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M-oscillator

Quality-Controlled Trend Strategy v2 (Expectancy Focused)This script focuses on quality control rather than curve-fitting. No repainting, no intrabar tricks, no fake equity curves. It uses confirmed-bar entries, ATR-based risk, and clean trend logic so backtests reflect what could actually be traded live. If you publish scripts, this is the minimum structure worth sharing. Why this script exists TradingView’s public scripts are flooded with: repainting indicators no stop-loss logic curve-fit entries that collapse live strategies that look good only in hindsight This script is intentionally boring but honest. No repainting. No intrabar tricks. No fake equity curves The goal is quality control, not hype. What this strategy enforces ✔ Confirmed bars only ✔ Single source of truth for indicators ✔ Fixed risk structure ✔ No signal repainting ✔ Clean exits with unique IDs ✔ Works on any liquid market Trading Logic (simple & auditable) Trend filter EMA 50 vs EMA 200 Entry Pullback to EMA 50 RSI confirms momentum (not oversold/overbought) Risk ATR-based stop Fixed R:R One position at a time This is the minimum bar for a strategy to be considered publish-worthy. Why this helps TradingView quality Most low-value scripts fail because they: hide repainting logic skip exits entirely use inconsistent calculations rely on hindsight candles This strategy forces discipline: every signal is confirmed every trade has defined risk behavior is repeatable across symbols & timeframes If more scripts followed this baseline, TradingView’s public library would be far more usable.
Pine Script® stratejisi
AIScripts tarafından
Stochastic MAs+ (K Logit Bands)Below is a ready-to-paste **English TradingView publish description** that is detailed enough to satisfy the “Originality & usefulness” and “Description” house-rule expectations. It explains **what is original**, **why the components are combined**, **how they work together**, and **how to use it**, including practical presets and cautions. --- ## Title **Stochastic MAs+ (K Logit Bands) — Extreme-Zone Reversion with Adaptive Percentile Bands** ## Overview This script is a **Stochastic-based extreme-zone tool** designed for traders who want signals that occur **near statistically-defined extremes**, while reducing noise and overtrading. It combines three ideas into one coherent workflow: 1. **Stochastic %K/%D with selectable smoothing MAs** (EMA/ZEMA/SMA/KAMA) 2. **Adaptive Logit Percentile Bands** computed **on %K** (not price) to define “extreme” zones dynamically 3. A **two-step signal workflow** (Touch → Re-entry → First K/D Cross) with **cooldown + invalidation rules** to suppress repeated signals in choppy markets This is not a “mashup for convenience.” The logit-percentile bands and the signal state-machine are explicitly built to **solve a common Stochastic problem**: fixed 20/80 levels are often too generic, and raw K/D crosses can fire repeatedly in ranges. The components here work together to make Stochastic extremes more **context-aware** and signals more **selective**. --- ## What makes it original / useful ### 1) Dynamic extremes based on the oscillator’s own distribution Instead of using fixed 20/80, the script builds **percentile-based bands on transformed %K values**: * **Logit transform** is used to expand sensitivity near 0 and 100 (where Stochastic tends to compress). * A rolling buffer stores recent transformed values. * **Percentiles** (e.g., 15% / 85%) define adaptive low/high bands that respond to changing volatility regimes. Result: “Extreme” zones are **relative to recent market behavior**, which is often more practical than static thresholds. ### 2) A structured signal process to reduce overtrading Classic Stochastic crossovers can spam signals. This script uses a **state-based trigger**: **Long logic** 1. %K drops below the **adaptive low band** (touch/arm) 2. %K re-enters above the low band (re-entry) 3. The first bullish crossover occurs (K crosses above D) while K remains below the mid-band **Short logic** is symmetrical. Then it adds: * **Cooldown**: prevents clustered entries during noisy periods * **Max wait**: invalidates old setups if confirmation takes too long * **Mid-band invalidation**: if K moves too far (crosses mid), the setup is considered late and discarded This turns Stochastic into a **controlled mean-reversion trigger** rather than an always-on crossover machine. --- ## How it works (plain-language) ### A) Stochastic with selectable smoothing (MAK/MAD) * `%K` is computed from the standard Stochastic formula, then smoothed with your chosen MA. * `%D` is computed by smoothing `%K` with a chosen MA. **MA options** * **EMA**: baseline responsive smoothing * **ZEMA**: reduced lag (faster reactions) * **SMA**: heavier smoothing (less noise) * **KAMA**: adaptive smoothing (reacts faster when price moves, slower in noise) ### B) K-based Logit Percentile Bands The script builds bands from **%K**, not from price: * Convert K into logit space → store in rolling buffer * Compute low/high percentiles in logit space * Convert back to 0–100 space with logistic function * Produce: **kLo / kHi / kMid** This keeps the bands stable and meaningful even when volatility changes. ### C) Signal state-machine * **Touch**: K enters extreme zone * **Re-entry**: K exits the extreme zone * **Trigger**: first K/D cross after re-entry, while still in the “early” half of the band (before mid) The idea is to catch reversals **early**, but not on the very first noisy bounce. --- ## How to use ### 1) Baseline setup (recommended starting point) These defaults are already aligned with the script’s intent: * Stoch: **21 / 3 / 7** * Bands: **bandLen 200**, **low/high 0.15/0.85**, **logitGain 1.0** * Signals: **cooldown 8**, **maxWait 24**, **Use D Direction Confirm ON** This typically produces fewer, more selective signals than traditional 14/3/3 style settings. ### 2) Interpreting the plots * **%K (purple)** and **%D (yellow)** are the smoothed oscillator lines. * **kLo / kHi / kMid** are the adaptive bands. * Labels: * **“L”** appears near the low band when a long setup completes * **“S”** appears near the high band when a short setup completes ### 3) Practical trading workflow * Prefer using signals as **timing cues**, not as a complete strategy by themselves. * Many traders combine this with: * a trend filter (e.g., EMA200 direction) * a volatility filter (avoid low-vol chop) * or higher timeframe confirmation The script is designed to give **high-quality entry timing near extremes**, but you still need a trade plan for exits and risk management. --- ## Tuning guide (fast) ### Want signals closer to extremes (more selective)? * Decrease / increase percentiles: * lowPct **0.12** and highPct **0.88** * Increase logitGain slightly: * logitGain **1.1–1.2** * Increase cooldown: * cooldown **10–14** ### Want earlier signals (faster confirmations)? * Use faster MA for %D (or reduce periodD): * maD = **ZEMA** (or EMA) * Reduce cooldown a bit: * cooldown **5–8** ### Getting too many signals in ranges? * Increase periodK to reduce chop: * periodK **34** * Increase cooldown * Keep D confirm enabled --- ## Strengths * **Adaptive extreme zones**: bands adjust to changing regimes (better context than static 20/80) * **Reduced noise**: the Touch→Re-entry→Cross structure avoids many “random” crosses * **Configurable smoothing**: lets you tune response vs stability via MA type * **Risk-friendly by design**: cooldown + invalidation reduce repeated entries during chop ## Limitations * **Not a full strategy**: no position management, take-profit/stop rules, or trend filter included * **Mean-reversion bias**: in strong trends, Stochastic can stay overbought/oversold for long periods * **Band buffer needs history**: percentile bands are more reliable after enough bars have accumulated (bandLen) --- ## Notes on repainting / confirmations * The percentile band buffer uses **confirmed bars** (optional) to avoid unstable band updates during an incomplete candle. * Signal labels are plotted when the full signal conditions are met (you can enforce confirmed-bar signals via settings). --- ## Suggested disclaimer (TradingView-friendly) This indicator is for research and educational purposes and does not constitute financial advice. Always test settings on your market/timeframe and use proper risk management.
