation
- Set stop-loss at recent swing low
- Take profits at resistance levels
### **Aggressive Approach**
- Trade on Strong Buy/Sell signals
- Use lower completion thresholds (70%+)
- Tighter stop-losses with faster exits
- Higher position sizes with confirmed trends
### **Hybrid Strategy**
- Combine with other indicators for confirmation
- Use different settings for different market conditions
- Scale in/out based on signal strength
- Adjust parameters based on market volatility
Squeeze Momentum Regression Clouds [SciQua]╭──────────────────────────────────────────────╮
☁️ Squeeze Momentum Regression Clouds
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🔍 Overview
The Squeeze Momentum Regression Clouds (SMRC) indicator is a powerful visual tool for identifying price compression , trend strength , and slope momentum using multiple layers of linear regression Clouds. Designed to extend the classic squeeze framework, this indicator captures the behavior of price through dynamic slope detection, percentile-based spread analytics, and an optional UI for trend inspection — across up to four customizable regression Clouds .
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⚙️ Core Features
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Up to 4 Regression Clouds – Each Cloud is created from a top and bottom linear regression line over a configurable lookback window.
Slope Detection Engine – Identifies whether each band is rising, falling, or flat based on slope-to-ATR thresholds.
Spread Compression Heatmap – Highlights compressed zones using yellow intensity, derived from historical spread analysis.
Composite Trend Scoring – Aggregates directional signals from each Cloud using your chosen weighting model.
Color-Coded Candles – Optional candle coloring reflects the real-time composite score.
UI Table – A toggleable info table shows slopes, compression levels, percentile ranks, and direction scores for each Cloud.
Gradient Cloud Styling – Apply gradient coloring from Cloud 1 to Cloud 4 for visual slope intensity.
Weight Aggregation Options – Use equal weighting, inverse-length weighting, or max pooling across Clouds to determine composite trend strength.
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🧪 How to Use the Indicator
1. Understand Trend Bias with Cloud Colors
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Each Cloud changes color based on its current slope:
Green indicates a rising trend.
Red indicates a falling trend.
Gray indicates a flat slope — often seen during chop or transitions.
Cloud 1 typically reflects short-term structure, while Cloud 4 represents long-term directional bias. Watch for multi-Cloud alignment — when all Clouds are green or red, the trend is strong. Divergence among Clouds often signals a potential shift.
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2. Use Compression Heat to Anticipate Breakouts
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The space between each Cloud’s top and bottom regression lines is measured, normalized, and analyzed over time. When this spread tightens relative to its history, the script highlights the band with a yellow compression glow .
This visual cue helps identify squeeze zones before volatility expands. If you see compression paired with a changing slope color (e.g., gray to green), this may indicate an impending breakout.
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3. Leverage the Optional Table UI
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The indicator includes a dynamic, floating table that displays real-time metrics per Cloud. These include:
Slope direction and value , with historical Min/Max reference.
Top and Bottom percentile ranks , showing how price sits within the Cloud range.
Current spread width , compared to its historical norms.
Composite score , which blends trend, slope, and compression for that Cloud.
You can customize the table’s position, theme, transparency, and whether to show a combined summary score in the header.
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4. Analyze Candle Color for Composite Signals
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When enabled, the indicator colors candles based on a weighted composite score. This score factors in:
The signed slope of each Cloud (up, down, or flat)
The percentile pressure from the top and bottom bands
The degree of spread compression
Expect green candles in bullish trend phases, red candles during bearish regimes, and gray candles in mixed or low-conviction zones.
Candle coloring provides a visual shorthand for market conditions , useful for intraday scanning or historical backtesting.
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🧰 Configuration Guidance
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To tailor the indicator to your strategy:
Use Cloud lengths like 21, 34, 55, and 89 for a balanced multi-timeframe view.
Adjust the slope threshold (default 0.05) to control how sensitive the trend coloring is.
Set the spread floor (e.g., 0.15) to tune when compression is detected and visualized.
Choose your weighting style : Inverse Length (favor faster bands), Equal, or Max Pooling (most aggressive).
Set composite weights to emphasize trend slope, percentile bias, or compression—depending on your market edge.
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✅ Best Practices
╰────────────────╯
Use aligned Cloud colors across all bands to confirm trend conviction.
Combine slope direction with compression glow for early breakout entry setups.
In choppy markets, watch for Clouds 1 and 2 turning flat while Clouds 3 and 4 remain directional — a sign of potential trend exhaustion or consolidation.
Keep the table enabled during backtesting to manually evaluate how each Cloud behaved during price turns and consolidations.
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📌 License & Usage Terms
╰───────────────────────╯
This script is provided under the Creative Commons Attribution-NonCommercial 4.0 International License .
✅ You are allowed to:
Use this script for personal or educational purposes
Study, learn, and adapt it for your own non-commercial strategies
❌ You are not allowed to:
Resell or redistribute the script without permission
Use it inside any paid product or service
Republish without giving clear attribution to the original author
For commercial licensing , private customization, or collaborations, please contact Joshua Danford directly.
Fundur - Trend LinesFundur - Trend Lines: Complete Trading Indicator Guide
Indicator Overview
The Fundur - Trend Lines is an advanced multi-layered trend analysis system that combines adaptive trend line technology, momentum analysis, and intelligent signal generation into one comprehensive trading tool. This indicator goes beyond traditional moving averages by utilizing volatility-adjusted trend lines that dynamically adapt to market conditions, providing traders with precise trend strength measurements and actionable trading signals.
What Makes Trend Lines Unique?
The Trend Lines indicator introduces Adaptive Trend Line Technology - a sophisticated methodology that uses Average True Range (ATR) calculations to create trend lines that respond intelligently to market volatility. Unlike static indicators, Trend Lines provides dynamic analysis that adapts its sensitivity based on current market conditions, offering more accurate trend identification and strength assessment.
Core Methodology
The indicator operates on the principle that trend strength can be quantified by analyzing the relationship between multiple adaptive trend lines, momentum indicators, and market structure. By combining Alignment Analysis , Distance Measurements , Momentum Confirmation , and Volatility Expansion Potential , the system generates a comprehensive trend strength score from 0-100% with corresponding trading signals.
