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Pattern armonici

Harmonic Confluence Wave Detector [JOAT]Harmonic Confluence Wave Detector Introduction The Harmonic Confluence Wave Detector is an open-source oscillator-based indicator that combines WaveTrend, Money Flow Index (MFI), RSI, MACD, and Stochastic RSI into a unified momentum analysis system. This mashup creates a multi-layered oscillator framework designed to identify momentum shifts, overbought/oversold conditions, and divergence patterns across multiple timeframes and calculation methods. The indicator addresses a common trading challenge: single oscillators can give conflicting or premature signals. By synthesizing five different momentum calculations that use distinct mathematical approaches, this tool provides confluence-based signals that occur when multiple momentum indicators align, significantly reducing false signals compared to using any single oscillator alone. Chart showing WaveTrend oscillator, MACD histogram, and multi-signal system on 1H timeframe Why This Mashup Exists This indicator combines five oscillators that complement each other through different calculation methodologies: WaveTrend: Smoothed momentum oscillator based on price deviation from exponential moving average Money Flow Index (MFI): Volume-weighted RSI showing buying/selling pressure RSI: Classic momentum oscillator measuring speed and magnitude of price changes MACD: Trend-following momentum indicator showing relationship between two EMAs Stochastic RSI: Stochastic calculation applied to RSI for enhanced sensitivity Each oscillator has unique strengths: WaveTrend excels at identifying wave-like momentum cycles, MFI incorporates volume for institutional flow analysis, RSI provides reliable overbought/oversold readings, MACD shows trend strength and direction, and Stochastic RSI catches early momentum shifts. Together, they create a comprehensive momentum picture that no single oscillator can provide. The mashup is justified because these oscillators use fundamentally different calculations (price-based, volume-weighted, moving average convergence, stochastic) that respond to different market conditions. When they align, it indicates genuine momentum shift rather than noise. Core Components Explained 1. WaveTrend Oscillator (Primary Signal Generator) WaveTrend is the primary oscillator, calculated using this methodology: // Calculate exponential average of HLC3 esa = ta.ema(hlc3, channelLength) // Calculate deviation d = ta.ema(abs(hlc3 - esa), channelLength) // Calculate channel index ci = (hlc3 - esa) / (0.015 * d) // Apply smoothing to create WaveTrend 1 wt1 = ta.ema(ci, averageLength) // Create WaveTrend 2 as simple moving average of WT1 wt2 = ta.sma(wt1, 4) WaveTrend oscillates around zero, with: Values above +60: Overbought zone Values above +80: Extreme overbought Values below -60: Oversold zone Values below -80: Extreme oversold Crossovers between WT1 and WT2: Momentum shift signals The indicator plots WT1 and WT2 as lines with dynamic coloring based on momentum direction and strength. 2. Money Flow Index (MFI) - Volume-Weighted Momentum MFI calculation incorporates both price and volume: // Calculate typical price typicalPrice = (high + low + close) / 3 // Calculate raw money flow rawMoneyFlow = typicalPrice * volume // Separate positive and negative money flow positiveFlow = close > close ? rawMoneyFlow : 0 negativeFlow = close < close ? rawMoneyFlow : 0 // Sum over MFI period positiveSum = sum(positiveFlow, mfiLength) negativeSum = sum(negativeFlow, mfiLength) // Calculate MFI mfi = 100 - (100 / (1 + positiveSum / negativeSum)) MFI ranges from 0-100, with readings above 80 indicating buying pressure and below 20 indicating selling pressure. The indicator plots MFI as a line and uses it for confluence scoring. 3. RSI - Classic Momentum Oscillator Standard RSI calculation over 14 periods (configurable): RSI > 70: Overbought RSI < 30: Oversold RSI > 65 with other bearish signals: Potential reversal RSI < 35 with other bullish signals: Potential reversal RSI provides reliable baseline momentum readings and is used for divergence detection. 4. MACD - Trend Momentum Indicator MACD uses standard 12/26/9 settings: = ta.macd(close, 12, 26, 9) The indicator displays MACD histogram with enhanced width (linewidth 8) for visibility. Histogram color changes based on: Green: Positive and increasing (bullish momentum) Light green: Positive but decreasing (weakening bulls) Red: Negative and decreasing (bearish momentum) Light red: Negative but increasing (weakening bears) MACD histogram provides visual confirmation of momentum strength and direction. 