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Indikatoren und Strategien

Dr. Wish GMI and GMI-2Dr. Wish General Market Index (GMI) and GMI-2 OVERVIEW This indicator recreates Dr. Wish's General Market Index (GMI) and expanded GMI-2 from the Wishing Wealth Blog (wishingwealthblog.com). The GMI is a breadth-based market timing tool that counts how many of 6 key conditions are positive. The GMI-2 extends this to 9 components. Dr. Wish has used these indicators since 2005 to stay on the right side of the market, successfully avoiding the 2000-2002, 2008, and 2020 bear markets by going to cash when the GMI turns RED. Apply this indicator to a QQQ daily chart for best results. GMI COMPONENTS (6 total, each scores 1 point) 1. Successful New High Index — Stocks that hit new highs 10 days ago are still higher today. Measures whether the market has the confidence to let winners run. 2. New Highs >= 100 — At least 100 stocks hitting new 52-week highs in a day. In a healthy market, there should be broad participation at the highs. 3. QQQ Daily Trend UP — QQQ is above its rising 10-day EMA and higher than 5 days ago. Tracks the short-term trend of the Nasdaq 100. 4. SPY Daily Trend UP — Same conditions applied to SPY. Confirms the broader S&P 500 is also trending up. 5. QQQ Weekly Trend UP — QQQ is above its 10-week (50-day) average and the 10-week is above the 30-week (150-day). This is the longer-term trend and the most important component for staying invested. 6. T2108 Proxy > 50% — Percentage of stocks above their 50-day moving average is above 50%. This is a proxy for the Worden T2108 and the IBD Mutual Fund Index component. When growth stocks are broadly healthy, this reading is above 50%. GMI-2 ADDITIONAL COMPONENTS (3 more, total 9) 7. More New Highs than New Lows — Daily new 52-week highs exceed new 52-week lows. Basic breadth confirmation. 8. QQQ Above 10-Week Average — QQQ is above its 50-day SMA. Dr. Wish states he can only make money when QQQ is above this level. 9. QQQ Above 4-Week Average — QQQ is above its 20-day SMA. Short-term momentum confirmation. HOW TO READ IT The indicator plots two lines in a separate pane below your chart: - Green line: GMI score (0 to 6) - Blue line: GMI-2 score (0 to 9) GREEN signal (green background): GMI has risen to 4 or above. This is the time to be invested and buying growth stocks. RED signal (red background): GMI has fallen to 2 or below. Time to go to cash, protect capital, or consider shorts. The green zone (4-6) and red zone (0-2) are shaded on the chart for quick reference. A small orange line shows the T2108 proxy value divided by 10 for scale reference. DASHBOARD TABLE A component breakdown table in the corner shows each of the 9 components with PASS or FAIL status, plus: - Current GMI and GMI-2 scores - GREEN or RED signal status - T2108 percentage reading - QQQ distance from its 10-week average HOW TO USE IT - When GMI = 5 or 6: Strong bull market. Be fully invested in leading growth stocks. Buy GLB breakouts and RWB rockets. - When GMI = 4: Bull market intact but watch for weakening. Stay invested but tighten stops. - When GMI = 3: Caution zone. Reduce exposure, raise cash, be selective. - When GMI = 1 or 2: Bear conditions developing. Go to cash in trading accounts. The signal turns RED. - When GMI = 0: Full bear mode. All components negative. Do not buy growth stocks. Consider shorts or stay in cash. Dr. Wish becomes very defensive when the GMI drops below 4 and considers going to cash. When it reaches 0, he also moves his longer-term pension accounts to money market funds. SYMBOLS USED - QQQ: NASDAQ:QQQ (configurable) - SPY: AMEX:SPY (configurable) - NYSE New Highs: INDEX:HIGN - NYSE New Lows: INDEX:LOWN - T2108 Proxy: INDEX:MMFI (Percent of Stocks Above 50-Day Average, 0.95 correlation with Worden T2108) All symbols are configurable in the settings if your data feed uses different tickers. ALERTS Six alerts are built in: - GMI Turns GREEN — GMI crosses above the green threshold - GMI Turns RED — GMI falls to the red threshold or below - GMI = 6 (Max Bullish) — All 6 components positive - GMI = 0 (Max Bearish) — All components negative - GMI-2 = 9 (Max) — All 9 components positive - GMI-2 Collapses — GMI-2 falls to 2 or below SETTINGS - Symbols for QQQ, SPY, new highs/lows, and T2108 proxy are all configurable - GREEN threshold (default 4) and RED threshold (default 2) can be adjusted - New highs minimum threshold (default 100) is adjustable - Successful new high lookback period (default 10 days) is adjustable - Dashboard table can be repositioned or hidden - GMI-2 line can be toggled on or off IMPORTANT NOTES - This is an approximation of Dr. Wish's proprietary GMI. Some components (like the Successful New High Index and the IBD Mutual Fund Index) are approximated using publicly available TradingView data since the exact TC2000 formulas are not disclosed. - The T2108 proxy (INDEX:MMFI) tracks the percentage of stocks above their 50-day MA rather than the original 40-day MA used by Worden. The two are highly correlated (0.95). - Best results are obtained on a daily QQQ chart, as the GMI components are designed around QQQ and SPY behavior. CREDITS Based on the work of Dr. Eric Wish (Dr. Wish) at wishingwealthblog.com. The GMI was first published in April 2005 and has been refined over nearly 20 years of market cycles. DISCLAIMER For educational purposes only. This is not financial advice. The GMI is one tool among many and is not perfect. Always perform your own research and risk management before making trading decisions.
