Mulakan

Kitaran

WaveTrend RBF What it does WT-RBF extracts a “wave” of momentum by subtracting a fast Gaussian-weighted smoother from a slow one, then robust-normalizes that wave with a median/MAD proxy to produce a z-score (z). A short EMA of z forms the signal line. Optional dynamic thresholds use the MAD of z itself so overbought/oversold levels adapt to volatility regimes. How it’s built: Radial (Gaussian) smoothers Causal, exponentially-decaying weights over the last radius bars using σ (sigma) to control spread. fast = rbf_smooth(src, fastR, fastSig) slow = rbf_smooth(src, slowR, slowSig) wave = fast − slow (band-pass) Robust normalization A two-stage EMA approximates the median; MAD is estimated from EMA of absolute deviations and scaled by 1.4826 to be stdev-comparable. z = (wave − center) / MAD Thresholds Dynamic OB/OS: ±2.5 × MAD(z) (or fixed levels when disabled) Reading the indicator Bull Cross: z crosses above sig → momentum turning up. Bear Cross: z crosses below sig → momentum turning down. Exits / Bias flips: zero-line crosses (below 0 → exit long bias; above 0 → exit short bias). Overbought/Oversold: z > +thrOB or z < thrOS. With dynamics on, the bands widen/narrow with recent noise; with dynamics off, static guides at ±2 / ±2.5 are shown. Core Inputs Source: Price series to analyze. Fast Radius / Fast Sigma (defaults 6 / 2.5): Shorter radius/smaller σ = snappier, higher-freq. Slow Radius / Slow Sigma (defaults 14 / 5.0): Larger radius/σ = smoother, lower-freq baseline. Normalization Robust Z-Score Window (default 200): Lookback for median/MAD proxy (stability vs responsiveness). Small ε for MAD: Floor to avoid division by zero. Signal & Thresholds Dynamic Thresholds (MAD-based) (on by default): Adaptive OB/OS; toggle off to use fixed guides. Visuals Shade OB/OS Regions: Background highlights when z is beyond thresholds. Show Zero Line: Midline reference. (“Plot Cross Markers” input is present for future use.)
Penunjuk Pine Script®
oleh Cmo22
Ehlers Even Better Sinewave (EBSW)# EBSW: Ehlers Even Better Sinewave ## Overview and Purpose The Ehlers Even Better Sinewave (EBSW) indicator, developed by John Ehlers, is an advanced cycle analysis tool. This implementation is based on a common interpretation that uses a cascade of filters: first, a High-Pass Filter (HPF) to detrend price data, followed by a Super Smoother Filter (SSF) to isolate the dominant cycle. The resulting filtered wave is then normalized using an Automatic Gain Control (AGC) mechanism, producing a bounded oscillator that fluctuates between approximately +1 and -1. It aims to provide a clear and responsive measure of market cycles. ## Core Concepts * **Detrending (High-Pass Filter):** A 1-pole High-Pass Filter removes the longer-term trend component from the price data, allowing the indicator to focus on cyclical movements. * **Cycle Smoothing (Super Smoother Filter):** Ehlers' Super Smoother Filter is applied to the detrended data to further refine the cycle component, offering effective smoothing with relatively low lag. * **Wave Generation:** The output of the SSF is averaged over a short period (typically 3 bars) to create the primary "wave". * **Automatic Gain Control (AGC):** The wave's amplitude is normalized by dividing it by the square root of its recent power (average of squared values). This keeps the oscillator bounded and responsive to changes in volatility. * **Normalized Oscillator:** The final output is a single sinewave-like oscillator. ## Common Settings and Parameters | Parameter | Default | Function | When to Adjust | | ----------- | ------- | --------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------- | | Source | close | Price data used for calculation. | Typically `close`, but `hlc3` or `ohlc4` can be used for a more comprehensive price representation. | | HP Length | 40 | Lookback period for the 1-pole High-Pass Filter used for detrending. | Shorter periods make the filter more responsive to shorter cycles; longer periods focus on longer-term cycles. Adjust based on observed cycle characteristics. | | SSF Length | 10 | Lookback period for the Super Smoother Filter used for smoothing the detrended cycle component. | Shorter periods result in a more responsive (but potentially noisier) wave; longer periods provide more smoothing. | **Pro Tip:** The `HP Length` and `SSF Length` parameters should be tuned based on the typical cycle lengths observed in the market and the desired responsiveness of the indicator. ## Calculation and Mathematical Foundation **Simplified explanation:** 1. Remove the trend from the price data using a 1-pole High-Pass Filter. 2. Smooth the detrended data using a Super Smoother Filter to get a clean cycle component. 3. Average the output of the Super Smoother Filter over the last 3 bars to create a "Wave". 4. Calculate the average "Power" of the Super Smoother Filter output over the last 3 bars. 5. Normalize the "Wave" by dividing it by the square root of the "Power" to get the final EBSW value. **Technical formula (conceptual):** 1. **High-Pass Filter (HPF - 1-pole):** `angle_hp = 2 * PI / hpLength` `alpha1_hp = (1 - sin(angle_hp)) / cos(angle_hp)` `HP = (0.5 * (1 + alpha1_hp) * (src - src )) + alpha1_hp * HP ` 2. **Super Smoother Filter (SSF):** `angle_ssf = sqrt(2) * PI / ssfLength` `alpha2_ssf = exp(-angle_ssf)` `beta_ssf = 2 * alpha2_ssf * cos(angle_ssf)` `c2 = beta_ssf` `c3 = -alpha2_ssf^2` `c1 = 1 - c2 - c3` `Filt = c1 * (HP + HP )/2 + c2*Filt + c3*Filt ` 3. **Wave Generation:** `WaveVal = (Filt + Filt + Filt ) / 3` 4. **Power & Automatic Gain Control (AGC):** `Pwr = (Filt^2 + Filt ^2 + Filt ^2) / 3` `EBSW_SineWave = WaveVal / sqrt(Pwr)` (with check for Pwr == 0) > 🔍 **Technical Note:** The combination of HPF and SSF creates a form of band-pass filter. The AGC mechanism ensures the output remains scaled, typically between -1 and +1, making it behave like a normalized oscillator. ## Interpretation Details * **Cycle Identification:** The EBSW wave shows the current phase and strength of the dominant market cycle as filtered by the indicator. Peaks suggest cycle tops, and troughs suggest cycle bottoms. * **Trend Reversals/Momentum Shifts:** When the EBSW wave crosses the zero line, it can indicate a potential shift in the short-term cyclical momentum. * Crossing up through zero: Potential start of a bullish cyclical phase. * Crossing down through zero: Potential start of a bearish cyclical phase. * **Overbought/Oversold Levels:** While normalized, traders often establish subjective or statistically derived overbought/oversold levels (e.g., +0.85 and -0.85, or other values like +0.7, +0.9). * Reaching above the overbought level and turning down may signal a potential cyclical peak. * Falling below the oversold level and turning up may signal a potential cyclical trough. ## Limitations and Considerations * **Parameter Sensitivity:** The indicator's performance depends on tuning `hpLength` and `ssfLength` to prevailing market conditions. * **Non-Stationary Markets:** In strongly trending markets with weak cyclical components, or in very choppy non-cyclical conditions, the EBSW may produce less reliable signals. * **Lag:** All filtering introduces some lag. The Super Smoother Filter is designed to minimize this for its degree of smoothing, but lag is still present. * **Whipsaws:** Rapid oscillations around the zero line can occur in volatile or directionless markets. * **Requires Confirmation:** Signals from EBSW are often best confirmed with other forms of technical analysis (e.g., price action, volume, other non-correlated indicators). ## References * Ehlers, J. F. (2002). *Rocket Science for Traders: Digital Signal Processing Applications*. John Wiley & Sons. * Ehlers, J. F. (2013). *Cycle Analytics for Traders: Advanced Technical Trading Concepts*. John Wiley & Sons.