5. Stochastic RSI - Enhanced Sensitivity Stochastic calculation applied to RSI values: stochRSI = ta.stoch(rsi, rsi, rsi, 14) Stochastic RSI oscillates between 0-100 and is more sensitive than regular RSI, catching momentum shifts earlier. The indicator plots both K and D lines for crossover analysis. Example showing all oscillators with divergence markers and signal labels Multi-Signal System The indicator generates six tiers of signals based on confluence strength: BUY Signals: BUY: WT1 crosses above WT2 in oversold zone (WT1 < -40) STRONG BUY: BUY + volume above average + MACD histogram positive MEGA BUY: STRONG BUY + WT1 < -60 (extreme oversold) + RSI < 35 ULTRA BUY: MEGA BUY + MFI < 30 + Stoch RSI oversold + bullish divergence SELL Signals: SELL: WT1 crosses below WT2 in overbought zone (WT1 > 40) STRONG SELL: SELL + volume above average + MACD histogram negative MEGA SELL: STRONG SELL + WT1 > 60 (extreme overbought) + RSI > 65 ULTRA SELL: MEGA SELL + MFI > 70 + Stoch RSI overbought + bearish divergence Signal labels appear on chart with size proportional to signal strength (tiny for BUY/SELL, normal for ULTRA). Divergence Detection System The indicator detects divergences across multiple oscillators: RSI Divergence: Bullish: Price makes lower low, RSI makes higher low Bearish: Price makes higher high, RSI makes lower high WaveTrend Divergence: Bullish: Price makes lower low, WT1 makes higher low Bearish: Price makes higher high, WT1 makes lower high MACD Divergence: Bullish: Price makes lower low, MACD histogram makes higher low Bearish: Price makes higher high, MACD histogram makes lower high Divergences are marked with bright orange/yellow "D" labels (color.rgb(255, 200, 0)) with black text for maximum visibility. When multiple oscillators show divergence simultaneously, it signals strong momentum exhaustion and potential reversal. Confluence Scoring System The indicator calculates a real-time confluence score (0-100) by evaluating: Confluence Components: - WaveTrend Position: Up to 25 points (extreme zones add more weight) - WaveTrend Momentum: Up to 15 points (WT1-WT2 relationship) - RSI Level: Up to 15 points (extreme readings add weight) - MFI Level: Up to 15 points (volume pressure confirmation) - MACD Histogram: Up to 15 points (trend momentum) - Stochastic RSI: Up to 10 points (early momentum detection) - Divergence Presence: Up to 5 points (any divergence detected) The dashboard displays the current confluence score with color coding: Green (80-100): Strong bullish confluence Light green (60-79): Moderate bullish confluence Yellow (40-59): Neutral/mixed signals Light red (20-39): Moderate bearish confluence Red (0-19): Strong bearish confluence Visual Elements WaveTrend Lines: WT1 (blue) and WT2 (orange) with dynamic coloring Overbought/Oversold Zones: Horizontal lines at +60/-60 and +80/-80 Zero Line: Reference line at 0 MACD Histogram: Large bars (linewidth 8) with gradient coloring MFI Line: Purple line showing volume-weighted momentum RSI Line: Green line with overbought/oversold reference levels Stochastic RSI: K (blue) and D (red) lines Signal Labels: BUY/SELL markers with size based on signal strength Divergence Labels: Bright orange "D" markers at divergence points Dashboard: Top-right table showing confluence score and oscillator readings Chart demonstrating signal hierarchy from BUY to ULTRA BUY with divergence markers How Components Work Together The mashup creates a layered momentum analysis: Layer 1 - Primary Momentum: WaveTrend identifies wave cycles and crossover signals Layer 2 - Volume Confirmation: MFI validates moves with volume-weighted pressure Layer 3 - Baseline Momentum: RSI provides reliable overbought/oversold context Layer 4 - Trend Strength: MACD histogram shows underlying trend momentum Layer 5 - Early Detection: Stochastic RSI catches momentum shifts before other oscillators Layer 6 - Exhaustion Signals: Divergences across oscillators indicate momentum exhaustion Example scenario: WT1 crosses above WT2 in oversold zone (Layer 1), MFI shows buying pressure increasing (Layer 2), RSI is below 35 (Layer 3), MACD histogram turns positive (Layer 4), Stochastic RSI crosses up (Layer 5), and RSI shows bullish divergence (Layer 6). This generates an ULTRA BUY signal with 90+ confluence score. Input Parameters WaveTrend Settings: Channel Length: Period for EMA calculation (default: 10) Average Length: Smoothing period for WT1 (default: 21) Overbought Level: Upper threshold (default: 60) Oversold Level: Lower threshold (default: -60) Extreme OB Level: Extreme upper threshold (default: 80) Extreme OS Level: Extreme lower threshold (default: -80) Oscillator Settings: RSI Length: Period for RSI calculation (default: 14) MFI Length: Period for MFI calculation (default: 14) MACD Fast: Fast EMA period (default: 12) MACD Slow: Slow EMA period (default: 26) MACD Signal: Signal line period (default: 9) Stochastic RSI Length: Period for Stoch RSI (default: 14) Signal Settings: Show Signals: Toggle signal labels (default: enabled) Show Divergences: Toggle divergence markers (default: enabled) Volume Confirmation: Require volume for STRONG signals (default: enabled) Min Confluence for Signals: Minimum score to display signals (default: 60) Display Options: Show Dashboard: Toggle confluence score table (default: enabled) Show MACD Histogram: Toggle MACD display (default: enabled) Show MFI Line: Toggle MFI display (default: enabled) Show RSI Line: Toggle RSI display (default: enabled) Show Stochastic RSI: Toggle Stoch RSI display (default: enabled) Color Theme: Choose between multiple color schemes How to Use This Indicator Step 1: Monitor WaveTrend Oscillator Watch for WT1/WT2 crossovers in extreme zones. Crossovers in oversold zone (< -60) suggest bullish reversals, crossovers in overbought zone (> 60) suggest bearish reversals. Step 2: Check Confluence Score Review the dashboard. Scores above 70 indicate strong momentum alignment. Higher scores generally produce more reliable signals. Step 3: Identify Signal Strength Pay attention to signal labels. ULTRA signals have highest probability but occur less frequently. STRONG signals offer good balance between frequency