Pine Script® Indikator
von alainraad
High/Low Price Tracker w/L20-Table by Deepsage V1This indicator/strategy was planned, designed, and coded with guidance from Deepsage AI Mentors, but reflects my own ideas and strategies. It identifies the highest and lowest price of each candle and includes a table showing high/low price information for up to 20 candles back, providing a clear overview for analysis. It is connected to SageMaster for risk management and smart trade execution, including entering, exiting, starting, or closing positions based on TradingView alerts. Deepsage AI Mentors provide guidance only and do not offer financial advice. They are trained on public trading data from major exchanges, insights from SageMaster users, and educational content from the World of Wisdom platform, providing support and insights for strategy development. SageMaster is a trading ecosystem, not a broker or trading platform. Users retain full control of any automation, and we do not access or manage your funds. Created by Andreas, a Deepsage and SageMaster user. Disclaimer: This is not an official Deepsage, or SageMaster product. Planned Upgrades We are planning V2 and V3 of this indicator with Deepsage: V2: Adds a second table with more price-focused data points: OHLC, Range (high–low), Body Size (|close–open|), Price Change (%), Candle Type/Pattern, Volume, Relative Candle Size. Practical uses include: Trend Continuations (Potential Trade Idea): large body + above-average relative candle size + high volume + bullish/bearish pattern. Potential Reversals (Potential Trade Idea): hammer, doji, engulfing patterns confirmed by volume and relative candle size. Exhaustion Detection: long wicks, large range, small body candles. Other strategies: Sudden volatility, volatility-based stops, pattern-based stops, volume confirmation, breakout trading, swing trading, scalping. V3: Focus on total price movement (sum of all price changes within the candle, not just high–low). Provides advanced volatility analysis beyond traditional high–low measures. Designed to give additional insights while remaining practical for retail traders.
Pine Script® Indikator
von andreasapelseth
Guppy Rolling VWAP Note on VWAP (Volume Weighted Average Price) and Advantages of Multiple VWAPs Introduction to VWAP The Volume Weighted Average Price (VWAP) is a widely used technical indicator in trading, particularly for intraday strategies, that calculates the average price of a security (like a stock or index) over a specified period, weighted by the trading volume at each price level. Unlike a simple moving average (SMA), which treats all prices equally, VWAP emphasizes prices where higher volumes were traded, providing a more accurate reflection of the "true" market value during the session. Key Calculation Formula: VWAP = Σ (Price × Volume) / Σ (Volume) Price: Typically the average of high, low, and close for each bar (e.g., 1-minute or 5-minute interval). Volume: The total shares traded at that price. It resets at the start of each trading day (or session) and accumulates cumulatively, making it ideal for assessing intraday trends. On a chart, VWAP appears as a single line (often with standard deviation bands for added context), and prices above VWAP indicate bullish sentiment (buyers in control), while below suggests bearish pressure. VWAP is favored by institutional traders as a benchmark to minimize market impact when executing large orders (e.g., aiming to buy below VWAP for value). For retail intraday traders, it serves as a dynamic support/resistance level, helping time entries/exits and gauge efficiency. Advantages of Using Multiple VWAPs While a standard VWAP (daily reset) is powerful, employing multiple VWAPs—such as Anchored VWAP (AVWAP), multi-session VWAPs, or VWAPs anchored to specific events (e.g., earnings releases or highs/lows)—enhances flexibility and provides deeper insights across timeframes. Anchored VWAP, for instance, allows customization by starting the calculation from a user-defined point (e.g., a pivot high/low or news event), rather than just the session open. This "multiple" approach (plotting several VWAP lines) addresses limitations of a single VWAP in volatile or multi-day trends. Here are the key advantages: Enhanced Customization and Adaptability: Multiple VWAPs let traders anchor to specific points (e.g., weekly high or post-earnings), making them suitable for swing trading or analyzing beyond intraday. This is more versatile than a standard VWAP, which resets daily and may ignore longer-term context. Better Identification of Support/Resistance Levels: Plotting VWAPs from different anchors (e.g., one from session open, another from a recent low) creates layered zones, helping spot confluence for stronger entries/exits. In choppy markets like Bank Nifty, this reduces false signals by confirming trends across multiple lines. Improved Trend and Momentum Analysis: Combining short-term (e.g., 1-hour anchored) and long-term VWAPs reveals divergences or alignments, signaling potential reversals or continuations earlier. For example, price respecting a multi-day VWAP while bouncing off an intraday one indicates building strength. Risk Management and Benchmarking: Institutions use multiple VWAPs to compare execution quality across sessions (e.g., vs. previous day's VWAP), minimizing slippage in large trades. For retail traders, it aids in setting dynamic stops/targets, improving risk-reward ratios. Volume-Integrated Insights: Like single VWAP, multiples incorporate volume for a "truer" average, but layering them filters noise better in high-vol environments, outperforming unweighted averages like SMA. Limitations and Best Practices VWAP isn't foolproof—it can lag in low-volume periods and isn't ideal for overnight holds (as it resets). When using multiples, avoid clutter by limiting to 2-3 lines; combine with your SMA/EMA for confirmation. In your intraday setup, test on historical charts (e.g., HDFC Bank) to see how multiple VWAPs align with trends for advance signals.