Pine Script® göstergesi
illbecmo tarafından
Goldilocks Pivot FractalsGOLDILOCKS PIVOT FRACTALS - DESCRIPTION Overview Goldilocks Pivot Fractals identifies swing highs and lows using fractal pattern recognition with professional visual presentation. This indicator marks potential reversal points where price creates distinct peaks and valleys - perfect pivot points for support, resistance, and market structure analysis. The "Goldilocks" name reflects the perfectly balanced visual presentation: not too cluttered, not too plain, just right for professional traders. Unlike standard fractal indicators, this edition features fully customizable Buy/Sell labels with tick-based positioning, independent toggle controls, and a high-contrast color scheme optimized for both dark and light chart themes. What Makes It Unique: - Professional label system with full customization (colors, sizes, tick-based offsets) - Toggle labels and arrow shapes independently - High-contrast default colors (teal/maroon) optimized for maximum visibility - Clean, trader-friendly interface with intuitive settings - Works flawlessly on all timeframes and instruments How to Use PERIOD ADJUSTMENT & ADJUSTING SENSITIVITY The Period(s) setting controls how many signals you see: • Period = 2 (default): Shows more signals, catches smaller price swings - best for day trading and scalping • Period = 3-4: Shows medium amount of signals, filters out tiny moves - good for swing trading (holding days to weeks) • Period = 5 or higher: Shows fewer signals, only the biggest turning points - best for long-term position trading - Simple rule: Lower number = more signals. Higher number = fewer, but stronger signals. SIGNALS 🟢 "BUY Label" (Down Fractal) - Marks swing lows and potential support zones - Look for price bouncing up after the fractal forms - Use for identifying pullback entry points in uptrends - Place stops below recent BUY fractals 🔴 "SELL Label" (Up Fractal) - Marks swing highs and potential resistance zones - Look for price rejecting down after the fractal forms - Use for identifying profit targets or short entries - Place stops above recent SELL fractals REPAINTING BEHAVIOR ⚠️ This indicator repaints by design. Fractals require N bars on both sides to confirm, so they appear N bars after the actual pivot point. This is normal and ensures accurate pivot identification. Wait for complete confirmation before trading. TRADING APPLICATIONS 1. Support/Resistance: Mark key price levels for entries and exits 2. Market Structure: higher BUY fractals = uptrend, lower SELL fractals = downtrend 3. Stop Placement: Use recent fractals as logical stop-loss levels 4. Breakout Trading: Monitor price breaking above/below fractal levels 5. Trend Following: Enter on pullbacks to BUY fractals in uptrends 6. Swing Trading: Identify major swing points for position entries CUSTOMIZATION OPTIONS • Show BUY/SELL Labels**: Toggle professional text labels on/off • Show Shapes: Toggle arrow shapes independently • Offset (ticks): Adjust label distance from price bars for perfect positioning • Colors: Customize backgrounds (default: teal/maroon) and text (default: white/yellow) • Label Size: Choose from tiny, small, normal, large, or huge The high-contrast default colors provide excellent visibility without adjustment, but full customization is available to match any chart theme. Key Settings Periods (n) (default: 2): Number of bars on each side of pivot. Lower = more signals, Higher = fewer, stronger signals Show BUY/SELL Labels (default: ON): Display professional text labels Show Shapes (default: ON): Display arrow shapes BUY offset (ticks) (default: 8): Distance BUY labels appear below lows SELL offset (ticks) (default: 8): Distance SELL labels appear above highs Colors: Full customization - defaults optimized for visibility Label size (default: normal): Visual prominence control Key Features ✅ Professional pivot fractal detection ✅ Fully customizable Buy/Sell labels ✅ Independent toggle for labels and shapes ✅ Tick-based offset positioning ✅ High-contrast color scheme ✅ Works on all timeframes and instruments ✅ Clean, intuitive interface ✅ Adjustable sensitivity ✅ Perfect for support/resistance identification ✅ Ideal for market structure analysis
Pine Script® göstergesi
NPR21 tarafından
1
IronRod Trigger SystemIRONROD TRIGGER SYSTEM DESCRIPTION IronRod Trigger System is a momentum oscillator based on the Stochastic Momentum Index (SMI) that identifies trend changes, momentum shifts, and range-bound "chop" zones. Features color-changing SMI lines, histogram columns showing momentum strength, and a visual chop zone that highlights when to trade versus when to stay on the sidelines. The system combines momentum direction (green/red lines), momentum strength (histogram columns), and market context (chop zone cloud) into one clean visual package. The dynamic zero line changes color to signal trade conditions (cyan) versus hold conditions (orange). What Makes It Unique: Dual color-changing lines (SMI and AvgSMI) show momentum direction Histogram columns display momentum strength Chop zone cloud identifies low-momentum periods Dynamic zero line (cyan = trade, orange = hold) Three-color histogram (green = strong up, red = strong down, gray = weak) Adjustable chop zone threshold How to Use THE DISPLAY Lines: Green = bullish momentum (rising) Red = bearish momentum (falling) Gray = neutral/sideways Histogram Columns: Green = strong bullish momentum Red = strong bearish momentum Gray = weak/choppy momentum Zero Line: Cyan (blue) = trade zone - momentum is directional Orange = chop zone - momentum is weak, avoid trading Chop Zone Cloud: Gray shaded area = range where momentum is indecisive (±30 default) TRADING STRATEGIES 1. Chop Zone Trading Trade: Only when SMI is outside gray cloud AND zero line is cyan Avoid: When SMI is inside cloud OR zero line is orange Long: Green line appears above chop zone Short: Red line appears below chop zone This is the key feature - dramatically reduces whipsaws 2. Zero Line Crosses Buy: SMI crosses above zero with cyan zero line Sell: SMI crosses below zero with cyan zero line Strongest signals when AvgSMI follows SMI across zero Ignore crosses when zero line is orange (choppy) 3. Histogram Strength Strong trend: Multiple consecutive green/red columns Momentum building: Columns getting taller Momentum fading: Columns turning gray = exit warning Reversal signal: Gray columns after strong trend 4. Divergence Trading Bearish divergence: Price higher high, SMI lower high → take red line signal Bullish divergence: Price lower low, SMI higher low → take green line signal Most powerful outside chop zone ENTRIES & EXITS Entries: SMI line turns green outside chop zone (long) SMI line turns red outside chop zone (short) SMI crosses zero with cyan zero line Exits: SMI line changes color SMI enters chop zone (orange zero line) Histogram turns gray Stops: Below recent swing low (longs) Above recent swing high (shorts) ADJUSTING SETTINGS Chop Zone (±) (default: 30): Lower (15-25) = More trades, more whipsaws Higher (35-50) = Fewer trades, higher quality Adjust based on instrument volatility Percent K Length (default: 5): Lower (3-4) = More sensitive, faster signals - good for scalping Higher (7-10) = Less sensitive, smoother - good for swing trading Percent D Length (default: 4): Controls smoothing SMI Bar Buffer (default: 4): Histogram color sensitivity TIMEFRAME GUIDE Scalping (1-5m): K=3, watch histogram color flips Day trading (15-60m): Default settings, focus on zero crosses outside chop Swing trading (4H-Daily): K=7-10, trade only strong trends outside chop Key Settings Percent K Length (default: 5): Lookback period - controls sensitivity Percent D Length (default: 4): Smoothing period Chop Zone (±) (default: 30): Range-bound zone threshold SMI Bar Buffer (default: 4): Histogram color change sensitivity Histogram Width (default: 1): Column thickness Key Features ✅ Dual color-changing momentum lines ✅ Histogram columns show strength ✅ Chop zone cloud filters bad trades ✅ Dynamic zero line color ✅ Three-color histogram ✅ Adjustable chop threshold ✅ All timeframes ✅ Reduces whipsaws
Pine Script® göstergesi
NPR21 tarafından
SMI Trigger SystemSMI TRIGGER SYSTEM - DESCRIPTION Overview SMI Trigger System is a momentum oscillator that identifies trend changes and reversals using the Smoothed Stochastic Momentum Index (SMI). Features a color-changing line (green = bullish, red = bearish), cloud shading for momentum zones, and triangle markers that appear exactly when momentum flips. What Makes It Unique: Real-time color-changing momentum line Cloud shading split at zero line Triangle triggers at exact momentum flip points Overbought/oversold limit lines Built-in alerts for all key signals Fully customizable appearance Works on all timeframes How to Use THE DISPLAY Green line/cloud: Bullish momentum Red line/cloud: Bearish momentum Above zero: Bulls in control Below zero: Bears in control Upper limit (+40): Overbought Lower limit (-40): Oversold SIGNALS 🟢 Green Triangle (▲) - Momentum flipping bullish. Buy signal, most powerful below zero. 🔴 Red Triangle (▼) - Momentum flipping bearish. Sell signal, most powerful above zero. TRADING STRATEGIES 1. Trend Following In uptrends: Only take green triangles, ignore red In downtrends: Only take red triangles, ignore green Use higher timeframe for trend, lower for entries Example: Daily uptrend → trade green triangles on 1H chart 2. Limit Reversals Red triangle at upper limit (+40) = strong reversal signal, go short Green triangle at lower limit (-40) = strong reversal signal, go long Wait for triangle AND price confirmation Most reliable on 4H/Daily timeframes 3. Zero Line Trading SMI crosses above zero → bullish bias, take green triangles SMI crosses below zero → bearish bias, take red triangles Zero acts as momentum baseline 4. Divergence Setups Price higher high + SMI lower high = bearish divergence → take next red triangle Price lower low + SMI higher low = bullish divergence → take next green triangle Most powerful at overbought/oversold limits ENTRIES & EXITS Enter: On triangle appearance Stop: Beyond recent opposite-color triangle Target: Limit levels or opposite triangle Add: Additional same-color triangles in strong trends TIMEFRAME GUIDE Scalping (1-5m): Lower %K to 3-4, take all trend-aligned triangles Day trading (15-60m): Default settings (5/3), focus on limit reversals Swing trading (4H-Daily): Higher %K to 7-10, trade only extreme readings ADJUSTING SENSITIVITY SMI %K Length (default: 5): Lower (3-4) = More signals, faster - good for scalping Higher (7-10) = Fewer signals, stronger - good for swing trading SMI %D Length (default: 3): Lower (1-2) = More responsive Higher (5-7) = Smoother ALERTS Built-in alerts for: Triangle appears (momentum flips) SMI crosses zero (trend change) SMI crosses limits (overbought/oversold) Enable in settings, configure in TradingView alert dialog. CUSTOMIZATION Toggle cloud/triangles on/off Adjust triangle size and positioning Customize all colors Triangle label cap prevents clutter Key Settings SMI %K Length (default: 5): Controls sensitivity and signal frequency SMI %D Length (default: 3): Controls smoothing SMI Limit (default: 40): Overbought/oversold threshold Show SMI Cloud (default: ON): Cloud shading Show SMI Flip Triangles (default: ON): Trigger markers Triangle Size/Offset: Appearance customization Enable Alerts (default: ON): Alert notifications Key Features ✅ Color-changing momentum line ✅ Cloud shading for momentum zones ✅ Triangle triggers at exact flips ✅ Overbought/oversold limits ✅ Built-in alert system ✅ Fully customizable ✅ All timeframes ✅ Adjustable sensitivity NPR21 Disclaimer The information and publications are not meant to be, and do not constitute, financial, investment, trading, or other types of advice or recommendations supplied or endorsed by TradingView.
