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Liquidity ZonesLiquidity Zones Liquidity Zones is a price-action–based indicator designed to identify high-probability support and resistance areas where liquidity has historically accumulated. Instead of drawing single lines, the script builds dynamic price zones based on repeated pivot reactions validated by volume, helping traders focus on meaningful levels rather than noise. How It Works Pivot Detection The indicator scans historical price data for pivot highs and pivot lows using a fixed pivot strength. Each pivot represents a potential liquidity interaction point. Volume Qualification A pivot is only considered valid if the volume at the pivot bar exceeds: Volume SMA × Sensitivity This filters out weak or low-participation levels and keeps zones formed during strong market interest. Zone Construction Nearby pivots are grouped into a single zone if their price difference stays within an ATR-based threshold. Each time price reacts within this threshold, the zone’s touch count increases. Once the minimum number of touches is reached, a liquidity zone is drawn and extended to the right. Adaptive Zone Expansion As new qualifying pivots appear, zones automatically expand to reflect the true liquidity range instead of staying static. Dynamic Zone Coloring Zones update their color in real time based on price position: Green (Support) → Price is above the zone Red (Resistance) → Price is below the zone Gray (In-Zone) → Price is trading inside the zone This allows instant visual feedback on whether a level is acting as support, resistance, or an active liquidity area. Settings Overview Bars to Apply Controls how much historical data is scanned for liquidity zones. Volume Sensitivity Higher values require stronger volume spikes to validate pivots, resulting in fewer but higher-quality zones. Styling Options Fully customizable colors and transparency for support, resistance, and in-zone states. Best Use Cases Identifying high-liquidity support and resistance zones Planning entries, exits, and stop placement Combining with trend-following or momentum indicators Filtering out weak levels in sideways or choppy markets
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ebecihalil의
Support and ResistanceSupport & Resistance Zones This indicator automatically identifies support and resistance zones by clustering confirmed pivot highs and lows into statistically valid price areas. Instead of drawing single horizontal lines, it creates price zones whose width is dynamically controlled using ATR (Average True Range), allowing the zones to adapt to market volatility. Core Logic The indicator scans a user-defined number of historical bars and detects pivot highs and pivot lows using a configurable pivot strength. Each new pivot is evaluated against previously detected zones: A zone becomes visible only after receiving sufficient confirmation (minimum number of pivot touches). This ensures that only structurally meaningful levels are drawn. Zone Construction Rules Zones are formed by grouping pivot points whose total price range remains within ATR range Each zone expands dynamically as new pivots confirm it Zones are drawn as rectangular areas, not lines Zones extend to the right, remaining active until price structure changes This approach avoids over-plotting and reduces noise commonly seen in traditional support/resistance tools. Dynamic Zone Coloring Zones automatically change color based on current price position: Support Color → Price is above the zone Resistance Color → Price is below the zone Neutral (In-Zone) Color → Price is trading inside the zone This makes it easy to visually assess market context without additional indicators. Inputs Explained Logic Settings Bars to Apply Number of historical bars scanned to detect pivots and construct zones. Pivot Strength Number of candles required on both sides of a pivot high/low for confirmation. Min Pivot Confirmation Minimum number of aligned pivots required before a zone is drawn. Styling Support, resistance, and in-zone colors Zone fill transparency Why This Approach Uses price structure, not arbitrary levels Adapts to market volatility via ATR Filters out weak, single-touch levels Works across all markets and timeframes This indicator is designed to highlight areas of interest, not generate buy or sell signals. It is best used in combination with trend, momentum, or volume-based tools.
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ebecihalil의
ICT Asian Range |MC|ICT Asian Range |MC| Indicator 💎 Overview 💎 Automatically highlights the Asian trading session on the chart with session High, Low, Midline, and a shaded box. Shows both current and previous sessions for quick reference. Range Definition: Identify the highest and lowest prices during this session Trading Setup: Use the defined range to anticipate future breakouts or liquidity sweeps 💎 Key Inputs 💎 ICT Session Range Time: 7:00pm – 0:00am EST (default, 👉 customizable) Label Text customizable: e.g. “ASIA RANGE” Line Colors: High/Low (customizable) Line Style & Width:(customizable) Midline: optional, calculated as session average Box Color: (customizable) Extension: how far lines extend into the future (customizable) Happy Trading!
