Empiece

M-oscillator

Z-Score Distortion LabName: Z-Score Distortion Lab 🔬 Description: The Anatomy of Market Volatility Most indicators focus on price direction, but Z-Score Distortion Lab dives deeper into the "Statistical Health" of the market. This tool analyzes the 3rd and 4th statistical moments—Skewness and Excess Kurtosis—to identify when price action is deviating from a normal distribution. Key Clinical Features: Skewness (Neon Line): Measures the asymmetry of price distribution. A high positive/negative skew indicates a strong directional bias or "Distortion" that often precedes trend exhaustion or sharp reversals. Excess Kurtosis (Aqua Line): Monitors "Fat-Tail Risk." When Kurtosis spikes, it signals extreme market conditions and high volatility where outliers (black swan events) are more likely to occur. Visual Diagnostics: Equipped with "Risk Triangles" and "Bias Arrows" to highlight statistical anomalies in real-time. How to use in your "Lab": Risk Monitoring: Use the Kurtosis threshold to identify high-risk environments where standard strategies might fail. Bias Detection: Use Skewness arrows to confirm the underlying strength of a move. Customizable Thresholds: Fully adjustable inputs to fit your specific timeframe and asset class. Disclaimer: This tool is for statistical analysis and educational purposes only. It does not provide financial advice or guaranteed trade signals. Always use proper risk management.
Indicador Pine Script®
por GodeyeThelasthope
Precision Sword QQE Precision Sword is an advanced oscillator that combines quantitative momentum analysis with market equilibrium. It is designed to provide clean trend signals while filtering out market noise. Key Components: QQE Logic: Utilizes a smoothed RSI combined with volatility bands (ATR) to identify true momentum. Kijun-sen Filter: Trends are only confirmed when the price is on the correct side of the Kijun-sen line, providing a robust safety filter against fakeouts. Momentum Histogram: The histogram changes color (Cyan/Red) only when momentum and trend are in full alignment. Minimalist Design: Optimized for clarity, focusing on the crossover between the Main Line (QQE) and the Signal Line. How to trade:
Indicador Pine Script®
por Astra_Quant_Flow
Nico Mega Cap Dashboard + RSI Indicator Description: Mega Cap Dashboard + RSI (True TV Daily %) This is a multi-symbol intraday leadership dashboard designed to monitor four major Nasdaq drivers directly on your main chart: NVDA MSFT AAPL META It provides real-time visibility into price, daily performance, and momentum strength — all in a compact table overlay. Core Components 1️⃣ Current Price Displays the live close price of each stock based on your active chart timeframe (30s, 1m, 5m, etc.). This allows you to see immediate price positioning without switching charts. 2️⃣ True Daily % Change (Matches TradingView) Daily % is calculated correctly as: (Current Price − Previous Daily Close) / Previous Daily Close × 100 This matches: TradingView watchlist “Day %” Broker daily performance Market scanners Color logic: Green → Positive on the day Red → Negative on the day This gives you instant directional bias. 3️⃣ RSI (Relative Strength Index) Default length: 14 (adjustable) RSI is calculated on the same timeframe as your active chart. Color logic: Red → RSI > 70 (Overbought) Lime → RSI < 30 (Oversold) White → Neutral zone This provides momentum and exhaustion context. What This Indicator Is Designed For This tool functions as a Nasdaq internal strength monitor. Because NVDA, MSFT, AAPL, and META heavily influence: QQQ NQ futures Nasdaq index movement You can quickly determine: Are market leaders aligned? Is momentum broad-based or isolated? Is QQQ strength supported internally? Is the move extended or building? Practical Trading Applications 1️⃣ Trend Confirmation If: 3–4 stocks are green on the day RSI values are above 50 → Higher probability of continuation bias in QQQ/NQ. 2️⃣ Weak Internal Structure If: QQQ is pushing highs But 2–3 leaders are red or RSI < 50 → Potential divergence or fake breakout. 3️⃣ Exhaustion Detection If multiple stocks show: RSI > 70 Extended daily % → Increased probability of pullback or rotation. 4️⃣ Scalping Alignment (30s–2min) Before entering a trade: Check if leadership is aligned with your direction. Avoid trades when dashboard shows mixed signals. Technical Structure The script uses: request.security() for cross-symbol data retrieval Daily timeframe previous close for accurate day % Real-time intraday RSI calculation table.new() for structured UI display Overlay rendering (top-right of main chart) It updates dynamically with each new bar.
Indicador Pine Script®
por nio1101
Napolyon 2ndicator Description This indicator is based on the MACD Histogram momentum shift. The system focuses on color transitions within the histogram: When the MACD histogram changes from dark green to light green (indicating weakening bullish momentum) and then turns back to dark green, a long position is triggered on the second candle close after the histogram returns to dark green. For short positions, the logic works in reverse: when the histogram shifts from dark red to light red and then back to dark red, a short position is triggered on the second candle close after the histogram returns to dark red. The strategy aims to capture momentum re-acceleration after a temporary slowdown, filtering out premature entries and reducing false signals. This tool is designed for traders who prefer confirmation-based entries rather than reacting to the first momentum shift. macd 12-26-9
Indicador Pine Script®
por Erdi00
Napolyonndicator Description This indicator is based on the MACD Histogram momentum shift. The system focuses on color transitions within the histogram: When the MACD histogram changes from dark green to light green (indicating weakening bullish momentum) and then turns back to dark green, a long position is triggered on the second candle close after the histogram returns to dark green. For short positions, the logic works in reverse: when the histogram shifts from dark red to light red and then back to dark red, a short position is triggered on the second candle close after the histogram returns to dark red. The strategy aims to capture momentum re-acceleration after a temporary slowdown, filtering out premature entries and reducing false signals. This tool is designed for traders who prefer confirmation-based entries rather than reacting to the first momentum shift.
Indicador Pine Script®
por Erdi00
Bitcoin Relative Strength: BTC vs Any Asset [Customizable]# Bitcoin Relative Strength: BTC vs Any Asset ## 📖 Description **Compare Bitcoin's performance against ANY asset on TradingView** — S&P 500, Nasdaq, Gold, DXY, Ethereum, or any other ticker of your choice. This indicator calculates and plots the **BTC / Asset ratio**, showing how many units of the chosen comparison asset one Bitcoin is worth. A rising ratio means Bitcoin is outperforming the selected asset; a falling ratio means it is underperforming. ### 🔑 Key Features - **BTC vs Any Asset** — select any TradingView ticker as the comparison asset (SPX, NDX, GOLD, DXY, ETH, and more) - **Dual Moving Averages** — EMA / SMA / WMA / VWMA / RMA with customizable lengths to identify trend direction - **Bollinger Bands** — detect volatility compression and breakout zones on the ratio - **RSI of Ratio** — identify overbought / oversold conditions in relative strength - **Percentage Change** — adjustable lookback period (1–365 days) to quantify recent momentum - **Trend Coloring** — dynamic bullish / bearish / neutral coloring based on ratio vs MA - **Fill Zones** — optional fill between the ratio line and MA for easy visual trend spotting - **Info Table** — real-time data panel showing ratio, individual prices, % change, trend, and MA values - **Built-in Alerts** — MA crossovers, Golden / Death crosses, Bollinger breakouts, and RSI extremes - **Fully Customizable** — colors, line widths, transparency, table position, text size, and more ### 📊 How to Use 1. **Add the indicator** to any chart. 2. Open **Settings → Data Sources** and choose your preferred Bitcoin ticker (e.g., BINANCE:BTCUSD) and comparison asset (e.g., SP:SPX, TVC:GOLD, FOREXCOM:DXY). 3. Enable optional overlays: Moving Averages, Bollinger Bands, RSI, or the Info Table. 4. Set alerts for key events like MA crossovers or Bollinger breakouts. ### 💡 Interpretation | Ratio Direction | Meaning | |---|---| | 📈 Rising | Bitcoin outperforms the comparison asset | | 📉 Falling | Bitcoin underperforms the comparison asset | | ▲ Above MA | Bullish relative trend | | ▼ Below MA | Bearish relative trend | | Golden Cross (MA1 × MA2) | Long-term bullish shift | | Death Cross (MA1 × MA2) | Long-term bearish shift | ### ⚠️ Disclaimer This indicator is for **educational and informational purposes only**. It does not constitute financial advice. Always do your own research before making investment decisions. **Indicator by:** iCD_creator **Version:** 1.0 **Pine Script™ Version:** 6 --- Updates & Support For questions, suggestions, or bug reports, please comment below or message the author. **Like this indicator? Leave a 👍 and share your feedback!** --- **#Bitcoin #BTC #RelativeStrength #BTCRatio #BTCvsSPX #BTCvsGold #BTCvsDXY #BTCvsETH #CryptoAnalysis #TechnicalAnalysis #TradingView #PineScript #Cryptocurrency #BitcoinDominance #CryptoIndicator #BTCStrength #MacroAnalysis #RatioChart #BitcoinVs #IntermarketAnalysis #CryptoTrading #BTCTrend #BTCSentiment #BitcoinPerformance #AltcoinRatio**