Key Features
🎯 Adaptive Trend Line System Slow Trend Line : Primary trend direction with lower sensitivity for major trend identification Fast Trend Line : Higher sensitivity trend line for early trend change detection Volatility Adaptation : Both lines automatically adjust to market volatility using ATR calculations Cloud Visualization : Colored areas between trend lines show trend strength and direction
📊 Comprehensive Trend Strength Analysis Quantified Strength (0-100%) : Precise trend strength measurement combining multiple factors Alignment Score : Measures agreement between multiple trend line systems Distance Analysis : Evaluates price proximity to trend lines using ATR normalization Momentum Integration : Incorporates Awesome Oscillator for momentum confirmation Squeeze Factor : Identifies volatility expansion potential for breakout opportunities
🧠 Intelligent Signal Generation Position Signals : Clear ADD LONG, ADD SHORT, REDUCE, HOLD recommendations Risk Zone Classification : STRONG, MEDIUM, WEAK trend categorization Trend Direction : Bullish, Bearish, or Neutral trend identification Dynamic Updates : Real-time signal adjustments based on changing conditions
⚡ Enhanced Momentum Analysis Smoothed Momentum : Configurable momentum smoothing to reduce noise Acceleration Detection : Identifies momentum acceleration and deceleration Divergence Alerts : Detects price-momentum divergences for reversal warnings Directional Bias : Momentum confirmation for trend direction validation
🔍 Advanced Market Structure Detection Momentum Squeeze : Identifies low-volatility periods preceding major moves Volatility Expansion : Detects when markets break out of consolidation phases Trend Weakness Detection : Early warning system for deteriorating trends Structure Transition : Identifies when trends change character or direction
🎨 Professional Visual Interface Comprehensive Analysis Table : All key metrics displayed in organized format Visual Strength Bar : Graphical representation of trend strength Color-Coded Components : Intuitive color scheme for quick analysis Customizable Display : Flexible positioning and sizing options
Setup Guide
Step 1: Adding the Indicator
Open TradingView and navigate to your desired chart Click the "Indicators" button or press "/" key Search for "Fundur - Trend Lines" Add the indicator to your chart
Step 2: Basic Configuration
Main Features Settings ✅ Show Trend Analysis Table : ON (Essential for comprehensive analysis) ✅ Enable Trend Strength Analysis : ON (Core functionality) ✅ Generate Trading Signals : ON (For position management guidance)
Trend Lines Display ✅ Show Slow Trend Line : ON (Primary trend identification) ✅ Show Fast Trend Line : ON (Early signal detection) Trend Cloud Transparency : 89% (Default recommended, adjust for visibility)
Table Positioning Table Position : Top Right (recommended for most setups) Table Size : Normal (adjust based on screen size)
Step 3: Advanced Analysis Configuration
Enhanced Features (Optional) ✅ Enhanced Momentum Analysis : ON (for more accurate signals) ✅ Divergence Detection : ON (for reversal warnings) ⚠️ Momentum Squeeze Analysis : OFF initially (can add visual complexity)
Sensitivity Settings Divergence Sensitivity : 5 (Default - lower = more sensitive) Momentum Smoothing : 3 (Default - higher = smoother signals)
Step 4: Alert Configuration
Essential Alerts (Recommended) Trading Signal Alerts : Enable for position changes Trend Strength Change Alerts : Enable for trend monitoring Strength Change Threshold : 15% (Default recommended)
Advanced Alerts (Optional) Divergence Alerts : Enable for reversal warnings Early Weakness Alerts : Enable for risk management Momentum Squeeze Alerts : Enable for breakout opportunities Trend Line Cross Alerts : Enable for level-based signals
Basic Trading Guide
Understanding Trend Strength
The indicator's foundation is the Trend Strength Score - a quantified measurement (0-100%) that combines four key factors:
Strong Trends (75%+ Strength) 🟢 Characteristics : High alignment, close price-to-trend proximity, strong momentum Signals : ADD LONG (bullish) or ADD SHORT (bearish) Strategy : Aggressive position building, trend continuation trades Risk : Lower risk due to strong trend confirmation
Medium Trends (35-75% Strength) 🟡 Characteristics : Mixed signals, moderate alignment, transitional phases Signals : HOLD current positions Strategy : Conservative approach, wait for clearer signals Risk : Medium risk, requires careful monitoring
Weak Trends (Below 35% Strength) 🔴 Characteristics : Poor alignment, distant from trend lines, weak momentum Signals : REDUCE positions or CLOSE Strategy : Risk reduction, position unwinding Risk : High risk, trend likely changing or failing
Entry Strategies
Primary Strategy: Trend Continuation Entries Setup : Strong trend strength (75%+) with clear directional bias Entry Trigger : ADD LONG or ADD SHORT signal confirmation Direction : Follow the trend direction (Bullish ⬆ or Bearish ⬇) Timing : Enter on signal generation or price pullback to trend lines
Stop Loss Placement Conservative Method : Beyond the opposite trend line Aggressive Method : Below/above recent swing points For Long Positions : Below the Slow Trend Line For Short Positions : Above the Slow Trend Line Dynamic Adjustment : Move stops with trend line progression
Profit Taking Strategy
For Long Positions (Bullish Trend): Take 50% profits when trend strength begins declining from peak Take another 25% when trend strength drops below 60% Close remaining position when REDUCE signal appears Trail stops using Fast Trend Line for remaining position
For Short Positions (Bearish Trend): Take 50% profits when trend strength begins declining from peak Take another 25% when trend strength drops below 60% Close remaining position when REDUCE signal appears Trail stops using Fast Trend Line for remaining position
Alternative Strategy: Divergence-Based Reversal Entries Setup : Bullish or bearish divergence detected with weakening trend strength Entry : On trend direction change confirmation Risk Management : Tight stops due to counter-trend nature Targets : Opposite trend line or previous swing levels
Risk Management Framework
Position Sizing Based on Trend Strength Strong Trends (75%+) : Full position size (within risk tolerance) Medium Trends (35-75%) : Reduced position size (50-75% of normal) Weak Trends (Below 35%) : Minimal or no new positions Transitional Periods : Smallest position sizes due to uncertainty
Dynamic Risk Adjustment Increasing Strength : Can add to positions gradually Decreasing Strength : Begin profit-taking and position reduction Rapid Strength Loss : Quick position reduction or exit Divergence Warning : Tighten stops and prepare for reversal
Analysis Setups
Setup 1: Scalping Configuration (1-5 minute charts)
Settings Optimization: Momentum Smoothing: 2 (more responsive) Divergence Sensitivity: 3 (higher sensitivity) Enhanced Momentum Analysis: ON All alerts: ON for rapid signal updates
Visual Settings: Table Size: Small (less screen space) Table Position: Top Right Trend Cloud Transparency: 85% (subtle background)
Trading Approach: Focus on quick ADD signals in strong trends Use Fast Trend Line for entry timing Quick profit-taking at first sign of strength decline Very tight risk management due to lower timeframe noise
Setup 2: Day Trading Configuration (5-15 minute charts)
Settings Optimization: All default settings work well Enable Momentum Squeeze Analysis for breakout identification Divergence Detection: ON for reversal warnings Trend Strength Change Threshold: 12% (more sensitive)
Visual Settings: Table Size: Normal Show all trend analysis components Trend Cloud Transparency: 89% (default)
Trading Approach: Wait for clear trend strength above 65% before entering Use momentum squeeze breakouts for early entries Hold positions through medium strength phases Exit on REDUCE signals or strength below 40%
Setup 3: Swing Trading Configuration (1-4 hour charts)
Settings Optimization: Momentum Smoothing: 4 (smoother for higher timeframe) Divergence Sensitivity: 7 (less sensitive, higher quality signals) Enhanced Momentum Analysis: ON Early Weakness Alerts: ON (important for swing trades)
Visual Settings: Table Size: Normal or Large Focus on trend strength and direction components Enable all visual features for comprehensive analysis
Trading Approach: Require trend strength above 70% for new positions Hold through temporary strength dips if above 50% Use divergence signals for early exit warnings Focus on major trend changes for position adjustments
Setup 4: Position Trading Configuration (4H-Daily charts)
Settings Optimization: Momentum Smoothing: 5 (maximum smoothing) Divergence Sensitivity: 10 (only high-quality divergences) Strength Change Threshold: 20% (major changes only) Focus on trend direction and strength alerts
Visual Settings: Table Size: Large (detailed analysis) Clean visual setup focusing on major components Minimal clutter for long-term perspective
Trading Approach: Only enter on very strong trends (80%+ strength) Hold through significant strength fluctuations Focus on major trend direction changes Use weekly/monthly trend alignment for confirmation
Setup 5: Multi-Asset Analysis Configuration
For Forex Pairs: Standard settings work well due to 24-hour markets Pay attention to session-based strength changes Use momentum squeeze for breakout trading Enable all alert types for continuous monitoring
For Cryptocurrency: Reduce momentum smoothing (2-3) due to high volatility Increase divergence sensitivity (3-4) for early warnings Focus on strength changes above 20% threshold Use squeeze analysis for breakout opportunities
For Stock Indices: Standard settings appropriate for most indices Enable early weakness alerts for risk management Consider market hours for signal validity Use higher timeframes for better signal quality
Visual Components