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MAC-Trading의
Stoch RSI M5 / M30 / H1_Brando ValenciaIndicator Description This indicator displays the Stochastic RSI for 5-minute, 30-minute, and 1-hour timeframes simultaneously in one stable MTF panel — no lookahead, no repainting. Red (5m) → entry timing Green (30m) → short-term / intraday bias Blue (1h) → higher-timeframe context & direction The calculation matches the TradingView default Stoch RSI (%K) exactly: RSI length: 14 Stochastic length: 14 Smoothing: 3 Levels Above 80 → overbought Below 20 → oversold 50 → trend filter / equilibrium Purpose This indicator is not a standalone entry trigger, but a context and timing tool: 1h & 30m define direction 5m provides precise entry windows Ideal for scalping and day trading (e.g. EUR/USD during London & New York sessions).
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brandor_valencia의
Scalping Signals with MTF Fibo BandsThis indicator is a scalping / intraday signal system built on Multi-Timeframe (MTF) Fibonacci Bands, combined with an RSI midline filter and an optional direction-lock mechanism to reduce consecutive losing entries. 🔹 What does this indicator do? It plots two independent Fibonacci Band sets (A & B), each calculated from a higher timeframe SMA + ATR. Entry zones are defined between Band 2 and Band 3, representing statistically extreme price areas. You can choose to generate signals from: Band A only Band B only BOTH (A + B confirmation) 📈 Entry Logic LONG Price closes inside the Lower Zone (between Fib2 Lower & Fib3 Lower) RSI is above the midline (default 50) SHORT Price closes inside the Upper Zone (between Fib2 Upper & Fib3 Upper) RSI is below the midline (default 50) 🟧 Direction Lock System If enabled, the indicator locks the trade direction when a position hits Stop Loss before reaching TP1. This prevents repeated entries in the same direction during unfavorable conditions. 🔓 Unlock Logic The lock can be removed when: RSI crosses back over the midline (RSI > 50 for LONG, RSI < 50 for SHORT) AND price closes again inside the valid Band 2–3 zone With the optional setting enabled, a new entry can occur on the same candle 🛑 Stop Loss Logic (Important) This indicator uses price-action-based stop logic, not fixed pip stops. 1️⃣ Before TP1 LONG: Two consecutive candle closes below Fib3 Lower SHORT: Two consecutive candle closes above Fib3 Upper ⚠️ Because SL depends on candle closes, you must monitor lower timeframes (1m or below) to react quickly and avoid delayed exits. 2️⃣ After TP1 (Break-Even Protection) Once TP1 is touched: SL automatically shifts to Break-Even (entry price) Any return to entry will close the position ⚠️ Usage Warning This indicator is NOT designed for sharp, explosive, or news-driven moves Avoid using it during: High-impact news Extremely fast impulsive candles Sudden volatility spikes Best performance is achieved in structured price action environments, not chaotic market conditions.
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RCOTradingHelpline의
ADX Volatility Waves [BOSWaves]ADX Volatility Waves - Trend-Weighted Volatility Mapping with State-Based Wave Transitions Overview ADX Volatility Waves is a regime-aware volatility framework designed to map statistically significant price extremes through adaptive wave structures driven by trend strength. Rather than treating volatility as a static dispersion metric, this indicator conditions all volatility expansion, contraction, and zone placement on ADX-derived trend intensity. Price behavior is interpreted through wave-like transitions between balance, expansion, and exhaustion states rather than isolated band interactions. The result is a dynamic, gradient-based wave system that visually encodes volatility cycles and regime shifts in real time, allowing traders to contextualize price movement within trend-weighted volatility waves. Price is evaluated not by static thresholds, but by its position and progression within adaptive volatility waves shaped by directional strength. Conceptual Framework ADX Volatility Waves is built on the premise that volatility unfolds in waves, not straight lines. Traditional volatility tools identify dispersion but fail to account for how volatility behaves differently across trend regimes. By embedding ADX directly into volatility construction, this indicator ensures that volatility waves expand during strong directional phases and compress during weak or transitioning regimes. Three guiding principles define the framework: Volatility must be conditioned on trend strength Extremes occur within zones, not at lines Signals should emerge from completed wave transitions, not instantaneous touches This reframes analysis from reactive mean-reversion toward regime-aware wave interpretation. Theoretical Foundation The indicator fuses directional movement theory with statistical volatility modeling. Bollinger-derived dispersion provides the structural base, while