and reliability. Step 4: Look for Divergences Divergence markers indicate momentum exhaustion. When divergences appear with extreme oscillator readings, reversal probability increases significantly. Step 5: Confirm with MACD Histogram Check MACD histogram direction and strength. Large histogram bars confirm strong momentum, shrinking bars suggest momentum loss. Step 6: Validate with Volume (MFI) Ensure MFI supports the move. Bullish signals with rising MFI are stronger, bearish signals with falling MFI are stronger. Best Practices Use on 15-minute to 4-hour timeframes for optimal signal quality Wait for STRONG or MEGA signals rather than acting on every BUY/SELL Divergences work best when combined with extreme oscillator readings Multiple oscillator divergences (RSI + WT + MACD) are most reliable Use confluence score as filter - avoid signals below 60 score MACD histogram size indicates momentum strength - larger bars = stronger moves MFI divergence from price often precedes reversals (volume leads price) Combine with price action and support/resistance for best results Indicator Limitations Oscillators can remain overbought/oversold longer than expected in strong trends Divergences can persist for multiple bars before reversal occurs Multiple signals in choppy markets can lead to whipsaws Confluence score is mathematical calculation, not prediction of future movement ULTRA signals are rare - waiting only for these may miss opportunities Volume data quality varies across markets and can affect MFI reliability Stochastic RSI is very sensitive and can generate premature signals No indicator combination eliminates false signals entirely Requires understanding of oscillator behavior for effective interpretation Technical Implementation Built with Pine Script v6 using: Custom WaveTrend calculation with dual-line system Proper MFI formula with volume-weighted money flow Multi-oscillator divergence detection with pivot analysis Confluence scoring algorithm with weighted components Enhanced MACD histogram visualization (linewidth 8) Dynamic color gradients for momentum visualization Anti-overlap logic for signal labels Real-time dashboard with oscillator readings The code is fully open-source and can be modified to adjust oscillator weights, signal thresholds, and visual preferences. Originality Statement This indicator is original in its multi-oscillator integration approach. While individual components (WaveTrend, MFI, RSI, MACD, Stochastic RSI) are established oscillators, this mashup is justified because: It combines five oscillators using fundamentally different calculation methods The tiered signal system (BUY to ULTRA) provides graduated confidence levels Multi-oscillator divergence detection catches momentum exhaustion across different timeframes Confluence scoring quantifies momentum alignment across all oscillators Volume integration through MFI adds institutional flow perspective Enhanced visualization (large MACD histogram, bright divergence markers) improves usability Each oscillator contributes unique information: WaveTrend provides wave-cycle analysis, MFI incorporates volume, RSI offers reliable baseline, MACD shows trend strength, and Stochastic RSI catches early shifts. The mashup's value lies in identifying when these different momentum calculations align, significantly reducing false signals compared to any single oscillator. Disclaimer This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Trading involves substantial risk of loss and is not suitable for all investors. Oscillator-based indicators are lagging tools that analyze past price data. They do not predict future price movement. Overbought conditions can persist in strong uptrends, and oversold conditions can persist in strong downtrends. Divergences can continue for extended periods before reversals occur. The confluence score is a mathematical calculation, not a guarantee of trade success. High confluence scores do not ensure profitable trades. Past signal performance does not guarantee future results. Market conditions change, and oscillator behavior varies across different market regimes. Always use proper risk management, including stop losses and position sizing appropriate for your account size and risk tolerance. Never risk more than you can afford to lose. Consider consulting with a qualified financial advisor before making investment decisions. The author is not responsible for any losses incurred from using this indicator. Users assume full responsibility for all trading decisions made using this tool. -Made with passion by officialjackofalltrades
Indicatore Pine Scriptยฎ
di officialjackofalltrades
Gann Projector by Santiago rebello๐ŸŽฏGANN PIVOT PROJECTOR by Santiago Rebello ๐Ÿ“ˆ SIMPLIFIED WD GANN TIME TOOL Enter ANY INSTRUMENT pivots โ†’ Get future turn dates instantly! โœจ FEATURES: โ€ข 3 customizable pivot dates + prices โ€ข High/Low ratio ร— swing days = turn projection โ€ข 9 table positions (move anywhere) โ€ข Color-coded turn boxes + exact dates โ€ข Pivot markers (โ–ฒโ–ผ) on chart โ€ข Clean Nifty-optimized interface works on all segments
Indicatore Pine Scriptยฎ
di gracentruth