Pine Script® göstergesi
NPR21 tarafından
3
DCA + VA (Value Averaging) | UA versionDCA + VA (Value Averaging) | UA version DCA + VA is a practical portfolio simulator for TradingView that compares two long-term investing approaches on any symbol: • DCA (Dollar-Cost Averaging) — invest a fixed amount on a fixed schedule. • VA (Value Averaging) — invest (and optionally sell) to keep the invested part of the portfolio close to a target growth path. The indicator is plotted in a separate lower pane and is designed for realistic capital efficiency analysis, including the effect of cash sitting idle (“cash drag”). What you see on the chart • Two thick yellow lines — DCA line: portfolio value under classic DCA — VA line: portfolio value under Value Averaging • Trade dots — Small green dots : buys — Small red dots : sells (VA only, if enabled) • UA table + right-side labels — key portfolio metrics for both strategies Core assumptions • Trades are executed at bar close ( close ) • Dividends and broker commissions are ignored (for now) • Optional tax logic is available for VA sells: tax is applied to realized profit using average cost basis Line mode • Капітал+Кеш (default): shows total portfolio value = holdings + cash (honest “cash drag”) • Лише капітал : shows holdings value only (invested part) DCA logic (classic) Start from Start date . On each scheduled period ( Week / Month / Half-year / Year ) the script: • adds the deposit amount to cash • buys the asset for that amount (if cash is available) VA logic (Value Averaging) VA maintains a target value for the invested holdings (asset value only, cash not included ). On each VA step: Regular deposit is added to VA cash Target is updated by period growth g (derived from annual CAGR and selected frequency) If holdings value is below target → buy using cash (optionally add extra if enabled) If holdings value is above target and selling is enabled → sell down to target (cash increases; optional profit tax applies) Target update formula: Target = Target × (1 + g) + Regular deposit Optional controls • Sell excess ( vaSellExcess ): allow sells when above target • Add extra on drawdowns ( vaAddExtra ): allow additional contributions when cash isn’t enough • Max extra per period ( vaMaxExtra ): cap extra contributions ( 0 = unlimited ) • Tax on sells ( vaUseTax / vaTaxRate ): apply tax to realized profit (average cost basis) Table metrics (UA) For both DCA and VA: • Накопичено — total contributed cash • Інвестовано — current invested cost basis • Кеш — cash balance • Капітал — portfolio value (based on selected line mode) • Прибуток % — ROI in percent • CAGR стратегії — annualized return based on elapsed time Best use (recommended settings) • Best timeframe: 1W Weekly candles make long-term simulations cleaner and more realistic: less noise, fewer “micro” fluctuations, and more stable periodic triggers for DCA/VA steps. • Recommended workflow: Set chart timeframe to 1W Choose deposit frequency (usually Тиждень or Місяць ) Start with Капітал+Кеш to see true cash drag Compare DCA vs VA using Прибуток % and CAGR (not only absolute $) • How to interpret results: — If VA has higher capital but lower ROI %, it usually means you contributed more (extra funding enabled). — If VA sells rarely, your target path may be aggressive (high CAGR + large deposits), so holdings don’t exceed the target often. Notes • If VA shows higher capital but lower profit % , it usually means more total contributions (extra funding enabled). • Sells can be rare if the target path grows aggressively (high CAGR + large deposits).
Pine Script® göstergesi
livesey83 tarafından
SCR Signals(개요) 스토캐스틱, CCI, RSI를 결합한 지표입니다. 편의상 SCR이라고 명명할게요 * 블로거 'SOXL연구원님의 SCR을 지표화했습니다. (지표설명) 1. 스토캐스틱은 %K길이, %K스무딩, %D스무딩이 각각 5,1,3 이 기본입니다. 어퍼밴드(과매수)는 80, 로우어밴드(과매도)는 20이며 설정해서 수정 가능합니다. 2. CCI는 길이 20이 기본입니다. 어퍼밴드(과매수)는 100, 로우어밴드(과매도)는 -100이며 역시 설정에서 변경가능합니다. 3. RSI 길이 14가 기본입니다. 어퍼밴드(과매수)는 70, 로우어밴드(과매도)는 30이며 역시 설정에서 변경가능합니다. (시그널) 세개 지표 중 1개지표가 동시에 과매수 해소되는 순간 S1, 2개지표가 동시에 과매수 해소되는 순간 S2, 3개지표 동시에 과매수 해소시 S3로 하고 캔들 위쪽에 표시 / 세개 지표 중 1개지표가 과매도 진입시 B1, 2개지표가 동시에 과매도 진입시 B2, 3개지표가 동시에 과매도 진입시 B3로 하고 캔들 아래쪽에 표시 Overview SCR is a combined signal system built from Stochastic, CCI, and RSI. For convenience, I call this indicator SCR. This script is an implementation/visualization of the SCR concept shared by the blogger “SOXL Researcher” (SOXL연구원). Indicator Settings Stochastic Default parameters: %K Length = 5, %K Smoothing = 1, %D Smoothing = 3 Default bands: Overbought (Upper) = 80, Oversold (Lower) = 20 All values can be changed in the settings. CCI Default length: 20 Default bands: Overbought (Upper) = 100, Oversold (Lower) = -100 All values can be changed in the settings. RSI Default length: 14 Default bands: Overbought (Upper) = 70, Oversold (Lower) = 30 All values can be changed in the settings. Signals (Plotted on the Main Price Chart) Signals are generated when the indicators trigger their conditions on the same bar (simultaneously). Overbought Resolution Signals (S) — plotted above candles S1: Exactly 1 of the three indicators resolves overbT (overbought resolution) on the same bar S2: Exactly 2 indicators resolve overbought on the same bar S3: All 3 indicators resolve overbought on the same bar Oversold Entry Signals (B) — plotted below candles B1: Exactly 1 of the three indicators enters oversold on the same bar B2: Exactly 2 indicators enter oversold on the same bar B3: All 3 indicators enter oversold on the same bar
Pine Script® göstergesi
lisnuby tarafından
Multi-Indicator DashboardMulti-timeframe trading dashboard overlay on your chart. Analyzes Trend, Momentum, Swing, Strength, Direction, Volatility, and delivers a final VIEW (Bullish/Bearish/Flat) across 5 key timeframes. Perfect for quick multi-TF alignment checks! W → D → 2H → 1H → 15M Features Color-Coded Cells: Green (Bullish), Red (Bearish), Gray (Neutral). Historical Mode: Toggle "Enable Historical View" → Slider picks N bars back (chart TF-aware: e.g., 10 bars = 2.5H on 15M). Yellow vertical line + date label marks the exact bar Quick Setup Add to chart → Customize inputs. Historical: Enable + slide "Bars Back" for past data snapshots. Views Update Live: Real-time on current/historical bars.