Trend Analysis Table Trend Strength : Percentage with visual strength bar Trend Signal : Current position recommendation Risk Zone : STRONG/MEDIUM/WEAK classification Alignment : Trend line agreement analysis Distance : Price proximity to trend lines Momentum : Current momentum direction and strength
Trend Lines and Clouds Colored Clouds : Green for bullish trends, red for bearish trends Cloud Intensity : Opacity reflects trend strength Dynamic Colors : Automatically adjust based on trend direction
Momentum Squeeze Visualization Yellow Highlights : Above and below price during squeeze periods Squeeze Indication : Identifies low-volatility consolidation Breakout Preparation : Visual cue for potential explosive moves
Alert System
Trading Signal Alerts ADD LONG : Strong bullish trend confirmed ADD SHORT : Strong bearish trend confirmed REDUCE : Trend weakness detected, position reduction recommended HOLD : Maintain current positions, no change needed
Trend Analysis Alerts Strength Increase : Trend gaining momentum Strength Decrease : Trend losing momentum Early Weakness : Warning of potential trend deterioration Trend Direction Change : Major trend shift detected
Technical Alerts Bullish Divergence : Price falling but momentum rising Bearish Divergence : Price rising but momentum falling Momentum Squeeze Start : Volatility contraction beginning Momentum Squeeze End : Breakout from low volatility period Trend Line Cross : Price crossing above/below trend lines
Setting Up Alerts Enable desired alert types in indicator settings Create TradingView alerts using "Fundur - Trend Lines" as source Configure notification methods (email, SMS, app notifications) Test alerts with paper trading before live implementation Adjust alert frequency settings to avoid spam
Best Practices
Trend Strength Interpretation Above 75% : High confidence trades, full position sizes 50-75% : Moderate confidence, reduced positions Below 50% : Low confidence, minimal or no positions Rapid Changes : Pay attention to sudden strength shifts
Signal Management Don't Chase : Wait for clear signals rather than predicting Confirm with Price Action : Use chart patterns for additional confirmation Respect Risk Zones : Adjust position sizes based on trend classification Monitor Alignment : Strong alignment increases signal reliability
Multi-Timeframe Integration Higher Timeframe Bias : Use daily/weekly for overall trend direction Lower Timeframe Entries : Use hourly/15min for precise entry timing Confirmation Requirement : Ensure alignment between timeframes Conflict Resolution : Higher timeframe takes precedence
Common Mistakes to Avoid
Signal Misinterpretation Ignoring Trend Strength : Don't trade weak signals (below 60%) Fighting the Trend : Don't go against strong trend directions Overreliance on Single Component : Consider all analysis factors Impatience : Wait for clear STRONG trend classification
Risk Management Errors Fixed Position Sizes : Adjust sizes based on trend strength Ignoring REDUCE Signals : Take profits when indicator suggests No Stop Losses : Always use stops beyond trend lines Overleveraging Weak Signals : Use smaller positions in MEDIUM zones
Technical Analysis Errors Ignoring Divergences : Pay attention to momentum warnings Missing Squeeze Opportunities : Watch for breakout setups Poor Timeframe Selection : Match timeframe to trading style Alert Fatigue : Don't enable too many alerts simultaneously
Advanced Techniques
Divergence Trading Early Reversal Detection : Use divergences to anticipate trend changes Confirmation Required : Wait for trend strength decline confirmation Tight Risk Management : Use smaller positions for counter-trend trades Quick Exits : Take profits rapidly on divergence trades
Momentum Squeeze Strategies Breakout Preparation : Position before squeeze resolution Direction Bias : Use trend direction for breakout direction Volume Confirmation : Combine with volume analysis when possible False Breakout Protection : Use tight stops for failed breakouts
Multi-Component Analysis Alignment Priority : Perfect alignment (100%) provides highest confidence Distance Consideration : Closer to trend lines = higher probability Momentum Confirmation : Rising momentum supports trend direction Squeeze Integration : High squeeze factor increases breakout potential
Dynamic Position Management Scaling In : Add to positions as trend strength increases Scaling Out : Reduce positions as trend strength decreases Stop Trailing : Move stops with Fast Trend Line progression Profit Optimization : Use strength peaks for profit-taking timing
Conclusion
The Fundur - Trend Lines indicator represents a sophisticated approach to trend analysis, combining adaptive trend line technology with comprehensive strength measurement and intelligent signal generation. By quantifying trend strength through multiple analytical components, this indicator provides traders with objective, data-driven insights for making informed trading decisions.
The indicator's strength lies in its ability to adapt to changing market conditions while providing clear, actionable signals. The comprehensive trend strength analysis removes guesswork from trend trading, allowing traders to size positions appropriately and manage risk effectively based on quantified market conditions.
Success with the Trend Lines indicator comes from understanding that trend strength is dynamic and requires continuous monitoring. The 0-100% strength scale provides an objective framework for position management, while the multi-component analysis ensures robust signal generation across different market conditions.
Remember that this indicator works best when combined with proper risk management, position sizing, and market context awareness. Start with conservative settings and smaller position sizes while learning the indicator's behavior in different market environments. The comprehensive alert system helps maintain awareness of changing conditions, but successful trading still requires discipline and adherence to your trading plan.
For optimal results, practice with the indicator across different timeframes and market conditions, always prioritizing risk management over profit potential, and maintaining realistic expectations about market behavior and indicator performance.
Smooth Cloud + RSI Liquidity Spectrum + Zig Zag Volume ProfileSmooth Cloud + RSI Liquidity Spectrum + Zig Zag++ Volume Profile" Indicator
| Advanced Trend & Liquidity Analysis.
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📌 Key Features & Enhancements (Zig Zag++)
This advanced indicator combines **trend-following moving averages, RSI momentum with liquidity factors, and an improved Zig Zag++ algorithm with volume profiling** for precise swing detection.
🔹 Zig Zag++ Upgrades:
✅ **Dynamic Reversal Detection** – Adapts to volatility using percentage-based pivots.
✅ **Volume-Weighted Swing Points** – Highlights high-liquidity turning points.
✅ **Multi-Timeframe Confirmation** – Uses historical pivots for stronger signals.
✅ **Volume Profile Clustering** – Reveals key support/resistance zones based on traded volume.
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📊 Indicator Components Breakdown
1️⃣ Smooth Cloud (Trend Filter)
- **Fast MA (20-period) & Slow MA (50-period)** – Configurable as EMA, SMA, or WMA.
- **Cloud Coloring** – Green when fast MA > slow MA (bullish), red otherwise (bearish).
- **Purpose**: Acts as a trend filter—only take trades in the direction of the cloud.
2️⃣ RSI Liquidity Spectrum (Momentum + Volume)
- **RSI (14-period default)** – Standard momentum oscillator.
- **Liquidity-Adjusted Momentum** = `(RSI + ROC(RSI,3)) * (Volume / SMA(Volume, RSI Length))`
- **Purpose**: Identifies overbought/oversold conditions with volume confirmation (high volume = stronger signal).
3️⃣ Zig Zag++ (Swing Detection & Volume Profiling)
📈 Zig Zag Logic:**
- **Percentage-Based Reversals** (default: 5%) – Only plots swings exceeding this threshold.
- **Pivot Tracking** – Stores price & bar index of each swing point in arrays.
- **Dynamic Line Drawing** – Connects swing points with yellow trendlines.
📊 Volume Profile at Swings:
- **Lookback Period** (200 bars default) – Analyzes volume distribution between Zig Zag turns.
- **10-Price Bin Clustering** – Splits the price range into 10 levels and calculates traded volume at each.
- **Transparency Scaling** – Higher volume zones appear darker (stronger support/resistance).
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🎯 Step-by-Step Trading Strategies
📈 Strategy 1: Trend-Following with RSI Liquidity Confirmation**
1. **Enter Long** when:
- Smooth Cloud is **green** (fast MA > slow MA).
- RSI Liquidity Momentum crosses above **30** (bullish momentum + volume).
- Price pulls back to the **Volume Profile high-volume zone** (demand area).
2. **Enter Short** when:
- Smooth Cloud is **red** (fast MA < slow MA).
- RSI Liquidity Momentum crosses below **70** (bearish momentum + volume).
- Price rallies into the **Volume Profile high-volume zone** (supply area).
3. **Exit** when:
- Zig Zag++ detects a new reversal (5% move against position).
- RSI Liquidity Momentum crosses back mid-level (50).
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📉 Strategy 2: Swing Trading with Zig Zag++ Pivots**
1. **Buy at Swing Lows** when:
- Zig Zag++ prints a **higher low** (bullish structure).
- Volume Profile shows **strong absorption** (high volume at the low).
- RSI Liquidity Momentum is rising from oversold (<30).
2. **Sell at Swing Highs** when:
- Zig Zag++ prints a **lower high** (bearish structure).
- Volume Profile shows **distribution** (high volume at the top).
- RSI Liquidity Momentum is falling from overbought (>70).
3. **Stop Loss**:
- Below the recent Zig Zag low (for longs).
- Above the recent Zig Zag high (for shorts).
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📌 Additional Enhancements (Pro Tips)**
- **Combine with Higher Timeframe (HTF) Cloud** – Use a 4H/1D cloud to filter trades.