Pine Script® Indikator
von akghuf19ag24
1
EMA 21 & EMA 50 Crossover + Close Line1️⃣ This indicator generates BUY and SELL signals based on EMA 21 and EMA 50 crossovers, where EMA 21 crossing above EMA 50 gives a BUY signal and crossing below gives a SELL signal. 2️⃣ All signals are confirmed only after candle close, which helps reduce false and premature entries. 3️⃣ Clear visual arrows (▲ / ▼) are plotted on the chart to easily identify BUY and SELL points. 4️⃣ A horizontal line is drawn at the signal candle’s close price, clearly marking the entry level on the chart. 5️⃣ The indicator includes built-in alert conditions, making it suitable for real-time alerts, manual trading, and algo/webhook-based execution.
Pine Script® Indikator
von yadav_surjeet379
1
Xiznit EMA Cross StrategyXiznit EMA Cross Strategy is a robust, filtered trend-following trading system built in Pine Script v6 for TradingView. It improves upon classic EMA crossover signals by incorporating multiple confirmations to reduce whipsaws and fakeouts, while using dynamic risk management to protect capital and let winners run in strong trends. Core Concept The strategy enters trades on Exponential Moving Average (EMA) crossovers (fast EMA crossing above/below slow EMA), but only when the market shows sufficient trend strength and momentum confirmation. This helps focus on higher-probability setups and avoids choppy, range-bound conditions where simple EMA crosses often fail. Key Features & Logic Entry Signals (Filtered for Quality) Long Entry: Fast EMA crosses above Slow EMA AND all filters pass: ADX > user-defined threshold (default 25) — confirms a strong trend. +DI > -DI — confirms bullish directional momentum. Current volume > SMA(volume, length) × multiplier (default 1.5) — ensures volume surge backing the move (reduces low-conviction fakeouts). Short Entry: Fast EMA crosses below Slow EMA AND: ADX > threshold. -DI > +DI (bearish momentum). Volume surge condition. Trades respect the selected direction mode: Long only, Short only, or Both (reversals allowed). Position Management & Exits Initial Stop-Loss: Placed at entry price ± ATR × multiplier (default 1.5× ATR(14)). Visualized as a short red dashed horizontal line for the first 10 bars after entry. Trailing Stop (Chandelier Exit style): Dynamic ATR-based trail: Longs: Trails below price at highest high since entry minus ATR × multiplier (default 3.0). Shorts: Trails above price at lowest low since entry plus ATR × multiplier. Updates every bar to move only in the trade's favor. Visualized as a stepped line on the chart (green/teal for longs, red/maroon for shorts) — only shown while position is open. Breakeven (BE) Move: When unrealized profit reaches RR × initial risk (default RR = 1.0), the stop-loss automatically moves to the exact entry price (breakeven). Triggers a label ("SL → BE") near the current price. Changes trailing line appearance: brighter color (lime for longs, fuchsia for shorts), thicker width, and solid style instead of dashed — clear visual cue that the trade is now risk-free. Exit: Position closes only when price hits the trailing stop (market order at close). No opposite EMA cross exits — allows trades to capture larger moves in trending markets. Visuals on the Chart (Clean & Informative) Fast EMA (orange, thick) and Slow EMA (blue, thick). Entry markers: Green upward triangle below bar + "Long" label for valid longs. Red downward triangle above bar + "Short" label for valid shorts. Trailing stop line (dynamic, position-based). Temporary initial SL dashed red line (fades after 10 bars). Breakeven trigger label and trailing line style/color change. ADX/DMI pane elements (overlaid but visually distinct): ADX line (purple). +DI (green) and -DI (red) lines. Dashed red horizontal at ADX threshold. Small diamond markers on +DI/-DI crossovers. Background fill: light green when ADX > threshold (trending allowed), light gray when below (range-bound, signals blocked). Overall chart background tint: subtle green/gray based on ADX condition for quick trend context. Inputs (Fully Customizable) Fast EMA & Slow EMA lengths (defaults 10 / 20). Trade Direction: Long, Short, or Both. ADX/DMI Length (default 14) and ADX Threshold (default 25.0). Volume SMA Length (default 20) and Volume Multiplier (default 1.5). ATR Length (default 14). Trailing ATR Multiplier (default 3.0 — Chandelier distance). Initial SL ATR Multiplier (default 1.5 — starting risk distance). RR for BE Move (default 1.0 — reward:risk ratio to trigger breakeven). Important Notes & Disclaimers This is a trend-following strategy — performs best in trending markets (e.g., stocks, forex, crypto on higher timeframes like 1H, 4H, Daily). It may underperform or generate few signals in sideways/choppy conditions due to strict ADX + DMI + volume filters. No guarantees of profitability — past backtest results do not predict future performance. Always forward-test, paper trade, and use proper risk management. Designed for illustration and educational purposes only. Not financial advice. Trading involves substantial risk of loss. Uses calc_on_every_tick=true for real-time responsiveness. No pyramiding, fixed quantity sizing (uses strategy defaults — adjust in Settings/Properties tab). Commission, slippage, and realistic fill assumptions should be set in the Strategy Tester for more accurate results.