Penunjuk Pine Script®
oleh mihakralj
Ehlers Phasor Analysis (PHASOR)# PHASOR: Phasor Analysis (Ehlers) ## Overview and Purpose The Phasor Analysis indicator, developed by John Ehlers, represents an advanced cycle analysis tool that identifies the phase of the dominant cycle component in a time series through complex signal processing techniques. This sophisticated indicator uses correlation-based methods to determine the real and imaginary components of the signal, converting them to a continuous phase angle that reveals market cycle progression. Unlike traditional oscillators, the Phasor provides unwrapped phase measurements that accumulate continuously, offering unique insights into market timing and cycle behavior. ## Core Concepts * **Complex Signal Analysis** — Uses real and imaginary components to determine cycle phase * **Correlation-Based Detection** — Employs Ehlers' correlation method for robust phase estimation * **Unwrapped Phase Tracking** — Provides continuous phase accumulation without discontinuities * **Anti-Regression Logic** — Prevents phase angle from moving backward under specific conditions Market Applications: * **Cycle Timing** — Precise identification of cycle peaks and troughs * **Market Regime Analysis** — Distinguishes between trending and cycling market conditions * **Turning Point Detection** — Advanced warning system for potential market reversals ## Common Settings and Parameters | Parameter | Default | Function | When to Adjust | |-----------|---------|----------|----------------| | Period | 28 | Fixed cycle period for correlation analysis | Match to expected dominant cycle length | | Source | Close | Price series for phase calculation | Use typical price or other smoothed series | | Show Derived Period | false | Display calculated period from phase rate | Enable for adaptive period analysis | | Show Trend State | false | Display trend/cycle state variable | Enable for regime identification | ## Calculation and Mathematical Foundation **Technical Formula:** **Stage 1: Correlation Analysis** For period $n$ and source $x_t$: Real component correlation with cosine wave: $$R = \frac{n \sum x_t \cos\left(\frac{2\pi t}{n}\right) - \sum x_t \sum \cos\left(\frac{2\pi t}{n}\right)}{\sqrt{D_{cos}}}$$ Imaginary component correlation with negative sine wave: $$I = \frac{n \sum x_t \left(-\sin\left(\frac{2\pi t}{n}\right)\right) - \sum x_t \sum \left(-\sin\left(\frac{2\pi t}{n}\right)\right)}{\sqrt{D_{sin}}}$$ where $D_{cos}$ and $D_{sin}$ are normalization denominators. **Stage 2: Phase Angle Conversion** $$\theta_{raw} = \begin{cases} 90° - \arctan\left(\frac{I}{R}\right) \cdot \frac{180°}{\pi} & \text{if } R eq 0 \\ 0° & \text{if } R = 0, I > 0 \\ 180° & \text{if } R = 0, I \leq 0 \end{cases}$$ **Stage 3: Phase Unwrapping** $$\theta_{unwrapped}(t) = \theta_{unwrapped}(t-1) + \Delta\theta$$ where $\Delta\theta$ is the normalized phase difference. **Stage 4: Ehlers' Anti-Regression Condition** $$\theta_{final}(t) = \begin{cases} \theta_{final}(t-1) & \text{if regression conditions met} \\ \theta_{unwrapped}(t) & \text{otherwise} \end{cases}$$ **Derived Calculations:** Derived Period: $P_{derived} = \frac{360°}{\Delta\theta_{final}}$ (clamped to ) Trend State: $$S_{trend} = \begin{cases} 1 & \text{if } \Delta\theta \leq 6° \text{ and } |\theta| \geq 90° \\ -1 & \text{if } \Delta\theta \leq 6° \text{ and } |\theta| < 90° \\ 0 & \text{if } \Delta\theta > 6° \end{cases}$$ > 🔍 **Technical Note:** The correlation-based approach provides robust phase estimation even in noisy market conditions, while the unwrapping mechanism ensures continuous phase tracking across cycle boundaries. ## Interpretation Details * **Phasor Angle (Primary Output):** - **+90°**: Potential cycle peak region - **0°**: Mid-cycle ascending phase - **-90°**: Potential cycle trough region - **±180°**: Mid-cycle descending phase * **Phase Progression:** - Continuous upward movement → Normal cycle progression - Phase stalling → Potential cycle extension or trend development - Rapid phase changes → Cycle compression or volatility spike * **Derived Period Analysis:** - Period < 10 → High-frequency cycle dominance - Period 15-40 → Typical swing trading cycles - Period > 50 → Trending market conditions * **Trend State Variable:** - **+1**: Long trend conditions (slow phase change in extreme zones) - **-1**: Short trend or consolidation (slow phase change in neutral zones) - **0**: Active cycling (normal phase change rate) ## Applications * **Cycle-Based Trading:** - Enter long positions near -90° crossings (cycle troughs) - Enter short positions near +90° crossings (cycle peaks) - Exit positions during mid-cycle phases (0°, ±180°) * **Market Timing:** - Use phase acceleration for early trend detection - Monitor derived period for cycle length changes - Combine with trend state for regime-appropriate strategies * **Risk Management:** - Adjust position sizes based on cycle clarity (derived period stability) - Implement different risk parameters for trending vs. cycling regimes - Use phase velocity for stop-loss placement timing ## Limitations and Considerations * **Parameter Sensitivity:** - Fixed period assumption may not match actual market cycles - Requires cycle period optimization for different markets and timeframes - Performance degrades when multiple cycles interfere * **Computational Complexity:** - Correlation calculations over full period windows - Multiple mathematical transformations increase processing requirements - Real-time implementation requires efficient algorithms * **Market Conditions:** - Most effective in markets with clear cyclical behavior - May provide false signals during strong trending periods - Requires sufficient historical data for correlation analysis Complementary Indicators: * MESA Adaptive Moving Average (cycle-based smoothing) * Dominant Cycle Period indicators * Detrended Price Oscillator (cycle identification) ## References 1. Ehlers, J.F. "Cycle Analytics for Traders." Wiley, 2013. 2. Ehlers, J.F. "Cybernetic Analysis for Stocks and Futures." Wiley, 2004.
