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Market Clarity Index (MCI) — ProThe MCI Pro++ expands on the Lite version with deeper controls, higher-timeframe blending, slope analysis, and clarity ranking. It captures the balance between trend coherence vs. noise using entropy, drift, and volume dynamics mapped through a φ²-based sigmoid. Key Features: Fully adjustable weights (drift, volume shocks, entropy) Higher-timeframe blending with adjustable weighting Clarity slope + histogram for momentum tracking Range rank (0–100) to spot relative extremes Bull/Bear markers + HTF alignment markers Optional status table with live clarity state Trading Logic: ✅ High-clarity regime when MCI > high threshold ❌ Low-clarity regime when MCI < low threshold Neutral otherwise; use slope, HTF alignment, and range rank as context filters. ⚠️ Invite-Only Access: This Pro version is available by subscription through SnapfrontTech.
Pine Script® 인디케이터
SnapfrontTech의
SCI - Snapfront Coherence IndicatorThe SMCI is an advanced, invite-only indicator designed to measure market coherence, volatility regimes, and trend stability. It combines entropy-based features, φ-cycle phase drivers, and custom exposure scaling into a single probabilistic framework. Core outputs: 📈 I_hat (probability of upward drift) — coherence-weighted probability score. 📊 Exposure (scaled proxy) — dynamic sizing aligned with volatility and drawdown control. 💰 Equity curve (proxy) — running performance simulation. 🔎 WCTφ + dWCTφ — entropy-based coherence metrics. ⚠️ Regime detection — classifies conditions as Trend / Chop / Panic. Signal Logic: ✅ Long bias when I_hat crosses above 0.5. ❌ Short bias when I_hat crosses below 0.5. HUD overlay shows live coherence stats, exposure, and regime classification. ⚠️ Invite-Only Notice: This script is restricted to approved users. Access requires subscription from Snapfront Technologies. snapjames.gumroad.com 📌 Disclaimer: For educational use only. This is not financial advice and should not be considered a trading recommendation.
Pine Script® 인디케이터
SnapfrontTech의
Snapfront Market Clarity Index (MCI) — LiteMarket Clarity Index (MCI) — Lite + Signals The Market Clarity Index (MCI) measures trend clarity vs. noise using returns, drift, and volume shock dynamics. Values are normalized through a φ²-based sigmoid for smooth, interpretable signals. Features: Clear 0–100 scale (Lite version) Heatmap background for clarity regimes Bull/Bear signal arrows with EMA filter High/Low threshold lines for easy context Trading Logic: ✅ Bull signal when MCI crosses into the high zone with price above EMA ❌ Bear signal when MCI crosses into the low zone with price below EMA Use MCI as a trend filter, entry trigger, or market condition gauge across any timeframe or asset.
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SnapfrontTech의
Multi Time Frame RSI [Horizonn Wealth]Multi-Time Frame Analysis: A key feature is the ability to choose a time frame for each of the four RSI lines from a predefined list (Chart, 1 day, 1 week, 1 month). The script uses the request.security() function with lookahead enabled to ensure the most accurate, real-time data is used for each calculation, eliminating look-ahead bias and calculation errors. Visual Levels: The indicator plots standard RSI levels at 30, 50, and 70, with a shaded background between the oversold (30) and overbought (70) zones to provide a clear visual reference. Momentum Alignment Signals: The script includes an optional feature that highlights the chart's background with a red or green color when all four RSIs simultaneously enter an overbought or oversold state. This serves as an immediate visual alert for a strong, multi-time frame momentum condition. This indicator is a robust tool for technical analysis, suitable for traders who use a top-down approach to their market analysis.