Pine Script® Strategie
von Xiznit
1
Swing EMA Structure RSI ATR v6 SuroThis strategy is specifically designed for H1 and H4 swing trading, using a structured trend-following approach. It combines: EMA 50 & EMA 200 → Primary trend filter Market Structure (HH/HL & LH/LL) → Directional confirmation RSI → Momentum and overbought/oversold filter ATR → Volatility-based dynamic Stop Loss Minimum Risk:Reward 1:2 Optional Break Even and ATR Trailing Stop The strategy focuses on entering retracements within a strong trend rather than chasing breakouts.
Pine Script® Strategie
von denidiana
FU candle Bidirectionally optimizedDetection of FU candles. Logic: A bearish candle qualifies as an FU candle when its high and low exceed the previous candle’s wicks. A bullish candle qualifies as an FU candle when its high and low exceed the previous candle’s wicks. A “bad” FU candle (with a smaller body) is marked separately. Includes alert functionality. Candles with double the body size of the previous candle are marked with a green dot. Default multiplier is 2, but it can be adjusted. A table appears that counts all FU variations within the last 100 candles. Default lookback is 100, but it can be adjusted.
Pine Script® Indikator
von SwoboHD
1
Blueprint Supply and DemandThis indicator identifies and plots Supply & Demand zones to help you spot areas where price previously moved away strongly (potential reaction zones). What it does Detects Demand zones (potential buy interest) and Supply zones (potential sell interest) Draws zones as rectangles with adjustable colors, transparency, and max zones Optional filtering to focus on stronger zones (based on displacement/structure) Optional alerts for: Zone touch Zone break Zone re-entry / mitigation (if enabled) How to use Look for reactions when price revisits a zone (confirmation is recommended) Combine with market structure (trend/HH-HL or LH-LL), volume, or candle confirmation Use zones to plan entries, invalidation points, and targets Disclaimer: Not financial advice. No indicator guarantees results.
Pine Script® Indikator
von husni_solo1
Magnetick Extension [MagnetickAI]Magnetick Extension measures how far price has stretched from its key moving averages, expressed in ATR units. A stock that's 7× ATR above its 50 EMA is statistically more likely to snap back than one that's 2× away — this indicator makes that distance visible at a glance. THE CONCEPT Price oscillates around moving averages. During strong trends it pulls away, and the further it stretches, the higher the probability of a mean reversion. This indicator quantifies that stretch using ATR as the ruler, so "5× from the 50 EMA" means the same thing whether you're looking at a $20 stock or a $500 one. The ATR calculation uses a long lookback (50 periods by default) to avoid a common trap: near the end of a parabolic move, recent candles are large, which inflates a standard 14-period ATR and makes the stock appear less extended than it actually is. A 50-period ATR represents the stock's normal volatility, giving an honest read on how far price has actually traveled. THE 3 LINES 1. Slow EMA Distance (thick, heat-colored) — The primary line. Changes color as extension increases: gray in normal territory, yellow at caution, soft red at profit-take, bright red at extreme. This EMA has the most research behind its thresholds. 2. Medium EMA Distance (purple) — Intermediate extension. Useful for swing traders or for confirming whether the trend is accelerating or fading relative to the slow line. 3. Fast EMA Distance (blue) — Short-term extension. Normally stays near zero; when it spikes, short-term momentum is intense. When it drops back toward zero while the slow line stays elevated, the pullback may be starting. ZONE THRESHOLDS Each EMA has its own configurable thresholds. Defaults for the slow EMA (50): Normal (below 4×): Healthy trend. Fine to hold or initiate positions. Caution (4×): No new entries zone. The risk/reward for fresh positions deteriorates above 4× ATR from the slow EMA. Profit-Take (7×): Begin scaling out partials. Empirically, 7× is where small and mid-cap momentum names start to stall. Large caps and indexes tend to mean-revert earlier (3-5×). Extreme (10×): Historical reversal zone. Multiple high-profile momentum stocks (PLTR, TSLA, NVDA, SOFI, VRT) have experienced stalls and reversals near this level. Defaults by EMA: Slow (50): 4 / 7 / 10 Medium (21): 2 / 4 / 6 Fast (9): 1 / 2 / 3 Signs matter: +7.2× means price is 7.2 ATR above the EMA. -5.1× means 5.1 ATR below. Zones are based on absolute distance — overextension applies in both directions. HOW TO USE IT Think of the slow EMA line as a speedometer for trend extension. The practical workflow: - Below 4× (slow EMA): business as usual — hold or add - 4× to 7×: tighten stops, no new entries - Above 7×: start scaling out (1/3 of position) - Above 10×: take another 1/3 off, expect a pullback The fast and medium lines add context. If the slow line shows 6× but the fast line is back near zero, short-term momentum has already faded — the pullback may be underway. If all three lines are elevated, the trend is still accelerating. Adjust thresholds by market cap: - Large caps / indexes: lower thresholds (3 / 5 / 7 for the slow EMA) - Small/mid-cap momentum: defaults work well (4 / 7 / 10) - Low-float runners: may need higher