Gann Projector by santiago rebello๐ŸŽฏ NIFTY PIVOT PROJECTOR by Santiago Rebello ๐Ÿ“ˆ SIMPLIFIED WD GANN TIME TOOL Enter Nifty pivots โ†’ Get future turn dates instantly! โœจ FEATURES: โ€ข 3 customizable pivot dates + prices โ€ข High/Low ratio ร— swing days = turn projection โ€ข 9 table positions (move anywhere) โ€ข Color-coded turn boxes + exact dates โ€ข Pivot markers (โ–ฒโ–ผ) on chart โ€ข Clean Nifty-optimized interface โš™๏ธ FORMULA: High รท Low = Ratio ร— Swing Days = Future Turns ๐Ÿ“Š EXAMPLE: 26373(High) รท 25450(Low) = 1.036 ratio 1.036 ร— 21 days = Mar 3 TURN BOX ๐ŸŽฎ 3-STEP SETUP: 1๏ธโƒฃ Enter recent Nifty high/low dates 2๏ธโƒฃ Set swing days between pivots 3๏ธโƒฃ Move table โ†’ See projections! ๐Ÿ’Ž PERFECT FOR: โœ… Nifty positional trading โœ… Swing time analysis โœ… BankNifty options timing โœ… Pivot backtesting ๐Ÿ”ฅ INSTANT RESULTS - No complex setup! #Nifty #Gann #Pivot #TimeProjection #TradingView ๐ŸŽฏ GANN PROJECTOR by Santiago Rebello ๐Ÿ“ˆ WD Gann Time Projection Tool for Nifty Traders โœจ FEATURES: โ€ข Enter 3 pivot dates + prices + swing days โ€ข High/Low ratio ร— days = Future turn dates โ€ข 9 movable table positions โ€ข 3 color-coded turn boxes (Orange/Yellow/Fuchsia) โ€ข 6 pivot markers (High=โ–ผ Low=โ–ฒ) โ€ข Dynamic date display (MMM d format) โš™๏ธ GANN FORMULA: High รท Low = Ratio ร— Swing Days = Turn Projection ๐Ÿ“Š LIVE EXAMPLE: 26373(High) รท 25450(Low) = 1.036 ratio 1.036 ร— 21 days = Mar 3 TURN BOX ๐ŸŽฎ INSTANT SETUP: 1๏ธโƒฃ Input recent Nifty pivots 2๏ธโƒฃ Set swing duration 3๏ธโƒฃ Move table anywhere 4๏ธโƒฃ Future turns appear instantly! ๐Ÿ’Ž PERFECT FOR: โœ… Nifty positional trading โœ… BankNifty options timing โœ… Swing trade planning โœ… Pivot backtesting ๐Ÿ”ฅ SIMPLIFIED GANN - No complex math! #Gann #Nifty #TradingView #Pivot #TimeProjection ๐ŸŽฏ GANN PROJECTOR by Santiago Rebello ๐Ÿ“ˆ WD Gann Time Projection Tool for Nifty Traders โœจ FEATURES: โ€ข Enter 3 pivot dates + prices + swing days โ€ข High/Low ratio ร— days = Future turn dates โ€ข 9 movable table positions โ€ข 3 color-coded turn boxes (Orange/Yellow/Fuchsia) โ€ข 6 pivot markers (High=โ–ผ Low=โ–ฒ) โ€ข Dynamic date display (MMM d format) โš™๏ธ GANN FORMULA: High รท Low = Ratio ร— Swing Days = Turn Projection ๐Ÿ“Š LIVE EXAMPLE: 26373(High) รท 25450(Low) = 1.036 ratio 1.036 ร— 21 days = Mar 3 TURN BOX ๐ŸŽฎ INSTANT SETUP: 1๏ธโƒฃ Input recent Nifty pivots 2๏ธโƒฃ Set swing duration 3๏ธโƒฃ Move table anywhere 4๏ธโƒฃ Future turns appear instantly! ๐Ÿ’Ž PERFECT FOR: โœ… Nifty positional trading โœ… BankNifty options timing โœ… Swing trade planning โœ… Pivot backtesting ๐Ÿ”ฅ SIMPLIFIED GANN - No complex math! #Gann #Nifty #TradingView #Pivot #TimeProjection
Indicatore Pine Scriptยฎ
di gracentruth
Fourier Series Model of the Market v2In the FSMM script the scaling of the harmonics is with the base frequency. Although this may help to visualize the harmonics, in a mathematically correct manner quadrature scaling is by the harmonics frequencies. As the derivative is numerical, the difference is not always noticed, but to include it makes sense, also when the purpose is to visualize the short underlying trend of Hurst, which is the base plus the 2nd and 4th harmonic. The 3rd harmonic then serves as a diagnostic marker, if the M-shape does not appear properly then there may be a contribution from the 3rd harmonics. Typical setting is 55 for intruments that trade 5 days a week and 82 for 7 days a week (Crypto) Enjoy!
Indicatore Pine Scriptยฎ
di huub_j_m_degroot
Pattern Detector by Dahhans DfirstX| Pattern | Description | Signal | | ---------------- | ----------------------------------------------------------------- | ---------------- | | Head & Shoulders | 3 peaks: left shoulder, higher head, right shoulder at same level | Bearish reversal | | Inverse H&S | 3 valleys: left, lower head, right at same level | Bullish reversal | | Double Top | 2 peaks at similar price level | Bearish reversal | | Double Bottom | 2 valleys at similar price level | Bullish reversal | | Bull Engulfing | Green candle completely covers red candle | Bullish | | Bear Engulfing | Red candle completely covers green candle | Bearish | | Hammer | Small body, long lower wick | Bullish reversal | | Shooting Star | Small body, long upper wick | Bearish reversal |
Indicatore Pine Scriptยฎ
di dahhan1996
Operation Assistant (Replay Trading Helper)**Operation Assistant (Replay Trading Helper)** This Pine Script is a visual execution helper designed for TradingView Bar Replay and discretionary practice. When you arm **BUY** or **SELL**, it triggers on the candle close and automatically calculates an **Entry** at the current barโ€™s close, a **Stop Loss** at the current barโ€™s wick (Low for BUY / High for SELL), and a **Take Profit** using a configurable **Risk-to-Reward (default RR=2)**. It then plots clear horizontal **ENTRY / SL / TP** lines and shows the exact prices in a compact on-chart panel, so you can copy them into the Trading panel quickly. No orders are sentโ€”this tool is for faster manual execution and consistent risk structure during replay or live chart review.
Indicatore Pine Scriptยฎ
di Fran_Pineda
Golden Zone + 50 % Line (Multi Moves) by GrimsonThis indicator displays the 50% line of a price move and the golden zone according to Fibonacci levels. You can freely choose between which Fibonacci levels the zone should be drawn. In addition, all colors, lines, and boundaries can be customized. You can also choose how many boxes should be displayed retrospectively. It also distinguishes whether the move was bullish or bearish. The zones stop once they are touched. The sensitivity of the move detection can also be freely adjusted. Enjoy and happy trading!