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HorizonnWealth의
FlowFusion Money Flow — FP + VWAP Drift + PVT (−100..+100)Title (ASCII only) FlowFusion Money Flow — Flow Pressure + Rolling VWAP Drift + PVT (Normalized −100..+100) Short Description Original money-flow oscillator combining Flow Pressure, Rolling VWAP Drift, and PVT Momentum into one normalized score (−100..+100) with a signal line, thresholds, optional component plots, and ready-made alerts. Full Description (meets “originality & usefulness”) What’s original FlowFusion Money Flow is not a generic mashup. It builds a single score from three complementary, volume-aware components that target different facets of order flow: Flow Pressure (FP) — In-bar directional drive scaled by relative volume. Drive = close − open max ⁡ ( high − low ,  tick ) ∈ = max(high−low, tick) close−open ​ ∈ . Relative Volume = volume average volume over  𝑓 𝑝 𝐿 𝑒 𝑛 = average volume over fpLen volume ​ . 𝐹 𝑃 𝑟 𝑎 𝑤 = Drive × RelVol FP raw ​ =Drive×RelVol then squashed (softsign) to . Why it belongs: distinguishes real pushes (big body and big volume) from noise. Rolling VWAP Drift — Direction of VWAP itself over a rolling window, normalized by ATR. 𝑉 𝑊 𝐴 𝑃 𝑡 = ∑ ( 𝑇 𝑃 × 𝑉 𝑜 𝑙 ) ∑ 𝑉 𝑜 𝑙 VWAP t ​ = ∑Vol ∑(TP×Vol) ​ over vwapLen. Drift = 𝑉 𝑊 𝐴 𝑃 𝑡 − 𝑉 𝑊 𝐴 𝑃 𝑡 − 1 𝐴 𝑇 𝑅 = ATR VWAP t ​ −VWAP t−1 ​ ​ → squashed to . Why it belongs: persistent VWAP movement signals sustained accumulation/distribution. PVT Momentum — Price-Volume Trend standardized (z-score) and squashed. 𝑃 𝑉 𝑇 𝑡 = 𝑃 𝑉 𝑇 𝑡 − 1 + 𝑉 𝑜 𝑙 × Δ 𝐶 𝑙 𝑜 𝑠 𝑒 𝐶 𝑙 𝑜 𝑠 𝑒 𝑡 − 1 PVT t ​ =PVT t−1 ​ +Vol× Close t−1 ​ ΔClose ​ . 𝑧 = 𝑃 𝑉 𝑇 − SMA ( 𝑃 𝑉 𝑇 ) StDev ( 𝑃 𝑉 𝑇 ) z= StDev(PVT) PVT−SMA(PVT) ​ → squashed to . Why it belongs: captures volume-weighted trend pressure without relying on price alone. Composite score: Score = 𝑤 𝐹 𝑃 ⋅ 𝐹 𝑃 + 𝑤 𝑉 𝑊 𝐴 𝑃 ⋅ 𝑉 𝑊 𝐴 𝑃 _ 𝐷 𝑟 𝑖 𝑓 𝑡 + 𝑤 𝑃 𝑉 𝑇 ⋅ 𝑃 𝑉 𝑇 _ 𝑀 𝑜 𝑚 𝑤 𝐹 𝑃 + 𝑤 𝑉 𝑊 𝐴 𝑃 + 𝑤 𝑃 𝑉 𝑇 Score= w FP ​ +w VWAP ​ +w PVT ​ w FP ​ ⋅FP+w VWAP ​ ⋅VWAP_Drift+w PVT ​ ⋅PVT_Mom ​ with a Signal = SMA(Score, sigLen). Thresholds mark strong accumulation/distribution zones. How it works (step-by-step) Compute FP, VWAP Drift, PVT Momentum. Normalize each to the same scale. Weighted average → FlowFusion Score. Smooth with a Signal line to reduce whipsaw. Optional background shading when Score exceeds thresholds. How to use Direction filter: Score > 0 favors longs; Score < 0 favors shorts. Momentum turns: Score crosses above Signal → setup for long; below → setup for short. Strength zones: Above Upper Threshold (default +40) = strong buy pressure; below Lower (−40) = strong sell pressure. Confluence: Best near S/R, trendlines, or HTF bias. For scalping on 1–5m, consider sigLen 9–13 and thresholds ±40 to ±50. Alerts included: zero cross, zone entries, and Score/Signal crossovers. Inputs (key) fpLen (20): relative-volume lookback for Flow Pressure. vwapLen (34): rolling VWAP window. pvtLen (50): PVT z-score window. sigLen (9): Signal smoothing. Weights: wFP, wVWAP, wPVT to bias the blend. Thresholds: upperBand / lowerBand (defaults +40/−40). Display: toggle component plots and background shading. Best practices Trending markets: increase wVWAP (VWAP Drift) or widen thresholds. Ranging markets: increase wFP and wPVT; take quicker profits. News: wait for bar close confirmation or reduce size. Data quality: use consistent volume feeds (especially in crypto). Limitations Oscillators can stay extreme in strong trends; use structure/trend filters. Volume anomalies (illiquid pairs, API glitches) can distort signals—sanity-check with another venue when possible. Disclaimer This indicator is for educational purposes only and is not financial advice. Trading involves risk; past performance does not guarantee future results. Always paper-trade first and use appropriate risk controls.