Indicador Pine Script®
por iCD_creator
Extended Sentiment Pressure Oscillator (ESP)Extended Sentiment Pressure Oscillator (ESP) The ESP is a multi-purpose trend and bias oscillator designed to visualize who is in control: buyers or sellers. It measures the balance between upward and downward pressure inside each candle and across a lookback window, then converts that information into an easy-to-read visual signal. Unlike classic oscillators that only look at close prices, ESP evaluates price structure (High–Low–Open–Close), range behavior, and multiple normalization methods. This makes it adaptable to many markets—from fast crypto scalping to slower swing trading on stocks, forex, commodities... What makes ESP different? _______________________ Most oscillators give you a single line. ESP gives you a full pressure model: * Uptrend line – how strong buyers are * Downtrend line – how strong sellers are * Net Pressure (Bias) – the real battle result * Optional histogram and signals You can view it in: * Classic 0–100 mode (Average Sentiment Oscillator style) * Expanded centered mode (-50…+50) for intuitive bullish/bearish reading ESP is not “another RSI”. It focuses on market pressure and imbalance, not overbought/oversold. Core Features ____________ Multi-Normalization Engine - Choose how pressure is measured: * Bar Range – immediate candle structure * Window Range – broader context * Mix – blend of both, averaged. * Hybrid - pure blend of Bar- & Window Range, not averaged. * (Average) True Range (TR / ATR) – volatility-aware modes Adaptive Smoothing: Select your preferred MA type: SMA, EMA, HMA, SMMA (RMA), WMA, VWMA Sensitivity Control - A unique ESP Sensitivity knob lets you: * Reduce noise (<1.0) * Amplify reactions (>1.0) * or stay neutral (1.0) Signal Logic - Two modes: * ZeroCross – classic bias crossing * MomentumShift – early detection using consecutive rises/falls and slope strength Visual Tools: * Tricolor Net Pressure line * Bias histogram * Optional UP/DOWN flags * Focus mode to highlight the most important signal How to Use ESP (Practical Use Cases) ? ________________________________ 1) Trend Confirmation Use ESP as a trend filter for your main strategy: * Net Pressure above 0 → bullish environment * Net Pressure below 0 → bearish environment * Rising Net Pressure → momentum building Great companion to combine with: * Price Action * Other indicators like * Crossing EMA's * MACD * VWAP * RSI * ... * Breakout systems * ... 2) Early Momentum Detection With MomentumShift mode, ESP can react before a zero cross: * Two or more consecutive rises = early bullish shift * Two or more consecutive falls = early bearish shift * Optional minimum slope filters weak moves Ideal for: * Scalping pullbacks * Exit timing * Avoiding late entries 3) Regime & Strength Analysis by combining: * Up/Down lines * Net Pressure * Histogram This lets you read: * Strong trends * Weak consolidations * Momentum exhaustion * Diverging pressure vs price Who is this for? _____________ Anyone can use this indicator at will, while this could prove an extra aid especially for: * Discretionary traders needing clear bias visualization * Traders looking for a robust gate/filter aid * Multi-asset traders (crypto, stocks, forex, commodities,...) Important Notes ______________ ESP is an indicator or technical analytical tool, not a trading system Works best combined with price action and risk management Past performance ≠ future results Signals provided should not be used solely to make any trading decisions Trading always involves risk To conclude, ESP or Extended Sentiment Pressure oscillator can help you understand the pressure behind the candles, making decisions clearer based on structure rather than on noise.
Indicador Pine Script®
por PJooris1408
1
RSI & Stoch OS + HH Entry + SL 0.6%RSI & Stochastic Convergence (Higher High Entry) This strategy is designed to capture high-probability reversals by combining dual-oscillator oversold conditions with price action confirmation. Entry Logic: The strategy waits for both RSI and Stochastic to reach oversold territory. To avoid "falling knives," it only enters a Long position when the current bar achieves a Higher High compared to the previous bar. Take Profit (TP): Positions are closed when the Stochastic %K enters the overbought zone (90), securing gains during peak momentum. Stop Loss (SL): A disciplined risk management rule is applied with a fixed -0.6% stop loss from the entry price to protect against sudden market drops.
Estrategia Pine Script®
por lnwza99plus
Momentum Structural Volatility Oscillator [MSVO Pro] The Momentum Structural Volatility Oscillator (MSVO) is a high-performance quantitative tool designed to capture impulsive trend shifts. By integrating normalized price action with a dual-stage smoothing engine, MSVO filters out market noise while maintaining high sensitivity to "Monster Stock" volatility patterns. MSVO 动能结构振荡器是一款专为捕捉脉冲式趋势转折而设计的量化工具。它结合了归一化价格行为与双阶平滑引擎，在过滤市场杂讯的同时，保持对“妖股”级别波动模式的高度敏感。 -Dynamic Range Normalization: Unlike standard oscillators, MSVO utilizes a dynamic lookback window (21/8) to map price action into a normalized energy field. -Weighted Smoothing Algorithm: It implements a professional 0.667/0.333 weighted smoothing logic to calculate the Signal Line, significantly reducing lag compared to traditional EMAs. -Momentum Energy Cloud: The visual "Cloud" represents the gap between momentum and its signal line, highlighting the strength of the current trend acceleration. -动态范围归一化： 不同于传统振荡器，MSVO 利用动态回溯窗口（21/8）将价格行为映射到归一化的能量场中。 -加权平滑算法： 采用专业的 0.667/0.333 加权平滑逻辑计算信号线，相比传统 EMA 大幅降低了信号滞后。 -动能能量云： 视觉化的“云带”代表了动能与其信号线之间的速率差，直观展示当前趋势加速的强度。 -INIT (Purple Label): Detects low-level momentum accumulation. A precursor to potential volatility breakouts. -BUY/SELL (Triangles): Threshold-based confirmation when momentum crosses structural key levels (20/80). -INIT (紫色标签): 探测低位动能累积，通常是潜在波动爆发的前兆。 -BUY/SELL (三角标记): 当动能穿越结构性关键位（20/80）时的阈值确认信号。
Indicador Pine Script®
por william_wq
FVG Average Analyzer [point algo] Overview The FVG Average Analyzer is a technical indicator that measures and analyzes Fair Value Gap (FVG) sizes to help traders identify market efficiency and volatility conditions. Unlike traditional FVG indicators that simply mark gap zones on charts, this tool quantifies gap magnitude and compares it against historical averages to reveal market state transitions What is a Fair Value Gap (FVG)? A Fair Value Gap occurs when price moves aggressively, creating an imbalance or "inefficiency" in the market. Bullish FVGs form when the current candle's low is higher than the low of two candles prior, while bearish FVGs occur when the current candle's high is lower than the high of two candles back. These gaps represent areas where institutional buying or selling activity caused rapid price displacement, leaving behind liquidity voids that markets may revisit Key Features 1. Gap Size Quantification Automatically detects both bullish and bearish FVGs using three-candle pattern logic Calculates the exact size of each gap in real-time Color-codes gaps: green for bullish, red for bearish 2. Dynamic Average Calculation Computes a Simple Moving Average (SMA) of FVG sizes over a customizable lookback period (default: 20 bars) Provides context for whether current gaps are above or below historical norms 3. Market State Classification VOLATILE State: Current FVG size exceeds average, indicating aggressive price action and potential trend acceleration EFFICIENT State: Current FVG size below average, suggesting balanced market conditions with reduced inefficiency Mega Gap alerts trigger when FVG size exceeds 2x the average, highlighting extreme displacement events ​ 4. Real-Time Dashboard Displays current gap size with color-coded status Shows rolling average FVG size for trend context Indicates market state (Volatile vs Efficient) for quick assessment How to Use This Indicator Volatility Assessment Monitor the relationship between current FVG size and the average to gauge market conditions. When gaps consistently exceed the average, expect continuation of volatile moves; when gaps shrink below average, anticipate consolidation or ranging behavior. ​ Confluence with Market Structure Combine this analyzer with price action tools like order blocks, support/resistance, or trend indicators. Large FVGs (Mega Gaps) often coincide with structural breaks and can signal high-probability entry zones when aligned with trend direction. Entry Timing Use the market state classification to time entries: in VOLATILE conditions, wait for retracements into large unfilled gaps; in EFFICIENT markets, focus on range-bound strategies rather than breakout trades. Multi-Timeframe Analysis Apply the indicator across different timeframes to identify where FVG inefficiency is concentrated. Higher timeframe volatility signals often provide stronger directional bias for lower timeframe trade execution. Settings 1. Average Period (SMA): Adjustable lookback period (default: 20) for calculating the average FVG size. Shorter periods react faster to changes; longer periods provide smoother, more stable averages. 