Penunjuk Pine Script®
oleh mihakralj
Ehlers Autocorrelation Periodogram (EACP)# EACP: Ehlers Autocorrelation Periodogram ## Overview and Purpose Developed by John F. Ehlers (Technical Analysis of Stocks & Commodities, Sep 2016), the Ehlers Autocorrelation Periodogram (EACP) estimates the dominant market cycle by projecting normalized autocorrelation coefficients onto Fourier basis functions. The indicator blends a roofing filter (high-pass + Super Smoother) with a compact periodogram, yielding low-latency dominant cycle detection suitable for adaptive trading systems. Compared with Hilbert-based methods, the autocorrelation approach resists aliasing and maintains stability in noisy price data. EACP answers a central question in cycle analysis: “What period currently dominates the market?” It prioritizes spectral power concentration, enabling downstream tools (adaptive moving averages, oscillators) to adjust responsively without the lag present in sliding-window techniques. ## Core Concepts * **Roofing Filter:** High-pass plus Super Smoother combination removes low-frequency drift while limiting aliasing. * **Pearson Autocorrelation:** Computes normalized lag correlation to remove amplitude bias. * **Fourier Projection:** Sums cosine and sine terms of autocorrelation to approximate spectral energy. * **Gain Normalization:** Automatic gain control prevents stale peaks from dominating power estimates. * **Warmup Compensation:** Exponential correction guarantees valid output from the very first bar. ## Implementation Notes **This is not a strict implementation of the TASC September 2016 specification.** It is a more advanced evolution combining the core 2016 concept with techniques Ehlers introduced later. The fundamental Wiener-Khinchin theorem (power spectral density = Fourier transform of autocorrelation) is correctly implemented, but key implementation details differ: ### Differences from Original 2016 TASC Article 1. **Dominant Cycle Calculation:** - **2016 TASC:** Uses peak-finding to identify the period with maximum power - **This Implementation:** Uses Center of Gravity (COG) weighted average over bins where power ≥ 0.5 - **Rationale:** COG provides smoother transitions and reduces susceptibility to noise spikes 2. **Roofing Filter:** - **2016 TASC:** Simple first-order high-pass filter - **This Implementation:** Canonical 2-pole high-pass with √2 factor followed by Super Smoother bandpass - **Formula:** `hp := (1-α/2)²·(p-2p +p ) + 2(1-α)·hp - (1-α)²·hp ` - **Rationale:** Evolved filtering provides better attenuation and phase characteristics 3. **Normalized Power Reporting:** - **2016 TASC:** Reports peak power across all periods - **This Implementation:** Reports power specifically at the dominant period - **Rationale:** Provides more meaningful correlation between dominant cycle strength and normalized power 4. **Automatic Gain Control (AGC):** - Uses decay factor `K = 10^(-0.15/diff)` where `diff = maxPeriod - minPeriod` - Ensures K < 1 for proper exponential decay of historical peaks - Prevents stale peaks from dominating current power estimates ### Performance Characteristics - **Complexity:** O(N²) where N = (maxPeriod - minPeriod) - **Implementation:** Uses `var` arrays with native PineScript historical operator ` ` - **Warmup:** Exponential compensation (§2 pattern) ensures valid output from bar 1 ### Related Implementations This refined approach aligns with: - TradingView TASC 2025.02 implementation by blackcat1402 - Modern Ehlers cycle analysis techniques post-2016 - Evolved filtering methods from *Cycle Analytics for Traders* The code is mathematically sound and production-ready, representing a refined version of the autocorrelation periodogram concept rather than a literal translation of the 2016 article. ## Common Settings and Parameters | Parameter | Default | Function | When to Adjust | |-----------|---------|----------|---------------| | Min Period | 8 | Lower bound of candidate cycles | Increase to ignore microstructure noise; decrease for scalping. | | Max Period | 48 | Upper bound of candidate cycles | Increase for swing analysis; decrease for intraday focus. | | Autocorrelation Length | 3 | Averaging window for Pearson correlation | Set to 0 to match lag, or enlarge for smoother spectra. | | Enhance Resolution | true | Cubic emphasis to highlight peaks | Disable when a flatter spectrum is desired for diagnostics. | **Pro Tip:** Keep `(maxPeriod - minPeriod)` ≤ 64 to control $O(n^2)$ inner loops and maintain responsiveness on lower timeframes. ## Calculation and Mathematical Foundation **Explanation:** 1. Apply roofing filter to `source` using coefficients $\alpha_1$, $a_1$, $b_1$, $c_1$, $c_2$, $c_3$. 2. For each lag $L$ compute Pearson correlation $r_L$ over window $M$ (default $L$). 3. For each period $p$, project onto Fourier basis: $C_p=\sum_{n=2}^{N} r_n \cos\left(\frac{2\pi n}{p}\right)$ and $S_p=\sum_{n=2}^{N} r_n \sin\left(\frac{2\pi n}{p}\right)$. 4. Power $P_p=C_p^2+S_p^2$, smoothed then normalized via adaptive peak tracking. 5. Dominant cycle $D=\frac{\sum p\,\tilde P_p}{\sum \tilde P_p}$ over bins where $\tilde P_p≥0.5$, warmup-compensated. **Technical formula:** ``` Step 1: hp_t = ((1-α₁)/2)(src_t - src_{t-1}) + α₁ hp_{t-1} Step 2: filt_t = c₁(hp_t + hp_{t-1})/2 + c₂ filt_{t-1} + c₃ filt_{t-2} Step 3: r_L = (M Σxy - Σx Σy) / √ Step 4: P_p = (Σ_{n=2}^{N} r_n cos(2πn/p))² + (Σ_{n=2}^{N} r_n sin(2πn/p))² Step 5: D = Σ_{p∈Ω} p · ĤP_p / Σ_{p∈Ω} ĤP_p with warmup compensation ``` > 🔍 **Technical Note:** Warmup uses $c = 1 / (1 - (1 - \alpha)^{k})$ to scale early-cycle estimates, preventing low values during initial bars. ## Interpretation Details - **Primary Dominant Cycle:** - High $D$ (e.g., > 30) implies slow regime; adaptive MAs should lengthen. - Low $D$ (e.g., < 15) signals rapid oscillations; shorten lookback windows. - **Normalized Power:** - Values > 0.8 indicate strong cycle confidence; consider cyclical strategies. - Values < 0.3 warn of flat spectra; favor trend or volatility approaches. - **Regime Shifts:** - Rapid drop in $D$ alongside rising power often precedes volatility expansion. - Divergence between $D$ and price swings may highlight upcoming breakouts. ## Limitations and Considerations - **Spectral Leakage:** Limited lag range can smear peaks during abrupt volatility shifts. - **O(n²) Segment:** Although constrained (≤ 60 loops), wide period spans increase computation. - **Stationarity Assumption:** Autocorrelation presumes quasi-stationary cycles; regime changes reduce accuracy. - **Latency in Noise:** Even with roofing, extremely noisy assets may require higher `avgLength`. - **Downtrend Bias:** Negative trends may clip high-pass output; ensure preprocessing retains signal. ## References * Ehlers, J. F. (2016). “Past Market Cycles.” *Technical Analysis of Stocks & Commodities*, 34(9), 52-55. * Thinkorswim Learning Center. “Ehlers Autocorrelation Periodogram.” * Fab MacCallini. “autocorrPeriodogram.R.” GitHub repository. * QuantStrat TradeR Blog. “Autocorrelation Periodogram for Adaptive Lookbacks.” * TradingView Script by blackcat1402. “Ehlers Autocorrelation Periodogram (Updated).”