- **Divergence Detection** – Hidden bullish/bearish divergences between Zig Zag & RSI Liquidity.
- **Volume Spike Confirmation** – Only trade if volume exceeds SMA(volume, 20) at reversal points.
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🚀 Conclusion
This **all-in-one indicator** provides:
✔ **Trend direction** (Smooth Cloud)
✔ **Momentum + Liquidity strength** (RSI Spectrum)
✔ **Precise swing points** (Zig Zag++)
✔ **Volume-based S/R zones** (Profile Clustering)
Best used on **15M-4H timeframes** for swing/day trading. Adjust parameters based on asset volatility.
ZigZag Volume Profile [ChartPrime]⯁ OVERVIEW
ZigZag Volume Profile combines swing structure with volume analytics by plotting a ZigZag of major price swings and overlaying a detailed volume profile around each swing. At the end of each swing, it highlights the Point of Control (POC) — the price level with the highest traded volume — and extends it forward to identify key areas of potential support or resistance.
⯁ KEY FEATURES
ZigZag Swing Detection:
Automatically detects swing highs and lows based on a user-defined length, creating clean visual segments of market structure.
These segments act as boundaries for volume profile calculations.
swingHigh = ta.highest(swingLength)
swingLow = ta.lowest(swingLength)
ZigZag Channel Visualization:
The ZigZag structure is connected with sloped lines, forming a visual “channel” of the price movement.
The ZigZag can optionally, scaled by ATR.
Volume Profile Around Each Swing:
For every completed swing (high to low or low to high), the indicator constructs a full volume profile using user-defined bin counts.
It scans volume across price levels in the swing and plots histogram-style bins using a gradient color to indicate volume magnitude.
Dynamic Bin Width and Slope Adjustment:
Bins are distributed across a vertical ATR-based range, and their width is adjusted based on the percentage of total swing volume.
The volume fill direction is adapted to the swing’s slope for visually aligned plotting.
POC Detection and Extension:
The highest volume bin in each swing is identified as the Point of Control (POC).
This level is plotted with a thicker line and extended horizontally into the future as a key reaction level.
Automatic POC Expiry on Price Interaction:
POC lines are continuously extended unless breached by price.
When price crosses the POC level, the extension is terminated — signaling that the level may have been absorbed.
Clean Volume Bin Visualization:
Bin colors range from green (low volume) to blue (higher volume), with the POC always marked in red by default for easy identification.
Volume percentages are optionally labeled at each bin level.
Flexible Swing Profile Parameters:
Users can control:
Number of volume bins
Bin width
Channel width (ATR factor)
Visibility of the swing channel or POC lines
Efficient Memory Handling:
Old POC lines and volume profiles are automatically removed from memory after a threshold to keep charts clean and performant.
⯁ USAGE
Use ZigZag swings to define market structure visually.
Analyze volume profile around each swing to understand where most trading activity occurred.
Use POC extensions as dynamic support/resistance zones for entries, stops, or take-profits.
Watch for price interaction with extended POC lines — breaks may suggest absorbed liquidity or breakout potential.
Use the ATR-based channel width to adapt profiles based on market volatility.
⯁ CONCLUSION
ZigZag Volume Profile offers a powerful fusion of structure and volume. By plotting detailed volume profiles over each price swing and extending the POC as actionable S/R levels, this tool provides deep insight into market participation zones — giving traders a tactical edge in both ranging and trending environments.
Time-Decaying Percentile Oscillator [BackQuant]Time-Decaying Percentile Oscillator
1. Big-picture idea
Traditional percentile or stochastic oscillators treat every bar in the look-back window as equally important. That is fine when markets are slow, but if volatility regime changes quickly yesterday’s print should matter more than last month’s. The Time-Decaying Percentile Oscillator attempts to fix that blind spot by assigning an adjustable weight to every past price before it is ranked. The result is a percentile score that “breathes” with market tempo much faster to flag new extremes yet still smooth enough to ignore random noise.
2. What the script actually does
Build a weight curve
• You pick a look-back length (default 28 bars).
• You decide whether weights fall Linearly , Exponentially , by Power-law or Logarithmically .
• A decay factor (lower = faster fade) shapes how quickly the oldest price loses influence.
• The array is normalised so all weights still sum to 1.
Rank prices by weighted mass
• Every close in the window is paired with its weight.
• The pairs are sorted from low to high.
• The cumulative weight is walked until it equals your chosen percentile level (default 50 = median).
• That price becomes the Time-Decayed Percentile .
Find dispersion with robust statistics
• Instead of a fragile standard deviation the script measures weighted Median-Absolute-Deviation about the new percentile.
• You multiply that deviation by the Deviation Multiplier slider (default 1.0) to get a non-parametric volatility band.
Build an adaptive channel
• Upper band = percentile + (multiplier × deviation)
• Lower band = percentile – (multiplier × deviation)
Normalise into a 0-100 oscillator
• The current close is mapped inside that band:
0 = lower band, 50 = centre, 100 = upper band.
• If the channel squeezes, tiny moves still travel the full scale; if volatility explodes, it automatically widens.
Optional smoothing
• A second-stage moving average (EMA, SMA, DEMA, TEMA, etc.) tames the jitter.
• Length 22 EMA by default—change it to tune reaction speed.
Threshold logic
• Upper Threshold 70 and Lower Threshold 30 separate standard overbought/oversold states.
• Extreme bands 85 and 15 paint background heat when aggressive fade or breakout trades might trigger.
Divergence engine
• Looks back twenty bars.
• Flags Bullish divergence when price makes a lower low but oscillator refuses to confirm (value < 40).
• Flags Bearish divergence when price prints a higher high but oscillator stalls (value > 60).
3. Component walk-through
• Source – Any price series. Close by default, switch to typical price or custom OHLC4 for futures spreads.
• Look-back Period – How many bars to rank. Short = faster, long = slower.
• Base Percentile Level – 50 shows relative position around the median; set to 25 / 75 for quartile tracking or 90 / 10 for extreme tails.
• Deviation Multiplier – Higher values widen the dynamic channel, lowering whipsaw but delaying signals.
• Decay Settings
– Type decides the curve shape. Exponential (default 1.16) mimics EMA logic.
– Factor < 1 shrinks influence faster; > 1 spreads influence flatter.
– Toggle Enable Time Decay off to compare with classic equal-weight stochastic.
• Smoothing Block – Choose one of seven MA flavours plus length.
• Thresholds – Overbought / Oversold / Extreme levels. Push them out when working on very mean-reverting assets like FX; pull them in for trend monsters like crypto.
• Display toggles – Show or hide threshold lines, extreme filler zones, bar colouring, divergence labels.
• Colours – Bullish green, bearish red, neutral grey. Every gradient step is automatically blended to generate a heat map across the 0-100 range.
4. How to read the chart
• Oscillator creeping above 70 = market auctioning near the top of its adaptive range.
• Fast poke above 85 with no follow-through = exhaustion fade candidate.
• Slow grind that lives above 70 for many bars = valid bullish trend, not a fade.
• Cross back through 50 shows balance has shifted; treat it like a micro trend change.
• Divergence arrows add extra confidence when you already see two-bar reversal candles at range extremes.
• Background shading (semi-transparent red / green) warns of extreme states and throttles your position size.
5. Practical trading playbook
Mean-reversion scalps
1. Wait for oscillator to reach your desired OB/ OS levels
2. Check the slope of the smoothing MA—if it is flattening the squeeze is mature.
3. Look for a one- or two-bar reversal pattern.
4. Enter against the move; first target = midline 50, second target = opposite threshold.
5. Stop loss just beyond the extreme band.
Trend continuation pullbacks
1. Identify a clean directional trend on the price chart.
2. During the trend, TDP will oscillate between midline and extreme of that side.
3. Buy dips when oscillator hits OS levels, and the same for OB levels & shorting
4. Exit when oscillator re-tags the same-side extreme or prints divergence.
Volatility regime filter
• Use the Enable Time Decay switch as a regime test.
• If equal-weight oscillator and decayed oscillator diverge widely, market is entering a new volatility regime—tighten stops and trade smaller.