Indicatore Pine Scriptยฎ
di Grimson55
1
Folded RSIFolded RSI: Spectral-Adaptive Momentum Oscillator A cycle-responsive RSI that automatically tunes its calculation period based on real-time spectral correlation analysis, featuring gradient-visualized momentum extremes. Overview The Folded RSI revolutionizes traditional momentum analysis by replacing static periods with dynamic, data-driven adaptation. Using phase-invariant spectral correlation , the indicator measures how closely price action aligns with theoretical cyclical patterns, then adjusts the RSI length accordingly. When markets exhibit strong cyclical structure, the RSI compresses to capture rapid oscillations; during chaotic or trendless periods, it expands to filter noise. Key Features Phase-Invariant Cycle Detection: Calculates Pearson correlation against pure sine/cosine waves to detect cyclical strength regardless of phase position (uses quadrature sum of sin/cos correlations) Dual-Harmonic Analysis: Optionally evaluates both the target period and its 2ร— harmonic, automatically selecting the stronger correlation for optimal adaptation Nonlinear Length Mapping: Maps correlation magnitude (0-1) to RSI length through a power functionโ€”strong cycles produce fast, responsive RSI; weak cycles produce smooth, lagged readings Pure Mathematical Implementation: Custom Wilder RSI using dynamic smoothing factors (alpha = 1/length) and custom EMAโ€”zero dependency on built-in TA functions Gradient Visual System: Dynamic color transitions from neutral blue to hot red (overbought) or cool green (oversold) with gradient fills showing momentum intensity Extreme Level Markers: Automatic visual alerts when RSI crosses above 70 (red markers) or below 30 (green markers) Real-Time Diagnostics: On-chart table displaying current correlation magnitude, adaptive length, and detected dominant period How It Works 1. Spectral Analysis The indicator computes correlation between price returns and synthetic sinusoidal basis functions over the Cycle Window . By testing both sine and cosine components simultaneously, it achieves phase-invariance โ€”detecting cyclical presence regardless of whether the cycle is currently at a peak, trough, or zero-crossing. 2. Harmonic Selection When enabled, the algorithm compares correlation strength at both the Target Period and its octave (2ร— length), selecting whichever exhibits stronger statistical alignment with price action. 3. Adaptive Length Calculation The correlation magnitude determines the RSI period through the formula: High correlation โ†’ Shorter length (minimum setting) Low correlation โ†’ Longer length (maximum setting) Adjustable nonlinearity (power) curve to emphasize or flatten the response 4. Dynamic RSI Computation A custom Wilder-style RSI calculates using the adaptive length, with optional post-smoothing EMA to reduce whipsaws. Settings Guide Cycle Window: Lookback bars for correlation calculation (40+ recommended for statistical significance) Target Sine Period: Expected dominant cycle in bars (e.g., 20 for monthly cycles on daily charts) RSI Length Min/Max: Bounds for adaptive calculation (5-50 standard range) Nonlinearity (Power): Response curve shapeโ€”>1.0 emphasizes strong cycles, <1.0 creates more gradual transitions Invert Mapping: Reverses logic (strong cycles โ†’ longer RSI) for contrarian strategies Post Smoothing: EMA period applied to raw RSI output (1 = no smoothing) Visual Interpretation โ–ผ Red Markers: RSI above 70 (potential overbought) โ–ฒ Green Markers: RSI below 30 (potential oversold) Diagnostics Table: Top-right display showing: Current RSI value Correlation magnitude (higher % = stronger cyclical structure) Current adaptive length Best detected period (base or harmonic) Monitor the correlation magnitude in the diagnostics table to gauge indicator confidenceโ€”values above 60% indicate strong cyclical behavior where the adaptive length is optimized for current market conditions. Values below 30% suggest the market is in a non-cyclical state (trending or chaotic), triggering longer, smoother RSI periods.
Indicatore Pine Scriptยฎ
di Cmo22
Adaptive Harmonic Forecast [LuxAlgo]The Adaptive Harmonic Forecast indicator decomposes price action into multiple cyclical components and a linear trend to forecast future market movement. By extracting the most dominant frequencies from recent price data, the tool projects a multi-harmonic model into the future to identify potential reversal points and trend continuations. ๐Ÿ”ถ USAGE The indicator provides a mathematical projection of price action based on the assumption that markets exhibit cyclical behavior. Users can utilize the forecast to anticipate upcoming shifts in momentum or to identify the underlying trend direction. It is important to note that the forecast is dynamic and recalculates on the most recent bar; therefore, it is best used to confirm momentum shifts when price action aligns with the projected harmonic direction. ๐Ÿ”น Historical Fit & Forecast The script displays a solid line over the historical lookback period, representing how well the harmonic model fits the actual price data. Beyond the current bar, a dotted line extends the forecast. This forecast is color-coded: green represents projected upward movement, while red represents projected downward movement. The forecast should be viewed primarily as a timing tool rather than an exact price target, as it projects where the "rhythm" of the market is heading based on current harmonics. ๐Ÿ”น Trend Line & Reversal Markers A linear trend line is calculated alongside the sinusoids to show the overall bias (slope) of the lookback period. Additionally, the indicator can plot reversal markers (dots) at the specific points where the forecasted cycles reach a peak or trough. These markers highlight potential future turning points where the composite cycles converge to create a local maximum or minimum. ๐Ÿ”น Detected Cycles Table The "Detected Cycles" dashboard allows traders to identify if current price action is dominated by short-term "noise" cycles or larger "structural" cycles. By observing the period lengths (in bars), users can determine the frequency of market swings. If the detected periods are small relative to the lookback, the market is in a high-frequency state; if they are large, the market is exhibiting more stable, long-term cyclicality. ๐Ÿ”ถ DETAILS The script operates through a two-step mathematical process involving spectral analysis and matrix-based regression: Periodogram Logic (Cycle Detection): The indicator first detrends the data within the lookback window using a linear fit. It then performs a spectral analysis by scanning a range of periods to calculate "spectral power" (the correlation between price and a specific frequency). It identifies "spectral peaks" where price variance is most concentrated, ensuring that only the most meaningful cycles are selected for modeling rather than random noise. Multi-Harmonic OLS Regression: Once the dominant periods are identified, the script uses Ordinary Least Squares (OLS) regression to solve for the coefficients of a linear combination of basis functions. Specifically, it constructs a model consisting of multiple sine and cosine waves (representing the cycles) and a first-order polynomial (representing the trend). By solving the normal equation using matrix math, the script finds the optimal amplitudes and phases that minimize the squared error against historical price. This composite model is then solved for future time coordinates to create the extrapolation. ๐Ÿ”ถ SETTINGS ๐Ÿ”น Settings Fit Lookback (N): Determines the number of historical bars used to analyze cycles and fit the model. Extrapolation Bars: Sets how many bars into the future the forecast should extend. Number of Sinusoids: The maximum number of individual cycles to include in the composite model (1-10). ๐Ÿ”น Automatic Cycle Detection Min Period: The shortest cycle length (in bars) the algorithm is allowed to detect. ๐Ÿ”น Visuals Show Reversal Dots: Toggles the markers at forecasted local highs and lows. Dot Size: Adjusts the visual scale of the reversal markers. Show Detected Periods: Toggles the data table showing the lengths of the dominant cycles. ๐Ÿ”น Trend Line Show Trend Line: Toggles the display of the underlying linear regression line. Trend Line Color: Sets the color for the historical and projected trend line.