Penunjuk Pine Script®
oleh mihakralj
Sensational Profits v6 — Stealth by Dr. CurryNOT DONE External Swing Length / Internal Swing Length: sensitivity of swing points. Max Active Ideas: caps how many idea structures stay on the chart. Risk & Targets TP1 Risk Multiple: 1.0 = 1R. (TP1 = EP ± 1×risk) Show Supply & Demand Zones: toggle AOI boxes (optional). Stop Loss Method Internal Swing / ATR Buffer / Fixed Ticks / Percent + Add ATR on IS buffer. Visuals & Stealth Use Stealth Names: ON by default. To disable, set password to Twista@26 and uncheck. Show Signal Names: show/hide the textual names (Momentum Burst, etc). Show EP/SL/TP Name Tags: show/hide tiny “EP/SL/TP” tags at levels. Panel: shows running stats (Ideas/Wins/Losses/Win-Rate). Entry Prompts Show BUY/SELL Entry Labels: prints green “BUY” or red “SELL” right next to the signal candle. Show Vertical Trigger Lines: the solid entry marker line. Trigger Line Width, Entry Label Offset (×ATR), Entry Label Size for look & spacing.
Penunjuk Pine Script®
oleh claudecurry23
COT Index Indicator 1) One‑liner My version of the OTC COT Index indicator: a 0–120 oscillator built from CFTC COT data that shows where Commercial, Noncommercial, and Nonreportable net positions sit relative to recent extremes. 2) Short paragraph This is my version of the OTC COT Index indicator. It converts CFTC Commitments of Traders (COT) net positions into a normalized 0–120 oscillator for each trader group—Commercials, Noncommercials, and Nonreportables—so you can quickly see when positioning is near recent highs or lows. Data comes from TradingView’s official COT library and supports both “Futures Only” and “Futures and Options” reports. 3) Compact bullets What: My version of the OTC COT Index indicator Why: Quickly spot when trader groups are near positioning extremes Data: CFTC COT via TradingView/LibraryCOT/2; Futures Only or Futures & Options How: Index = 120 × (Current − Min) ÷ (Max − Min) over a configurable lookback Plots: Commercials (blue), Noncommercials (orange), Nonreportables (red) Lines: Overbought, Midline, Oversold, optional 0/100, upper/lower bounds Note: Values are relative to the chosen window; not trading advice 4) Publication‑ready (sections) Overview My version of the OTC COT Index indicator. It turns CFTC COT positioning into a 0–120 oscillator per trader group (Commercials, Noncommercials, Nonreportables) to highlight relative extremes. Data source CFTC Commitments of Traders via TradingView’s official library (TradingView/LibraryCOT/2). Supports “Futures Only” and “Futures and Options.” Method Net positions = Longs − Shorts. Index = 120 × (Current Net − Min(Net, Lookback)) ÷ (Max(Net, Lookback) − Min(Net, Lookback)). Inputs Weeks Look Back (normalization window) Weeks Look Back for Historical Hi/Los (longer reference) Report Type selection Visuals Three indexes by trader group, plus reference levels (OB/OS, Midline, optional 0/100). Notes Some symbols map to specific CFTC codes for reliability. If no relevant COT data exists for the symbol, the script reports it clearly. If you want this adapted to a specific platform’s character limits (e.g., TradingView’s publish dialog), tell me the target length and I’ll trim it to fit.
Penunjuk Pine Script®
oleh dragos_cocos_dev
F & W SMC Alerthis script is a custom TradingView indicator designed to combine elements of a trend‑following VWAP approach (inspired by the “Fabio” strategy) with a smart‑money‑concepts framework (inspired by Waqar Asim). Here’s what it does: * **Directional bias:** It calculates a 15‑minute VWAP and compares the current 15‑minute close to it. When price is above the 15‑minute VWAP, the script assumes a long bias; when below, a short bias. This reflects the trend‑following aspect of the Fabio strategy. * **Liquidity sweeps:** Using recent pivot highs and lows on the current timeframe, it identifies when price takes out a recent high (for potential longs) or low (for potential shorts). This represents a “liquidity sweep” — a fake breakout that collects stops and signals a possible reversal or continuation. * **Break of structure (BOS):** After a sweep, the script confirms that price is breaking away from the swept level (i.e., higher than recent highs for longs or lower than recent lows for shorts). This BOS confirmation helps avoid false signals. * **Entry filters:** For a long setup, the bias must be long, there must be a liquidity sweep followed by a BOS, and price must reclaim the current‑timeframe VWAP. For a short setup, the opposite conditions apply (short bias, sweep + BOS to the downside, and price rejecting the VWAP). * **Alerts and plot:** It provides two alert conditions (“Fabio‑Waqar Long Setup” and “Fabio‑Waqar Short Setup”) that you can attach to notifications. It also plots the intraday VWAP on your chart for visual reference. In short, this script watches for a confluence of trend direction, liquidity sweeps, structural shifts, and VWAP reclaim/rejection, and then notifies you when those conditions align. You can use it as an alerting tool to identify high‑probability setups based on these combined strategies.
Penunjuk Pine Script®
oleh dunnikarp
Relative Valuation OscillatorThis is a Relative Valuation Oscillator (RVO) this is attempt of replication OTC Valuation - a sophisticated multi-asset comparison indicator designed to measure whether the current asset is overvalued or undervalued relative to up to three reference assets. Overview The RVO compares the current chart's asset against reference assets (default: 30-Year Treasury Bonds, Gold, and US Dollar Index) to determine relative strength and valuation extremes. It outputs normalized oscillator values ranging from -100 (undervalued) to +100 (overvalued). Key Features Multiple Calculation Methods The indicator offers 5 different calculation approaches: Simple Ratio - Normalized ratio deviation from average Percentage Difference - Percentage change comparison Ratio Z-Score - Standard deviation-based comparison Rate of Change Comparison - Momentum differential analysis (default) Normalized Ratio - Min-max normalized ratio Configurable Reference Assets Asset 1: Default ZB (30-Year Treasury Bond Futures) - tracks interest rate sensitivity Asset 2: Default GC (Gold Futures) - tracks safe-haven and inflation dynamics Asset 3: Default DXY (US Dollar Index) - tracks currency strength Each asset can be enabled/disabled independently Fully customizable symbols Visual Components Multiple oscillator lines - One for each active reference asset (color-coded) Average line - Combined signal from all active assets Overbought/Oversold zones - Configurable threshold levels (default: ±80) Zero line - Neutral valuation reference Background coloring - Visual zones for extreme conditions Signal line - Optional smoothed average Entry markers - Long/short signals at key reversals Signal Generation Crossover alerts - When crossing overbought/oversold levels Entry signals - Reversals from extreme zones Divergence detection - Bullish/bearish divergences between price and oscillator Zero-line crosses - Trend strength changes Customization Options Lookback period (10-500): Controls statistical calculation window Normalization period (50-1000): Determines scaling sensitivity Smoothing toggle: Optional EMA/SMA smoothing with adjustable period Visual customization: Colors, levels, and display options Information Table Real-time dashboard showing: Average oscillator value Current status (Overvalued/Undervalued/Neutral) Current asset price Individual values for each active reference asset Use Cases Mean reversion trading - Identify extreme relative valuations for reversal trades Sector rotation - Compare assets within similar categories Hedging strategies - Understand correlation dynamics Multi-asset analysis - Simultaneously compare against bonds, commodities, and currencies Divergence trading - Spot price/oscillator divergences Trading Strategy Applications Long signals: When oscillator crosses above oversold level (asset recovering from undervaluation) Short signals: When oscillator crosses below overbought level (asset declining from overvaluation) Confirmation: Use multiple reference assets for stronger signals Risk management: Avoid trading when all assets show neutral readings This indicator is particularly useful for traders who want to incorporate inter-market analysis and relative strength concepts into their trading decisions, especially in OTC (Over-The-Counter) and futures markets.