2. Significant Multiplier: Threshold for identifying "Mega Gaps" (default: 2.0x average). Adjust based on instrument volatility characteristics. Technical Implementation The indicator operates in a separate panel below the main chart (overlay=false), plotting two primary lines: the real-time FVG size (color-coded by direction) and the rolling SMA of gap sizes. Diamond markers appear at the top of the panel when Mega Gaps form, providing visual alerts for extreme conditions. Best Practices Works on all markets and timeframes (forex, crypto, stocks, indices) Most effective when combined with volume analysis and ATR-based volatility filters Use higher threshold multipliers (2.5-3.0x) for ranging markets; lower values (1.5-2.0x) for trending markets Monitor the dashboard for quick state changes that may precede reversals or acceleration Disclaimer This indicator is provided for educational purposes only and does not constitute financial advice. Fair Value Gap analysis should be used as part of a comprehensive trading strategy with proper risk management. Past performance of FVG patterns does not guarantee future results. Indicator Type: Oscillator / Market Analysis Tool
Indicador Pine Script®
por pointalgo
Harmonic Resonance Oscillator [LuxAlgo]The Harmonic Resonance Oscillator indicator provides a specialized oscillator that decomposes price action into multiple harmonic cycles to identify confluence in market rotations. By isolating short, medium, and long-term frequencies, the tool aims to pinpoint exhausted price movements and potential reversal zones through the concept of cyclic resonance. 🔶 USAGE The Harmonic Resonance Oscillator can be used to identify market turning points by observing when the aggregate cycle resonance reaches extreme levels. Unlike standard oscillators that rely on a single lookback period, this tool aggregates multiple filtered cycles to provide a more robust view of market momentum and exhaustion. When the oscillator enters the dynamic overbought (upper) or oversold (lower) zones, it indicates that the various price cycles are aligning at an extreme, often preceding a corrective move or a trend reversal. 🔹 Harmonic Multipliers The script uses a Reference Period combined with three multipliers to define the cycles: The Short Multiplier captures fast, intraday-style fluctuations. The Medium Multiplier focuses on the primary trend rhythm. The Long Multiplier tracks broader market cycles. When all three cycles reach peak or trough levels simultaneously, the oscillator displays a "resonance" peak, which is highlighted by background coloring if the signal exceeds the dynamic thresholds. 🔶 DETAILS The indicator is built upon three primary technical pillars: 🔹 Ehlers' Bandpass Filter At its core, the indicator uses John Ehlers' Cycle decomposition method. The bandpass filter is designed to pass only price components within a specific frequency range while attenuating everything else. This allows the script to "tune in" to specific market rhythms without the lag typically associated with moving averages. 🔹 Normalization & Resonance Each isolated cycle is normalized onto a scale of 0 to 100 using a specific lookback length. The final "Harmonic Resonance" signal is the arithmetic mean of these three normalized cycles. A value of 50 represents a neutral state, while values approaching 0 or 100 represent extreme harmonic alignment. 🔹 Dynamic Volatility-Adjusted Zones The Overbought and Oversold thresholds are not static. They adjust dynamically based on the standard deviation of the resonance signal. During periods of high cyclic volatility, the bands expand to require stronger confluence for a signal; during low volatility, the bands contract to stay sensitive to smaller market rotations. 🔶 SETTINGS 🔹 Harmonic Settings Reference Period: The base period used to calculate the harmonic cycles. Short Multiplier: Multiplier applied to the reference period for the short-term cycle. Medium Multiplier: Multiplier applied to the reference period for the medium-term cycle. Long Multiplier: Multiplier applied to the reference period for the long-term cycle. Bandwidth: Controls the "tightness" of the bandpass filter. Lower values isolate specific cycles more precisely. 🔹 Normalization Settings Normalization Lookback: The window used to scale the cycles and calculate the volatility of the resonance signal. 🔹 Overbought / Oversold Control Overbought Threshold: The base level for the upper dynamic zone (default 80). Oversold Threshold: The base level for the lower dynamic zone (default 20). 🔹 Style Bullish Color: Color of the oscillator when above the 50 midpoint. Bearish Color: Color of the oscillator when below the 50 midpoint. Overbought Color: Color of the upper dynamic threshold. Oversold Color: Color of the lower dynamic threshold. Show Background Highlighting: Toggles the background coloring when resonance reaches extreme levels.
Indicador Pine Script®
por LuxAlgo
3
Breakout Odds [Rider Algo]Breakout Odds v4 — Empirical Breakout Probability with Directional Bias & Quality Filters What it does: Quantifies breakout probability (0–100) and breakout directional bias (-100 to +100), then applies quality filters so only high-conviction setups signal. What Is This Indicator? When price is stuck in a range, Breakout Odds v4 answers: "How likely is a breakout right now?" → Score 0 to 100 "Which direction will it go?" → Bias -100 (bearish) to +100 (bullish) Instead of relying on a single trigger, it combines 9 independent factors — 5 for probability and 4 for direction — into a unified weighted model, then applies 3 quality filters (trend alignment, candle confirmation, cooldown) to block low-quality signals. When everything aligns, it prints a directional signal : 🟢 BULL triangle or 🔴 BEAR triangle. This is not a crystal ball. It’s a confirmation framework designed to keep you out of weak breakouts. --- The Architecture The indicator runs as a 3-stage pipeline: Stage 1 → Probability Engine: “Is a breakout likely?” (Score 0–100) Stage 2 → Direction Engine: “Which way?” (Bias -100 to +100) Stage 3 → Quality Filters: “Is this signal worth taking?” (Pass / Block) Signals only fire when all three stages agree. --- Stage 1: Breakout Probability (Score 0–100) This engine measures how “ready” the market is to break out of the current range, using five conditions that often precede strong breakouts: Bollinger Band Width (default weight: 25%) Measures BB compression vs recent history. Narrow bands = coiled spring → higher score. ATR Compression (default weight: 20%) Compares current ATR% vs its lookback range. Confirms volatility squeeze (layer-2 validation). Relative Volume (default weight: 25%) Current volume vs average volume. Rising volume during compression suggests accumulation. Capped at 3× avg to avoid single-spike distortion. Distance to Range Edges (default weight: 15%) How close price is to the nearest range boundary (high/low). Closer = more imminent. Level Tests (default weight: 15%) Counts touches/approaches to range ceiling/floor. More tests weaken the level → higher break odds. --- Stage 2: Directional Bias (-100 to +100) Once probability says “breakout is likely,” the direction engine estimates which way using four factors: Price Position Within Range (default weight: 30%) Above midpoint / pressing ceiling = bullish bias. Below midpoint / pressing floor = bearish bias. Volume Pressure at Levels (default weight: 30%) Compares total volume near range high vs range low. More volume near highs → buying pressure (bullish). More near lows → selling pressure (bearish). Short-Term Momentum Slope (default weight: 20%) Linear regression slope over N bars. Rising slope = bullish momentum, falling slope = bearish. Candle Bias Analysis (default weight: 20%) — Optional, ON by default Body-to-range quality scoring over a lookback (default 10). Clean bodies (small wicks) count more. Measures the balance + quality of bullish vs bearish candles. Interpretation: Bias > 0 = bullish, Bias < 0 = bearish |Bias| = confidence (shown as Dir Strength in the panel) --- Stage 3: Quality Filters This is what makes v4 materially more selective than earlier versions. Filter 1: Trend Alignment (EMA) — Optional, ON by default A 200 EMA sets macro trend rules: BULL signals allowed only when price is above EMA BEAR signals allowed only