Pine Script® 인디케이터
fts4sure의
MACD_magistraturaCustom Indicator "MACD Magistratura" — Precision in Momentum, Clarity in Structure 🔹 Why trade with outdated MACD settings? — Classic MACD is useful, but limited: → One timeframe, one signal, one view, → Often noisy, lagging, and hard to contextualize. — Most traders use it blind — without knowing when it works, and when it misleads. 🔹 What is MACD Magistratura? — A custom-built evolution of the classic MACD, — Engineered for multi-timeframe clarity, — Designed to show not just momentum — but its hierarchy across timeframes. 🔹 Key advantages: ✅ No more clutter — one indicator replaces 2+ classic MACDs, ✅ No repaint — values are stable, based on closed candles, ✅ Clear divergence detection — compare price vs. multi-TF MACD perpendicularly, ✅ Perfect for trend confirmation — especially when combined with SMA Magistratura.
Pine Script® 인디케이터
NZ_27의
RSI_magistratura⚜️ Custom Indicator "RSI_Magistratura" — Combining the Best Oscillators in One Tool 🔹 What we’re learning: — The difference between classic oscillators (MACD, RSI, Stochastic) and our custom RSI Magistratura indicator, — Why using three indicators is inefficient, — How one single tool can replace an entire arsenal. 🔹 Classic indicators: what do they show? — MACD — convergence/divergence of moving averages, — RSI — relative strength of price movement, — Stochastic — price level within the current range. 📌 Common features: → All three show similar dynamics: Smoothed lines, Divergences, Crossovers. → But each has its own nuances. 🔹 Why do traders combine them? — Some use: MACD + Stochastic → to confirm signals, RSI + Stochastic → to assess overbought/oversold conditions, Or all three at once — to "not miss" a signal. 📌 The problem: — The more indicators you add — the more noise you get, — Less space left for the actual price chart, — Decisions become emotional, not systematic. 🔹 How many indicators are needed? — Just for trend analysis: → 3–4 Moving Averages (SMA), — Plus 3 oscillators: MACD, RSI, Stochastic, → Total: 7 indicators. 📌 This clutters the chart and makes it hard to see the real picture. And it often requires a paid TradingView subscription. 🔹 How did we solve this? — We created the custom RSI Magistratura indicator, — It combines: Key features of MACD, RSI, and Stochastic, Data from all timeframes in one place. 🔹 Advantage #1: Color-coded system — Colors match those in SMA Magistratura: 1 hour — purple, 4 hours — black/white, 1 day — aqua, 1 week — peach, 1 month — maroon, 3 months — brown. → Easy to remember, easy to navigate. 🔹 Advantage #2: Universality — On any timeframe, you see: Current, Higher, And up to 5 higher timeframes. → For example: on 15-minute chart — you see 1H, 4H, 1D, → On 1H — you see 4H, 1D, 1W, → No need to switch between multiple indicators. 🔹 Advantage #3: Precision and speed — You see simultaneously: Short-term fluctuations, Mid-term trends, Long-term context, → Without switching charts or timeframes. 🔹 Example: RSI across timeframes — On Daily — RSI moves slowly, — On 4H — faster, — On 1H — even more responsive, → But crossovers and divergences remain consistent — just scaled. 📌 Important: — You don’t need all timeframes at once, — Enough to track: current, senior, and next one, → This is the perfect balance between information and clarity. 🔹 Conclusion: — Classic indicators are good — but inefficient when used in bulk, — The RSI Magistratura is: A system, not a toolkit, Simplification, not clutter, Quality analysis, not guesswork. 💡 Use it — and you’ll see the market clearer, make decisions with more confidence.