Pine Script® göstergesi
prabhu_ken01 tarafından
Market Entropy [Alpha Extract]A sophisticated information theory-based market analysis system that measures price randomness and structural order using Shannon entropy calculations across price, returns, and volume distributions. Utilizing adaptive percentile-based thresholds and multi-timeframe confirmation, this indicator delivers institutional-grade regime classification distinguishing between structured trending conditions and chaotic ranging environments. The system's composite entropy framework combined with dynamic gradient visualization and MTF alignment validation provides comprehensive market state assessment for optimal strategy selection and risk management. 🔶 Advanced Shannon Entropy Engine Implements pure information theory methodology using histogram distribution analysis with configurable bin counts to calculate normalized entropy values for price, returns, and volume metrics. The system constructs probability distributions from rolling windows, applies logarithmic entropy calculations, and normalizes against theoretical maximum entropy to produce 0-1 bounded measurements of market randomness and predictability. float entropy = 0.0 float total = float(len) for i = 0 to bins - 1 float count = array.get(bin_counts, i) if count > 0 float prob = count / total entropy -= prob * math.log(prob) / math.log(2) float max_entropy = math.log(bins) / math.log(2) result := entropy / max_entropy 🔶 Adaptive Percentile Threshold System Features intelligent threshold determination using rolling percentile calculations over configurable calibration periods to establish structure and chaos zones that adapt to changing market characteristics. The system calculates lower percentile for structure threshold (ordered markets) and upper percentile for chaos threshold (random markets), enabling regime classification that adjusts automatically to market evolution. 🔶 Multi-Timeframe Alignment Framework Implements comprehensive MTF entropy analysis retrieving composite entropy from three configurable higher timeframes with alignment validation logic. The system calculates divergence between current timeframe entropy and higher timeframe values, generating confirmation signals only when all timeframes exhibit entropy agreement within tolerance bands for enhanced signal reliability. 🔶 Three-Regime Classification Engine Provides sophisticated market state determination classifying conditions as structure (entropy below lower threshold), chaos (entropy above upper threshold), or neutral (entropy between thresholds) with regime strength measurement. The system tracks regime transitions and calculates conviction scores based on distance from thresholds, enabling nuanced assessment of market order versus randomness. 🔶 Composite Entropy Architecture Combines three distinct entropy measurements weighted by relevance to create unified market randomness metric with exponential smoothing for stability. The system applies 40% weight to price entropy (distribution shape), 35% to return entropy (movement patterns), and 25% to volume entropy (participation randomness), capturing comprehensive market microstructure information. 🔶 Dynamic Gradient Visualization System Features advanced color blending engine that transitions between primary and secondary colors based on entropy momentum intensity with glow effects for conviction emphasis. The system calculates entropy rate of change, normalizes against recent extremes, and applies smooth color interpolation from secondary to primary hues as momentum intensifies, creating intuitive visual representation of regime strength. 🔶 Intelligent Zone Fill Architecture Implements multi-layer gradient fills within structure and chaos zones that intensify as entropy moves deeper into extremes, providing immediate visual feedback on regime conviction. The system creates three-tier gradient levels at 33%, 66%, and 100% penetration into zones with progressively lower transparency, emphasizing extreme entropy conditions requiring attention. 🔶 Momentum-Based Divergence Detection Generates entry signals when entropy crosses below bull divergence level or above bear divergence level, identifying potential regime transitions before price confirmation. The system monitors entropy momentum direction during threshold crossings and validates with MTF alignment, producing high-probability reversal signals at entropy extremes. 🔶 Normalized Display Framework Provides 0-100 scaled visualization using adaptive min-max normalization calculated from percentile analysis, ensuring consistent visual interpretation across different market conditions and instruments. The system transforms raw composite entropy into normalized space with dynamic thresholds, enabling cross-market and cross-timeframe entropy comparison. 🔶 Regime Strength Measurement Calculates conviction scores measuring depth of entropy penetration into structure or chaos zones relative to historical ranges, quantifying how definitively current conditions favor trending versus ranging strategies. The system produces 0-1 strength values that modulate visual intensity and can inform position sizing or strategy allocation decisions. 🔶 Performance Optimization Framework Utilizes efficient array operations with optimized histogram calculations and configurable lookback limits to balance accuracy with computational efficiency. The system includes intelligent caching of percentile calculations and streamlined probability summations for smooth real-time entropy updates across extended historical periods. 🔶 Why Choose Market Entropy ? This indicator delivers sophisticated market regime analysis through pure information theory methodology measuring actual randomness versus structure in price behavior. Unlike traditional volatility or trend indicators that measure price movement characteristics, Market Entropy quantifies the fundamental predictability of market conditions using Shannon entropy calculations. The system's composite approach combining price, return, and volume distributions with adaptive thresholds, MTF confirmation, and gradient visualization makes it essential for traders seeking objective regime classification to optimize strategy selection. Low entropy (structure zone) indicates ordered, trending conditions favorable for directional strategies, while high entropy (chaos zone) signals random, ranging markets better suited for mean reversion or reduced exposure. The indicator excels at identifying regime transitions before they become obvious in price action across cryptocurrency, forex, and equity markets.
Pine Script® göstergesi
AlphaExtract tarafından
Nuh's Complete Multi-Timeframe Dashboard v4.0Nuh's Complete Multi-Timeframe Dashboard v4.0 - Unified Power System Professional Multi-Timeframe Technical Analysis Dashboard Nuh's Complete Multi-Timeframe Dashboard v4.0 represents a comprehensive trading analysis system that unifies 20 powerful technical indicators across up to 6 customizable timeframes into a single, intelligent dashboard. This advanced indicator combines trend analysis (EMA, Alpha Trend, SuperTrend, ADX, DI), momentum oscillators (RSI, Stochastic RSI, MACD, CCI, Williams %R, WaveTrend, KST), volume indicators (OBV, CMF, Volume Analysis, MFI), and volatility measures (Squeeze Momentum, Bollinger Bands, ATR, Williams VIX Fix) to provide traders with a holistic market perspective. Each indicator can be independently enabled or disabled, allowing complete customization based on your trading strategy and preferences. The revolutionary Weighted Power System is the core innovation of this dashboard, transforming raw indicator signals into actionable market power scores. Unlike traditional dashboards that simply count bullish or bearish signals, this system applies sophisticated weighting to each indicator based on your chosen preset (Balanced, Trend Focus, Momentum Focus, Volume Focus) or custom weights. It then combines these weighted signals across multiple timeframes—with timeframe-specific weighting for scalping, day trading, or swing trading styles—to calculate an Overall Market Power score. This provides you with clear percentage-based bullish and bearish power readings, eliminating guesswork and enabling confident trade decisions backed by mathematical confluence. Built for serious traders who demand precision and flexibility, the dashboard features a fully customizable display with 20 indicator rows that can be reordered to match your preferences, color-coded gradient visualization for instant market sentiment recognition, and integrated Wundertrading-compatible alerts for automated trading. The system supports both legacy count-based alerts and modern power-threshold alerts, allowing you to receive notifications when market conditions meet your specified confluence requirements. Whether you're scalping on lower timeframes or swing trading on higher timeframes, this professional-grade tool adapts to your trading style while maintaining clean, readable visualization that won't clutter your charts.