ADX normalization controls the amplitude of volatility waves. As ADX increases, volatility waves widen and deepen; as ADX weakens, waves compress and tighten around equilibrium. From this foundation, extended upper and lower wave zones are constructed and smoothed to represent statistically significant expansion and contraction phases. At its core are three interacting systems: ADX-Controlled Volatility Engine : Standard deviation is dynamically scaled using normalized ADX values, producing trend-weighted volatility waves. Wave Zone Construction : Smoothed volatility boundaries are offset and expanded to form upper and lower wave zones, defining overextension and compression regions. State-Based Wave Transition Logic : Signals occur only after price completes a full wave cycle: expansion into an extreme wave zone followed by a confirmed return to equilibrium. This structure ensures that signals reflect completed volatility waves, not transient noise. How It Works ADX Volatility Waves processes price action through layered wave mechanics: Trend-Weighted Volatility Calculation : Volatility boundaries are dynamically adjusted using ADX influence, allowing wave amplitude to scale with trend strength. Structural Smoothing : Volatility boundaries are smoothed to stabilize wave geometry and reduce short-term distortions. Wave Offset & Expansion : Upper and lower wave zones are positioned beyond equilibrium and expanded proportionally to volatility range, forming clearly defined expansion waves. Gradient Wave Depth Mapping : Each wave zone is subdivided into multiple gradient layers, visually encoding increasing extremity as price moves deeper into a wave. Wave State Tracking & Cooldown Control : The system tracks prior wave occupancy, enforces neutral stabilization periods, and applies cooldowns to prevent overlapping wave signals. Compression Detection : Volatility width monitoring identifies compression phases, highlighting conditions where new volatility waves are likely to form. Together, these processes create a continuous, adaptive wave map of volatility behavior. Interpretation ADX Volatility Waves reframes market reading around volatility cycles: Upper Volatility Waves (Red Gradient) : Represent upside expansion phases. Deeper wave penetration indicates increased overextension relative to trend-adjusted volatility. Lower Volatility Waves (Green Gradient) : Represent downside expansion phases. Sustained presence signals pressure, while exits toward balance suggest wave completion. Equilibrium Zone : The neutral region between volatility waves. Confirmed re-entry into this zone marks the completion of a wave cycle and forms the basis for BUY and SELL signals. Regime Context via ADX : Strong ADX regimes widen waves, reducing premature reversal signals. Weak ADX regimes compress waves, increasing sensitivity to reversion. Wave progression and completion matter more than single-bar interactions. Signal Logic & Visual Cues ADX Volatility Waves produces single-entry BUY and SELL labels as its visual cues, plotted only when price first enters a volatility wave zone after the defined cooldown period. Buy Signal (Bottom Zone Entry) : A BUY label appears when price enters the lower volatility wave (oversold zone). This highlights potential expansion into undervalued extremes, providing visual context for trend assessment rather than a guaranteed execution trigger. Sell Signal (Top Zone Entry) : A SELL label appears when price enters the upper volatility wave (overbought zone). This marks potential overextension into upper volatility extremes, serving as a contextual indicator of trend stress. All labels respect cooldown tracking to prevent clustering. Alerts are tied directly to these zone-entry signals, and a separate alert monitors volatility squeezes for awareness of compression periods. Strategy Integration ADX Volatility Waves integrates cleanly into volatility-aware trading frameworks: Wave Context Mapping : Use wave depth to assess expansion and exhaustion risk rather than forcing immediate entries. Transition-Based Execution : Prioritize BUY and SELL signals formed after confirmed wave completion. Trend-Regime Filtering : In strong ADX regimes, treat waves as continuation pressure. In weak regimes, favor completed wave reversions. Volatility Cycle Awareness : Monitor compression phases to anticipate the emergence of new volatility waves. Multi-Timeframe Alignment : Apply higher-timeframe ADX regimes to contextualize lower-timeframe wave behavior. Technical Implementation Details Core Engine : ADX-normalized volatility expansion Wave System : Smoothed, offset, expanded volatility waves Visualization : Multi-layer gradient wave zones Signal Logic : State-based wave transitions with cooldown enforcement Alerts : Wave entry, wave completion, volatility compression Performance Profile : Lightweight, real-time optimized overlay Optimal Application Parameters Timeframe Guidance: 1 - 5 min : Short-term volatility waves and intraday transitions 15 - 60 min : Structured intraday wave cycles 4H - Daily : Macro volatility regimes and expansion phases Suggested Baseline Configuration: BB Length : 20 BB StdDev : 1.5 ADX Length : 14 ADX Influence : 0.8 Wave Offset : 1.0 Wave Width : 1.0 Neutral Confirmation : 5 bars These suggested parameters should be used as a baseline; their effectiveness depends on the asset volatility, liquidity, and preferred entry frequency, so fine-tuning is expected for optimal performance. Performance Characteristics High Effectiveness: Markets exhibiting rhythmic volatility expansion and contraction Assets with responsive ADX regime behavior Reduced Effectiveness: Erratic, news-driven price action Illiquid markets with distorted volatility metrics Integration Guidelines Confluence : Combine with BOSWaves structure or trend tools Discipline : Respect wave completion and cooldown logic Risk Framing : Interpret wave depth probabilistically, not predictively Regime Awareness : Always contextualize waves within ADX strength Disclaimer ADX Volatility Waves is a professional-grade volatility and regime-mapping tool. It does not predict price and does not guarantee profitability. Performance depends on market conditions, parameter calibration, and disciplined execution. BOSWaves recommends using this indicator as part of a comprehensive analytical framework incorporating trend, volatility, and structural context.
Pine Script® 인디케이터
BOSWaves의
10
FX Session High/Low Bands - Last 5 EST Days FX Session High/Low Bands - Last 5 Days Description: This indicator plots horizontal bands representing the high and low price levels from the major forex trading sessions over the last 5 days. It helps traders identify key support and resistance zones based on recent session activity. Features: Multiple Session Tracking: Displays high/low levels for major FX sessions: Asian Session (Tokyo) European Session (London) US Session (New York) 5-Day Lookback: Captures the highest high and lowest low from each session over the previous 5 trading days Visual Bands: Clear horizontal lines or filled zones showing session boundaries Dynamic Updates: Automatically recalculates as new session data becomes available How to Use: Support/Resistance: Previous session highs/lows often act as key price levels Breakout Trading: Watch for price breaking above/below session bands Range Trading: Trade within the bands during consolidation periods Session Overlap: Pay attention to multiple session bands converging Ideal For: Forex day traders Session-based trading strategies Support/resistance identification Multi-timeframe analysis
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drlicht1의
Probability-Based Adaptive Detection🙏🏻 PBAD (Probability-Based Adaptive Detection) : adaptive control tool for outliers || novelty detection, made for worst case data & processes, for the highest time complexity O(n^2) compared with the alternatives (would be explained in a sec). Thresholds are completely data driven and axiomatic, no need in provided hyperparameters, are not learned or optimized. The method accepts multiple weights, e.g. both temporal and volatility weights. Method briefly explained (I can go deeper if any1 asks explicitly): Performs weighted KDE on initial input data, finds KDE global maximum (mode), creates new “residuals” dataset by centering initial data around this value; Performs weighted KDE on residuals, uses sigmoid based probability mass targets with increasing probability coverage to construct a set of non-disjoint High Density Intervals (also called HDR, HPD in Bayesian terms); Uses these intervals to calculate analogs of centralized & standardized moments; Uses these ^^ moments to construct a set of control thresholds. The scheme used in PBAD is not only based on a central threshold, or on neighboring ones, it utilizes all previous thresholds, gaining more information. ... The most important part is to understand whether you really need PBAD. Because even tho it seems to be the best one given highest algocomplexity, irl it would work worse in cases when it’s not required by your data. Here’s the menu (aka taxonomy omg) of methods you can use that would let you make the right choice: Moment-Based Adaptive Detection (MBAD) : Norm: L2 Time complexity: original O(n), successfully reduced to O(1) in online version Use case: default, general purpose Based on: method of moments (powers of residuals from mean) Thresholds architecture: centralized Quantile-Based Adaptive Detection (QBAD): Norm: L1 Time complexity: O(nlogn) Use case: either bad data Or process instability Based on: quantile moments (dyadic percentiles of residuals from median) Thresholds architecture: chained/recursive/sequential Probability-Based Adaptive Detection (PBAD): Norm: L0 Time complexity: O(n^2) Use case: both bad data And process instability Based on: probability moments (target probability masses of residuals