Divergence confirmation for other indicators
• Pair TDP divergence arrows with MACD histogram or RSI to filter false positives.
• The weighted nature means TDP often spots divergence a bar or two earlier than standard RSI.
Swing breakout strategy
1. During consolidation, band width compresses and oscillator oscillates around 50.
2. Watch for sudden expansion where oscillator blasts through extreme bands and stays pinned.
3. Enter with momentum in breakout direction; trail stop behind upper or lower band as it re-expands.
6. Customising decay mathematics
Linear – Each older bar loses the same fixed amount of influence. Intuitive and stable; good for slow swing charts.
Exponential – Influence halves every “decay factor” steps. Mirrors EMA thinking and is fastest to react.
Power-law – Mid-history bars keep more authority than exponential but oldest data still fades. Handy for commodities where seasonality matters.
Logarithmic – The gentlest curve; weight drops sharply at first then levels off. Mimics how traders remember dramatic moves for weeks but forget ordinary noise quickly.
Turn decay off to verify the tool’s added value; most users never switch back.
7. Alert catalogue
• TD Overbought / TD Oversold – Cross of regular thresholds.
• TD Extreme OB / OS – Breach of danger zones.
• TD Bullish / Bearish Divergence – High-probability reversal watch.
• TD Midline Cross – Momentum shift that often precedes a window where trend-following systems perform.
8. Visual hygiene tips
• If you already plot price on a dark background pick Bullish Color and Bearish Color default; change to pastel tones for light themes.
• Hide threshold lines after you memorise the zones to declutter scalping layouts.
• Overlay mode set to false so the oscillator lives in its own panel; keep height about 30 % of screen for best resolution.
9. Final notes
Time-Decaying Percentile Oscillator marries robust statistical ranking, adaptive dispersion and decay-aware weighting into a simple oscillator. It respects both recent order-flow shocks and historical context, offers granular control over responsiveness and ships with divergence and alert plumbing out of the box. Bolt it onto your price action framework, trend-following system or volatility mean-reversion playbook and see how much sooner it recognises genuine extremes compared to legacy oscillators.
Backtest thoroughly, experiment with decay curves on each asset class and remember: in trading, timing beats timidity but patience beats impulse. May this tool help you find that edge.
Ultimate Precision Buy/Sell with SL - Clean Labels FIXThis is a premium indicator designed for traders who demand accuracy, simplicity, and clean visual signals.
✅ Key Features:
📈 Precise Buy/Sell entries based on trend confirmation (EMA) and momentum (RSI)
🛡️ Automatic Stop Loss (SL) drawn for every trade, calculated from ATR
🔄 SL line dynamically moves with each new candle to reflect live action
❗ Only one active signal at a time – no clutter, no repaints
⏱ Optimized for 1H timeframe
💰 Best for Forex pairs, Gold (XAUUSD), Silver (XAGUSD), Platinum (XPTUSD)
🧠 How it works:
Buy Signal: When fast EMA > slow EMA & RSI crosses above 30
Sell Signal: When fast EMA < slow EMA & RSI crosses below 70
A single SL line is drawn per trade and remains until either:
Opposite signal appears, or
SL is hit
⚠️ No repainting. No noise. Just precision.
If you want to trade smart, clean and with confidence – this indicator is built for you.
Composite Trend Trader Module [BackQuant]Composite Trend Trader Module
Overview and Purpose
The Composite Trend Trader Module (CTM) is an invite-only Pine Script indicator designed to provide traders with a comprehensive tool for trend-following, dip-buying, and market strength assessment. By integrating multiple market data inputs—price momentum, volatility, volume, and statistical baselines—the CTM generates actionable outputs for trend identification, swing trade entries, and dip-buying opportunities. The indicator is intended for traders seeking a systematic approach to market analysis with customizable settings, while maintaining simplicity in its user interface. As a closed-source script, the underlying calculations remain proprietary, but this description outlines its functionality, features, and practical applications in trading.
Visual Components
The CTM provides the following visual elements on the chart:
• Signal Spine – A colored line (default 25-period weighted moving average) that reflects the dominant trend—green for bullish, red for bearish, and grey for neutral or transitional periods.
• Swing Triggers – Unicode markers ("𝕃" for long, "𝕊" for short) appear below or above bars when the trend shifts, signaling potential swing trade entries.
• Dip-Hunter Signals – Green arrows mark dip-buying opportunities, accompanied by faint green background highlights and forward-projecting entry lines for precise entry levels.
• Heat Meter – A horizontal strip at the bottom of the chart, graded from -50 (overheated) to +50 (deep dip), visually indicates the strength of dip conditions using a red-to-green gradient.
Core Features
The CTM comprises several components that work together to deliver a cohesive trading framework. Below is a detailed explanation of each, without disclosing proprietary calculations.
1. Universal Trend Tracking (UTT)
The UTT combines multiple momentum and statistical indicators into a single composite score ranging from -1 to +1. This score is derived from:
• Price-based momentum metrics.
• Volatility-adjusted thresholds.
• Statistical measures of price deviation and market structure.
When the UTT score exceeds +0.2, the market is considered in an actionable uptrend; below -0.2, a downtrend is identified. Values between these thresholds indicate a neutral or choppy market, helping traders avoid low-probability setups during consolidation.
2. Signal Spine
The signal spine is a 25-period weighted moving average of price, colored according to the UTT score (green for bullish, red for bearish, grey for neutral). This line serves as a visual anchor for tracking the prevailing trend and highlights regime changes in real time, enabling traders to align their strategies with market direction.
3. Swing Triggers (𝕃/𝕊)
Swing trade signals are generated when the UTT crosses the zero line, indicating a shift in market regime. A "𝕃" marker appears below the bar for a bullish crossover (potential long entry), and a "𝕊" marker appears above for a bearish crossover (potential short entry). These signals incorporate volatility-adaptive thresholds to minimize false triggers during low-volatility periods, improving reliability compared to traditional moving-average crossovers.
4. Dip-Hunter Engine
The Dip-Hunter subsystem identifies high-probability dip-buying opportunities by evaluating five conditions:
• Dip Magnitude – The price must have fallen by a user-defined percentage (default 2%) from a recent swing high, calculated over a specified lookback period (default 5 bars).
• Volume Burst – Current volume must exceed the average volume over a user-defined lookback (default 65 bars) by a specified multiplier (default 2x).
• Volatility Spike – The intraday range or Average True Range (ATR) must exceed a statistical baseline by a user-defined multiplier (default 1.5x).
• Structural Permission – Price must be below a fast Exponential Moving Average (EMA, default 20 periods), and the market structure must be bearish (fast EMA below slow EMA, default 50 periods).
• Trend Filter (Optional) – When enabled, dip signals are only generated if the UTT indicates a bullish trend, preventing trades against a bearish macro environment.
When these conditions align, the Dip-Hunter plots a green arrow, highlights the candle background, and draws a forward-projecting horizontal line at a user-selected price level (Low, Close, or calculated dip percentage).
5. Strength Score and Heat Meter
Each bar is assigned a strength score (0 to 5, or -50 to +50 when scaled for the heat meter) based on the following criteria:
• +1 for meeting the dip threshold.
• +1 for a volume spike.
• +1 for a volume momentum spike (based on rate-of-change).
• +1 for a confirmed volatility spike.
• +1 if price is below the fast EMA.
• +2 if the macro trend filter is bullish (when enabled).
The heat meter visualizes this score as a pointer on a red-to-green gradient strip, enabling traders to quickly assess the intensity of dip conditions and prioritize high-quality setups.
6. Entry-Line Generator
For each dip signal, the CTM draws a forward-projecting horizontal line to mark potential entry levels. Traders can configure:
• The price level for the line (Low, Close, or exact dip percentage).
• The duration of the line (default 100 bars).
• A minimum gap between signals (default 5 bars) to prevent overlapping lines during clustered events.
These lines serve as visual guides for setting limit orders or stop-loss levels.
7. Alerts
The CTM includes seven pre-configured alert conditions to support automated workflows:
• CTM Long/Short – Triggered on bullish or bearish UTT zero-line crossovers for swing trades.
• Market Overheated – Activates when the strength score falls below -40, indicating potential exhaustion.
• Close to Dip – Signals when the strength score reaches 0.6, suggesting an impending dip opportunity.