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nuhkoc1960 tarafından
Harmonic Liquidity Waves [JOAT]Harmonic Liquidity Waves Overview Harmonic Liquidity Waves is an open-source oscillator indicator that combines multiple volume-based analysis techniques into a unified liquidity flow framework. It integrates VWAP calculations, Chaikin Money Flow (CMF), Money Flow Index (MFI), and Klinger Volume Oscillator (KVO) with custom harmonic wave calculations to provide a comprehensive view of volume dynamics and money flow. What This Indicator Does The indicator calculates and displays: Liquidity Flow - Volume-weighted price movement accumulated over a lookback period Harmonic Wave - Multi-depth smoothed oscillator derived from liquidity flow Chaikin Money Flow (CMF) - Classic accumulation/distribution indicator Money Flow Index (MFI) - Volume-weighted RSI showing buying/selling pressure Klinger Volume Oscillator (KVO) - Trend-volume relationship indicator Wave Interference - Combined constructive/destructive wave patterns Volume Profile POC - Point of Control from simplified volume distribution How It Works The core liquidity flow calculation tracks volume-weighted price changes: calculateLiquidityFlow(series float vol, series float price, simple int period) => float priceChange = ta.change(price) float volumeFlow = vol * math.sign(priceChange) // Accumulated over period using buffer array float avgFlow = flowSum / period avgFlow The harmonic oscillator applies multi-depth smoothing: harmonicOscillator(series float flow, simple int depth, simple int period) => float harmonic = 0.0 for i = 1 to depth float wave = ta.ema(flow, period * i) / i harmonic += wave harmonic / depth CMF measures accumulation/distribution using the Money Flow Multiplier: float mfm = ((close - low) - (high - close)) / (high - low) float mfv = mfm * vol float cmf = ta.sum(mfv, period) / ta.sum(vol, period) * 100 Signal Generation Liquidity shift signals occur when: Bullish Shift: Smoothed wave crosses above signal line Bearish Shift: Smoothed wave crosses below signal line Strong signals require volume indicator confirmation: Strong Bull: Bullish shift + CMF > 0 + MFI > 50 + KVO > 0 Strong Bear: Bearish shift + CMF < 0 + MFI < 50 + KVO < 0 Divergence detection compares price pivots with liquidity wave pivots to identify potential reversals. Dashboard Panel (Bottom-Right) Wave Strength - Normalized wave magnitude Volume Pressure - Current volume vs average percentage Flow Direction - BUYING or SELLING based on wave sign Histogram - Wave minus signal line value CMF - Chaikin Money Flow reading MFI - Money Flow Index value (0-100) KVO - Klinger oscillator value Vol Confluence - Combined volume indicator score Signal - Current actionable status Visual Elements Liquidity Wave - Main oscillator line Wave Signal - Smoothed signal line for crossover detection Wave Histogram - Difference between wave and signal Wave Interference - Area plot showing combined wave patterns CMF/KVO/MFI Lines - Individual volume indicator plots Divergence Labels - BULL DIV / BEAR DIV markers Shift Markers - Triangles for basic shifts, labels for strong shifts Input Parameters Wave Period (default: 21) - Base period for liquidity calculations Volume Weight (default: 1.5) - Multiplier for volume emphasis Harmonic Depth (default: 3) - Number of smoothing layers Smoothing (default: 3) - Final wave smoothing period Suggested Use Cases Identify accumulation/distribution phases using CMF and wave direction Confirm momentum with MFI overbought/oversold readings Watch for divergences between price and liquidity flow Use strong signals when multiple volume indicators align Timeframe Recommendations Best on 15m to Daily charts. Volume-based indicators require sufficient trading activity for meaningful readings. Limitations Volume data quality varies by exchange and instrument Divergence detection uses pivot-based lookback and may lag Volume Profile POC is simplified and not a full profile analysis Open-Source and Disclaimer This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. It does not constitute financial advice. Past performance does not guarantee future results. Always use proper risk management. - Made with passion by officialjackofalltrades
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officialjackofalltrades tarafından
[RoyalNeuron] RSI-SMA [WidowMaker v1.0]Hey everyone,👋 This is WidowMaker v1.0 — my free take on a really clean, zero-lag smoothed RSI that actually helps you see momentum without all the noise. What makes it different: - Smoothed RSI (you pick SMA or EMA) so it doesn’t whipsaw as much as the default one - Green line when momentum is rising, red when it’s falling — super easy to read at a glance - Histogram turns solid green for strong upward push, solid red when things are fading - Very faint green background in oversold (buy zone) and faint red in overbought (caution zone) Quick way to use it: - Green line + solid green histogram near the bottom (oversold) → good spot for longs - Red line + solid red histogram near the top (overbought) → time to think about shorts or taking profit I made it because I was tired of cluttered indicators that look cool but don’t help much in real trading. I am thinking of an updated version, still thinking of what to add so that to add value. Would love your honest feedback — like it, use it, tell me what you’d add. More free tools on the way! Cheers, RoyalNeuron 👑 RSI, Smoothed RSI, Momentum, Oscillator, Overbought, Oversold, Histogram, Green Red, Free, Alerts
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Relative Strength Index SmoothedDefinition The Relative Strength Index (RSI) is a well versed momentum based oscillator which is used to measure the speed (velocity) as well as the change (magnitude) of directional price movements. Essentially RSI, when graphed, provides a visual mean to monitor both the current, as well as historical, strength and weakness of a particular market. The strength or weakness is based on closing prices over the duration of a specified trading period creating a reliable metric of price and momentum changes. Given the popularity of cash settled instruments (stock indexes) and leveraged financial products (the entire field of derivatives); RSI has proven to be a viable indicator of price movements. History J.Welles Wilder Jr. is the creator of the Relative Strength Index. A former Navy mechanic, Wilder would later go on to a career as a mechanical engineer. After a few years of trading commodities, Wilder focused his efforts on the study of technical analysis. In 1978 he published New Concepts in Technical Trading Systems. This work featured the debut of his new momentum oscillator, the Relative Strength Index, better known as RSI. Over the years, RSI has remained quite popular and is now seen as one of the core, essential tools used by technical analysts the world over. Some practitioners of RSI have gone on to further build upon the work of Wilder. One rather notable example is Andrew Cardwell who used RSI for trend confirmation. Calculation RSI = 100 – 100/ (1 + RS) RS = Average Gain of n days UP / Average Loss of n days DOWN For a practical example, the built-in Pine Script function rsi(), could be replicated in long form as follows. change = change(close) gain = change >= 0 ? change : 0.0 loss = change < 0 ? (-1) * change : 0.0 avgGain = rma(gain, 14) avgLoss = rma(loss, 14) rs = avgGain / avgLoss rsi = 100 - (100 / (1 + rs)) "rsi", above, is exactly equal to rsi(close, 14). The basics As previously mentioned, RSI is a momentum based oscillator. What this means is that as an oscillator, this indicator operates within a band or a set range of numbers or parameters. Specifically, RSI operates between a scale of 0 and 100. The closer RSI is to 0, the weaker the momentum is for price movements. The opposite is also true. An RSI closer to 100 indicates a period of stronger momentum. - 14 days is likely the most popular period, however traders have been known to use a wide variety of numbers of days. What to look for Overbought/Oversold Wilder believed that when prices rose very rapidly and therefore momentum was high enough, that the underlying financial instrument/commodity would have to eventually be considered overbought and a selling opportunity was possibly at hand. Likewise, when prices dropped rapidly and therefore momentum was low enough, the financial instrument would at some point be considered oversold presenting a possible buying opportunity. There are set number ranges within RSI that Wilder consider useful and noteworthy in this regard. According to Wilder, any number above 70 should be considered overbought and any number below 30 should be considered oversold. An RSI between 30 and 70 was to be considered neutral and an RSI around 50 signified “no trend”. Some traders believe that Wilder’s overbought/oversold ranges are too wide and choose to alter those ranges. For example, someone might consider any number above 80 as overbought and anything below 20 as oversold. This is entirely at the trader’s discretion. Divergence RSI Divergence occurs when there is a difference between what the price action is indicating and what RSI is indicating. These differences can be interpreted as an impending reversal. Specifically there are two types of divergences, bearish and bullish. Bullish RSI Divergence – When price makes a new low but RSI makes a higher low. Bearish RSI Divergence – When price makes a new high but RSI makes a lower high. Wilder believed that Bearish Divergence creates a selling opportunity while Bullish Divergence creates a buying opportunity. Failure Swings Failure swings are another occurrence which Wilder believed increased the likelihood of a price reversal. One thing to keep in mind about failure swings is that they are completely independent of price and rely solely on RSI. Failure swings consist of four “steps” and are considered to be either Bullish (buying opportunity) or Bearish (selling opportunity). Bullish Failure Swing RSI drops below 30 (considered oversold). RSI bounces back above 30. RSI pulls back but remains above 30 (remains above oversold) RSI breaks out above its previous high. Bearish Failure Swing RSI rises above 70 (considered overbought) RSI drops back below 70 RSI rises slightly but remains below 70 (remains below overbought) RSI drops lower than its previous low. Cardwell’s trend confirmations Of course no one indicator is a magic bullet and almost nothing can be taken simply at face value. Andrew Cardwell, who was mentioned earlier, was one of those students who took Wilder’s RSI interpretations and built upon them. Cardwell’s work with RSI led to RSI being a great tool not just for anticipating reversals but also for confirming trends. Uptrends/Downtrends Cardwell made keen observations while studying Wilder’s ideas of divergence. Cardwell believed that: Bullish Divergence only occurs in a Bearish Trend. Bearish Divergence only occurs in an Bullish Trend. Both Bullish and Bearish Divergence usually cause a brief price correction and not an actual trend reversal. What this means is that essentially Divergence should be used as a way to confirm trends and not necessarily anticipate reversals. Reversals Cardwell also discovered what are referred to as Positive and Negative Reversals. Positive and Negative Reversals are basically the opposite of Divergence. Positive Reversal occurs when price makes a higher low while RSI makes a lower low. Price proceeds to rise. Positive Reversals only occur in Bullish Trends. Negative Reversal occurs when price makes a lower high while RSI makes a higher high. Price proceeds to fall. Negative Reversals only occur in Bearish Trends. Positive and Negative Reversals can be boiled down to cases where price outperformed momentum. And because Positive and Negative Reversals only occur in their specified trends, they can be used as yet another tool for trend confirmation. Summary For more than four decades the Relative Strength Index (RSI) has been an extremely valuable tool for almost any serious technical analyst. Wilder’s work with momentum laid the groundwork for future chartists and analysts to dive in deeper to further explore the implications of his RSI modeling and its correlation with underlying price movements. As such, RSI is simply one of the best tools or indicators in a trader’s arsenal of market metrics to develop most any trading methodology. Only the novice will take one look at RSI and assume which direction the market will be heading next based off of one number. Wilder believed that a bullish divergence was a sign that the market would soon be on the rise, while Cardwell believed that such a divergence was merely a slight price correction on the continued road of a downward trend. As with any indicator, a trader should take the time to research and experiment with the indicator before relying on it as a sole source of information for any trading decision. When used in proper its perspective, RSI has proven to be a core indicator and reliable metric of price, velocity and depth of market.