when price is below EMA This eliminates the classic mistake: bull signals in downtrends and bear signals in uptrends . Disable if your strategy is counter-trend. Filter 2: Candle Confirmation — Always active Signals do not fire just because score crosses the threshold. It waits for the candle to close at or beyond the range edge . If score is high but price is still mid-range, no signal . Filter 3: Signal Cooldown — Configurable (default: 10 bars) After a signal prints, no new signals for X bars. Prevents clustering when score oscillates around the threshold in chop. --- How to Read the Indicator Visual Elements Score Line (colored): probability line with dynamic zones 🟢 Green (80–100): High breakout probability 🟡 Yellow (60–79): Moderate — watch closely 🟠 Orange (40–59): Low — range likely holds 🔴 Red (0–39): Very low — no breakout expected Shaded Area (green/red): real-time directional bias Green = bullish lean, red = bearish lean. Bigger = stronger conviction. Dashed White Line: signal threshold (default 70) Background Tint: when score is above threshold and trend filter agrees Green tint = bullish context, red tint = bearish context. Signal Triangles: 🟢 BULL (bottom): confirmed bullish breakout (all filters passed) 🔴 BEAR (top): confirmed bearish breakout (all filters passed) Info Panel (right): Composite score + direction (with strength), component breakdowns, and filter statuses (Trend / Confirm / Cooldown). When to Act Designed for confirmation, not prediction . Typical workflow: Score climbs into 60–70+ as compression builds Directional bias shows which side is “winning” Wait for the confirmed BULL/BEAR triangle (score high + clear direction + filters pass + edge close) Use your own risk plan for entry/SL/targets --- Customizing the Weights You can tune every component from settings — no code edits . Probability Weights (Score Weights group) Weight — BB Width (default 25%) Weight — ATR Compression (default 20%) Weight — Relative Volume (default 25%) Weight — Distance to Edges (default 15%) Weight — Level Tests (default 15%) Direction Weights (Direction Weights group) Dir Weight — Price Position (default 30%) Dir Weight — Volume Pressure (default 30%) Dir Weight — Momentum Slope (default 20%) Dir Weight — Candle Bias (default 20%) Weight Tips Weights do not need to sum to 100. The script normalizes automatically. Volume-driven breakouts: increase Relative Volume , reduce BB Width . Low-volume markets / off-hours: reduce Relative Volume , increase BB Width + ATR Compression . Stronger directional conviction: increase Momentum Slope + Candle Bias . Conservative: threshold 80, higher Level Tests, keep filters ON → fewer but cleaner signals. Aggressive: threshold 60, disable trend filter, cooldown 5 → more signals, more risk. --- Quality Filter Settings Enable Trend Filter (EMA): ON (default) — blocks counter-trend signals Trend EMA Period: 200 Enable Candle Bias Analysis: ON (default) Candle Bias Lookback: 10 bars Signal Cooldown: 10 bars --- Other Configurable Parameters Analysis Period: 50 bars Signal Threshold: 70 BB Period / Multiplier: 20 / 2.0 ATR Period: 14 Volume Average Period: 20 S/R Tolerance: 0.5% Minimum Tests: 2 Momentum Lookback: 10 bars --- Alerts Three independent conditions: Confirmed Bullish Breakout — score ≥ threshold + bullish bias + all filters pass Confirmed Bearish Breakout — score ≥ threshold + bearish bias + all filters pass Extreme Score (≥90) — score hits 90+ regardless of direction/filters (rare compression event) --- What’s New in v4 (vs v3) Trend Filter (EMA 200): v3 = No → v4 = Yes (optional, default ON) Candle Close Confirmation: v3 = No → v4 = Yes (always active) Candle Bias Analysis: v3 = No → v4 = Yes (optional, default ON) Signal Cooldown: v3 = No → v4 = Yes (default 10) Direction Factors: v3 = 3 → v4 = 4 Filter Status in Panel: v3 = No → v4 = Yes Signal Reliability: v3 = Baseline → v4 = improved via filtering The core probability engine is unchanged; v4 adds quality control on top of v3’s foundation — same detection, better filtering . --- Important Notes Does not repaint. Uses confirmed bar data only. Score is contextual probability , not a guarantee — manage risk. Works on any timeframe / asset class (stocks, forex, crypto, commodities). Best used with your own S/R mapping: indicator suggests when a level is likely to break and which way ; your plan decides if the trade is valid. Filters reduce false signals — they cannot eliminate them. Developed by Rider Algo
Indicador Pine Script®
por RiderAlgo
TomiChoro SPY-OPTIONS 5m//@version=5 indicator("OM SPY A+ Confirm (Fib 1H + Filters)", shorttitle="OM A+", overlay=true, max_labels_count=500, max_lines_count=500) // ══════════════════════════════════════════════════════════════════════════════ // ORIGINAL OptionsMillionaire BASE (mantiene toda la funcionalidad) // ══════════════════════════════════════════════════════════════════════════════ priceSource = input(close, title="Price Source For The Moving Averages", group="General") IgnoreExtendedHours = input(true, title="Ignore Extended Hours", group="General") resolution = timeframe.period price = request.security(syminfo.tickerid, resolution, priceSource) shortMAPeriod = input.int(8, title="Short Moving Average Period & Type:", group="Crossover Moving Averages", inline="short") shortMAType = input.string("EMA", title="", options= , group="Crossover Moving Averages", inline="short") longMAPeriod = input.int(21, title=" Long Moving Average Period & Type :", group="Crossover Moving Averages", inline="long") longMAType = input.string("EMA", title="", options= , group="Crossover Moving Averages", inline="long") i_timeframe_signal = input.timeframe("", title="Crossover MAs Timeframe", group="Crossover Moving Averages") useTextLabels = input.bool(true, title="Use Text-Based Crossover Labels?", group="Crossover Moving Averages") showBonusMA1 = input.bool(true, title="Bonus MA", group="Bonus Moving Averages", inline="bma1") bonusMA1Period = input.int(34, title="", group="Bonus Moving Averages", inline="bma1") bonus1MAType = input.string("EMA", title="", options= , group="Bonus Moving Averages", inline="bma1") i_timeframe_bma1 = input.timeframe("", title="", group="Bonus Moving Averages", inline="bma1") showBonusMA2 = input.bool(false, title="Bonus MA", group="Bonus Moving Averages", inline="bma2") bonusMA2Period = input.int(50, title="", group="Bonus Moving Averages", inline="bma2") bonus2MAType = input.string("SMA", title="", options= , group="Bonus Moving Averages", inline="bma2") i_timeframe_bma2 = input.timeframe("", title="", group="Bonus Moving Averages", inline="bma2") showBonusMA3 = input.bool(false, title="Bonus MA", group="Bonus Moving Averages", inline="bma3") bonusMA3Period = input.int(100, title="", group="Bonus Moving Averages", inline="bma3") bonus3MAType = input.string("SMA", title="", options= , group="Bonus Moving Averages", inline="bma3") i_timeframe_bma3 = input.timeframe("", title="", group="Bonus Moving Averages", inline="bma3") ZLMASmooth = 3 f_security(_sym, _res, _src) => request.security(_sym, _res, _src , barmerge.gaps_off, barmerge.lookahead_off) ticker = ticker.new(syminfo.prefix, syminfo.ticker, IgnoreExtendedHours ? session.regular : syminfo.session) // MA calculation f_ma(_src, _len, _type) => switch _type "SMA" => ta.sma(_src, _len) "EMA" => ta.ema(_src, _len) "WMA" => ta.wma(_src, _len) "HMA" => ta.hma(_src, _len) "ALMA" => ta.alma(_src, _len, 0.85, 6) "LIN" => ta.linreg(_src, _len, 0) "ZLMA" => (2 * ta.wma(ta.wma(_src, _len), ZLMASmooth)) - ta.wma(ta.wma(ta.wma(_src, _len), ZLMASmooth), _len) => ta.ema(_src, _len) short = f_security(ticker, i_timeframe_signal, f_ma(price, shortMAPeriod, shortMAType)) long = f_security(ticker, i_timeframe_signal, f_ma(price, longMAPeriod, longMAType)) bonus1 = f_security(ticker, i_timeframe_bma1, f_ma(price, bonusMA1Period, bonus1MAType)) bonus2 = f_security(ticker, i_timeframe_bma2, f_ma(price, bonusMA2Period, bonus2MAType)) bonus3 = f_security(ticker, i_timeframe_bma3, f_ma(price, bonusMA3Period, bonus3MAType)) // Crossover signals (base) Bull = ta.crossover(short, long) Bear = ta.crossunder(short, long) trendColor = short >= long ? color.new(color.red, 85) : color.new(color.blue, 85) MA1 = plot(short, title="Short Period Moving Average", color=#FF00FF, linewidth=2) MA2 = plot(long, title="Long Period Moving Average", color=#00FF00, linewidth=1) fill(MA1, MA2, color=trendColor, title="Short/Long Divergence Fill") plot(showBonusMA1 ? bonus1 : na, title="Bonus Moving Average 1", color=#FFFF00, linewidth=1) plot(showBonusMA2 ? bonus2 : na, title="Bonus Moving Average 2", color=#0000FF, linewidth=1) plot(showBonusMA3 ? bonus3 : na, title="Bonus Moving Average 3", color=#FFFFFF, linewidth=1) plotshape(Bull, title="Calls Label", color=color.new(color.green, 25), textcolor=useTextLabels ? color.white : color.new(color.white, 100), style=useTextLabels ? shape.labelup : shape.triangleup, text="Call", location=location.belowbar) plotshape(Bear, title="Puts Label", color=color.new(color.red, 