thresholds (5 / 10 / 15) DASHBOARD TABLE A compact table (top-right) shows each EMA's current price, ATR distance, and zone classification. Distance and zone text are color-coded: green for normal, yellow for caution, soft red for profit-take, bright red for extreme. The footer shows the ATR value and calculation timeframe. CALCULATION TIMEFRAME By default, EMAs and ATR are calculated on the daily timeframe regardless of your chart timeframe. On a 1-minute chart, you see how far the current price is from the daily 50 EMA in daily ATR units — exactly the context a day trader needs. The reference values update once per day (stable anchor), while the distance updates in real-time as price moves. Set the calculation timeframe to blank for chart-timeframe calculations if you prefer intraday EMAs on intraday charts. SETTINGS - EMA lengths: 9, 21, 50 (all configurable) - ATR length: 50 (configurable, longer = more stable) - Calculation timeframe: daily by default, blank for chart timeframe - Zone thresholds: three levels per EMA (Caution, Profit-Take, Extreme) - Toggle each EMA line independently - Toggle area fill, zone backgrounds, and dashboard table ALERTS - Slow EMA reaches Profit-Take zone - Slow EMA reaches Extreme zone - Medium EMA reaches Extreme zone - Fast EMA reaches Extreme zone - Any EMA reaches Extreme zone (composite) - Slow EMA returns to Normal zone LIMITATIONS - Thresholds are heuristics, not physics. 10× is where many stocks have reversed, but some push to 15× or higher before correcting. - The indicator shows extension, not timing. A stock at 8× can stay at 8× for days before pulling back. - Default thresholds are calibrated for daily charts on U.S. equities. Crypto, forex, and intraday-only setups may need different values. - On intraday charts with daily calculation timeframe, the EMA and ATR values use the prior day's confirmed close. They don't update intraday. - Zone reference lines and fills are shown on the positive (bullish) side only. Bearish overextension is visible via the area fill turning red below zero and the table's zone classification. - The thresholds are informed by the ATR% Multiple framework and empirical observation across momentum stocks, but originate from a specific research dataset — not a universal backtest. Built by MagnetickAI — open source indicator suite for intraday traders.
Pine Script® Indikator
von MagnetickAI
Lucia XAUUSD Complete Indicator (FVG, High, Low, OB)This indicator is a complete multi‑timeframe Smart Money Concept toolkit designed specifically for XAUUSD intraday trading. It combines high‑timeframe levels, liquidity, imbalances, order blocks, sessions, and trend tools into one clean overlay indicator with optional labels and alerts. All modules can be enabled or disabled individually in the settings. 📌 Features Overview 1. Previous Day High/Low (D1) Automatically plots the previous day's High and Low. Strong liquidity levels for intraday gold trading. Optional labels: “Daily High (Prev Day)” / “Daily Low (Prev Day)”. Optional alerts for crossing these levels. 2. 4‑Hour Imbalances (H4) Detects newly formed H4 imbalances (Fair Value Gaps). Plots colored boxes for both bullish and bearish imbalances. Optional label: “Imbalance 4H (UP)” “Imbalance 4H (DOWN)” Optional alert when price touches the most recent imbalance. 3. 1‑Hour Fair Value Gaps (H1 FVG) Detects 1H FVGs with clear colored boxes. Shows text labels: “FVG 1H (UP)” “FVG 1H (DOWN)” Optional alert when price enters the latest FVG zone. 4. 1‑Hour Order Blocks + 50% Mean Threshold Detects bullish and bearish 1H Order Blocks based on the previous candle structure. Plots: OB top line OB median line (50% MT level) Text labels: “Order Block 1H (Bull)” “Order Block 1H (Bear)” “MT 50% 1H” Optional alert when price taps the most recent OB. 5. EMAs and VWAP Trend filters: EMA 8 (micro‑trend) EMA 20 (intraday trend) EMA 200 (macro bias) Volume‑weighted trend: VWAP All can be individually toggled ON/OFF. 6. Session Tools Asian Session Range Draws a box for the 00:00–06:59 UTC session. Label: “Asian Range”. London Open Draws a dotted line at 07:00 UTC (≈08:00 CET). Label: “London Open”. Optional alert on price cross. New York Open Draws a solid line at 14:30 UTC (≈15:30 CET). Label: “New York Open”. Optional alert on price cross. 7. H1 Liquidity Levels (Swing High/Low) Detects H1 swing highs and swing lows with pivot settings (left/right bars). Plots thin black dashed lines as liquidity levels. Labels: “H1 Liquidity High” “H1 Liquidity Low” Adjustable: Pivot size Maximum number of lines ON/OFF toggle 📌 Customization Options Label Settings Enable/disable all text labels. Choose label size (tiny, small, normal). Set label background transparency. Session Controls Enable/disable Asian box, London open line, NY open line. Alert Settings Alerts available for: Daily High/Low cross 4H Imbalance touch 1H FVG touch 1H OB touch London/NY open cross You can create alerts using Create Alert → Condition: This indicator → Choose event. 📌 Designed For: XAUUSD intraday trading Smart Money Concepts (SMC) Precision liquidity entries Session trading strategies Confluence stacking (FVG + OB + EMA + VWAP + Liquidity) 📌 Notes Works best on lower timeframes (1m–15m) with higher‑timeframe logic built‑in (H1, H4, D1). All objects (lines, boxes, labels) are optimized to avoid exceeding TradingView limits.