Indicatore Pine Scriptยฎ
di LuxAlgo
10
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. ๐Ÿ”ถ 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. ๐Ÿ”น 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. ๐Ÿ”ถ DETAILS The indicator is built upon three primary technical pillars: ๐Ÿ”น 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. ๐Ÿ”น 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. ๐Ÿ”น 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. ๐Ÿ”ถ SETTINGS ๐Ÿ”น 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. ๐Ÿ”น Normalization Settings Normalization Lookback: The window used to scale the cycles and calculate the volatility of the resonance signal. ๐Ÿ”น 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). ๐Ÿ”น 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.
Indicatore Pine Scriptยฎ
di LuxAlgo
3
PyraTime Liquidity & TimeThe Problem: Why Most Traders Get Trapped Most trading indicators fail because they only look at half the picture: Price. Traders draw support and resistance lines, wait for the price to hit them, and then get stopped out by a wick that instantly reverses. This is a "Liquidity Sweep," and it is how institutional algorithms trap retail traders. Furthermore, free indicators often suffer from the "Floating Indicator" bugโ€”where lines detach from price during zoomingโ€”making them unreliable for precision trading. The Solution: PyraTime Liquidity & Time PyraTime L&T solves this by filtering every price move through Time. It does not just ask "Is price at support?" It asks "Is price at support at the exact right time?" This tool combines three institutional concepts into one dashboard: Geometric Liquidity Traps: Identifies when a swing point is swept (false breakout) exactly during a Fibonacci Time Cluster. Institutional Time Cycles: Projects future volatility windows (Gold Lines) based on the geometry of past pivots. Silver Bullet Zones: Automatically highlights the specific hours where algorithms are most active (London, NY, Tokyo sessions). How to Use This Indicator 1. The "Trap" Signal (Your Entry Trigger) The core function of this tool is to identify "Time-Price Traps." Wait for a Signal: A "TRAP" or "SWEEP" label will appear when price breaks a previous high/low but closes back inside the range AND this happens inside a Fibonacci Time Cluster. The Logic: This confirms that Time and Price have squared. It is a high-probability reversal signal. Cyan Label: Bullish Trap (Look for Longs) Pink Label: Bearish Trap (Look for Shorts) 2. The Golden Time Lines (Your Filter) The vertical Gold lines are future time projections. Cluster Confirmation: If you see multiple Gold lines grouped closely together, expect high volatility or a reversal at that specific time. Trade Filter: Do not take a trade just because a line appears. Use it to time your entry at a key price level. 3. Silver Bullet Zones (Session Awareness) The indicator highlights the three most powerful 60-minute windows in the market (New York Time). London SB (03:00 - 04:00): Often sets the high or low of the London session. New York SB (10:00 - 11:00): The classic "Silver Bullet" continuation or reversal window. Tokyo SB (22:00 - 23:00): Key for crypto and Asian forex pairs. PRO TIP: Managing the Noise For High Timeframes (4H, Daily): Go to Settings and uncheck "Silver Bullet Zones." These zones are designed for intraday "zoning in" (1m to 15m charts) and will look cluttered on a Daily chart. For Precision (1m - 15m): Turn the Silver Bullet Zones ON to see exactly when the algorithmic windows open. Technical Features & Compliance Zero Repainting: Signals are confirmed on candle close. History is never altered. Floating Fix: Built with xloc.bar_time to ensure all drawings stay locked to their exact historical moment, regardless of chart scaling. Memory Optimized: Automatically cleans up old lines to maintain maximum performance on all devices.