from KDE mode) Thresholds architecture: decentralized (for lack of a better name xd, the idea is that these thresholds gain information from the all other threshold and are Not exclusively based on the central or neighboring thresholds) ... Examples of true use cases: ^^ an appropriate financial instrument to use PBAD ^^ and another one ... Additional details about how to use it: Keep the student5 kernel, it’s the best you can do. I added others mostly for comparisons and if you want to use the tool Not for its primary purpose (on a fine data) “Calculate for N bars” and “Starting at bar N” options allow to reduce calculation period only on the N number of last bars or next bars from a chosen one. It's vital, because calculations here are heavy Keep plotting offset at 1 (allows to visually compare current bar with the previous threshold values). This is the way it should be done on price data. HLC3 is the optimal source input, unless you want to use your own better one point estimate of each datapoint (in the best case done by using PBAD itself on OHLC+ values). In essence it should be used just like MBAD or QBAD, fade/push extensions and limit, fade/push/skip deviations & basis, or other strategies of your. Again, the only reason for 3 methods to exist is to be chosen for according data characteristics. Btw: This is the initial version, I don’t consider it perfected tbh, even tho it works as expected, however this method is very situational anyways. In this script KDE function is modified to ensure the outcoming probabilities Do sum up to 1. I didn’t do this normalization in Weighted KDE Mode script , but there it’s not required since we just need a KDE global max. see ya ∞
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gorx1의
1
Selected Days Indicator V3-TrDoes the stock drop every Wednesday? Do March months always move similarly? Does the 1st week of the month behave differently? Do you ever say "it always makes this move in these months"? Don't you want to see more clearly whether it actually makes this move or not? Don't you want to see and test periodically repeating price patterns? Hisse her Çarşamba düşüyor mu? Mart ayları hep benzer mi hareket ediyor? Ayın 1. haftası farklı mı davranıyor? Bazen "bu aylarda hep bu hareketi yapıyor" dediğiniz oluyor mu? Gerçekten de bu hareketi yapıp yapmadığını daha net görmek istemez misiniz? Periyodik tekrarlayan fiyat kalıplarını görmek ve test etmek istemiyor musunuz? 1. Problem Some stocks or crypto assets exhibit systematic behaviors on certain days, weeks, or months. But it's hard to see - everything is mixed together on the chart. This indicator isolates the days/weeks/months you want and shows only them. Hides everything else. 2. How It Works Three-layer filter: Day (Monday, Tuesday...), Week (1st, 2nd, 3rd week of the month), Month (January, February...). Select what you want, let the rest disappear. Example: Show only Thursdays of March-June-September. Or compare every 1st week of the month. View as candlestick, line, or column chart. 3. What's It Good For? Test "end-of-month effect". Find "day-of-the-week anomaly". Analyze crypto volatility by days. See seasonality in commodities. Discover patterns specific to your own strategy. Past data doesn't guarantee the future but provides statistical advantage.
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ExperiMentalist의
EMA 8 / 20 / 200Created to easily use the 8/20/200 strategy. This indicator is designed to give a clear, multi-timeframe view of trend, momentum, and structure using three exponential moving averages. 1. Trend direction (EMA 200 – pink) The 200 EMA acts as the long-term trend filter. Price above the 200 EMA suggests a bullish market bias. Price below the 200 EMA suggests a bearish market bias. Many traders avoid taking trades against this higher-timeframe direction. 2. Momentum and trade bias (EMA 20 – blue) The 20 EMA reflects short-term momentum. When price respects the 20 EMA in an uptrend, pullbacks often provide continuation entries. In downtrends, the 20 EMA frequently acts as dynamic resistance. 3. Entry timing (EMA 8 – yellow) The 8 EMA is a fast reaction line used for precise timing. Crosses of the 8 EMA over the 20 EMA can signal momentum shifts. Strong trends often show price holding above (or below) the 8 EMA during impulse moves. 4. Confluence and trade filtering The indicator works best when the EMAs are aligned: Bullish alignment: EMA 8 > EMA 20 > EMA 200 Bearish alignment: EMA 8 < EMA 20 < EMA 200 Misaligned EMAs usually indicate consolidation or low-probability conditions. 5. Risk management context EMAs can act as dynamic support and resistance: Stops are often placed beyond the 20 EMA or 200 EMA depending on trade horizon. Loss of EMA structure is a warning sign that the trend may be weakening. In short, the indicator is a trend-first, momentum-second framework that helps you decide when to trade, in which direction, and when to stay out.