Pine Script® Indikator
von lucinka_krchlikova
Parkinson Range Oscillator [BackQuant]Parkinson Range Oscillator Overview Parkinson Range Oscillator is a volatility regime indicator built around the Parkinson volatility estimator , a high-low based variance model originally proposed as a more statistically efficient alternative to close-to-close volatility. Instead of measuring volatility from closing returns, this script measures volatility from the intrabar price range using ln(H/L), then converts it into a normalized oscillator (z-score) so you can identify volatility expansion vs compression relative to the asset’s own history. The indicator is designed to answer questions like: Is volatility currently elevated or suppressed relative to its baseline? Is volatility expanding (risk rising) or compressing (coiling)? How extreme is the current vol state in percentile terms? How does range-based vol compare to a more common ATR-based vol read? It plots: A Parkinson-based volatility z-score oscillator with gradient fills. A signal line (EMA) for expansion/compression transitions. An ATR-based z-score for context comparison. A dashboard with current vol %, z-score, percentile rank, regime label, and ATR z-score. Where Parkinson volatility comes from (origin and intuition) The Parkinson estimator comes from academic finance and the study of volatility estimation. The key insight is simple: The daily high and low contain more information about variability than the close alone. Close-to-close volatility only uses one price per bar (the close), throwing away intrabar information. The high-low range captures the realized dispersion inside the bar, so under ideal assumptions it can estimate variance more efficiently. The Parkinson model is derived assuming: Price follows a continuous-time diffusion process (often framed like geometric Brownian motion). No drift matters for the variance estimate over the interval. No jumps and no microstructure distortions (idealized). Even though real markets violate these assumptions (gaps, jumps, wicks from order flow), the estimator remains useful because: Range is still a strong proxy for realized volatility. It reacts to intrabar expansion earlier than close-based methods. It is less dependent on where the bar closes. Core Parkinson formula (what the script implements) Parkinson variance for a window of n bars is: Var = (1 / (4 * n * ln(2))) * Σ This script computes it in the common rolling form: logHL2 = (ln(high/low))² parkVar = SMA(logHL2, n) / (4 * ln(2)) parkVol = sqrt(parkVar) * 100 Key details: ln(H/L) makes the range scale-invariant (percent-like), so it behaves more consistently across price levels. Squaring gives variance contribution. The 1/(4 ln 2) constant comes from the expected distribution of high-low range under a Brownian diffusion. sqrt converts variance to standard deviation (volatility). *100 expresses it as a percentage for readability. So parkVol is a “range-based realized volatility proxy” in percent terms. Why range-based volatility behaves differently than ATR ATR measures average true range, which is a linear range magnitude measure (high-low plus gaps). Parkinson uses ln(H/L) which is: Log-scaled (closer to a return-based measure). More directly tied to variance estimation theory. In practice: ATR can be driven by gaps and absolute range. Parkinson is driven by proportional range and tends to emphasize how wide the bar is relative to its price level. Parkinson often reacts sharply when wicks expand even if closes are stable. Normalization into an oscillator (making it comparable through time) Raw volatility values are hard to interpret across regimes because every market has different “normal.” This script normalizes Parkinson volatility against its own rolling baseline using a z-score: parkMA = SMA(parkVol, baselineLen) parkSD = stdev(parkVol, baselineLen) osc = (parkVol - parkMA) / parkSD Interpretation: osc = 0 means current vol is at its baseline average. osc = +1 means 1 standard deviation above normal (high vol). osc = -1 means 1 standard deviation below normal (compressed). osc > +2 flags extreme expansion states. This is the core output. It turns “volatility” into “volatility regime” in standardized units. Signal line and expansion/compression transitions The oscillator is smoothed with an EMA to create a signal line: signal = EMA(osc, signalLen) Then transitions are defined as: Expansion cross: crossover(osc, signal) and osc > 0 Compression cross: crossunder(osc, signal) and osc < 0 Why the extra osc > 0 and osc < 0 conditions: It prevents treating small oscillations around zero as meaningful. It forces expansion signals to occur in above-average volatility territory. It forces compression signals to occur in below-average volatility territory. So signals are regime-confirming, not constant cross spam. Percentile rank (how extreme is vol relative to the past) In addition to the z-score, the script computes the percentile rank of the raw Parkinson volatility: pctRank = percentrank(parkVol, pctRankLookback) Interpretation: pctRank near 90–100 means current vol is among the highest levels seen in that lookback. pctRank near 0–10 means it is among the lowest (compression). Z-score tells you “how many SDs from mean.” Percentile tells you “how rare is this state historically.” Those are different but complementary. ATR comparison line (context, not the main engine) The indicator also computes an ATR-based volatility proxy and normalizes it in the same way: atrVol = ATR(n) / close * 100 atrOsc = zscore(atrVol, baselineLen) This gives you a direct visual comparison: If Parkinson oscillator is high but ATR oscillator isn’t, range expansion may be happening in a way ATR is not emphasizing (or vice versa). If both agree, you have stronger confirmation of a true volatility regime shift. ATR is included as a “common benchmark,” not as the primary signal. Regime classification (human-readable state mapping) The script labels regimes from osc: osc > 2.0 → EXTREME osc > 1.0 → HIGH osc > 0.0 → ABOVE AVG osc > -1.0 → BELOW AVG else → COMPRESSED This is a practical mapping for dashboards and quick reads. It is not pretending that 2.0 is a universal