Pine Script® 인디케이터
NZ_27의
RSI Plus – Divergence + EMA/WMARSI Plus – Divergence + EMA/WMA This is an advanced RSI indicator designed for traders who want to maximize the power of RSI. Beyond the standard RSI plot, this tool adds extra features to help analyze trends and identify better entry signals. Key Features: Standard RSI with highlighted zones (20–30, 30–40, 40–60, 60–70, 70–80) Multiple smoothing options: SMA, EMA, SMMA, WMA, VWMA Bullish/Bearish divergence detection with labels and alerts WMA(45) on RSI for mid-term trend confirmation EMA vs WMA45 color-fill (green for bullish, red for bearish) Multi-timeframe support (Daily, H4, H1) How to use: Spot potential reversals with RSI divergence Confirm trend direction when RSI EMA > WMA45 (bullish) or EMA < WMA45 (bearish)
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phamhaihoclt의
1
Nearest Rank For Loop - [JTCAPITAL]Nearest Rank For Loop is used for trend-following using the median of the data. The indicator works by calculating in the following steps: 1. The median is calculated using the ranking length of the source and using "percentile nearest rank" to determine the middle value. This is done with the original length and the length devided by 3, averaged out to eliminate false signals from extremely fast and temporary market movements. 2. Over the length of the loop values get added based on the median being higher than the previous median. 3. The results of the for loop segment get smoothed out using an EMA. --Buy and sell conditions-- -When the for loop values get above the long threshold we enter a buying condition, we dont exit the buying condition until the for loop values get below the short condition. Which signals a short. -When the values stay between the thresholds the signal doesnt change. This and smoothing out the for loop values is used to eliminate false signals as much as possible. --Features and Parameters-- -Allows the changing of the length of the ranking (median) -Allows the usage of different sources -Allows changing of the paramaters over the start and end of the for loop segment -Allows changing the thresholds for longs and shorts -Allows changing the parameter for the smoothing using an EMA --Details-- Both the wide thresholds and the use of an EMA over the for loop values are used to eliminate as much false signals as possible. Aswell as deviding the length by 3 and taking the average from the medians. From testing this indicator we have found that using a very small value for the shorting gives the overall best performance. Since a fast market move wont immediately trigger a false signal, but it also wont massively delay entries and exits. It is recommended to change the parameter settings for different asset classes and timeframes based off volatility and fast and confusing market movements. Enjoy!