Indicatore Pine Scriptยฎ
di PyraTime
1
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 โ€œtrend indicatorโ€ 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 โ€œsnapshotโ€ 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 cycleโ€™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 โ€œfrequencyโ€ and โ€œcyclesโ€ mean in trading terms A cycle period (say 21 bars) means: โ€œa repeating pattern that tends to complete one full oscillation every 21 bars.โ€ 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: Fourierโ€™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 โ€œin-phaseโ€ alignment with the cycle. Sine component captures โ€œquadratureโ€ (90-degree shifted) alignment. Combining them gives full information: amplitude + phase. Mathematically, a single frequency component can be written as: A * cos(ฯ‰t + ฯ†) But DFT estimates A and ฯ† 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 โ€œcyclical structure in standardized deviations,โ€ not raw dollars. Projection onto cosine and sine For each tested period P: ฯ‰ = 2ฯ€ / P (angular frequency for that period) Compute: - sCos = ฮฃ(norm * cos(ฯ‰k)) - sSin = ฮฃ(norm * sin(ฯ‰k)) 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(sCosยฒ + sSinยฒ) 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 0โ€“100 โ€œdisplay amplitudeโ€: amp = sqrt(sCosยฒ + sSinยฒ) / 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 โ€œsignal quality.โ€ It is a standardized โ€œhow much of that cycle exists in the recent windowโ€ 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 -ฯ€ to +ฯ€. Phase tells you where you are within the cycle: Two cycles can have same amplitude but opposite phase. Phase is what lets you infer โ€œapproaching peak vs troughโ€ 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 (0โ€“100) on the y-axis. X-axis meaning Each x position corresponds to a period (5 โ†’ 120 bars). You are not looking at โ€œfrequency in Hz.โ€ You are looking at โ€œperiod in bars,โ€ 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 โ–ฒ or โ–ผ. Phase direction logic: rising = sin(phase) < 0 โ–ฒ means cycle is in a โ€œrisingโ€ phase segment โ–ผ means cycle is in a โ€œfallingโ€ phase segment This is not โ€œprice will rise now.โ€ It is โ€œthe dominant cycleโ€™s instantaneous phase suggests you are on the upward vs downward half of that oscillation.โ€ In real markets, you use this as context, not as a standalone trade trigger. It also draws small โ–ฒ/โ–ผ markers on secondary peaks (amp > 15) to show phase direction of other meaningful cycles, giving you a richer picture than โ€œone dominant period.โ€ 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 โšก 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 โ€œvibratingโ€ together at a shared period. Resonance is not automatically bullish or bearish. It is telling you โ€œcycle length agreement,โ€ 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 โ†’ 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 symbolโ€™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 0โ€“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) โ‰ˆ +1, oscillator near 100 (cycle peak zone). When cos(phase) โ‰ˆ -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 โ€œtiming contextโ€ 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 โ€œprevious confirmed closeโ€ 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 โ–ฒ/โ–ผ markers derived from sin(phase). Useful for quick cycle position intuition, but do not treat โ–ฒ as โ€œbuy.โ€ 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 โ€œabsolute truth.โ€ 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 (5โ€“13) dominate, market is often choppy, reactive, and mean-reverting. If mid periods (21โ€“55) dominate, market often shows swing structure. If long periods (89โ€“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 0โ€“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.
Indicatore Pine Scriptยฎ
di BackQuant
TS Pressure OscillatorThis indicator is a TS Pressure Oscillator. Its job is to turn a lot of small โ€œTS eventsโ€ (liquidity sweeps + rejection) into a single, easy-to-read curve that helps you spot short-term exhaustion and possible trend shifts. What it detects (TS events) A โ€œTSโ€ here means a candle that: briefly breaks the previous candleโ€™s high and then closes back below it (bearish rejection), or briefly breaks the previous candleโ€™s low and then closes back above it (bullish rejection). In simple words: price tried to continue, failed, and got rejected. What the oscillator measures Instead of counting every TS equally, this version gives each event a score based on its quality: Wick size vs ATR (how meaningful the sweep was) Body size vs ATR (how strong the rejection candle was) Then it filters events by context: bearish TS only matter most near the top of a recent range bullish TS only matter most near the bottom of a recent range After that, it combines multiple timeframes (M15 / M5 / M1) into one curve: If bearish TS pressure dominates, the oscillator tends to move up (more rejection from above). If bullish TS pressure dominates, the oscillator tends to move down (more rejection from below). Why there are two lines (Main vs EMA) Main line shows the current pressure. EMA line is the smoothed version (the โ€œtrendโ€ of the pressure). The gap between them is useful: when the Main line pulls away from the EMA, it often means pressure is accelerating. The most important part: parameters This indicator is only as good as its tuning. The key settings control what it considers โ€œrelevantโ€ TS events: Zone lookback (HH/LL): defines what โ€œtopโ€ and โ€œbottomโ€ mean Zone thresholds (zoneHi / zoneLo): how strict the โ€œextreme areaโ€ filter is Window lengths per timeframe: how much history youโ€™re measuring ATR length + caps: how sensitive the scoring is Baseline: prevents the oscillator from sticking at extremes If your parameters are too loose, youโ€™ll get noise. If theyโ€™re too strict, youโ€™ll miss opportunities. Dialing them in for each asset/session is the difference between a โ€œnice curveโ€ and a useful signal. If you want, tell me the asset (e.g., XAUUSD) and your main chart timeframe, and Iโ€™ll suggest a solid starting preset for the parameters.