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cpolaritz2 tarafından
Stochastic RSI (adjustable fast line color)Definition The Stochastic RSI indicator (Stoch RSI) is essentially an indicator of an indicator. It is used in technical analysis to provide a stochastic calculation to the RSI indicator. This means that it is a measure of RSI relative to its own high/low range over a user defined period of time. The Stochastic RSI is an oscillator that calculates a value between 0 and 1 which is then plotted as a line. This indicator is primarily used for identifying overbought and oversold conditions. History The Stochastic RSI (Stoch RSI) indicator was developed by Tushard Chande and Stanley Kroll. They introduced their indicator in their 1994 book The New Technical Trader. Calculation In this example, a very common 14 Period Stoch RSI is used. Stoch RSI = (RSI - Lowest Low RSI) / (Highest High RSI - Lowest Low RSI) Here are some approximate benchmark levels: 14 Day Stoch RSI = 1 when RSI is at its highest level in 14 Days. 14 Day Stoch RSI = .8 when RSI is near the high of its 14 Day high/low range. 14 Day Stoch RSI = .5 when RSI is in the middle of its 14 Day high/low range. 14 Day Stoch RSI = .2 when RSI is near the low of its 14 Day high/low range. 14 Day Stoch RSI = 0 when RSI is at its lowest level in 14 Days. The basics It is important to remember that the Stoch RSI is an indicator of an indicator making it two steps away from price. RSI is one step away from price and therefore a stochastic calculation of the RSI is two steps away. This is important because as with any indicator that is multiple steps away from price, Stoch RSI can have brief disconnects from actual price movement. That being said, as a range bound indicator, the Stoch RSI's primary function is identifying crossovers as well as overbought and oversold conditions. What to look for Overbought/Oversold Overbought and Oversold conditions are traditionally different than the RSI. While RSI overbought and oversold conditions are traditionally set at 70 for overbought and 30 for oversold, Stoch RSI are typically .80 and .20 respectively. When using the Stoch RSI, overbought and oversold work best when trading along with the underlying trend. During an uptrend, look for oversold conditions for points of entry. During a downtrend, look for overbought conditions for points of entry. Summary When using Stoch RSI in technical analysis, a trader should be careful. By adding the Stochastic calculation to RSI, speed is greatly increased. This can generate many more signals and therefore more bad signals as well as the good ones. Stoch RSI needs to be combined with additional tools or indicators in order to be at its most effective. Using trend lines or basic chart pattern analysis can help to identify major, underlying trends and increase the Stoch RSI's accuracy. Using Stoch RSI to make trades that go against the underlying trend is a dangerous proposition. Inputs K The time period to be used in calculating the %K. 3 is the default. D % D = Percent of Deviation between price and the average of previous prices (Momentum). The time period to be used in calculating the %D. 3 is the default. RSI Length The time period to be used in calculating the RSI Stochastic Length The time period to be used in calculating the Stochastic RSI Source Determines what data from each bar will be used in calculations. Close is the default.
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Elite Cumulative Volume Delta OscillatorOverview The Elite CVD+ is a premium-grade, session-resettable Cumulative Volume Delta indicator designed exclusively for professional futures and volume-profile traders. By focusing on the cleaner and more actionable Line-Focused mode, it transforms raw order flow data into a precise decision engine that reveals institutional buying/selling pressure, absorption, exhaustion, and high-probability reversal/continuation zones. Unlike standard CVD tools that accumulate indefinitely or reset awkwardly, this version resets cleanly at your chosen anchor period (default daily) while pulling granular delta from lower timeframes when desired. The result: a smooth, non-repainting line that highlights real-time shifts in aggressive participation without the noise of perpetual accumulation. Why This Indicator Is Elite-Level Useful True Institutional Footprint Cumulative Volume Delta measures the net aggressive buying (bid hits) vs. selling (ask hits). Sustained positive CVD = buyers in control; negative = sellers dominating. When price makes new highs on weakening CVD → classic bearish divergence signaling distribution. The session reset prevents old data from distorting current conviction, making divergences far more reliable than perpetual CVD. Early Reversal Detection via Absorption & Extremes Absorption highlighting flags scenarios where heavy delta pushes against price but price refuses to follow (e.g., massive selling into lows yet price holds or closes higher) — textbook trapping/retail stop-hunting. Session CVD extremes with dynamic test zones pinpoint where aggressive flow is exhausted. Price returning to test these levels often produces high-R:R reversals. Confluence-Rich Signals Dual EMAs provide trend/filter context (crossovers, zero-line bounces). Dynamic coloring instantly shows momentum strength. Extreme single-bar delta highlights climax buying/selling. Built-in regular + hidden divergences align order flow with price structure. Multi-Timeframe Consistency Optional custom lower-TF delta fetch ensures the same granular data regardless of chart timeframe — critical for traders who switch between 1-min execution charts and 15-min/1H analysis charts. Clean, Low-Lag Visuals Thick CVD line with intelligent coloring, subtle backgrounds, persistent extreme lines, and optional labels keep the pane readable even during fast markets. No clutter from inferior candle representations. How Professional Traders Use Elite CVD+ Most Successfully Primary Setup Framework Use on futures with reliable volume delta (ES, NQ, YM, CL, GC, etc.). Best timeframes: 3–15 minutes for intraday, 1H–4H for swing. Combine with price action structure (order blocks, fair value gaps, market profile highs/lows). Practical Tips for Maximum Edge Anchor Period: '1D' for regular session trading (resets at 00:00 exchange time). Use '1W' for weekly bias or '4H' for London/NY session-specific flow. Lower Timeframe Delta: Enable custom and set to '1' or '3' for maximum granularity on indices. Leave disabled on higher charts for smoother read. Absorption Tuning: Raise threshold to 80–90 on volatile instruments (NQ) to filter noise; lower to 70 on quieter ones (CL, GC). Divergences: Most powerful on 15M+. Disable hidden on very low TFs if too noisy. Alerts: Use the master “Any Event” alert for push/email/webhook notifications of zero crosses or new extremes — perfect for mobile monitoring. Combination Tools: Pair with session VWAP, volume profile (fixed range at highs/lows), or psychological levels for triple confluence.
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Manifesting_Gains tarafından
5
BTC - StableFlow: Pit-Stop & Refuel EngineBTC – StableFlow: Pit-Stop & Refuel Engine | RM Strategic Context: The Institutional Gas Station In the high-speed race of the crypto markets, Stablecoins (USDT, USDC, DAI) represent the Fuel, and Bitcoin is the Race Car. Most traders only look at the car's speed (Price), but they ignore the gas tank. The StableFlow Engine is a telemetry dashboard designed to monitor the "Fuel Pressure" within the ecosystem, identifying exactly when the car is being refueled and when it is running on empty. The Telemetry Logic: How to Read the Race The indicator operates on a Relative Velocity model. We aren't just looking at how many Stablecoins exist; we are measuring the Acceleration of Stablecoin Market Cap relative to the Acceleration of BTC Price. 1. The Fuel Reservoir (The Histogram) • Cyan Zones (Refuel): The gas station is open. Institutional "Dry Powder" is flowing into stables faster than it is being spent on BTC. The tank is filling up. • Orange Zones (Exhaust): The "Overdrive." The car is driving faster than the gas can be pumped. Price is outperforming the stablecoin supply—this is unsustainable and usually precedes a stall. 2. Lap Transitions (The Grey Lines) These vertical markers signify a Regime Shift . They trigger the moment the momentum crosses the zero-axis, visually distinguishing the transition between a "Net-Refueling" period and a "Net-Exhaustion" period. While not used as direct entry signals, they define the Macro Lap we are currently in. Operational Playbook: The Pit-Stop Signals We don't just buy because the tank is full; we buy when the car exits the pits and begins to accelerate. This is captured by our proprietary Pit-Stop Pips. • Blue Pip (Pit-Stop Buy): Triggered when the Refuel momentum has peaked and is now rotating back into the market. The refuel is complete; the car is rejoining the race with a full tank. • Red Pip (Exhaust Sell): Triggered when the price acceleration has overextended relative to its fuel source and begins to "roll over." The tank is near empty; time for a tactical pull-back. Settings & Calibration: The Pit Wall Dashboard Signal Mode & Logic The engine features a dual-mode signaling system to adapt to different market conditions (or your personal preferred logic): • Consecutive Mode: Best for high-velocity trends. Fires a pip after n bars of momentum reversal (Default: 2 bars). • Percentage (%) Mode: Best for structural fades. Fires a pip when the momentum retraces by a specific percentage (e.g., 15%) from its local peak, regardless of the bar count. Recommended Calibration While the engine is versatile across various timeframes, the Weekly (1W) chart is the preferred setting for identifying high-conviction macro signals. Lower timeframes provide tactical speed, but the 1W frame offers significantly cleaner signals by filtering out the daily market noise. Weekly (1W) — The Macro Signal (Preferred): * Velocity Lookback: 20 | Smoothing: 5. Peak Lookback: 25 (Represents roughly half a year of telemetry data). This is a good starting point for identifying major