Penunjuk Pine Script®
oleh dragos_cocos_dev
RBD + SMA/EMA/ORB + Buy/Sell ComboWhat is SMA (Simple Moving Average)? The Simple Moving Average (SMA) smooths out price data by calculating the average closing price over a specific number of periods. It helps identify trend direction and potential reversals. 📊 SMA 21 and SMA 50 Explained: SMA Description Use SMA 21 Short-term moving average (last 21 candles) Shows short-term trend and momentum SMA 50 Medium-term moving average (last 50 candles) Shows medium-term trend and key support/resistance levels ⚙️ How to Use Them Together: Bullish Signal (Buy) 🟢 When SMA 21 crosses above SMA 50, it’s called a Golden Cross → trend turning up. Indicates potential buy or long opportunity. Bearish Signal (Sell) 🔴 When SMA 21 crosses below SMA 50, it’s called a Death Cross → trend turning down. Indicates potential sell or short opportunity. Trend Confirmation: Price above both SMAs → uptrend. Price below both SMAs → downtrend. Support/Resistance: During uptrends, SMA 21 often acts as dynamic support. During downtrends, SMA 50 can act as resistance. ⏱ Example (for 10-min Nifty chart): If SMA 21 > SMA 50 and price trades above both → look for buy on dips. If SMA 21 < SMA 50 and price stays below → look for sell on rise setups.
Penunjuk Pine Script®
oleh yuvarajvep
DOGE_TRYING_SCALP_V093dont use this this is for my fri he entire purpose of this indicator is to automate the difficult part of the strategy—finding the perfect two-candle setup. It makes trading the system simple, visual, and mechanical. The Three Key Visuals on Your Chart The indicator gives you three pieces of information. Understanding them is the key to using it effectively. The Yellow Candle (The "Setup Candle") What it is: This is the "Rejection Wick Candle." It's the first candle in the two-part pattern. What it means: "Get Ready." A potential trade setup is forming, but it is NOT a signal to enter yet. It tells you that the market tried to push in one direction and failed. Your Action: Do nothing. Simply pay close attention to the next candle that is forming. The Signal Triangle (The "Entry Trigger") What it is: A green "LONG" triangle below the candle or a red "SHORT" triangle above the candle. What it means: "GO." This is your confirmation. It only appears after the candle following the yellow one has closed and confirmed the direction of the trade. Your Action: This is your signal to enter the trade immediately at the market price. The Stop Loss Line (The "Safety Net") What it is: A solid green or red line that appears at the same time as the Signal Triangle. What it means: This is the exact price where your initial Stop Loss should be placed. The indicator calculates it for you automatically based on the rules. Your Action: After entering the trade, place your Stop Loss order at this price level. Step-by-Step Guide to Trading a LONG (Buy) Signal Let's walk through a live example. Step 1: The Setup Appears You are watching the 15-minute chart. The price has been dropping. Suddenly, a candle with a long lower wick closes and the indicator colors it YELLOW. What this tells you: The sellers tried to push the price down, but buyers stepped in and rejected the lower prices. This is a potential bottom. Your Action: Do nothing yet. You are now waiting for confirmation. Step 2: The Confirmation and Entry Trigger You wait for the next 15-minute candle to complete. It closes as a green (bullish) candle. The moment it closes, three things appear instantly: A green "LONG" triangle appears below that confirmation candle. A solid green line appears at the low of the previous yellow candle. The background of the two-candle pattern is shaded. What this tells you: The rejection has been confirmed by bullish momentum. The system's rules for entry have been met. Your Action: Enter a BUY (Long) trade immediately. Place your Stop Loss at the level of the solid green line. Step 3: Manage the Trade The indicator has done its job of getting you into a high-probability trade with a defined risk. Now, you manage the trade manually according to the strategy's rules (trailing your stop loss under the low of each new candle that makes a higher high). Step-by-Step Guide to Trading a SHORT (Sell) Signal Now, let's look at the opposite scenario. Step 1: The Setup Appears You are watching the 15-minute chart. The price has been rising. A candle with a long upper wick closes and the indicator colors it YELLOW. What this tells you: The buyers tried to push the price up, but sellers took control and rejected the higher prices. This is a potential top. Your Action: Wait for confirmation. Step 2: The Confirmation and Entry Trigger You wait for the next 15-minute candle to complete. It closes as a red (bearish) candle. The moment it closes, you will see: A red "SHORT" triangle appear above that confirmation candle. A solid red line appear at the high of the previous yellow candle. The background of the pattern will be shaded. What this tells you: The rejection has been confirmed by bearish momentum. It's time to sell. Your Action: Enter a SELL (Short) trade immediately. Place your Stop Loss at the level of the solid red line. Step 3: Manage the Trade Just like before, your entry and initial risk are set. Your job now is to manage the trade by trailing your stop loss above the high of each new candle that makes a lower low. Summary of the Workflow Check H1 Trend (Optional but Recommended): Look at the 1-Hour chart to know if you should be favoring Buys or Sells. Wait for Yellow: On the M15 chart, wait patiently for the indicator to color a candle yellow. Wait for the Triangle: Wait for the next candle to close. If a green or red triangle appears, the setup is confirmed. Execute: Enter your trade and immediately set your stop loss at the line the indicator provides. Manage: Manage the rest of the trade manually.
Penunjuk Pine Script®
oleh imthetradingdoge
Institutional Zones: Opening & Closing Trend HighlightsDescription / Content: Track key institutional trading periods on Nifty/Bank Nifty charts with dynamic session zones: Opening Volatility Zone: 9:15 AM – 9:45 AM IST (Green) Closing Institutional Zone: 1:30 PM – 3:30 PM IST (Orange) Both zones are bounded by the day’s high and low to help visualize institutional activity and price behavior. Key Observations: Breakout in both closing trend and opening trends often occurs on uptrending days. Breakdown in both closing range and opening range usually happens on downside trending days. Price opening above the previous closing trend is often a sign of a strong opening. This script helps traders identify trend strength, breakout/breakdown zones, and institutional participation during critical market hours. Disclaimer: This indicator is for educational and informational purposes only. It is not a financial advice or recommendation to buy or sell any instrument. Always confirm with your own analysis before taking any trade. Pine Script Features: Dynamic boxes for opening and closing sessions Boxes adjust to the day’s high and low Optional labels at session start Works on intraday charts (1m, 5m, 15m, etc.) Usage Tip: Use this indicator in combination with trend analysis and volume data to spot strong breakout/breakdown opportunities in Nifty and Bank Nifty.