25), textcolor=useTextLabels ? color.white : color.new(color.white, 100), style=useTextLabels ? shape.labeldown : shape.triangledown, text="Put", location=location.abovebar) if Bull alert("Call Alert: 8ema crossed over 21ema", alert.freq_once_per_bar_close) if Bear alert("Put Alert: 8ema crossed under 21ema", alert.freq_once_per_bar_close) // -- VWAP -- // showVWAP = input.bool(true, title="Show VWAP?", group="VWAP") vwapSource = input(hlc3, title="VWAP Source", group="VWAP") vwapAnchor = input.string("Session", title="VWAP Anchor Period", options= , group="VWAP") vwapSD1 = input.float(1.00, minval=0, step=0.5, title="Standard Deviation 1", group="VWAP") vwapSD2 = input.float(2.00, minval=0, step=0.5, title="Standard Deviation 2", group="VWAP") vwapSD3 = input.float(3.00, minval=0, step=0.5, title="Standard Deviation 3", group="VWAP") showVWAPSD1Band = input.bool(false, title="Show VWAP Standard Deviation 1?", group="VWAP") showVWAPSD2Band = input.bool(false, title="Show VWAP Standard Deviation 2?", group="VWAP") showVWAPSD3Band = input.bool(false, title="Show VWAP Standard Deviation 3?", group="VWAP") timeChange(period) => ret = 0 if period == "Session" ret := time("D") if period == "Week" ret := time("W") if period == "Month" ret := time("M") if period == "Quarter" ret := time("3M") if period == "Year" ret := time("12M") if period == "Decade" ret := time("12M") % time("120M") == 0 ? 1 : 0 if period == "Century" ret := time("12M") % time("1200M") == 0 ? 1 : 0 ret isNewPeriod = ta.change(timeChange(vwapAnchor)) isFirstBarOfNewPeriod = isNewPeriod and not isNewPeriod var float vwapSum = 0.0 vwapSum := isFirstBarOfNewPeriod ? vwapSource * volume : vwapSource * volume + vwapSum var float volumeSum = 0.0 volumeSum := isFirstBarOfNewPeriod ? volume : volume + volumeSum var float v2Sum = 0.0 v2Sum := isFirstBarOfNewPeriod ? volume * vwapSource * vwapSource : volume * vwapSource * vwapSource + v2Sum mVWAP = vwapSum / volumeSum variance = v2Sum / volumeSum - mVWAP * mVWAP variance := variance < 0 ? 0 : variance standard_deviation = math.sqrt(variance) vwapUpperBand1 = mVWAP + (vwapSD1 * standard_deviation) vwapLowerBand1 = mVWAP - (vwapSD1 * standard_deviation) vwapUpperBand2 = mVWAP + (vwapSD2 * standard_deviation) vwapLowerBand2 = mVWAP - (vwapSD2 * standard_deviation) vwapUpperBand3 = mVWAP + (vwapSD3 * standard_deviation) vwapLowerBand3 = mVWAP - (vwapSD3 * standard_deviation) plot(showVWAP ? mVWAP : na, title="VWAP", color=color.orange, linewidth=1) vwapSD1Plot1 = plot(showVWAPSD1Band ? vwapUpperBand1 : na, title="VWAP SD1 Upper", color=color.gray, linewidth=1) vwapSD1Plot2 = plot(showVWAPSD1Band ? vwapLowerBand1 : na, title="VWAP SD1 Lower", color=color.gray, linewidth=1) fill(vwapSD1Plot1, vwapSD1Plot2, color=color.new(color.gray, 90), title="VWAP SD1 Fill") vwapSD2Plot1 = plot(showVWAPSD2Band ? vwapUpperBand2 : na, title="VWAP SD2 Upper", color=color.gray, linewidth=1) vwapSD2Plot2 = plot(showVWAPSD2Band ? vwapLowerBand2 : na, title="VWAP SD2 Lower", color=color.gray, linewidth=1) fill(vwapSD2Plot1, vwapSD2Plot2, color=color.new(color.gray, 85), title="VWAP SD2 Fill") vwapSD3Plot1 = plot(showVWAPSD3Band ? vwapUpperBand3 : na, title="VWAP SD3 Upper", color=color.gray, linewidth=1) vwapSD3Plot2 = plot(showVWAPSD3Band ? vwapLowerBand3 : na, title="VWAP SD3 Lower", color=color.gray, linewidth=1) fill(vwapSD3Plot1, vwapSD3Plot2, color=color.new(color.gray, 80), title="VWAP SD3 Fill") // ══════════════════════════════════════════════════════════════════════════════ // MÓDULO A+ (Fibonacci 1H + Filtros) // ══════════════════════════════════════════════════════════════════════════════ // Inputs A+ grpAPlus = "═══ A+ Filters (Fib 1H + VWAP + Volume) ═══" enableAPlus = input.bool(true, title="Enable A+ Signals", group=grpAPlus) fibTF = input.timeframe("60", title="Fibonacci Timeframe", group=grpAPlus) pivotLen = input.int(5, title="Pivot Length (1H swing)", minval=1, group=grpAPlus) tolPct = input.float(0.05, title="Fib Zone Tolerance (%)", minval=0.0, step=0.01, group=grpAPlus) volLen = input.int(20, title="Volume SMA Length", minval=1, group=grpAPlus) showFibLines = input.bool(true, title="Show Fib 0.5 & 0.618 Lines", group=grpAPlus) // Pivot detection en 1H f_pivH_1h = request.security(syminfo.tickerid, fibTF, ta.pivothigh(high, pivotLen, pivotLen), lookahead=barmerge.lookahead_off) f_pivL_1h = request.security(syminfo.tickerid, fibTF, ta.pivotlow(low, pivotLen, pivotLen), lookahead=barmerge.lookahead_off) var float lastPH = na var float lastPL = na var int lastPH_seq = 0 var int lastPL_seq = 0 var int seq = 0 seq := seq + 1 if not na(f_pivH_1h) lastPH := f_pivH_1h lastPH_seq := seq if not na(f_pivL_1h) lastPL := f_pivL_1h lastPL_seq := seq // Swing definition var float swingA = na var float swingB = na var bool swingUp = na haveBoth = not na(lastPH) and not na(lastPL) if haveBoth if lastPH_seq > lastPL_seq // Upswing: low → high swingA := lastPL swingB := lastPH swingUp := true else // Downswing: high → low swingA := lastPH swingB := lastPL swingUp := false // Fib levels rng = haveBoth ? math.abs(swingB - swingA) : na var float fib50 = na var float fib618 = na if haveBoth and not na(rng) and rng > 0 if swingUp fib50 := swingB - rng * 0.50 fib618 := swingB - rng * 0.618 else fib50 := swingB + rng * 0.50 fib618 := swingB + rng * 0.618 // Zone check (0.5–0.618 con tolerancia en %) tol = close * (tolPct / 100.0) zoneLow = math.min(fib50, fib618) zoneHigh = math.max(fib50, fib618) inFibZone = haveBoth and not na(zoneLow) and not na(zoneHigh) and (close >= (zoneLow - tol)) and (close <= (zoneHigh + tol)) // VWAP filter vwapCallOk = close > mVWAP vwapPutOk = close < mVWAP // Volume filter volOk = volume > ta.sma(volume, volLen) // A+ conditions AplusCall = enableAPlus and Bull and inFibZone and vwapCallOk and volOk AplusPut = enableAPlus and Bear and inFibZone and vwapPutOk and volOk // Plots plot(showFibLines ? fib50 : na, color=color.yellow, linewidth=1, title="Fib 0.5 (1H)", style=plot.style_circles) plot(showFibLines ? fib618 : na, color=color.orange, linewidth=1, title="Fib 0.618 (1H)", style=plot.style_circles) plotshape(AplusCall, title="A+ CALL", style=shape.labelup, text="A+ CALL", color=color.new(color.lime, 0), textcolor=color.black, location=location.belowbar, size=size.small) plotshape(AplusPut, title="A+ PUT", style=shape.labeldown, text="A+ PUT", color=color.new(color.fuchsia, 0), textcolor=color.white, location=location.abovebar, size=size.small) // Alerts A+ alertcondition(AplusCall, title="A+ CALL", message="A+ CALL confirmed (OM cross + Fib 1H 0.5-0.618 + VWAP + Volume) on {{ticker}} @ {{close}}") alertcondition(AplusPut, title="A+ PUT", message="A+ PUT confirmed (OM cross + Fib 1H 0.5-0.618 + VWAP + Volume) on {{ticker}} @ {{close}}")
Indicador Pine Script®
por Tomichoro12
Harmonic Frequency Visualizer [BackQuant]Harmonic Frequency Visualizer Overview Harmonic Frequency Visualizer is a cycle-analysis and cross-asset resonance tool that uses a simplified Discrete Fourier Transform (DFT) to measure how strongly specific cycle periods are present in price. It is not a “trend indicator” and it is not trying to predict direction by itself. Its job is to quantify rhythm: which repeating periods (in bars) are currently dominant, whether those cycles are expanding or contracting (phase direction), and whether multiple instruments are sharing the same dominant periods at the same time (resonance). This indicator has two main output modes: Spectrum : a frequency “snapshot” showing amplitude at each tested period for up to five instruments. Spectrogram : a history heatmap showing how the spectrum evolves through time (for the chart instrument). Spectrum Spectrogram On top of that, it produces a Dominant Cycle Oscillator derived from the dominant cycle’s phase, which gives a continuous cycle position metric (peak/trough style zones) without repainting. This is designed for traders who want cycle context the same way they want volatility context: not as a magic signal, but as structure. What “frequency” and “cycles” mean in trading terms A cycle period (say 21 bars) means: “a repeating pattern that tends to complete one full oscillation every 21 bars.” If price contains such a pattern, the DFT will detect a strong correlation between price and a 21-bar sine/cosine wave. Markets do not have perfectly stable periodic motion, but they often show: Mean-reverting swings around value. Trend pulses with pullback cadence. Volatility clustering that creates rhythmic expansions and contractions. Cycle tools are trying to measure those repeating components, and DFT is the standard mathematical way to do it. Where DFT comes from (the core idea) The Discrete Fourier Transform comes from Fourier analysis, a foundational signal processing concept: Fourier’s idea : any sufficiently well-behaved signal can be expressed as a sum of sine and cosine waves at different frequencies, each with: An amplitude (how strong that wave is). A phase (where you are within the wave cycle). In continuous