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JTCapitalNL의
Big Mo’s Glaskugel — Macro Drawdown Risk (v1.1.2)What it does / what you see An at-a-glance drawdown-risk oscillator that blends several macro US signals. • A smooth, color-blended line (green→orange→red) shows the scaled risk score (0–100). • Subtle shading marks “re-steepen warning windows” (starts when the yield curve re-steepens after an inversion; ends on normalization/cool-down). • A compact status table summarizes: overall risk level, Yield Curve (10y–3m), Credit Stress (Baa–10y), Economy (LEI), and Valuation (CAPE). Data used & why Yield Curve (10y–3m) — FRED:T10Y3M. Inversions and subsequent re-steepens often precede recessions/equity drawdowns. Credit Stress — FRED:BAA10Y vs its 1-year average (deviation in bps). Widening credit spreads flag tightening financial conditions. Economy (LEI) — ECONOMICS:USLEI. 6-month annualized growth below a cutoff highlights macro deterioration. Valuation (CAPE) — SHILLER_PE_RATIO_MONTH. Elevated valuations can amplify downside risk. VIX spikes — optional boost that recognizes sudden risk repricings. Important disclaimer This is not a reliable or predictive indicator in all regimes. No guarantees or warranties of any kind are provided. It is not financial advice. Signals can be early, late, or wrong. That said, it leans on well-studied warning factors (yield-curve dynamics, credit spreads, LEI weakness, valuation extremes) that have flagged major market downturns in the past. Key customization / tweaks Weights for each component (Yield, Credit, LEI, VIX, CAPE). Thresholds: yield inversion months, re-steepen lookback, credit-stress bps, LEI cutoff, CAPE level, VIX spike levels. Re-steepen boost: enable/disable, base points, half-life decay. Shading behavior: cool-down bars to “unwarn,” max warning duration, only shade when risk ≠ green. Scaling & smoothing: dynamic rolling max, EMA length, yellow/red thresholds. Status table: position, and a snapshot mode to view values at a chosen historical time.
Pine Script® 인디케이터
BigMo_GQ의
Standardized Cumulative Deltas [LuxAlgo]The Standardized Cumulative Deltas tool allows traders to compare the cumulative standardized open-close difference for up to 10 different tickers, allowing them to visualize the general sentiment for all selected tickers. These results allow the construction of two areas showing the average or extreme bullish and bearish cumulative change for all enabled tickers, providing a summarized view of the overall ticker group sentiment. 🔶 USAGE This tool is meant to give a full picture of the individuals and/or overall selected tickers, and unlike classical indicators, the displayed series of values is not meant to be directly interpreted over time. Given the selected lookback period, a majority of observations being above 0 indicate an overall bullish market for the asset. By default, the auto lookback period feature is enabled, allowing the tool to use all the visible bars for its calculations. Traders can also set the lookback period manually. The above chart uses a fixed lookback period of 500. Up to 10 tickers can be used. While major cryptocurrencies are set by default, the users can set a specific basket of assets, such as US equities, forex pairs, commodities, etc. 🔹 Densities The provided areas, here called densities, can be used to get an overall sentiment of the selected tickers. The upper density (bullish) processes positive deltas, while the lower one (bearish) processes negative ones. Interpretation is subject to the selected "Density Mode". Average: Densities track the average bullish/bearish cumulative deltas for the selected tickers. For example, a more prominent bullish density would indicate that, on average, cumulative deltas were positive across the tickers. Envelope: Densities track the extreme values made by bullish/bearish cumulative deltas for the selected tickers. Here, a more prominent density would indicate more volatile bullish/bearish movements, depending on the density. 🔹 Dashboard The tool features a dashboard with active tickers and their respective colors for traders' convenience. 🔶 DETAILS 🔹 Densities Densities are obtained by applying a forward-backward exponential moving average on the average, or the highest/lowest cumulative series, depending on the selected Density Mode. The resulting densities are smoothed by the "Smoothing" parameter located in the Settings panel, with higher values returning smoother envelopes with less variability. Do note that the smoothing method used here is subject to repainting. 🔶 SETTINGS Lookback: Select the lookback period and enable/disable the Auto Lookback feature Tickers: Enable/disable and select up to 10 tickers and their colors Density Mode: Determine how densities are calculated 🔹 Dashboard Show Dashboard: Enable/disable the dashboard Position: Select the dashboard position Size: Select the dashboard size 🔹 Style Density: Enable/disable the density areas Bullish Density: Select the color of the top density area Bearish Density: Select the color of the bottom density area Smoothing: Select the smoothing constant for the EMA calculation