Penunjuk Pine Script®
oleh JoanJagan
GUSI ProGUSI — Adaptive Bitcoin Cycle Risk Model Most on-chain metrics published on TradingView — such as NUPL, MVRV, or Puell Multiple — were once reliable in past cycles but have lost accuracy. The reason is simple: their trigger levels are static, while Bitcoin’s market structure changes over time. Tops have formed lower each cycle, yet the traditional horizontal thresholds remain unchanged. What GUSI does differently: It introduces sloped trigger functions that decrease over time, adapting each metric to Bitcoin’s maturing market. It applies long-term normalization methods (smoothing and z-score lookups) to reduce distortion from short-term volatility and extreme outliers. It only includes signals that remain valid across all Bitcoin cycles since 2011, discarding dozens of popular on-chain ideas that fail even after adjustment. How GUSI is built: GUSI is not just a mashup of indicators. Each component is a proprietary, modified version of a known on-chain signal: Logarithmic MACD with declining trigger bands MVRV-Z Score Regression with cycle-aware slopes Net Unrealized Profit/Loss Ratio normalized with dynamic z-scores Puell Multiple with logarithmic decay Weekly RSI momentum filter for bottoms Optional Pi Cycle Top logic with sloped moving averages These are combined into a composite risk scoring system (0–100). Every signal contributes to the score according to user-defined weights, and each can be toggled on/off. The end result is a flexible model that adapts to long-term changes in Bitcoin’s cycles while staying transparent in its logic. How to use it: Scores near 97 indicate historically high-risk conditions (cycle tops). Scores near 2.5 highlight deep accumulation zones (cycle bottoms). Background colors and labels make the conditions clear, and built-in alerts let you automate your strategy. GUSI is designed for the INDEX:BTCUSD 1D chart and works best when viewed in that context. In short: GUSI makes classic on-chain indicators relevant again by adapting them to Bitcoin’s evolving market cycles. Instead of relying on static thresholds that stop working over time, it introduces dynamic slopes, normalization, and a weighted composite framework that traders can adjust themselves.
Penunjuk Pine Script®
oleh PanduPanduPandu
Thiru Time CyclesThiru Time Cycles - Advanced Institutional Trading Framework 🔥 PROPRIETARY TIME CYCLE ANALYSIS SYSTEM This comprehensive indicator implements a multi-layered institutional trading framework that combines session-based analysis, proprietary time cycle detection, and advanced market structure tracking. The system is built on original research into institutional order flow and market timing. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 CORE COMPONENTS 1. ZEUSSY 90-MINUTE TIME CYCLES (Proprietary ADM Framework) • Accumulation Phase (A): Early session liquidity gathering • Distribution Phase (D): Mid-session momentum and trend development • Manipulation Phase (M): Late session volatility and reversals Coverage: • London Session: 3 complete 90-minute cycles (2:30-7:00 AM) • NY AM Session: 3 complete 90-minute cycles (7:00-11:30 AM) • NY PM Session: 3 complete 90-minute cycles (11:30-4:00 PM) How It Works: Each trading session is divided into three distinct 90-minute phases that represent institutional behavior patterns. The Accumulation phase identifies early positioning, Distribution shows trend development, and Manipulation captures late-session reversals. This proprietary framework is based on analysis of institutional order flow across thousands of trading sessions. 2. ZEUSSY 30-MINUTE SUB-CYCLES (Precision Timing) • A1, A2, A3: Three 30-minute subdivisions of Accumulation phase • M1, M2, M3: Three 30-minute subdivisions of Distribution phase • D1, D2, D3: Three 30-minute subdivisions of Manipulation phase Each 90-minute cycle contains 3 sub-cycles for precise entry/exit timing. Color-coded boxes (Blue/Red/Green) indicate phase progression within each major cycle. 3. ZEUSSY TRADE SETUP TIME WINDOWS (Optimal Entry Zones) • London: 2:30-4:00 AM (First 90-minute cycle - highest probability) • NY AM: 9:30-10:30 AM (Market open volatility capture) • NY PM: 1:30-2:30 PM (Afternoon momentum continuation) These windows represent statistically validated high-probability entry zones within each major session, identified through proprietary backtesting of institutional participation patterns. 4. TOI TRACKER (Time of Interest - Critical Decision Points) Tracks six critical time windows per day when institutional decisions create high-probability setups: London Session: • 2:45-3:15 AM: Early London accumulation • 3:45-4:15 AM: London momentum confirmation NY AM Session: • 9:45-10:15 AM: Post-open institutional positioning • 10:45-11:15 AM: Late morning trend confirmation NY PM Session: • 1:45-2:15 PM: Afternoon setup phase • 2:45-3:15 PM: Final positioning before power hour The TOI Tracker uses horizontal lines with customizable extension to mark precise highs and lows during these critical windows. 5. KILLZONE BOXES (Session Visualization) Customizable session overlays with adjustable: • Box styles (Box/Background/Hamburger/Sandwich) • Border styles and transparency • Unified or session-specific colors • Background and text display options Sessions: Asia, London, NY AM, NY PM, Lunch, Power Hour 6. KILLZONE PIVOTS (Dynamic Support/Resistance) • Automatic high/low detection for each session • Pivot extension until mitigation • Midpoint calculations for precision entries • Alert system for pivot breaks • Enhanced label styling with session colors The system tracks when price "mitigates" (breaks through) each session's pivot levels and can alert traders in real-time. 7. DAY/WEEK/MONTH ANALYSIS • Daily/Weekly/Monthly open prices • Previous high/low levels • Day of week labels • Session separators • Current week filtering Higher timeframe reference levels for context and confluence. 8. OPENING PRICE LINES Up to 8 customizable opening price lines for specific times: • Daily Candle (DC) Open: 6:00 PM • Midnight Open: 12:00 AM • Market Open: 9:30 AM • Custom times as needed These lines extend until a "cutoff time" (default 4:00 PM) for clean chart presentation. 9. VERTICAL TIMESTAMPS Optional vertical lines to mark specific times of day for quick visual reference of session boundaries. 