cycle rotations. Daily (1D) — The Tactical Pulse: * Velocity Lookback: 20 | Smoothing: 5. Peak Lookback: 25 (Represents one trading month of telemetry). Useful for active swing traders looking for entry/exit timing within an established macro trend. Technical Documentation Data Sourcing & Aggregation The script utilizes request.security to aggregate a "Big Three" Stablecoin Market Cap (USDT + USDC + DAI). This prevents "False Exhaustion" signals caused by capital simply migrating between different stablecoin assets. Mathematical Foundation The core engine calculates the Rate of Change (ROC) for the Aggregate Stablecoin Supply and BTC Price over a synchronized lookback window. Formula Logic: Fuel Pressure = EMA ( ROC(Stables) - ROC(BTC) ) The Pit-Stop Pips utilize a local peak-finding algorithm via ta.highest and ta.lowest within a rolling 25-bar window to calculate the Relative Retracement Magnitude . This ensures signals are mathematically tied to the volatility of the current market regime. The Dual-Fuel Framework: StableFlow x Liquisync The StableFlow Engine is designed to function as the tactical counterpart to the Liquisync: Macro Pulse Engine . While Liquisync monitors the Global Supply Line (the "Tanker Truck" of M2 Liquidity moving from Central Banks toward the track with a 60-day lead), StableFlow measures the Immediate Fuel Pressure (the "Dry Powder" already in the pit lane, ready to be pumped into the car). By using both indicators in tandem, you can follow the Dual-Fuel Strategy: Liquisync identifies the fundamental macro regime, while StableFlow identifies the specific "Refuel" and "Exhaustion" pivots within that regime. We will be providing a comprehensive breakdown of this synchronized telemetry in our upcoming Substack Masterclass: The Dual-Fuel Architecture. Risk Disclaimer & Credits The StableFlow is a thematic macro tool tracking on-chain liquidity proxies. Stablecoin data is subject to exchange reporting delays. This is not financial advice; it is a telemetry model for institutional education. Rob Maths is not liable for losses incurred via use of this model. Tags: indicator, bitcoin, btc, stablecoins, usdt, flow, liquidity, macro, refuel, institutional, robmaths, Rob Maths
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Rob_Maths tarafından
KAMA Oscillator | IkkeOmarThis script transforms the Kaufman Adaptive Moving Average (KAMA) into an oscillator format, designed to visualize trend direction with reduced noise sensitivity. It operates in two modes: a Raw mode that tracks price levels directly, and a Normalized mode that bounds the oscillator between -1 and +1 for easier comparison across assets. The calculations are the same as for the Normalized KAMA Oscillator, but I added a few features that users of the old version wouldn't necessarily want. How it works Efficiency Ratio (ER): The script calculates the "efficiency" of price movement by comparing the net direction of price to the total volatility over a set period. Adaptive Smoothing: When volatility is high but direction is unclear (choppy), the KAMA slows down to filter noise. When price trends clearly, the KAMA speeds up to track the move. Normalization (Optional): If enabled, the script takes the raw KAMA value and scales it relative to its highest and lowest points over the Normalization lookback period. The result oscillates between -1 (extreme low) and +1 (extreme high). The SMA Signal Logic The script allows you to overlay an SMA (Simple Moving Average) on the oscillator. This serves as a dynamic baseline for the oscillator's momentum. Signal Generation: A signal is generated when the KAMA Oscillator crosses its SMA. Bullish: Oscillator crosses above the SMA. Bearish: Oscillator crosses below the SMA. Lag vs. Noise Trade-off: Advantage (Reduced Lag): Crossing the SMA often triggers a signal earlier than waiting for the oscillator to change color (slope change) or cross the zero line. It identifies when immediate momentum is outperforming the recent average. Risk (Increased Noise): During consolidation, the oscillator will hover close to the SMA line. This increases the probability of "whipsaws" (false signals) where the line crosses back and forth rapidly without a sustained trend. This signal is aggressive and should be used with trend filters.
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IkkeOmar tarafından
Smart WaveTrend Crossover█ OVERVIEW Smart WaveTrend Crossover is an indicator based on WaveTrend crossovers, designed to reduce the number of false signals typically produced by classic oscillator crossovers. Instead of triggering a signal immediately at the line crossover, the indicator requires additional confirmation in the form of a price breakout from a box, created at the moment of the WaveTrend signal. The script also includes: - a trend filter based on a separate WaveTrend - “fog” visualization - candle coloring based on trend direction - fully configurable entry signals - automatic Take Profit / Stop Loss levels - a real-time TP/SL table █ CONCEPTS Classic WaveTrend crossovers often generate noise, especially during consolidation. Smart WaveTrend Crossover attempts to address this issue using a breakout confirmation mechanism: - at the moment WT1 crosses WT2, a horizontal price box is created - a trade signal is generated only when price closes outside the box - an optional trend filter limits signals to the dominant market direction The trend filter is built on a WaveTrend crossover using larger, slower parameters, independent from the signal-generating WaveTrend. This allows short-term momentum to be separated from the broader market direction, and all trend filter parameters can be freely adjusted. WaveTrend signal settings are not identical to the original / classic values. They are configured to generate a higher number of signals, which works better in combination with breakout boxes and confirmation logic. Signal sensitivity can be easily adjusted by modifying channel length and averaging parameters. By default, show_only_matching is enabled: - bullish crossover → bullish breakout only (BUY) - bearish crossover → bearish breakout only (SELL) █ FEATURES WaveTrend (Signals & Trend): - two independent WaveTrend setups: - one for signal generation - one for trend determination - signal parameters configured more aggressively than classic defaults - trend filter based on a slower WaveTrend crossover - trend direction visualized using directional fog, not a histogram WaveTrend Input Explanation: - Channel Length – controls WaveTrend reaction speed (shorter = more signals) - Average Length – smoothing of the main WT1 line - MA Length – smoothing of the signal line WT2 - Source – price source used in calculations (default: hlc3) Fog (Visualization): - visual representation of market pressure in the direction of the trend - fog height based on average candle size × offset_mult - adjustable transparency or fully disableable Breakout Boxes: - a box is created on every WaveTrend direction change - default height based on the signal candle range - optional box expansion using average candle size × box_multiplier Signals: - triangles or “BUY / SELL” labels - direction matching filter (show_only_matching) - option to display all breakouts regardless of crossover direction - built-in BUY and SELL alerts Visual Settings: - candle coloring based on WaveTrend trend direction - full control over bullish and bearish colors Risk Management – TP / SL: - automatic TP1, TP2, TP3 and SL levels - two calculation modes: - Candle Multiplier – based on average candle range - Percentage – percentage from entry price - separate parameters for each level - TP/SL lines drawn on the chart - real-time TP/SL price table █ HOW TO USE Add the indicator to your TradingView chart → Indicators → search “Smart WaveTrend Crossover” Key settings: - WaveTrend Settings for Signals – signal sensitivity - WaveTrend Settings for Trend – market direction filter - Signal Settings – signal type and box logic - Fog – pressure visualization - Risk Management – TP/SL configuration Signal meaning: - BUY → upward breakout from a box after a bullish crossover - SELL → downward breakout from a box after a bearish crossover - visible boxes → breakout watch zones - fog and candle color → current market direction █ APPLICATIONS Standalone entry system - entering directly on BUY / SELL signals - or entering on trend color change Filter for price-action strategies - using WaveTrend signals as directional confirmation - e.g. level breakout + WaveTrend confirmation = entry Trend indicator - trading other tools only in the direction of the WaveTrend trend - e.g. RSI breaks above 50 while WaveTrend trend is bullish █ NOTES - Default settings are a starting point and may require adjustment - The indicator works best as part of a broader trading system
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Uncle_the_shooter tarafından
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Rachev Regime AnalyzerRachev Regime Analyzer ~ GForge What It Does Measures the ratio of extreme gains to extreme losses to identify whether markets favor bulls or bears. When your best moves are bigger than your worst moves, conditions are bullish. When the opposite is true, conditions are bearish. Simple Interpretation: Ratio > 1.2 → Bullish regime (tail gains exceed tail losses) Ratio < 0.8 → Bearish regime (tail losses exceed tail gains) Between → Neutral/transitional Key Features Two Modes: Single Asset: Analyze current chart Multi-Asset: Aggregate regime across 5 assets with custom weights (great for gauging overall crypto/market conditions) Customizable: Lookback period (20-200 bars) Tail percentile (what counts as "extreme") Bullish/bearish thresholds 6 color schemes Optional MA smoothing Visual Signals: Buy/sell markers at threshold crosses Background regime coloring Info table with current values and confidence score Configurable alerts How to Use Choose lookback period based on your timeframe (40-60 bars is a good start) Watch for threshold crosses - these mark regime changes Check confidence score - higher = more reliable Use multi-asset mode to see if entire market is shifting (not just one coin) Best combined with: Trend indicators, support/resistance, volume analysis Parameters Lookback: More bars = smoother, less responsive Alpha (0.10): Defines extreme events - lower = more extreme Thresholds: Adjust based on asset volatility Return Type: Log returns recommended for most assets What Makes It Useful Unlike simple volatility measures, this shows asymmetry - whether extreme moves favor upside or downside. A ratio of 1.5 means your extreme gains are 50% larger than extreme losses - that's actionable information about risk-reward dynamics. Multi-asset aggregation is particularly powerful for crypto traders wanting to gauge if BTC, ETH, SOL, etc. are all showing similar regime characteristics. Disclaimer Educational tool only. Not financial advice. Use proper risk management. No indicator works in isolation - always consider broader market context. Developed by GForge Comments and feedback welcome! 👍