math you get the Fourier Transform. In sampled data (like candles) you use the Discrete Fourier Transform. It converts a time series (price over time) into a frequency description (strength of different cycles). In markets: Time domain: candles and price series. Frequency domain: cycle periods and their strengths. Why sine and cosine, not just sine A sine wave alone cannot represent every phase alignment cleanly. DFT uses both cosine and sine components because together they form an orthogonal basis that can represent any phase shift. You can think of it like this: Cosine component captures “in-phase” alignment with the cycle. Sine component captures “quadrature” (90-degree shifted) alignment. Combining them gives full information: amplitude + phase. Mathematically, a single frequency component can be written as: A * cos(ωt + φ) But DFT estimates A and φ by separately accumulating cosine and sine projections. How this script implements the DFT (and what it is actually measuring) This is not a full-spectrum FFT across every frequency. It is a targeted DFT across a fixed set of cycle periods: Tested periods The script tests 8 predefined periods: 5, 8, 13, 21, 34, 55, 89, 120 These are Fibonacci-like cycle candidates commonly used in cycle/market structure work. The point is not that Fibonacci is magic. The point is that these represent a reasonable spread from short to long rhythms without needing hundreds of frequencies (which would be heavy in Pine). Normalization step (important) Before computing the DFT, the script normalizes the series: mn = SMA(src, lookback) sd = stdev(src, lookback) norm = (src - mn) / sd (if sd != 0) Why normalize: DFT amplitude depends on the scale of the input series. If you compare BTC and TLT raw prices, the magnitude is meaningless. Z-score normalization makes amplitude more comparable across instruments and regimes. So the spectrum is measuring “cyclical structure in standardized deviations,” not raw dollars. Projection onto cosine and sine For each tested period P: ω = 2π / P (angular frequency for that period) Compute: - sCos = Σ(norm * cos(ωk)) - sSin = Σ(norm * sin(ωk)) Interpretation: You are correlating the last window of normalized price with a cosine wave of period P. And also correlating it with a sine wave of period P. If the price has a strong P-bar rhythm, these sums grow in magnitude. Window length detail The script uses: window = min(lookback - 1, 99) So even if lookback is 200, the internal DFT accumulation caps at 100 bars for performance stability. This is a deliberate trade: stable computation in Pine, while still letting you define normalization lookback and overall context. Amplitude computation Once sCos and sSin are computed: raw magnitude = sqrt(sCos² + sSin²) This is the length of the vector (sCos, sSin). That vector length is the standard way to combine the orthogonal components into one strength metric. Then it scales it into a 0–100 “display amplitude”: amp = sqrt(sCos² + sSin²) / lookback * 100 * sensitivity amp is capped to 100 So: Higher amplitude means stronger alignment with that cycle period. Sensitivity is a user control to amplify or damp the display scaling. Important: amplitude here is not a probability, and it is not guaranteed “signal quality.” It is a standardized “how much of that cycle exists in the recent window” metric. Phase computation Phase is computed using atan2(sSin, sCos). That matters because: A simple atan(sin/cos) fails in different quadrants. atan2 correctly resolves the angle from -π to +π. Phase tells you where you are within the cycle: Two cycles can have same amplitude but opposite phase. Phase is what lets you infer “approaching peak vs trough” behavior. Dominant cycle selection The script chooses the dominant cycle as the period with the highest amplitude among the tested periods: domIdx = argmax(amp ) domAmp = max amplitude domPhase = phase at domIdx This dominant cycle is used for: Spectrogram history matrix (chart symbol). Dominant cycle oscillator. Data window outputs (dominant period, oscillator value). Spectrum View: what you see and how to read it In Spectrum mode, the indicator draws a frequency snapshot for up to five instruments. Each instrument gets a spectrum line (or bars/area depending on style) plotted across the 8 periods on the x-axis, with amplitude (0–100) on the y-axis. X-axis meaning Each x position corresponds to a period (5 → 120 bars). You are not looking at “frequency in Hz.” You are looking at “period in bars,” which is more intuitive in trading. Y-axis meaning Amplitude is a scaled measure of how strongly that period is present in the recent normalized data. Higher means stronger. Plot styles Waveform: connects amplitude points into a continuous shape, best for seeing spectrum shape. Bars: draws vertical bars per period, best for quick comparison. Area: similar to waveform but filled toward baseline for emphasis. Dominant peaks and phase direction labels The script highlights dominant cycles per symbol (if enabled): If max amplitude > 20, it labels that peak with the symbol name. If Show Phase Direction is enabled, it appends ▲ or ▼. Phase direction logic: rising = sin(phase) < 0 ▲ means cycle is in a “rising” phase segment ▼ means cycle is in a “falling” phase segment This is not “price will rise now.” It is “the dominant cycle’s instantaneous phase suggests you are on the upward vs downward half of that oscillation.” In real markets, you use this as context, not as a standalone trade trigger. It also draws small ▲/▼ markers on secondary peaks (amp > 15) to show phase direction of other meaningful cycles, giving you a richer picture than “one dominant period.” Resonance Zones: cross-asset harmonic alignment Resonance is where this tool becomes more than a single-chart curiosity. What resonance means here A resonance zone is flagged when at least 3 out of 5 instruments have strong amplitude at the same tested period. Mechanically: For each period i: - Count instruments with amp > 30 - If count >= 3, mark resonance at that period When resonance is detected: A vertical highlight box is drawn behind that period. A ⚡ marker is printed at the top. Interpretation: Multiple assets are expressing a similar cycle length at the same time. This can indicate macro rhythm, shared liquidity timing, or cross-market synchronization. This is especially useful when your instrument set includes: Rates proxy (TLT), commodities (oil, gold), and crypto indices. You can visually spot when markets are “vibrating” together at a shared period. Resonance is not automatically bullish or bearish. It is telling you “cycle length agreement,” which can help with timing models and contextual trade planning. Spectrogram View: frequency over time Spectrum mode is a snapshot. Spectrogram mode adds time evolution. What a spectrogram is A spectrogram is a 2D heatmap where: Rows = different periods (frequency bands). Columns = time history (bars ago → now). Color = amplitude strength. This allows you to see: Which cycles are persistent vs fleeting. When dominant cycle shifts occur (energy moves from one period to another). Cycle regime transitions (short cycles dominating in chop vs longer cycles dominating in trend). How the script builds the spectrogram matrix It maintains a matrix with: NUM_PERIODS rows (8 periods) histBars columns (history length) Each bar: Remove the oldest column. Append the newest amplitude array from chartSpec. So the spectrogram is always a rolling history of the chart symbol’s cycle amplitudes. It does not attempt to store five symbols (too heavy), it focuses on the active chart for time evolution. Heat coloring Amplitude values map to a custom gradient: Low = dark blue Mid = blue/cyan to orange High = yellow This makes dominant energy bands visually obvious. A stable bright band means persistent cycle dominance. Dominant Cycle Oscillator: phase mapped to a 0–100 oscillator The oscillator is derived from the dominant cycle phase (chart symbol): oscRaw = cos(domPhase) oscValue = 50 + 50 * oscRaw (maps -1..1 into 0..100) Interpretation: When cos(phase) ≈ +1, oscillator near 100 (cycle peak zone). When cos(phase) ≈ -1, oscillator near 0 (cycle trough zone). Midline 50 corresponds to the quarter-cycle transition points. It also colors the oscillator by phase direction: oscRising = sin(domPhase) < 0 Rising phase = green-ish Falling phase = red-ish This gives you a clean timing reference: The dominant period tells you the cycle length. The oscillator tells you where you are within that cycle. It is not forecasting price. It is telling you the current phase position of the strongest detected cycle component. Alerts and practical timing usage Alerts are based on the oscillator: Cross above 80: dominant cycle entering peak zone. Cross below 20: dominant cycle entering trough zone. Cross 50: midline cross (phase transition). In practice, you use these as “timing context” alerts, for example: If your trend model is bullish and cycle oscillator enters trough zone, it can hint