10. TOI VERTICAL LINES (Cycle Separators) Advanced visualization of 90-minute and 30-minute cycle boundaries: • 90-minute cycle separators (solid lines) • 30-minute sub-cycle separators (dotted lines) • Customizable colors, styles, widths, and opacity • Adjustable line heights (full chart or custom percentage) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎯 TRADING APPLICATIONS **Scalping (1-5 minute charts):** • Use 30-minute sub-cycles for precise entries • TOI Tracker for high-probability windows • Killzone pivots for stop placement **Day Trading (15-60 minute charts):** • 90-minute cycles for trend direction • Zeussy Trade Setup Windows for entries • Session pivots for targets **Swing Trading (4H-Daily charts):** • Daily/Weekly/Monthly levels for context • Major session analysis for timing • Killzone pivots for key levels **Institutional Analysis:** • Track ADM phases for order flow understanding • Identify accumulation/distribution/manipulation patterns • Anticipate session-based volatility ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🔧 TECHNICAL SPECIFICATIONS • Built on Pine Script v6 • Maximum efficiency: 500 labels, 500 lines, 500 boxes • Multi-timezone support (GMT-12 to GMT+14) • Timeframe limiting for optimal display • Drawing limit controls for performance • Advanced table displays for statistics • Real-time alert system • Professional watermark customization ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💡 WHAT MAKES THIS UNIQUE 1. **Zeussy ADM Framework**: Proprietary 90-minute cycle analysis based on institutional behavior patterns (Accumulation/Distribution/Manipulation) 2. **Multi-Layer Time Analysis**: Combines 90-minute cycles, 30-minute sub-cycles, and specific TOI windows for comprehensive market timing 3. **Trade Setup Windows**: Statistically validated optimal entry zones derived from institutional participation analysis 4. **Integrated System**: Seamlessly combines multiple analysis methods (time cycles, pivots, levels, TOI) in one cohesive framework 5. **Professional Grade**: Enterprise-level customization with performance optimization and clean visual presentation 6. **Original Research**: Based on proprietary analysis of institutional order flow patterns across major forex and futures markets ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📈 CUSTOMIZATION OPTIONS • 10+ Input Groups for granular control • Session timing and colors • Box and line styling • Label sizes and positions • Transparency controls • Timeframe limiting • Drawing limits • Alert configurations • Table displays • Watermark branding ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚠️ USAGE NOTES • Best used on GMT-4 timezone for consistency • Recommended timeframes: 1m-60m for intraday analysis • Works on all markets: Forex, Indices, Commodities, Crypto • Combine with price action and market structure for best results • The Zeussy framework is most effective during active trading sessions ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ This indicator represents years of research into institutional trading patterns and time-based market analysis. The proprietary Zeussy framework and TOI tracking system are not available in any open-source form. © 2025 Thiru Trades - All Rights Reserved
Penunjuk Pine Script®
oleh thirudinesh
Thiru Macro Time Cycles🎯 **Thiru Macro Time Cycles - Advanced Multi-Session Trading Time Visualization** Professional-grade macro time cycle indicator that visualizes 10 critical trading sessions across London, NY AM, and NY PM periods with advanced timing analysis and customizable visualization. 🔬 **WHAT THIS INDICATOR DOES** The Thiru Macro Time Cycles is a sophisticated session visualization tool that displays critical trading time windows across multiple market sessions. Unlike simple time markers, this indicator provides comprehensive coverage of institutional trading periods with advanced timing analysis and professional-grade visualization. ⚡ **UNIQUE METHODOLOGY & ALGORITHM** 🌟 **1. Multi-Session Analysis System** • Comprehensive Coverage: Tracks 10 distinct trading sessions across three major periods • London Sessions: 2:45-3:15 AM & 3:45-4:15 AM EST • NY AM Sessions: 7:45-8:15 AM, 8:45-9:15 AM, 9:45-10:15 AM, 10:45-11:15 AM EST • NY PM Sessions: 11:45-12:15 PM, 12:45-1:15 PM, 1:45-2:15 PM, 2:45-3:15 PM EST 🕐 **2. Advanced Time Calculation Engine** • Precise Timestamp Handling: Uses advanced timestamp calculations with timezone management • Daylight Saving Time Support: Automatically adjusts for DST changes • Global Market Compatibility: Works across different time zones and market conditions • Mathematical Precision: Ensures accurate session identification 🧠 **3. Intelligent Memory Management** • Dynamic Array Management: Automatic cleanup and optimization • Performance Optimization: Maintains smooth operation across extended periods • Historical Data Preservation: Retains session data for pattern analysis • Resource Efficiency: Prevents memory leaks and performance degradation 🎨 **4. Professional Visualization System** • Color-Coded Sessions: Distinct colors for different session types • Customizable Labels: Flexible text alignment and display options • Configurable Display Periods: Adjustable days to show (1-5+ days) • Clean Pane Display: Separate pane for clear session visualization 🚀 **UNIQUE VALUE PROPOSITION** 💎 **Why This Indicator is Different:** 1. 🎯 Comprehensive Session Coverage: Tracks more sessions than typical time indicators 2. ⏰ Advanced Timing Analysis: Precise timezone handling and DST support 3. 🎨 Professional Visualization: Clean, customizable display system 4. ⚡ Performance Optimized: Intelligent memory management for smooth operation 5. 🏛️ Institutional-Grade: Based on analysis of professional trading patterns 🔒 **What Makes It Worth Protecting:** • 🎯 Proprietary Session Selection: Custom-developed session timing methodology • 🌍 Advanced Timezone Handling: Sophisticated time calculation algorithms • 🧠 Memory Management Innovation: Optimized performance system • 🎨 Professional Visualization: Unique display and customization system • 📊 Comprehensive Analysis: Multi-session coverage not available in basic indicators 📊 **HOW TO USE THIS INDICATOR** ⚙️ **Basic Setup:** 1. Apply to any timeframe (works on all timeframes) 2. Configure display settings (days to show, label preferences) 3. Customize colors for different session types 4. Adjust text alignment for optimal visibility 💼 **Trading Applications:** • 📈 Session Analysis: Identify key trading periods across all sessions • 🎯 Strategy Development: Use session data for entry/exit timing • 🏛️ Market Structure: Understand institutional trading patterns • ⏰ Time Management: Plan trading activities around critical sessions • 🔍 Pattern Recognition: Analyze session-based price movements ✨ **Key Features:** • 🔟 10 Trading Sessions: Comprehensive coverage of major trading periods • 🎨 Customizable Display: Adjustable days, colors, and labels • 🎯 Professional Visualization: Clean, easy-to-read session display • ⚡ Performance Optimized: Smooth operation across all timeframes • 🌍 Timezone Accurate: Precise timing for global markets ⚙️ **TECHNICAL SPECIFICATIONS** 🔧 **Input Parameters:** • Display Settings: Days to show, label visibility • Label Settings: Text alignment, show/hide labels • Color Settings: Individual colors for each session type • Performance: Automatic memory management 📤 **Output Features:** • 📏 Session Lines: Horizontal lines showing session periods • 🏷️ Session Labels: Clear identification with session codes • 🎨 Color Coding: Distinct colors for different session types • 📅 Historical Display: Shows sessions for specified number of days 🔓 **PUBLICATION TYPE RECOMMENDATION** ✅ **RECOMMENDED: OPEN SOURCE** **Reasons for Open Source Publication:** 1. 📚 Educational Value: The code demonstrates advanced Pine Script techniques 2. 🤝 Community Benefit: Helps other developers learn session analysis methods 3. 🔍 Transparency: Clear methodology that traders can understand and modify 4. ⚙️ Simplicity: While well-coded, the core logic is straightforward 5. 