Pine Script® 인디케이터
LuxAlgo의
5
Adaptive Valuation [BackQuant]Adaptive Valuation What this is A composite, zero-centered oscillator that standardizes several classic indicators and blends them into one “valuation” line. It computes RSI, CCI, Demarker, and the Price Zone Oscillator, converts each to a rolling z-score, then forms a weighted average. Optional smoothing, dynamic overbought and oversold bands, and an on-chart table make the inputs and the final score easy to inspect. How it works Components • RSI with its own lookback. • CCI with its own lookback. • DM (Demarker) with its own lookback. • PZO (Price Zone Oscillator) with its own lookback. Standardization via z-score Each component is transformed using a rolling z-score over lookback bars: z = (value − mean) ÷ stdev , where the mean is an EMA and the stdev is rolling. This puts all inputs on a comparable scale measured in standard deviations. Weighted blend The z-scores are combined with user weights w_rsi, w_cci, w_dm, w_pzo to produce a single valuation series. If desired, it is then smoothed with a selected moving average (SMA, EMA, WMA, HMA, RMA, DEMA, TEMA, LINREG, ALMA, T3). ALMA’s sigma input shapes its curve. Dynamic thresholds (optional) Two ways to set overbought and oversold: • Static : fixed levels at ob_thres and os_thres . • Dynamic : ±k·σ bands, where σ is the rolling standard deviation of the valuation over dynLen . Bands can be centered at zero or around the valuation’s rolling mean ( centerZero ). Visualization and UI • Zero line at 0 with gradient fill that darkens as the valuation moves away from 0. • Optional plotting of band lines and background highlights when OB or OS is active. • Optional candle and background coloring driven by the valuation. • Summary table showing each component’s current z-score, the final score, and a compact status. How it can be used • Bias filter : treat crosses above 0 as bullish bias and below 0 as bearish bias. • Mean-reversion context : look for exhaustion when the valuation enters the OB or OS region, then watch for exits from those regions or a return toward 0. • Signal confirmation : use the final score to confirm setups from structure or price action. • Adaptive banding : with dynamic thresholds, OB and OS adjust to prevailing variability rather than relying on fixed lines. • Component tuning : change weights to emphasize trend (raise DM, reduce RSI/CCI) or range behavior (raise RSI/CCI, reduce DM). PZO can help in swing environments. Why z-score blending helps Indicators often live on different scales. Z-scoring places them on a common, unitless axis, so a one-sigma move in RSI has comparable influence to a one-sigma move in CCI. This reduces scale bias and allows transparent weighting. It also facilitates regime-aware thresholds because the dynamic bands scale with recent dispersion. Inputs to know • Component lookbacks : rsilb, ccilb, dmlb, pzolb control each raw signal. • Standardization window : lookback sets the z-score memory. Longer smooths, shorter reacts. • Weights : w_rsi, w_cci, w_dm, w_pzo determine each component’s influence. • Smoothing : maType, smoothP, sig govern optional post-blend smoothing. • Dynamic bands : dyn_thres, dynLen, thres_k, centerZero configure the adaptive OB/OS logic. • UI : toggle the plot, table, candle coloring, and threshold lines. Reading the plot • Above 0 : composite pressure is positive. • Below 0 : composite pressure is negative. • OB region : valuation above the chosen OB line. Risk of mean reversion rises and momentum continuation needs evidence. • OS region : mirror logic on the downside. • Band exits : leaving OB or OS can serve as a normalization cue. Strengths • Normalizes heterogeneous signals into one interpretable series. • Adjustable component weights to match instrument behavior. • Dynamic thresholds adapt to changing volatility and drift. • Transparent diagnostics from the on-chart table. • Flexible smoothing choices, including ALMA and T3. Limitations and cautions • Z-scores assume a reasonably stationary window. Sharp regime shifts can make recent bands unrepresentative. • Highly correlated components can overweight the same effect. Consider adjusting weights to avoid double counting. • More smoothing adds lag. Less smoothing adds noise. • Dynamic bands