constant, it is just a standardized “rare expansion” threshold. Coloring follows the same logic: More positive = more “expansion” coloring (bearCol). More negative = more “compression” coloring (bullCol). Note: the color naming is semantic here: “Low Vol / Compression” is bullCol because compression often precedes trend expansion opportunities. “High Vol / Expansion” is bearCol because high vol often implies risk, disorder, liquidation, or unstable conditions. You can interpret those however you prefer, the tool is measuring volatility regime, not directional bias. Plot design (why the oscillator is split into positive/negative) The oscillator is split into two series: oscPos = osc if osc > 0 else na oscNeg = osc if osc < 0 else na This is purely for visuals: Positive region is drawn with expansion color and expansion gradient fill to zero. Negative region is drawn with compression color and compression gradient fill to zero. This makes it obvious at a glance which side of “normal volatility” you’re on. How to interpret the indicator correctly 1) The oscillator is volatility regime, not price direction High osc does not mean price will go down. It means the market is moving violently relative to its baseline. That can occur in: Selloffs, liquidations, panic. Breakouts and momentum expansions. News-driven repricing. Low osc does not mean price will go up. It means the market is quiet relative to baseline: Ranges, coils, low realized movement. Slow grind trends with suppressed pullbacks. Pre-breakout compressions. 2) Compression regimes are often “setup states” When osc is deeply negative (compressed), it often indicates that realized movement has collapsed. In many markets this precedes: Breakouts (vol expansion from compression). Trend acceleration. Mean reversion bursts. But compression can also persist. This is why the script includes signal crosses and percentile rank to judge when compression is shifting. 3) Expansion regimes are often “risk states” When osc is positive and rising, the environment is more chaotic: Stops are more likely to be hit. Mean reversion can get violent. Trend continuation can be strong but timing becomes harder. In those regimes, the tool can be used to: Reduce leverage. Widen stops (if your system supports it). Switch to volatility-aware sizing. Wait for stabilization if you trade mean reversion. 4) Use percentile rank to identify “rare” volatility Two markets can both show osc = +1, but one might be at the 95th percentile and the other at the 70th depending on distribution shape. Percentile tells you whether the current vol is truly rare in that lookback. Cross dots (how to treat them) ExpansionCross and CompressionCross are not buy/sell signals. They are “volatility phase change” markers: ExpansionCross: vol regime moving up, above baseline, acceleration risk increases. CompressionCross: vol regime moving down, below baseline, quieting environment. These are useful for: Strategy toggles (trend mode vs chop mode). Sizing changes. Timing filters (avoid entries during extreme expansion if your edge hates noise). Dashboard (what it gives you at a glance) The table summarizes everything that matters without you needing to interpret plots manually: Parkinson Vol %: current raw range-based volatility level. Z-Score: current standardized regime reading. Percentile: rarity of current vol in the lookback. Regime: discrete label based on z-score thresholds. ATR Z-Score: comparison metric in standardized units. The dashboard is positioned and sized via inputs so it can fit different chart layouts. Parameter tuning guidance Parkinson Length Controls how quickly the raw Parkinson vol responds: Shorter = more reactive to immediate range changes. Longer = smoother volatility estimate, less noisy. Baseline Length Controls what “normal” means: Long baseline (like 100) creates stable regime definitions. Short baseline makes z-scores jump around and can overreact. Signal Length Controls how quickly you detect regime turning points: Short signal = more crosses, earlier detection, more noise. Long signal = fewer crosses, later detection, cleaner regime shifts. Percentile Lookback Controls rarity context: 252 approximates one trading year on daily charts. On intraday, it becomes “252 bars,” so adjust to match your horizon. Limitations and what to watch for Parkinson assumes continuous diffusion. Jumps and gaps can distort it. Wicks caused by illiquidity can inflate ln(H/L) and produce false “expansion.” Z-score assumes the baseline distribution is reasonably stable. If volatility distribution shifts structurally, your z-scores can be biased until baseline catches up. Percentile rank is lookback-dependent. Different lookbacks can change “rarity” classification materially. Summary Parkinson Range Oscillator converts a statistically grounded high-low volatility estimator into a regime oscillator by z-scoring Parkinson volatility against its own rolling baseline. It highlights expansion vs compression states with clear gradients, flags volatility phase changes via oscillator-signal crosses, ranks current volatility by percentile for rarity context, and overlays an ATR-based z-score for comparison. This makes it a practical tool for volatility-aware trading, regime filtering, sizing adjustments, and identifying compression-to-expansion transitions.
Pine Script® Indikator
von BackQuant
Blueprint Supply and DemandThis indicator identifies and plots Supply & Demand zones to help you spot areas where price previously moved away strongly (potential reaction zones). What it does Detects Demand zones (potential buy interest) and Supply zones (potential sell interest) Draws zones as rectangles with adjustable colors, transparency, and max zones Optional filtering to focus on stronger zones (based on displacement/structure) Optional alerts for: Zone touch Zone break Zone re-entry / mitigation (if enabled) How to use Look for reactions when price revisits a zone (confirmation is recommended) Combine with market structure (trend/HH-HL or LH-LL), volume, or candle confirmation Use zones to plan entries, invalidation points, and targets Disclaimer: Not financial advice. No indicator guarantees results.