• Dip Confirmed – Fires on the first bar meeting all dip conditions.
• Dip Active – Triggers while dip conditions remain valid.
• Dip Fading – Activates when the strength score crosses below 0.5, indicating a weakening dip.
• Trend-Blocked – Alerts when dip conditions are met but blocked by the trend filter.
These alerts can be routed to brokers or trading bots for seamless execution.
"CPM Long Signal {{exchange}}:{{ticker}}")
"CPM Short Signal {{exchange}}:{{ticker}}")
"Market overheated {{ticker}}")
"Close to a dip {{ticker}}")
"Dip confirmed {{ticker}}")
"Dip active {{ticker}}")
"Dip strength fading {{ticker}}")
"Signal blocked by trend filter {{ticker}}")
User Controls
The CTM offers extensive customization to adapt to different trading styles and preferences:
• Signal Settings – Toggle the signal spine, composite score plot, swing triggers, and bar coloring. Adjust line width for visibility.
• Display Settings – Customize bullish, bearish, and neutral colors to match chart templates.
• Dip-Hunter Settings – Configure volume lookback, spike multipliers, EMA periods, volatility thresholds, dip percentage, and lookback bars.
• Trend Filter – Enable or disable the requirement for a bullish UTT before dip signals are generated.
• Strength & Meter – Toggle bar coloring based on the strength score, adjust the number of meter cells (default 60), and select meter position (e.g., bottom-center).
• Entry Settings – Control entry line visibility, length, and price source (Low, Close, or dip percentage).
Trading Applications
The CTM supports multiple trading strategies, each leveraging its outputs for specific market conditions:
• Trend-Ride Mode – Trade in the direction of the signal spine. Enter long positions on the first "𝕃" marker in a green (bullish) regime, and scale out when the UTT returns to grey (neutral). This is ideal for trend-following traders seeking to capture sustained moves, with the first signal in a new trend regime offering high statistical expectancy.
• Forced Dip Entries – Enable the trend filter and focus on dip signals (green arrows). Place limit orders at the entry line, set stops below the line, and target the midpoint of the prior value area (e.g., using support/resistance levels). This suits mean-reversion traders aiming to buy dips in bullish trends, with clear risk management via entry lines.
• Scalp Confirmation – Hide the signal spine and use bar coloring to identify short-term momentum. Green bars indicate broad buying pressure, while red bars warn against long scalps in oversold conditions. This is useful for intraday scalpers seeking confirmation of momentum before entering trades.
• Event Guardrails – Avoid trading when the heat meter is below -40 before major economic releases (e.g., FOMC, CPI), as spreads and slippage may widen. This enhances risk management by flagging high-risk periods during macroeconomic events.
• Multi-Timeframe Analysis – Apply the CTM on a daily timeframe in a secondary pane and a lower timeframe (e.g., hourly) on the primary chart. Trade only when both timeframes align (e.g., both in bullish regimes). This increases conviction for swing or position traders by confirming trend alignment across timeframes.
Frequently Asked Questions
• How does the CTM differ from a moving-average ribbon? The CTM integrates multiple momentum, volatility, and statistical indicators, using adaptive thresholds and proprietary calculations to respond faster to structural changes while filtering noise more effectively than traditional dual-EMA systems.
• Can the underlying formulas be accessed? No, the script is closed-source, and calculations are protected to preserve intellectual property. Users receive all outputs, alerts, and customizable parameters.
• Does the indicator repaint? No, all calculations use confirmed historical data without look-ahead bias. Entry lines are static from the signal bar.
• Which markets is it suitable for? The CTM is optimized for equities, futures, and cryptocurrencies. Adjust dip percentage and volume multipliers for low-liquidity markets.
• What about latency? The script uses efficient Pine Script functions and lightweight loops, ensuring minimal performance impact.
Limitations and Best Practices
• Market-Specific Tuning – Thinly traded markets may require adjustments to dip percentage and volume thresholds to avoid excessive signals.
• Complementary Tools – Combine the CTM with price action, support/resistance levels, or order flow analysis to confirm signals and avoid over-reliance on the indicator.
• Event Risk – Be cautious during high-impact news events, as volatility spikes may trigger signals that are quickly reversed.
• Trend Filter Use – Enabling the trend filter reduces false dip signals in bearish markets but may delay entries in rapidly reversing markets.
Conclusion
The Composite Trend Trader Module consolidates trend-following, dip-buying, and strength assessment into a single, customizable indicator. By providing clear visual cues, actionable alerts, and flexible settings, it equips traders with a robust framework for navigating various market conditions. While the proprietary calculations remain protected, the CTM’s outputs enable traders to make informed decisions, align strategies with market regimes, and manage risk effectively. Use it as a strategic tool alongside sound risk management and complementary analysis for optimal results.
Time-Price Velocity [QuantAlgo]🟢 Overview
The Time-Price Velocity indicator uses advanced velocity-based analysis to measure the rate of price change normalized against typical market movement, creating a dynamic momentum oscillator that identifies market acceleration patterns and momentum shifts. Unlike traditional momentum indicators that focus solely on price change magnitude, this indicator incorporates time-weighted displacement calculations and ATR normalization to create a sophisticated velocity measurement system that adapts to varying market volatility conditions.
This indicator displays a velocity signal line that oscillates around zero, with positive values indicating upward price velocity and negative values indicating downward price velocity. The signal incorporates acceleration background columns and statistical normalization to help traders identify momentum shifts and potential reversal or continuation opportunities across different timeframes and asset classes.
🟢 How It Works
The indicator's key insight lies in its time-price velocity calculation system, where velocity is measured using the fundamental physics formula:
velocity = priceChange / timeWeight
The system normalizes this raw velocity against typical price movement using Average True Range (ATR) to create market-adjusted readings:
normalizedVelocity = typicalMove > 0 ? velocity / typicalMove : 0
where "typicalMove = ta.atr(lookback)" provides the baseline for normal price movement over the specified lookback period.
The Time-Price Velocity indicator calculation combines multiple sophisticated components. First, it calculates acceleration as the change in velocity over time:
acceleration = normalizedVelocity - normalizedVelocity
Then, the signal generation applies EMA smoothing to reduce noise while preserving responsiveness:
signal = ta.ema(normalizedVelocity, smooth)
This creates a velocity-based momentum indicator that combines price displacement analysis with statistical normalization, providing traders with both directional signals and acceleration insights for enhanced market timing.
🟢 How to Use
1. Signal Interpretation and Threshold Zones
Positive Values (Above Zero): Time-price velocity indicating bullish momentum with upward price displacement relative to normalized baseline
Negative Values (Below Zero): Time-price velocity indicating bearish momentum with downward price displacement relative to normalized baseline
Zero Line Crosses: Velocity transitions between bullish and bearish regimes, indicating potential trend changes or momentum shifts
Upper Threshold Zone: Area above positive threshold (default 1.0) indicating strong bullish velocity and potential reversal point
Lower Threshold Zone: Area below negative threshold (default -1.0) indicating strong bearish velocity and potential reversal point
2. Acceleration Analysis and Visual Features
Acceleration Columns: Background histogram showing velocity acceleration (the rate of change of velocity), with green columns indicating accelerating velocity and red columns indicating decelerating velocity. The interpretation depends on trend context: red columns in downtrends indicate strengthening bearish momentum, while red columns in uptrends indicate weakening bullish momentum
Acceleration Column Height: The height of each column represents the magnitude of acceleration, with taller columns indicating stronger acceleration or deceleration forces
Bar Coloring: Optional price bar coloring matches velocity direction for immediate visual trend confirmation
Info Table: Real-time display of current velocity and acceleration values with trend arrows and change indicators
3. Additional Features:
Confirmed vs Live Data: Toggle between confirmed (closed) bar analysis for stable signals or current bar inclusion for real-time updates
Multi-timeframe Adaptability: Velocity normalization ensures consistent readings across different chart timeframes and asset volatilities
Alert System: Built-in alerts for threshold crossovers and direction changes
🟢 Examples with Preconfigured Settings
Default : Balanced configuration suitable for most timeframes and general trading applications, providing optimal balance between sensitivity and noise filtering for medium-term analysis.