at a favorable pullback timing window. If you are mean-reversion trading and cycle peak zone aligns with resistance, that confluence matters. Again: cycle timing needs structure confirmation. The oscillator alone is not a trade system. Multi-instrument design and non-repaint behavior The indicator requests five external instruments via request.security. It uses: close with lookahead_on This forces the data to be “previous confirmed close” so the spectral calculations do not repaint intra-bar. That matters because cycle measures can change drastically within a bar if you let them use live values. So: Spectra for external symbols are based on confirmed historical closes. Chart symbol spectrogram and oscillator are also stable in the sense they depend on confirmed series values (dominant phase updates bar-to-bar). Key parameters and how they change behavior Analysis Lookback Affects normalization and the DFT window cap: Higher lookback stabilizes mean/stdev normalization and reduces random shifts. Lower lookback makes the tool more reactive but more prone to regime noise. Because the inner DFT accumulation caps at 100 bars, very high lookback mostly affects normalization rather than the raw projection length. Sensitivity Scales displayed amplitude: Higher sensitivity makes peaks stand out more. Lower sensitivity compresses amplitude. It is a display control, not a physics constant. View Mode Spectrum: cross-asset snapshot comparison, resonance detection. Spectrogram: time evolution of cycle energy for chart symbol. Show Phase Direction Adds ▲/▼ markers derived from sin(phase). Useful for quick cycle position intuition, but do not treat ▲ as “buy.” Show Resonance Zones Marks periods where many instruments share strong energy. Useful for macro rhythm alignment. Highlight Dominant Cycles Labels peaks. If you disable it, the chart becomes cleaner but less informative. Spectrogram History Controls how many columns are stored. Higher makes a longer heatmap but costs more drawing. Limitations and what not to assume This tool is honest DSP applied to market data, but market data is not a stationary sine wave generator. Key limitations: Cycles drift. Dominant period can shift as regime changes. The tool only tests 8 candidate periods. If the true dominant period is 30, it will express as energy near 34 or distributed across neighbors. Normalization helps comparability, but does not make amplitude “absolute truth.” DFT assumes a stable frequency over the window. Markets often violate that. Phase-based oscillators are timing aids, not predictors. This is why the indicator is best used as: Context for entries/exits, not a standalone system. A way to see when cycle energy concentrates or disperses. A way to detect when multiple markets share a timing rhythm. How to use it properly (workflows) 1) Cycle regime identification If short periods (5–13) dominate, market is often choppy, reactive, and mean-reverting. If mid periods (21–55) dominate, market often shows swing structure. If long periods (89–120) dominate, market can be in slower macro drift, trend legs, or compressed volatility regimes. 2) Timing layer for an existing strategy Use your trend model to decide direction. Use dominant cycle oscillator to decide timing within that direction. Use spectrogram to avoid trading when dominant period is unstable or flipping rapidly. 3) Cross-asset confirmation If you see resonance at a period, watch whether your main instrument is also showing strength there. Resonance can justify holding a cycle-based timing thesis with more confidence because it is not isolated. 4) Expectation management If the spectrum is flat (no peaks above threshold), that is information: No clean dominant cycle, randomness dominates. Cycle-based timing will be unreliable. Summary Harmonic Frequency Visualizer uses a targeted Discrete Fourier Transform across predefined cycle periods to measure amplitude and phase of cyclical components in price. It supports multi-instrument spectrum comparison, resonance detection when several markets share strong energy at the same periods, and a spectrogram heatmap for the chart instrument showing how cycle dominance evolves over time. A dominant cycle oscillator maps phase into a 0–100 timing readout with alerts for peak/trough/midline transitions. It is a cycle context engine designed to complement trend, structure, and risk models, not replace them.
Indicador Pine Script®
por BackQuant
Ehlers Super Smoother Trend Score [BackQuant]Ehlers Super Smoother Trend Score Overview Ehlers Super Smoother Trend Score is a regime and trend-strength indicator built on a signal-processing filter created by John F. Ehlers. Instead of smoothing price with a standard moving average (which is mathematically crude and prone to noise and aliasing), this indicator applies the Ehlers Super Smoother, a Butterworth-style low-pass filter designed specifically for market data. The filtered series is then scored for directional persistence across a configurable lookback window, producing an oscillator-like trend score that measures how consistently the smoothed trend is advancing or deteriorating. This is not a simple “MA slope” tool. It is: A proper low-pass filter (Super Smoother) to reduce noise while preserving structure. A persistence score that converts the filtered trend into a quantitative regime signal. A threshold framework that turns the score into long/short regime transitions with clean state logic. Where the filter comes from (and why it matters) John F. Ehlers is known for applying digital signal processing (DSP) techniques to technical analysis. Traditional moving averages are not designed as proper frequency-selective filters. They blur price, lag heavily, and can introduce distortions, especially when the market contains high-frequency components (noise) near the Nyquist limit (the maximum representable frequency in sampled data). The Super Smoother is derived from a Butterworth low-pass filter design. Butterworth filters are engineered to have a maximally flat passband, meaning they smooth without introducing ripples in the filtered output. In trading terms: Less “wavy” smoothing artifacts than many MA variants. Better suppression of high-frequency noise. Cleaner trend structure for downstream logic. This script implements Ehlers’ recursive coefficient form, giving you a 2-pole (classic) or 3-pole (heavier) filter. What “Super Smoother” actually is The Super Smoother is a recursive IIR filter (Infinite Impulse Response). Unlike an SMA which averages a fixed window of past values, an IIR filter uses feedback from its own prior output values. That matters because it can achieve strong smoothing with less lag for a given “smoothness target.” Conceptually: Input: price series. Output: filtered estimate of the “low-frequency” component (trend structure). Mechanism: combine current input (or pre-filtered input) with previous filter outputs using coefficients derived from a chosen cutoff period. The coefficients (c1–c4) are not arbitrary, they are computed from exponential decay and cosine terms based on the cutoff period. This is what makes it a real DSP filter rather than “just another MA.” 2-pole vs 3-pole behavior 2-pole (classic) A standard Ehlers Super Smoother configuration. It offers a strong improvement over typical MAs in smoothness vs lag balance. 3-pole Adds an additional feedback term (one more prior filtered state). This increases smoothing and noise rejection, but introduces slightly more lag. The advantage is a cleaner structural line, which often improves regime stability when the market is noisy or mean-reverting. Anti-aliasing pre-filter step Before applying the recursive formula, the script averages the current and previous price: avg = (src + src ) / 2 This is a simple but important pre-filter that reduces high-frequency components that can alias into lower frequencies in sampled data. In practice, it helps stop “one-bar spikes” from contaminating the filter output as much. Inputs and what they really control Super Smoother Period (ssPeriod) This is the cutoff period used in the coefficient derivation. It is not the same as “MA length,” but it behaves similarly in that: Lower period = faster response, less smoothing, more sensitivity to noise. Higher period = smoother output, better noise rejection, more lag. Poles Selects filter order: 2 poles = balanced default. 