recalibrate with dynLen ; if set too short, bands may swing excessively. If too long, bands can be slow to adapt. Practical tuning tips • Trending symbols: increase w_dm , use a modest smoother like EMA or T3, and use centerZero dynamic bands. • Choppy symbols: increase w_rsi and w_cci , consider ALMA with a higher sigma , and widen bands with a larger thres_k . • Multiday swing charts: lengthen lookback and dynLen to stabilize the scale. • Lower timeframes: shorten component lookbacks slightly and reduce smoothing to keep signals timely. Alerts • Enter and exit of Overbought and Oversold, based on the active band choice. • Bullish and bearish zero crosses. Use alerts as prompts to review context rather than as stand-alone trade commands. Final Remarks We created this to show people a different way of making indicators & trading. You can process normal indicators in multiple ways to enhance or change the signal, especially with this you can utilise machine learning to optimise the weights, then trade accordingly. All of the different components were selected to give some sort of signal, its made out of simple components yet is effective. As long as the user calibrates it to their Trading/ investing style you can find good results. Do not use anything standalone, ensure you are backtesting and creating a proper system.
Pine Script® 인디케이터
BackQuant의
Pi Cycle OscillatorThis oscillator combines the Pi Cycle Top indicator with a percentile-based approach to create a more precise and easy to read market timing tool. Instead of waiting for moving average crossovers, it shows you exactly how close you are to a potential market top. Orange background means you should start preparing for a potential top and look into taking profits. Red background means that the crossover has happened on the original Pi Cycle Indicator and that you should have already sold everything. (Crossover of the gray line aka 100) Thank you Bollinger Band Width Percentile - The_Caretaker Pi Cycle Top - megasyl20
Pine Script® 인디케이터
jinasora의
1
SMC - Institutional Confidence Oscillator [PhenLabs]📊 Institutional Confidence Oscillator Version: PineScript™v6 📌 Description The Institutional Confidence Oscillator (ICO) revolutionizes market analysis by automatically detecting and evaluating institutional activity at key support and resistance levels using our own in-house detection system. This sophisticated indicator combines volume analysis, volatility measurements, and mathematical confidence algorithms to provide real-time readings of institutional sentiment and zone strength. Using our advanced thin liquidity detection, the ICO identifies high-volume, narrow-range bars that signal institutional zone formation, then tracks how these zones perform under market pressure. The result is a dual-wave confidence oscillator that shows traders when institutions are actively defending price levels versus when they’re abandoning positions. The indicator transforms complex institutional behavior patterns into clear, actionable confidence percentiles, helping traders align with smart money movements and avoid common retail trading pitfalls. 🚀 Points of Innovation Automated thin liquidity zone detection using volume threshold multipliers and zone size filtering Dual-sided confidence tracking for both support and resistance levels simultaneously Sigmoid function processing for enhanced mathematical accuracy in confidence calculations Real-time institutional defense pattern analysis through complete test cycles Advanced visual smoothing options with multiple algorithmic methods (EMA, SMA, WMA, ALMA) Integrated momentum indicators and gradient visualization for enhanced signal clarity 🔧 Core Components Volume Threshold System: Analyzes volume ratios against baseline averages to identify institutional activity spikes Zone Detection Algorithm: Automatically identifies thin liquidity zones based on customizable volume and size parameters Confidence Lifecycle Engine: Tracks institutional defense patterns through complete observation windows Mathematical Processing Core: Uses sigmoid functions to convert raw market data into normalized confidence percentiles Visual Enhancement Suite: Provides multiple smoothing methods and customizable display options for optimal chart interpretation 🔥 Key Features Auto-Detection Technology: Automatically scans for institutional zones without manual intervention, saving analysis time Dual Confidence Tracking: Simultaneously monitors both support and resistance institutional activity for comprehensive market view Smart Zone Validation: Evaluates zone strength through volume analysis, adverse excursion measurement, and defense success rates Customizable Parameters: Extensive input