Indicatore Pine Scriptยฎ
di Fran_Pineda
MemoMeister Capsules: Boost Your Concentration and MemoryMemoMeister Capsules: Boost Your Concentration and Memory In todayโ€™s fast-paced digital world, concentration and memory have become essential skills for both professional success and everyday life. MemoMeister capsules are increasingly discussed as a supplement designed to support cognitive performance, mental clarity, and sustained focus. Before forming an opinion about MemoMeister, it is important to consult independent analyses and explanatory resources that examine the product from multiple perspectives. An in-depth independent review that closely examines MemoMeister capsules, their positioning, and general user perception can be found in this detailed analysis, which provides structured insight and contextual evaluation: www.tumblr.com . Such comprehensive references help establish a clearer understanding of how MemoMeister is discussed in real-world contexts. 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Whether managing complex work tasks, studying for exams, or handling multiple responsibilities at once, cognitive endurance is often tested daily. MemoMeister capsules are positioned toward individuals who seek steady support for mental performance rather than short-term stimulation. As cognitive demands increase, many people look for ways to maintain clarity and attention over longer periods. Memory and concentration are closely linked, and supporting both can help reduce mental fatigue while improving the ability to process and retain information consistently throughout the day. How MemoMeister Capsules Fit Into Daily Cognitive Support MemoMeister capsules are commonly discussed as part of a routine-based approach to mental performance. Rather than expecting immediate or dramatic effects, many users focus on gradual cognitive support that integrates into everyday habits. This aligns with how memory and focus supplements are typically evaluated, as improvements are often subtle and develop over time. Consistency plays a key role when it comes to cognitive supplements. By incorporating MemoMeister capsules into a regular schedule, users often aim to support mental clarity during periods of increased cognitive workload, such as demanding work phases or extended periods of concentration. Long-Term Cognitive Support and Realistic Expectations When evaluating supplements designed to support concentration and memory, long-term perspective is essential. Cognitive performance is influenced by multiple factors, including lifestyle, workload, and mental habits, which means that products like MemoMeister capsules are typically viewed as supportive tools rather than instant solutions. Many users focus on maintaining stable mental clarity and consistent focus over time, especially during periods of sustained cognitive demand. By setting realistic expectations and combining supplementation with balanced routines, adequate rest, and mental engagement, MemoMeister capsules are often discussed within a broader strategy aimed at preserving cognitive efficiency and supporting memory function in a sustainable and measured way. MemoMeister Capsules in Everyday Mental Performance Scenarios In everyday situations that require sustained attention, such as long workdays, complex problem-solving, or continuous learning, mental performance can fluctuate significantly. MemoMeister capsules are often discussed in connection with these real-life scenarios, where concentration and memory are tested repeatedly rather than occasionally. Instead of targeting short bursts of stimulation, the product is typically associated with maintaining a steady level of cognitive support throughout the day. This makes MemoMeister particularly relevant for individuals who value mental consistency, structured thinking, and the ability to stay focused across multiple tasks without experiencing rapid mental exhaustion. Independent Perspectives and Information Sources One reason MemoMeister capsules continue to attract attention is their presence across various independent publishing platforms. Articles, reviews, and explanatory pages provide different viewpoints and allow readers to compare interpretations and experiences. This variety of independent content sources contributes to discoverability and encourages a more balanced evaluation. Access to multiple perspectives helps readers move beyond promotional messaging and focus instead on informative content. When a supplement is discussed in analytical articles and independent resources, it becomes easier to assess expectations realistically and understand its intended role. Final Thoughts on MemoMeister Capsules MemoMeister capsules are aimed at individuals who want to support their concentration and memory in a structured and informed way. Whether used during mentally demanding workdays, study periods, or phases of high cognitive load, the product is positioned as a supplement worth examining more closely through independent sources. Making an informed decision involves understanding realistic expectations, consulting transparent information, and focusing on long-term cognitive well-being. By exploring detailed analyses, explanatory articles, and credibility-focused resources, readers can form a clearer picture of how MemoMeister capsules may fit into their personal approach to mental performance and memory support.
Indicatore Pine Scriptยฎ
di XbnPP12
Time Cycles# Time Cycles Indicator **Time Cycles Indicator** is a time-based visualization tool designed to map repeating market rhythms as smooth arches in a separate pane. Rather than reacting to price, the script focuses purely on **time cycles**, helping you visualize potential **liquidity flow, expansion, and contraction phases** across the chart. --- ## ๐Ÿ” What This Indicator Does - Translates a user-defined **time cycle (in days)** into repeating **semi-circular arches** - Anchors cycles to a **fixed start date** - Displays cycles in a **clean, price-independent pane** - **Projects cycles forward into the future** (e.g. 6 months) so you can anticipate upcoming time windows - Designed to complement **structure, liquidity, and narrative-based analysis** --- ## ๐Ÿง  How It Works Each cycle is mathematically modeled as a **semicircle**: - Start of cycle โ†’ low energy - Mid-cycle โ†’ peak / expansion - End of cycle โ†’ decay / reset This produces a smooth โ€œarchโ€ that visually represents **temporal momentum**, independent of market volatility. --- ## โš™๏ธ Key Settings ### Cycle Settings - **Start Date (UTC)** โ€“ Anchor point for all cycles - **Period (Days)** โ€“ Length of each cycle (supports decimals) - **Phase Shift (Days)** โ€“ Slide cycles forward or backward in time - **Plot Only After Start Date** โ€“ Ignore cycles before the anchor ### Visual Controls - **Amplitude** โ€“ Vertical scale of the arches - **Baseline** โ€“ Vertical offset for positioning - **Invert** โ€“ Flip arches into valleys - **Baseline Guide** โ€“ Optional reference line - **Shaded Fill** โ€“ Visual emphasis of cycle energy ### Forward Projection - **Project Forward** โ€“ Enable future cycle rendering - **Forward Distance (Days)** โ€“ How far into the future to extend (default โ‰ˆ 6 months) - **Step Size (Days)** โ€“ Smoothness vs performance control --- ## ๐Ÿ“ˆ How to Use It - Pair with **market structure**, **VWAP**, **HTF levels**, or **liquidation maps** - Watch for **confluence** between cycle peaks/troughs and price events - Use forward projections to anticipate **time-based inflection zones** - Works across all markets and timeframes --- ## โš ๏ธ Important Notes - This is **not a price predictor** - Cycles represent **time windows**, not directional bias - Best used as a **contextual overlay**, not a standalone signal --- ## ๐Ÿงฉ Ideal For - Liquidity & narrative traders - Time-cycle analysts - Macro rhythm mapping - Traders who believe *โ€œtime reveals structure before price doesโ€* --- *Time does not repeat โ€” but it often rhymes.*
Indicatore Pine Scriptยฎ
di tjvsx