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Knotty0807의
MA20 ATR Trend Failure FilterA volatility-adaptive filter designed to identify early trend invalidation. This indicator combines a 20-period Moving Average (MA20) with Average True Range (ATR) to dynamically define a lower volatility boundary. When price closes below this boundary, it signals that the current trend is no longer valid and risk is increasing. Core Concept（核心思想） MA defines the trend baseline ATR measures current market volatility MA − k × ATR forms a dynamic risk threshold A close below this threshold = trend failure 👉 中文补充： 这不是反转指标，而是趋势失效过滤器，用于避免在趋势已经被破坏后继续持仓或加仓。 How It Works Calculate MA20 as the trend reference Calculate ATR(14) as volatility proxy Build adaptive bands: Upper Band = MA20 + k × ATR Lower Band = MA20 − k × ATR If close < Lower Band, trend is considered failed The ATR multiplier k automatically adjusts the tolerance based on volatility, avoiding rigid fixed-percentage rules. Visual Elements Yellow line: MA20 Green band: MA20 + k × ATR Red band: MA20 − k × ATR (key risk boundary) Red triangle + “FAIL” label: Trend failure signal Optional background shading to highlight risk zones Typical Use Cases Trend-following strategies (exit / reduce exposure) Breakout strategies (filter false continuation) Risk management overlay (non-intrusive, no repaint) Combine with HMA, SuperTrend, structure-based entries 👉 中文补充： 非常适合作为**“不该再拿”的客观判断条件**，而不是频繁交易信号。 Why This Indicator Volatility-adaptive (ATR-based) No future data, no repaint Simple logic, strong risk control Works across stocks, crypto, futures, indices This tool is designed to answer one question only: Is the current trend still valid? Parameters MA Length (default: 20) ATR Length (default: 14) ATR Multiplier k (default: 0.8) Lower k → stricter risk control Higher k → more tolerance, fewer false signals SSE:600595
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LuckyFirst의
Market + Direction + Entry + Hold + Exit v1.5 FINALOverview This script is a complete trend-based trading framework designed to filter market conditions, determine directional bias, detect high-quality pullback entries, manage active trades, and identify trend-weakening exit points. It is optimized for NQ futures, Gold (XAUUSD), and Bitcoin, with adaptive parameters for each asset. The logic focuses on trading only when conditions are favorable, aligning entries with the primary trend, and avoiding low-probability setups. 1. Market Condition Filter Before any signal appears, the script checks whether the market is active using three conditions: ATR compared to ATR moving average (volatility condition) Volume compared to average volume (liquidity condition) Price distance from VWAP (suppression of mean-reversion environments) A trade environment is considered active when at least two of these three conditions are positive. 2. Trend Direction Filter Directional bias is defined by: EMA21 relative to EMA55 Price relative to VWAP Heikin-Ashi structure When these conditions align, the script switches into long-only or short-only mode. No counter-trend signals are displayed. 3. Entry Logic (L, L2, L3 and S, S2, S3) The system identifies pullback entries within a confirmed trend. Long entries require: Uptrend confirmation Price dipping toward EMA21 or EMA55 A constructive Heikin-Ashi candle Market environment active Short entries mirror the same structure in bearish conditions. Re-entries (L2, L3, S2, S3) are given only if the trend remains intact after the first entry. 4. Hold Logic A hold signal appears if momentum remains aligned with the trend. Momentum is evaluated using the Stochastic indicator (K and D lines). 