Scalping : High sensitivity setup with shorter lookback period and reduced smoothing for ultra-short-term trades on 1-15 minute charts, optimized for capturing rapid momentum shifts and frequent trading opportunities.
Swing Trading : Extended lookback period with enhanced smoothing and higher threshold for multi-day positions, designed to filter market noise while capturing significant momentum moves on 1-4 hour and daily timeframes.
Price Widget on ScreenSimple yet useful script, to see the PRICE/CHANGE of the chart you are on. I use it in my 6/8 charts screen, so you can see the graph and the price.
MERV: Market Entropy & Rhythm Visualizer [BullByte]The MERV (Market Entropy & Rhythm Visualizer) indicator analyzes market conditions by measuring entropy (randomness vs. trend), tradeability (volatility/momentum), and cyclical rhythm. It provides traders with an easy-to-read dashboard and oscillator to understand when markets are structured or choppy, and when trading conditions are optimal.
Purpose of the Indicator
MERV’s goal is to help traders identify different market regimes. It quantifies how structured or random recent price action is (entropy), how strong and volatile the movement is (tradeability), and whether a repeating cycle exists. By visualizing these together, MERV highlights trending vs. choppy environments and flags when conditions are favorable for entering trades. For example, a low entropy value means prices are following a clear trend line, whereas high entropy indicates a lot of noise or sideways action. The indicator’s combination of measures is original: it fuses statistical trend-fit (entropy), volatility trends (ATR and slope), and cycle analysis to give a comprehensive view of market behavior.
Why a Trader Should Use It
Traders often need to know when a market trend is reliable vs. when it is just noise. MERV helps in several ways: it shows when the market has a strong direction (low entropy, high tradeability) and when it’s ranging (high entropy). This can prevent entering trend-following strategies during choppy periods, or help catch breakouts early. The “Optimal Regime” marker (a star) highlights moments when entropy is very low and tradeability is very high, typically the best conditions for trend trades. By using MERV, a trader gains an empirical “go/no-go” signal based on price history, rather than guessing from price alone. It’s also adaptable: you can apply it to stocks, forex, crypto, etc., on any timeframe. For example, during a bullish phase of a stock, MERV will turn green (Trending Mode) and often show a star, signaling good follow-through. If the market later grinds sideways, MERV will shift to magenta (Choppy Mode), warning you that trend-following is now risky.
Why These Components Were Chosen
Market Entropy (via R²) : This measures how well recent prices fit a straight line. We compute a linear regression on the last len_entropy bars and calculate R². Entropy = 1 - R², so entropy is low when prices follow a trend (R² near 1) and high when price action is erratic (R² near 0). This single number captures trend strength vs noise.
Tradeability (ATR + Slope) : We combine two familiar measures: the Average True Range (ATR) (normalized by price) and the absolute slope of the regression line (scaled by ATR). Together they reflect how active and directional the market is. A high ATR or strong slope means big moves, making a trend more “tradeable.” We take a simple average of the normalized ATR and slope to get tradeability_raw. Then we convert it to a percentile rank over the lookback window so it’s stable between 0 and 1.
Percentile Ranks : To make entropy and tradeability values easy to interpret, we convert each to a 0–100 rank based on the past len_entropy periods. This turns raw metrics into a consistent scale. (For example, an entropy rank of 90 means current entropy is higher than 90% of recent values.) We then divide by 100 to plot them on a 0–1 scale.
Market Mode (Regime) : Based on those ranks, MERV classifies the market:
Trending (Green) : Low entropy rank (<40%) and high tradeability rank (>60%). This means the market is structurally trending with high activity.
Choppy (Magenta) : High entropy rank (>60%) and low tradeability rank (<40%). This is a mostly random, low-momentum market.
Neutral (Cyan) : All other cases. This covers mixed regimes not strongly trending or choppy.
The mode is shown as a colored bar at the bottom: green for trending, magenta for choppy, cyan for neutral.
Optimal Regime Signal : Separately, we mark an “optimal” condition when entropy_norm < 0.3 and tradeability > 0.7 (both normalized 0–1). When this is true, a ★ star appears on the bottom line. This star is colored white when truly optimal, gold when only tradeability is high (but entropy not quite low enough), and black when neither condition holds. This gives a quick visual cue for very favorable conditions.
What Makes MERV Stand Out
Holistic View : Unlike a single-oscillator, MERV combines trend, volatility, and cycle analysis in one tool. This multi-faceted approach is unique.
Visual Dashboard : The fixed on-chart dashboard (shown at your chosen corner) summarizes all metrics in bar/gauge form. Even a non-technical user can glance at it: more “█” blocks = a higher value, colors match the plots. This is more intuitive than raw numbers.
Adaptive Thresholds : Using percentile ranks means MERV auto-adjusts to each market’s character, rather than requiring fixed thresholds.
Cycle Insight : The rhythm plot adds information rarely found in indicators – it shows if there’s a repeating cycle (and its period in bars) and how strong it is. This can hint at natural bounce or reversal intervals.
Modern Look : The neon color scheme and glow effects make the lines easy to distinguish (blue/pink for entropy, green/orange for tradeability, etc.) and the filled area between them highlights when one dominates the other.
Recommended Timeframes
MERV can be applied to any timeframe, but it will be more reliable on higher timeframes. The default len_entropy = 50 and len_rhythm = 30 mean we use 30–50 bars of history, so on a daily chart that’s ~2–3 months of data; on a 1-hour chart it’s about 2–3 days. In practice:
Swing/Position traders might prefer Daily or 4H charts, where the calculations smooth out small noise. Entropy and cycles are more meaningful on longer trends.
Day trader s could use 15m or 1H charts if they adjust the inputs (e.g. shorter windows). This provides more sensitivity to intraday cycles.
Scalpers might find MERV too “slow” unless input lengths are set very low.
In summary, the indicator works anywhere, but the defaults are tuned for capturing medium-term trends. Users can adjust len_entropy and len_rhythm to match their chart’s volatility. The dashboard position can also be moved (top-left, bottom-right, etc.) so it doesn’t cover important chart areas.
How the Scoring/Logic Works (Step-by-Step)
Compute Entropy : A linear regression line is fit to the last len_entropy closes. We compute R² (goodness of fit). Entropy = 1 – R². So a strong straight-line trend gives low entropy; a flat/noisy set of points gives high entropy.
Compute Tradeability : We get ATR over len_entropy bars, normalize it by price (so it’s a fraction of price). We also calculate the regression slope (difference between the predicted close and last close). We scale |slope| by ATR to get a dimensionless measure. We average these (ATR% and slope%) to get tradeability_raw. This represents how big and directional price moves are.
Convert to Percentiles : Each new entropy and tradeability value is inserted into a rolling array of the last 50 values. We then compute the percentile rank of the current value in that array (0–100%) using a simple loop. This tells us where the current bar stands relative to history. We then divide by 100 to plot on .
Determine Modes and Signal : Based on these normalized metrics: if entropy < 0.4 and tradeability > 0.6 (40% and 60% thresholds), we set mode = Trending (1). If entropy > 0.6 and tradeability < 0.4, mode = Choppy (-1). Otherwise mode = Neutral (0). Separately, if entropy_norm < 0.3 and tradeability > 0.7, we set an optimal flag. These conditions trigger the colored mode bars and the star line.
Rhythm Detection : Every bar, if we have enough data, we take the last len_rhythm closes and compute the mean and standard deviation. Then for lags from 5 up to len_rhythm, we calculate a normalized autocorrelation coefficient. We track the lag that gives the maximum correlation (best match). This “best lag” divided by len_rhythm is plotted (a value between 0 and 1). Its color changes with the correlation strength. We also smooth the best correlation value over 5 bars to plot as “Cycle Strength” (also 0 to 1). This shows if there is a consistent cycle length in recent price action.
Heatmap (Optional) : The background color behind the oscillator panel can change with entropy. If “Neon Rainbow” style is on, low entropy is blue and high entropy is pink (via a custom color function), otherwise a classic green-to-red gradient can be used. This visually reinforces the entropy value.
Volume Regime (Dashboard Only) : We compute vol_norm = volume / sma(volume, len_entropy). If this is above 1.5, it’s considered high volume (neon orange); below 0.7 is low (blue); otherwise normal (green). The dashboard shows this as a bar gauge and percentage. This is for context only.