options for volume thresholds, observation windows, and visual preferences Real-Time Updates: Continuously processes market data to provide current institutional confidence readings Enhanced Visualization: Features gradient fills, momentum indicators, and information panels for clear signal interpretation 🎨 Visualization Dual Oscillator Lines: Support confidence (cyan) and resistance confidence (red) plotted as percentage values 0-100% Gradient Fill Areas: Color-coded regions showing confidence dominance and strength levels Reference Grid Lines: Horizontal markers at 25%, 50%, and 75% levels for easy interpretation Information Panel: Real-time display of current confidence percentiles with color-coded dominance indicators Momentum Indicators: Rate of change visualization for confidence trends Background Highlights: Extreme confidence level alerts when readings exceed 80% 📖 Usage Guidelines Auto-Detection Settings Use Auto-Detection Default: true Description: Enables automatic thin liquidity zone identification based on volume and size criteria Volume Threshold Multiplier Default: 6.0, Range: 1.0+ Description: Controls sensitivity of volume spike detection for zone identification, higher values require more significant volume increases Volume MA Length Default: 15, Range: 1+ Description: Period for volume moving average baseline calculation, affects volume spike sensitivity Max Zone Height % Default: 0.5%, Range: 0.05%+ Description: Filters out wide price bars, keeping only thin liquidity zones as percentage of current price Confidence Logic Settings Test Observation Window Default: 20 bars, Range: 2+ Description: Number of bars to monitor zone tests for confidence calculation, longer windows provide more stable readings Clean Break Threshold Default: 1.5 ATR, Range: 0.1+ Description: ATR multiple required for zone invalidation, higher values make zones more persistent Visual Settings Smoothing Method Default: EMA, Options: SMA/EMA/WMA/ALMA Description: Algorithm for signal smoothing, EMA responds faster while SMA provides more stability Smoothing Length Default: 5, Range: 1-50 Description: Period for smoothing calculation, higher values create smoother lines with more lag ✅ Best Use Cases Trending market analysis where institutional zones provide reliable support/resistance levels Breakout confirmation by validating zone strength before position entry Divergence analysis when confidence shifts between support and resistance levels Risk management through identification of high-confidence institutional backing Market structure analysis for understanding institutional sentiment changes ⚠️ Limitations Performs best in liquid markets with clear institutional participation May produce false signals during low-volume or holiday trading periods Requires sufficient price history for accurate confidence calculations Confidence readings can fluctuate rapidly during high-impact news events Manual fallback zones may not reflect actual institutional activity 💡 What Makes This Unique Automated Detection: First Pine Script indicator to automatically identify thin liquidity zones using sophisticated volume analysis Dual-Sided Analysis: Simultaneously tracks institutional confidence for both support and resistance levels Mathematical Precision: Uses sigmoid functions for enhanced accuracy in confidence percentage calculations Real-Time Processing: Continuously evaluates institutional defense patterns as market conditions change Visual Innovation: Advanced smoothing options and gradient visualization for superior chart clarity 🔬 How It Works 1. Zone Identification Process: Scans for high-volume bars that exceed the volume threshold multiplier Filters bars by maximum zone height percentage to identify thin liquidity conditions Stores qualified zones with proximity threshold filtering for relevance 2. Confidence Calculation Process: Monitors price interaction with identified zones during observation windows Measures volume ratios and adverse excursions during zone tests Applies sigmoid function processing to normalize raw data into confidence percentiles 3. Real-Time Analysis Process: Continuously updates confidence readings as new market data becomes available Tracks institutional defense success rates and zone validation patterns Provides visual and numerical feedback through the oscillator display 💡 Note: The ICO works best when combined with traditional technical analysis and proper risk management. Higher confidence readings indicate stronger institutional backing but should be confirmed with price action and volume analysis. Consider using multiple timeframes for comprehensive market structure understanding.
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