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BB Squeeze - HighQToolsBBW Squeeze — HighQTools As always, if anyone has any tips or additional features they'd like to see, feel free to reach out! Overview The BBW Percentile Squeeze highlights periods of exceptionally compressed volatility by measuring Bollinger Band Width (BBW) and ranking it within a rolling historical percentile. When BBW falls into the lowest portion of its own distribution, price is statistically “tight” relative to recent history—a condition that often precedes volatility expansion. Instead of plotting an oscillator in a separate pane, this tool expresses information directly on the price chart by changing bar colors during squeeze conditions, keeping charts clean and execution-focused. How It Works Standard Bollinger Bands are calculated using a configurable length and standard deviation. Band width is normalized and evaluated against a rolling lookback window. The current width is converted into a percentile rank (0–100): Lower percentile = tighter volatility Higher percentile = expanded volatility When the percentile drops below the user-defined threshold, the market is considered to be in a squeeze. An optional RTH-only mode allows the percentile calculation to consider Regular Trading Hours bars only, which is especially useful for futures traders who want to ignore overnight volatility distortions. Visual Signals Squeeze Bars Bars are recolored when BBW percentile falls below the selected threshold, indicating extreme compression. Release Bar (optional) The first bar exiting the squeeze can be highlighted separately, marking the resolution of compression. No oscillator, no bands, no shapes—only context applied directly to price. How to Use It The squeeze itself is not a trade signal. Squeeze conditions indicate stored energy—expect range expansion, not direction. Focus on: Market structure Higher-timeframe context Volume, delta, or acceptance/rejection The release from squeeze often provides the best opportunity, especially when aligned with directional bias or structural breaks. For best results, use this tool as a context filter alongside execution setups rather than as a standalone entry signal. Recommended Settings BB Length: 10 Std Dev: 2.0 Percentile Lookback: 200–300 bars Squeeze Threshold: 5-10 percentile RTH-only: Enabled for index futures Disclaimer This indicator is designed to provide context, not predictions. Always combine volatility information with sound risk management and a complete trading plan.
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HighQTools tarafından
Confluence Strength Meter (Bull/Bear) [v6]This indicator provides a quantified "Strength Score" (0-5) for price action setups by measuring the confluence of five key technical drivers. It features a Strategy Mode toggle, allowing traders to instantly switch between Bullish (Long) and Bearish (Short) scoring logic. How it Works: The script analyzes the following factors to build a Confluence Score: Trend Direction: Price relation to the Slow EMA (50). EMA Stack: Fast EMA (20) vs. Slow EMA (50) alignment. Volume Sentiment: Price relation to the Intraday VWAP. Momentum: MACD vs. Signal line crossover. RSI Health: Checks for momentum in the correct direction while filtering out extreme exhaustion (Overbought/Oversold). Features: Visual Histogram: Color-coded bars (Green/Red for strong setups, Orange for moderate, Gray for weak) make it easy to spot high-confluence zones. Dual Modes: Input setting to switch the entire logic engine between Bullish and Bearish detection. Alerts: Pre-configured alert conditions for both Long and Short setups, ready for webhook integration. Usage: Look for a score of 4 or 5 (brightly colored bars) to confirm high-probability entries in the direction of your selected trend.
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the_outvestor tarafından
3D Isometric MFI (Christmas Edition) [Kodexius]3D Isometric MFI (Christmas Edition) is a visual-first interpretation of the classic Money Flow Index, rendered as a projected 3D-style ribbon using an isometric mapping. Instead of plotting a standard oscillator line, the script reconstructs recent MFI history as a depth-aware ribbon that moves from back to front, producing a layered perspective effect that helps you read momentum shifts, regime transitions, and relative strength changes as a continuous structure. This Christmas Edition was also built for fun and as a creative seasonal experiment. The goal is to keep the underlying indicator logic familiar, while presenting it in a playful, “3D showroom” style that looks great in a separate oscillator panel. The indicator is designed for presentation quality and chart readability. It uses controlled object management (lines, polylines, labels) and renders only the most recent portion of the MFI history (user-defined depth). A decorative snow background effect adds atmosphere. 🔹 Features 🎄 🔸 Isometric 3D Projection Engine The ribbon is produced by projecting 3D points (time offset, MFI value, depth) into 2D chart coordinates. - X represents bar offset into history - Y represents the MFI value - Z introduces depth and perspective Angle controls the projection direction, and Vertical Zoom scales the perceived amplitude. 🔸 Depth-Limited Ribbon Rendering (Back to Front) Only the most recent History Depth values are drawn to keep performance and readability stable. - Each segment connects two consecutive MFI values - A top edge, bottom edge, and filled face are drawn to simulate thickness - Older segments fade into the background 🔸 Dynamic Gradient Coloring + Depth Fade Ribbon color follows a value-based gradient: - Lower values lean red (risk-off pressure) - Higher values lean green (risk-on pressure) - Mid values blend naturally Transparency increases with depth so older history is less dominant but still readable. 🔸 Tip Label (Value + Candy Marker) 🍭🍬 The most recent ribbon tip displays current MFI value. A candy symbol that switches based on the 50 midpoint The label is offset so it does not cover the ribbon tip. 🔸 Projected Reference Grid (80, 50, 20) A projected grid is drawn at classic MFI reference levels to improve orientation: - 80 Overbought reference - 50 Midpoint reference - 20 Oversold reference These grid lines use the same projection math, so they stay aligned at any angle or zoom. 🔸 Seasonal Snow Background Effect ❄️ Randomized snow is rendered behind the ribbon using lightweight labels. This is purely decorative and does not alter MFI values or logic. 🔸 Object Lifecycle Management Because 3D-style drawing uses many objects, the script manages them explicitly by storing references in arrays, deleting old objects, and redrawing on the last bar. This helps prevent visual stacking artifacts and keeps the panel clean. 🔹 Calculations 1) Money Flow Index Computation The script separates “positive” and “negative” money flow based on the direction of change in the selected source, then converts their ratio into the standard 0 to 100 oscillator. Classic MFI Calculations. calc_mfi(int length, float source) => float upper = math.sum(volume * (ta.change(source) <= 0 ? 0 : source), length) float lower = math.sum(volume * (ta.change(source) >= 0 ? 0 : source), length) float mfi = 100.0 if lower != 0 float r = upper / lower mfi := 100 - (100 / (1 + r)) mfi Interpretation: upper accumulates volume-weighted source values on up moves lower accumulates volume-weighted source values on down moves if lower is zero, MFI defaults to 100 to avoid division errors otherwise, MFI is computed from the ratio transform 2) History Buffer Management The current MFI value is pushed into the front of an array every bar. The array is trimmed to History Depth so rendering stays bounded. array.unshift(ctx.history_val, mfi_curr) if ctx.history_val.size() > depth ctx.history_val.pop() 3) 3D Point Model and Ribbon Thickness Each segment is built from four projected points to form a filled face (a simple quad). A small thickness is applied to create the “ribbon” look, and depth is used to simulate perspective. 4) Isometric Projection to Chart Coordinates 3D points are mapped into chart coordinates with an angle rotation and scaling for zoom and depth. method project(Point3 p, int anchor_bar, float angle_rad, float zoom, float z_scale) => float x_world = -float(p.x) * 2.0 float z_val = p.z * z_scale float screen_x_offset = (x_world * math.cos(angle_rad)) - (z_val * 1.0) float screen_y_offset = (p.y * zoom) + (x_world * math.sin(angle_rad)) * 0.5 int final_x = anchor_bar + int(math.round(screen_x_offset)) float final_y = screen_y_offset chart.point.from_index(final_x, final_y) 5) Gradient and Depth Transparency Color is derived from MFI value via a gradient, and transparency increases with segment depth so recent data remains dominant while older context stays visible. 6) Projected Reference Grid Construction The 80, 50, 20 levels are drawn as dotted segments across the same historical span, using the same projection and depth fade logic for consistent alignment. 🎆 Wishing you a great year ahead 🎄✨ May your charts be clear, your risk be controlled, and your next year be filled with health, peace, and good trades. Happy Holidays and Happy New Year.
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UnknownUnicorn113699460 tarafından