Oscillator Plot – How to Read It
The main panel (oscillator) has multiple colored lines on a 0–1 vertical scale, with horizontal markers at 0.2 (Low), 0.5 (Mid), and 0.8 (High). Here’s each element:
Entropy Line (Blue→Pink) : This line (and its glow) shows normalized entropy (0 = very low, 1 = very high). It is blue/green when entropy is low (strong trend) and pink/purple when entropy is high (choppy). A value near 0.0 (below 0.2 line) indicates a very well-defined trend. A value near 1.0 (above 0.8 line) means the market is very random. Watch for it dipping near 0: that suggests a strong trend has formed.
Tradeability Line (Green→Yellow) : This represents normalized tradeability. It is colored bright green when tradeability is low, transitioning to yellow as tradeability increases. Higher values (approaching 1) mean big moves and strong slopes. Typically in a market rally or crash, this line will rise. A crossing above ~0.7 often coincides with good trend strength.
Filled Area (Orange Shade) : The orange-ish fill between the entropy and tradeability lines highlights when one dominates the other. If the area is large, the two metrics diverge; if small, they are similar. This is mostly aesthetic but can catch the eye when the lines cross over or remain close.
Rhythm (Cycle) Line : This is plotted as (best_lag / len_rhythm). It indicates the relative period of the strongest cycle. For example, a value of 0.5 means the strongest cycle was about half the window length. The line’s color (green, orange, or pink) reflects how strong that cycle is (green = strong). If no clear cycle is found, this line may be flat or near zero.
Cycle Strength Line : Plotted on the same scale, this shows the autocorrelation strength (0–1). A high value (e.g. above 0.7, shown in green) means the cycle is very pronounced. Low values (pink) mean any cycle is weak and unreliable.
Mode Bars (Bottom) : Below the main oscillator, thick colored bars appear: a green bar means Trending Mode, magenta means Choppy Mode, and cyan means Neutral. These bars all have a fixed height (–0.1) and make it very easy to see the current regime.
Optimal Regime Line (Bottom) : Just below the mode bars is a thick horizontal line at –0.18. Its color indicates regime quality: White (★) means “Optimal Regime” (very low entropy and high tradeability). Gold (★) means not quite optimal (high tradeability but entropy not low enough). Black means neither condition. This star line quickly tells you when conditions are ideal (white star) or simply good (gold star).
Horizontal Guides : The dotted lines at 0.2 (Low), 0.5 (Mid), and 0.8 (High) serve as reference lines. For example, an entropy or tradeability reading above 0.8 is “High,” and below 0.2 is “Low,” as labeled on the chart. These help you gauge values at a glance.
Dashboard (Fixed Corner Panel)
MERV also includes a compact table (dashboard) that can be positioned in any corner. It summarizes key values each bar. Here is how to read its rows:
Entropy : Shows a bar of blocks (█ and ░). More █ blocks = higher entropy. It also gives a percentage (rounded). A full bar (10 blocks) with a high % means very chaotic market. The text is colored similarly (blue-green for low, pink for high).
Rhythm : Shows the best cycle period in bars (e.g. “15 bars”). If no calculation yet, it shows “n/a.” The text color matches the rhythm line.
Cycle Strength : Gives the cycle correlation as a percentage (smoothed, as shown on chart). Higher % (green) means a strong cycle.
Tradeability : Displays a 10-block gauge for tradeability. More blocks = more tradeable market. It also shows “gauge” text colored green→yellow accordingly.
Market Mode : Simply shows “Trending”, “Choppy”, or “Neutral” (cyan text) to match the mode bar color.
Volume Regime : Similar to tradeability, shows blocks for current volume vs. average. Above-average volume gives orange blocks, below-average gives blue blocks. A % value indicates current volume relative to average. This row helps see if volume is abnormally high or low.
Optimal Status (Large Row) : In bold, either “★ Optimal Regime” (white text) if the star condition is met, “★ High Tradeability” (gold text) if tradeability alone is high, or “— Not Optimal” (gray text) otherwise. This large row catches your eye when conditions are ripe.
In short, the dashboard turns the numeric state into an easy read: filled bars, colors, and text let you see current conditions without reading the plot. For instance, five blue blocks under Entropy and “25%” tells you entropy is low (good), and a row showing “Trending” in green confirms a trend state.
Real-Life Example
Example : Consider a daily chart of a trending stock (e.g. “AAPL, 1D”). During a strong uptrend, recent prices fit a clear upward line, so Entropy would be low (blue line near bottom, perhaps below the 0.2 line). Volatility and slope are high, so Tradeability is high (green-yellow line near top). In the dashboard, Entropy might show only 1–2 blocks (e.g. 10%) and Tradeability nearly full (e.g. 90%). The Market Mode bar turns green (Trending), and you might see a white ★ on the optimal line if conditions are very good. The Volume row might light orange if volume is above average during the rally. In contrast, imagine the same stock later in a tight range: Entropy will rise (pink line up, more blocks in dashboard), Tradeability falls (fewer blocks), and the Mode bar turns magenta (Choppy). No star appears in that case.
Consolidated Use Case : Suppose on XYZ stock the dashboard reads “Entropy: █░░░░░░░░ 20%”, “Tradeability: ██████████ 80%”, Mode = Trending (green), and “★ Optimal Regime.” This tells the trader that the market is in a strong, low-noise trend, and it might be a good time to follow the trend (with appropriate risk controls). If instead it reads “Entropy: ████████░░ 80%”, “Tradeability: ███▒▒▒▒▒▒ 30%”, Mode = Choppy (magenta), the trader knows the market is random and low-momentum—likely best to sit out until conditions improve.
Example: How It Looks in Action
Screenshot 1: Trending Market with High Tradeability (SOLUSD, 30m)
What it means:
The market is in a clear, strong trend with excellent conditions for trading. Both trend-following and active strategies are favored, supported by high tradeability and strong volume.
Screenshot 2: Optimal Regime, Strong Trend (ETHUSD, 1h)
What it means:
This is an ideal environment for trend trading. The market is highly organized, tradeability is excellent, and volume supports the move. This is when the indicator signals the highest probability for success.
Screenshot 3: Choppy Market with High Volume (BTC Perpetual, 5m)
What it means:
The market is highly random and choppy, despite a surge in volume. This is a high-risk, low-reward environment, avoid trend strategies, and be cautious even with mean-reversion or scalping.
Settings and Inputs
The script is fully open-source; here are key inputs the user can adjust:
Entropy Window (len_entropy) : Number of bars used for entropy and tradeability (default 50). Larger = smoother, more lag; smaller = more sensitivity.
Rhythm Window (len_rhythm ): Bars used for cycle detection (default 30). This limits the longest cycle we detect.
Dashboard Position : Choose any corner (Top Right default) so it doesn’t cover chart action.
Show Heatmap : Toggles the entropy background coloring on/off.
Heatmap Style : “Neon Rainbow” (colorful) or “Classic” (green→red).
Show Mode Bar : Turn the bottom mode bar on/off.
Show Dashboard : Turn the fixed table panel on/off.
Each setting has a tooltip explaining its effect. In the description we will mention typical settings (e.g. default window sizes) and that the user can move the dashboard corner as desired.
Oscillator Interpretation (Recap)
Lines : Blue/Pink = Entropy (low=trend, high=chop); Green/Yellow = Tradeability (low=quiet, high=volatile).
Fill : Orange tinted area between them (for visual emphasis).
Bars : Green=Trending, Magenta=Choppy, Cyan=Neutral (at bottom).
Star Line : White star = ideal conditions, Gold = good but not ideal.
Horizontal Guides : 0.2 and 0.8 lines mark low/high thresholds for each metric.
Using the chart, a coder or trader can see exactly what each output represents and make decisions accordingly.
Disclaimer
This indicator is provided as-is for educational and analytical purposes only. It does not guarantee any particular trading outcome. Past market patterns may not repeat in the future. Users should apply their own judgment and risk management; do not rely solely on this tool for trading decisions. Remember, TradingView scripts are tools for market analysis, not personalized financial advice. We encourage users to test and combine MERV with other analysis and to trade responsibly.
-BullByte