5. Exit Logic An exit signal appears when: The recent structural low (for longs) or high (for shorts) is broken, and The EMA slope indicates weakening trend strength This combination identifies high-probability trend exhaustion. How to Use Add the script to your chart. Select an asset preset (NQ, GOLD, BTC). Wait for the market to be active. Follow the entry signals (L, L2, L3 or S, S2, S3). Hold signals help confirm continuation. Exit signals indicate potential trend reversal or weakness. Feature Summary Market environment filter Trend direction filter Pullback-based entry system Multi-stage re-entry framework Momentum-based hold signal Structure-based exit Asset-adaptive parameters Clean chart visualization Disclaimer This script is for research and educational use. It does not constitute financial advice. Always backtest before using in live markets. 개요 이 스크립트는 시장 상태 필터링, 추세 방향 판단, 고품질 눌림목 진입, 보유 판단, 추세 약화 기반 청산까지 모두 포함하는 완전한 트레이딩 프레임워크입니다. NQ, 골드(XAUUSD), 비트코인에 맞게 최적화되어 있습니다. 1. 시장 필터 다음 세 가지 중 두 가지 이상이 충족될 때만 매매 환경을 ‘활성’으로 판단합니다. ATR 기준 변동성 체크 거래량 활성도 체크 가격의 VWAP 거리 체크 2. 방향(추세) 필터 다음 조건을 기반으로 상승·하락 추세를 결정합니다. EMA21 vs EMA55 가격 vs VWAP Heikin-Ashi 구조 이 조건이 일치할 때만 롱 전용 또는 숏 전용 모드로 진입합니다. 3. 진입 로직 추세가 유지되는 상태에서 EMA21 또는 EMA55까지 눌림이 나올 때 L 또는 S 신호를 제공합니다. 추세가 유지되면 L2/L3, S2/S3 재진입 신호가 추가로 발생합니다. 4. 보유(Hold) 모멘텀이 추세 방향과 일치할 때 보유 신호를 제공합니다. 5. 청산(Exit) 다음 두 조건이 동시에 나타날 때 청산 신호가 표시됩니다. 직전 구조(스윙)가 붕괴될 때 EMA 기울기가 약화될 때 사용 방법 차트에 스크립트를 추가합니다. 자산 프리셋(NQ, GOLD, BTC)을 선택합니다. 시장이 활성일 때만 신호를 참고합니다. L/S 진입 신호와 보유/청산 신호를 활용해 매매 흐름을 관리합니다.
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ninnikuya2294의
Supply and Demand Zones [BigBeluga]🔵 OVERVIEW The Supply and Demand Zones indicator automatically identifies institutional order zones formed by high-volume price movements. It detects aggressive buying or selling events and marks the origin of these moves as demand or supply zones. Untested zones are plotted with thick solid borders, while tested zones become dashed, signaling reduced strength. 🔵 CONCEPTS Supply Zones: Identified when 3 or more bearish candles form consecutively with above-average volume. The script then searches up to 5 bars back to find the last bullish candle and plots a supply zone from that candle’s low to its low plus ATR. Demand Zones: Detected when 3 or more bullish candles appear with above-average volume. The script looks up to 5 bars back for a bearish candle and plots a demand zone from its high to its high minus ATR. Volume Weighting: Each zone displays the cumulative bullish or bearish volume within the move leading to the zone. Tested Zones: If price re-enters a zone and touches its boundary after being extended for 15 bars, the zone becomes dashed , indicating a potential weakening of that level. Overlap Logic: Older overlapping zones are removed automatically to keep the chart clean and only show the most relevant supply/demand levels. Zone Expiry: Zones are also deleted after they’re fully broken by price (i.e., price closes above supply or below demand). 🔵 FEATURES Auto-detects supply and demand using volume and candle structure. Extends valid zones to the right side of the chart. Solid borders for fresh untested zones. Dashed borders for tested zones (after 15 bars and contact). Prevents overlapping zones of the same type. Labels each zone with volume delta collected during zone formation. Limits to 5 zones of each type for clarity. Fully customizable supply and demand zone colors. 🔵 HOW TO USE Use supply zones as potential resistance levels where sell-side pressure could emerge. Use demand zones as potential support areas where buyers might step in again. Pay attention to whether a zone is solid (untested) or dashed (tested). Combine with other confluences like volume spikes, trend direction, or candlestick patterns. Ideal for swing traders and scalpers identifying key reaction levels. 🔵 CONCLUSION Supply and Demand Zones is a clean and logic-driven tool that visualizes critical liquidity zones formed by institutional moves. It tracks untested and tested levels, giving traders a visual edge to recognize where price might bounce or reverse due to historical order flow.
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BigBeluga의
10