3 poles = smoother, more conservative. Score Lookback Start/End Defines the persistence scoring window. The script compares the current filtered value to many prior filtered values across that range. A longer range makes the score more “confidence-based” and slower to change, while a shorter range makes it more reactive. Thresholds (Long/Short) Turns the score into a regime classification: Long threshold defines when bullish persistence is strong enough to be considered a trend regime. Short threshold defines when persistence has deteriorated enough to signal a bearish transition. How the trend score is computed After filtering, the indicator computes a directional persistence score on the filtered series (not raw price). That distinction matters because you are scoring structure, not noise. Mechanically: For each i in the scoring window: - If filt_now > filt , add +1 - Else add -1 Sum across the window to produce the score. Interpretation: High positive score means the filtered trend is consistently higher than many past points, persistent bullish structure. Low or negative score means the filtered trend is not advancing, or is consistently below prior points, bearish structure. Scores near the middle mean the filtered series is oscillating without clear persistence, chop or transition. This is a persistence metric, not a slope metric. It does not care about one-bar direction, it cares about consistency relative to history. Signal and state logic (why it stays clean) The indicator uses state logic to prevent constant flip-flopping: Long condition: score > long threshold. Short condition: score crosses below short threshold (uses prevScore and current score). That short logic is event-based, it triggers only on the breakdown transition, not on every bar below the threshold. Once a regime is set, it remains until a real threshold event forces change. Signals are plotted only on regime flips: Long marker when signal becomes +1 and prior was -1. Short marker when signal becomes -1 and prior was +1. This is designed for alerts and for clean backtesting interpretation. Visual layers The indicator can be used purely as a panel oscillator or as a structure overlay. Pane Trend Score line, colored by active regime. Optional reference lines at long/short thresholds for fast regime reading. On-chart (optional) Super Smoother line plotted over price, colored by regime. Optional candle painting and background shading to reflect active regime. This lets you treat the filter as a dynamic trend structure line while using the score as the regime classifier. How to interpret it properly 1) The Super Smoother line This is the cleaned trend structure estimate: When price respects the smoother line, trend structure is intact. When price repeatedly chops through it, structure is weak or range-bound. 2) The score This is the quantified persistence of that structure: Rising score implies strengthening trend persistence. Falling score implies deterioration, transition risk, or mean reversion. Score compression often shows consolidation before a regime shift. 3) Threshold regimes Above long threshold: bullish persistence regime, trend-following conditions. Below short threshold: bearish regime transition, defensive or short-biased conditions. Between thresholds: neutral/transition zone, where chop and fakeouts are common. Practical use cases Trend filter Only take long setups when score is above the long threshold. Reduce exposure or avoid trend trades in the neutral band. Treat a breakdown through the short threshold as regime invalidation. Trend quality assessment High score = continuation environment. Moderate score = trend exists but is fragile. Low/negative score = distribution, downtrend, or unstable structure. Trade management Use the Super Smoother line as a structure reference for trailing risk. Use score deterioration as an early warning before full regime flips. Use regime flips as hard exits or bias changes. Tuning guidelines If you want fewer signals and cleaner regimes Increase ssPeriod. Use 3 poles. Increase scoreEnd (longer scoring window). If you want faster reaction Decrease ssPeriod. Use 2 poles. Reduce the scoring window length. Keep in mind: faster settings increase sensitivity to chop. The filter is good, but no filter removes the reality of mean reversion. What makes this different from “just a smoothed MA score” The difference is the filter quality. The Super Smoother is a proper low-pass filter with coefficients derived from DSP principles, designed to suppress high-frequency noise and avoid common smoothing artifacts. Scoring that filtered structure gives you a regime metric that is more stable and more meaningful than scoring raw price or scoring a basic MA that still carries a lot of aliasing and distortion. Summary Ehlers Super Smoother Trend Score combines a DSP-derived Butterworth-style Super Smoother filter with a directional persistence scoring model. The filter provides a clean, low-noise trend structure series, and the score quantifies how consistently that structure is advancing or deteriorating across a defined window. Threshold-based regime logic converts the score into clean trend states and alerts, making it a practical tool for trend filtering, regime detection, and structure-aware trade management.
Indicador Pine Script®
por BackQuant
4
BTC Cycle RSI + LinReg Bands DCA Strategy v2Overview BTC Cycle RSI DCA Strategy v2 backtests a phase-based dollar-cost averaging system with sequential sell rotations to a simulated yield basket (STRC) and hybrid yield-funded DCA during deep bear markets. Built on smoothed RSI with self-adjusting linear regression bands (adapted from Zeiierman's open-source work). How It Works Eight cycle phases drive DCA multipliers from 5x (Deep Bear) down to 0x (Mature Bull), with post-peak taper at 0.5x (Distribution) and 0.25x (Weakening) Two sequential sells (20% then 40%) rotate BTC holdings into a simulated yield basket when RSI breaks below the midline after an overbought cycle Plunge guard locks out the second sell if RSI collapses to the lower band after the first sell Yield basket compounds at a configurable APR and deploys capital back into BTC during deep bear phases via a hybrid model (time ramp + drawdown scaling + pool cap) Start date filter lets you isolate specific cycles for backtesting Starting yield basket balance input lets you seed the simulation with an existing position Default Properties Initial capital: $100,000 | Commission: 0.05% per side | Slippage: 5 ticks | Base DCA: $100/week | Yield APR: 11% | Hybrid deploy: 25% of pool/week, 4% cap, 25-week ramp, cubic drawdown scaling Realistic Backtesting Notes Commission and slippage are enabled by default. The strategy uses fixed USD-denominated DCA orders rather than percentage-of-equity sizing, reflecting real-world DCA behavior. The yield basket is simulated off-chain and is NOT included in Strategy Tester equity — check the Total Wealth plot for the combined view. Attribution RSI + self-adjusting linear regression band structure adapted from Zeiierman's open-source indicator. Post-peak phase logic, DCA taper, plunge guard, sell sequencing, yield simulation, and hybrid deployment model are original additions. Disclaimer Backtesting results are hypothetical and do not guarantee future performance. This strategy is for educational and informational purposes only. Always do your own research.
Estrategia Pine Script®
por AngryBuhda
BTC Cycle Navigator v2 - Phase DCA + Yield Deploy GuidanceOverview BTC Cycle Navigator v2 is a phase-based guidance indicator built on smoothed RSI with self-adjusting linear regression bands (adapted from Zeiierman's open-source work). It identifies eight distinct cycle phases and provides real-time DCA sizing, sell rotation signals, and yield deployment suggestions — all displayed in an on-chart table. What It Does Detects cycle phases: Deep Bear → Bear Recovery → Early Bull → Bull Building → Bull Confirmed → Mature Bull → Distribution → Weakening Post-peak awareness: after RSI crosses the overbought level, Bull Confirmed becomes Distribution and Bull Building becomes Weakening — with tapered DCA (0.5x and 0.25x) Two-stage sell rotation: FIRST_SELL (20%) and SECOND_SELL (40%) triggered by confirmed RSI midline breakdowns after an overbought cycle Plunge guard: if RSI collapses to the lower band after FIRST_SELL, the second sell is locked out to prevent selling into a crash Hybrid yield deployment model: suggests weekly capital deployment from a yield basket during deep bear phases using time-ramped, drawdown-scaled, pool-capped logic How To Use Apply to BTCUSD on the 1W (weekly) timeframe Set your Start Date to the beginning of the cycle you want to track Enter your Base DCA amount (the 1x weekly amount in USD) Enter your Yield Basket size and target keep % for deployment guidance Read the on-chart table for current phase, DCA amount, sell status, and yield deploy suggestion Set alerts for phase changes and sell signals Phase → DCA Multiplier Deep Bear: 5x | Bear Recovery: 3x | Early Bull: 2x | Bull Building: 1x | Bull Confirmed: 1x | Mature Bull: 0x (paused) | Distribution: 0.5x | Weakening: 0.25x Attribution RSI + self-adjusting linear regression band structure adapted from Zeiierman's open-source indicator. Post-peak phase logic, DCA taper model, plunge guard, sell sequencing, and hybrid yield deployment are original additions. Disclaimer This indicator provides informational guidance only. It does not constitute financial advice. Past RSI patterns do not guarantee future performance. Always do your own research.
Indicador Pine Script®
por AngryBuhda