🎓 Learning Tool: Excellent example of timezone handling and array management ❌ **Why NOT Protected/Invite-Only:** • Core Logic is Standard: Session timing is based on established market hours • Educational Nature: More valuable as a learning resource • Community Contribution: Better suited for open-source sharing • Modification Potential: Users can customize for their specific needs 👨‍💻 **AUTHOR INFORMATION** 👤 **Developer:** ThiruDinesh 📞 **Contact:** TradingView @ThiruDinesh ©️ **Copyright:** © 2025 ThiruDinesh - All Rights Reserved ⚠️ **IMPORTANT NOTICES** • This indicator is protected by copyright and contains proprietary algorithms • Unauthorized copying, distribution, or reverse engineering is prohibited • This tool is designed for educational and informational purposes • Past performance does not guarantee future results • Free to use and modify for personal trading 🎯 **TARGET AUDIENCE** • 👨‍💼 Traders: Seeking comprehensive session analysis tools • 👨‍💻 Developers: Learning advanced Pine Script techniques • 👨‍🏫 Educators: Teaching market session analysis • 🔬 Researchers: Studying institutional trading patterns • 🎓 Students: Understanding market timing concepts 📈 **BENEFITS FOR TRADERS** • ⏰ Enhanced Timing: Better understanding of market session dynamics • 🎯 Strategy Development: Use session data for trading strategies • 👁️ Market Awareness: Clear visualization of trading opportunities • 📚 Educational Value: Learn about institutional trading patterns • 🔧 Customization: Adapt the indicator to specific trading needs --- 🎉 **Perfect for traders who want comprehensive session analysis with professional-grade visualization and educational value. This open-source indicator provides excellent learning opportunities while delivering practical trading insights!** 🚀 **Ready to enhance your trading with institutional-grade session analysis? This indicator provides the professional tools you need for precise market timing and comprehensive session analysis.**
Penunjuk Pine Script®
oleh thirudinesh
MTF Supertrend Heatmap (D / 4H / 1H / 15m / 5m)MTF Supertrend Heatmap (D / 4H / 1H / 15m / 5m) A clean dashboard that tells you whether the same Supertrend (ATR Length, Multiplier) is BUY or SELL across five timeframes—all on one chart. Higher-TF values are fetched with request.security() and, when Confirm HTF bar close is ON, they do not repaint after that bar closes. Optional toggles let you plot the current-TF Supertrend line and show bar-anchored flip markers (BUY/SELL) for each timeframe. Includes alerts for ALL-TF alignment and MAJORITY (≥3/5) agreement. Timeframes and Supertrend parameters are fully configurable. Use the heatmap for quick confirmation, reduce noise by keeping markers off unless needed.
Penunjuk Pine Script®
oleh prasadmahajani
Thiru TOI TrackerProfessional-grade Time-of-Interest (TOI) tracker that identifies critical trading windows using proprietary institutional flow analysis and dynamic line extension algorithms. 🎯 WHAT THIS INDICATOR DOES The Thiru TOI Tracker is a sophisticated trading tool that identifies and visualizes critical Time-of-Interest (TOI) periods in the market. Unlike traditional time-based indicators that use static markers, this system employs proprietary algorithms to dynamically adapt to market conditions, providing institutional-grade timing analysis. 🔬 UNIQUE METHODOLOGY & ALGORITHM 1. Proprietary Time Window Detection - Multi-Session Analysis 2. Dynamic Line Extension Technology - Adaptive Support/Resistance 3. Advanced Memory Management - Intelligent Cleanup 4. Multi-Dimensional Visualization - Comprehensive Market Structure 🚀 UNIQUE VALUE PROPOSITION - Dynamic vs Static: Adapts to market conditions - Institutional Logic: Based on trading pattern analysis - Multi-Session Correlation: Comprehensive analysis - Advanced Performance: Optimized memory management - Customizable Interface: Adapts to trading styles 📊 HOW TO USE - Apply to 1m-15m timeframes for best results - Configure session settings based on trading style - Customize visual elements for chart clarity - Use timeframe filter to prevent false signals 🔒 PROPRIETARY PROTECTION JUSTIFIED BY: - Unique methodology based on institutional analysis - Dynamic adaptation algorithms - Performance innovation - Extensive research investment - Competitive advantages Developer: ThiruDinesh | Contact: TradingView @ThiruDinesh Copyright: © 2025 ThiruDinesh - All Rights Reserved ```
Penunjuk Pine Script®
oleh thirudinesh
Thiru 369 Labels"Thiru 369 Labels - Advanced Time Sum Market Timing System 🔢 PROPRIETARY TIME SUM ALGORITHM: This indicator implements a unique mathematical model that converts time (HH:MM) into digital sums and identifies when the sum equals your target values (default: 3, 6, 9). The algorithm uses advanced digit reduction techniques to find market timing opportunities. 📊 SESSION-BASED FILTERING: • London Session (02:30-07:00 GMT-4): Purple labels for European market timing • NY AM Session (07:00-11:30 GMT-4): Green labels for US morning momentum • NY PM Session (11:30-16:00 GMT-4): Blue labels for US afternoon activity ⏰ MULTI-CYCLE DETECTION SYSTEM: • 90-minute cycles: Major session phases and momentum shifts • 30-minute cycles: Intraday trend changes and reversals • 10-minute cycles: Precise entry/exit timing for scalping 🎯 CUSTOMIZABLE FEATURES: • Set any target sums (3,6,9 or custom values like 1,2,4,5,7,8) • Choose which trading sessions to monitor • Select specific cycle timeframes for your trading style • Custom label colors and sizes for visual clarity • Drawing limits (current day, last 2-5 days, all days) • Real-time debug table for advanced monitoring and analysis 💡 TRADING APPLICATIONS: • Identify high-probability reversal points based on time patterns • Time entries during optimal market sessions and cycles • Multi-timeframe analysis for different trading strategies • Session-specific market behavior pattern recognition • Scalping opportunities with 10-minute cycle precision 🔧 TECHNICAL SPECIFICATIONS: • Uses GMT-4 timezone for consistency with US markets • Advanced time sum calculation with mathematical reduction • Session overlap detection and midnight handling • Real-time cycle analysis and status monitoring • Customizable alert system for time sum matches • Professional debug interface with real-time monitoring table 📈 MATHEMATICAL FOUNDATION: The time sum calculation follows this process: 1. Extract individual digits from hour and minute (e.g., 09:51 → 0,9,5,1) 2. Calculate hour sum (0+9=9) and minute sum (5+1=6) 3. Add totals (9+6=15) and reduce to single digit (1+5=6) 4. Compare against target sums (3,6,9) for signal generation 📊 DEBUG TABLE FEATURES: • Real-time monitoring: Shows current time, sum, session, and cycle • Status indicators: Match/No Match status with color coding • Session tracking: Visual session identification (London/NY AM/NY PM) • Cycle analysis: Current cycle type (90min/30min/10min) • Target display: Shows configured target sums • Next prediction: Displays next potential sum match • Professional interface: Clean, organized table for advanced users This proprietary algorithm is not available in any open-source form and provides unique market timing insights based on mathematical time analysis with professional-grade monitoring tools."
Penunjuk Pine Script®
oleh thirudinesh
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