Pine Script® Indikator
von husni_solo1
LOWESS Adaptive Envelope [BackQuant]LOWESS Adaptive Envelope Overview LOWESS Adaptive Envelope is a nonparametric trend-fit and volatility envelope tool built around LOWESS (Locally Weighted Scatterplot Smoothing). Instead of smoothing price with a fixed-form moving average, this indicator performs a rolling set of local weighted linear regressions across a chosen historical window and stitches those local fits into a single smooth curve that adapts to changing market structure. On top of the fitted curve, the script builds an adaptive envelope whose width is driven by the local magnitude of the model’s residuals (how far price deviates from the fit). That means the envelope automatically expands when the market is noisy or trending aggressively, and contracts when price is stable or mean-reverting cleanly. The output is a complete “structure map”: A LOWESS fitted centerline (trend estimate). Upper and lower adaptive bands derived from smoothed residual spread. A filled region that changes color based on where price sits relative to the fit. Optional extrapolation of the fit and envelope into the future using last slope, with widening uncertainty. An info label showing fit quality (R²), position inside the envelope, and direction. Where LOWESS comes from (and why it is different from moving averages) LOWESS (also written LOESS) is a classic statistical smoothing technique used in exploratory data analysis and robust curve fitting. It became popular because it can approximate complex shapes without assuming a single global model. Instead of forcing the entire window to follow one equation (like a single linear regression or a single moving average kernel), LOWESS fits many small local regressions , each one tailored to its neighborhood. Key distinction: A moving average is a fixed smoother, it applies the same weighting rule everywhere, regardless of whether the market is trending, chopping, or accelerating. LOWESS is a locally re-fitted model, it re-estimates slope and intercept at each point based on nearby data. In price terms: LOWESS is better at “hugging structure” when the market curves or transitions. It can follow gradual regime shifts without the same lag profile as long-window MAs. It does not assume the trend is constant across the whole lookback, it assumes trend can vary locally. What the indicator is modeling Think of the lookback window as a dataset of points: x = bar index (0..length-1 inside the window) y = price For every point i inside that window, the indicator estimates the best local line: y ≈ a + b * x But it does this using only nearby points, and it weights them by distance from i. So the fitted value at i is a locally weighted regression prediction. The final fitted curve is the collection of those predictions across i = 0..length-1. Core mechanics: local weighted linear regression 1) Neighborhood size (bandwidth) The “locality” is controlled by a bandwidth parameter. In this script: h = max(bandwidth * length / 2, 2) Interpretation: h acts like a radius measured in bars inside the fitting window. Lower bandwidth → smaller h → more local fit (more responsive, can track curvature, more sensitive to noise). Higher bandwidth → larger h → more global fit (smoother, more stable, more lag in transitions). So bandwidth controls the bias-variance tradeoff: Small bandwidth: low bias, high variance. Large bandwidth: higher bias, lower variance. 2) Tricube kernel weighting LOWESS requires a weight function that decays smoothly with distance. This script uses the classic tricube kernel : For each candidate point j around target i: u = |i - j| / h If u < 1: - w = (1 - u³)³ If u ≥ 1: - w = 0 Why tricube: Weights go to zero smoothly at the boundary (no sharp cutoff artifacts). Nearby points dominate the fit, distant points contribute little or nothing. It is a standard LOWESS choice because it produces stable smooth curves. 3) Weighted least squares fit For each i, the script accumulates weighted sums over j in the neighborhood: sumW, sumWX, sumWY, sumWXX, sumWXY These correspond to the normal equations for weighted linear regression. From those, it computes: denom = sumW * sumWXX - sumWX² a and b derived from sums (intercept and slope) fitted = a + b * i If denom is too small (numerical instability, insufficient variation), it falls back to the raw price at that i. This entire process is repeated for every i in the window, which is why it is done only on the last bar (performance). Why it fits inside the window rather than a single line A single regression across 200 bars assumes one slope b explains the whole move. Markets rarely do that. LOWESS allows the slope to drift through time, which is exactly what “trend structure” actually does in real price. Residuals: turning model error into volatility structure Once the LOWESS fitted curve is computed, the script measures the residual at each point: res = price - fitted Residuals are the model’s error. In trading terms, residual magnitude is a proxy for: Local noise level. Deviations from trend structure (overextension/underextension). Regime instability (trend is less “explanatory”). The script takes absolute residuals: absRes = |res | This is important because envelope width should reflect spread size regardless of direction. R²: fit quality and regime information The indicator also computes R² over the window: ssRes = Σ(res²) ssTot = Σ((price - meanPrice)²) R² = 1 - ssRes/ssTot Interpretation: Higher R² means the LOWESS fit explains more of the variation inside the window. Lower R² means price is behaving in a way the smooth trend model cannot explain well (chop, shocks, irregular volatility). In markets, R² can be read as “how trend-like vs how noisy” the recent environment is, but remember it depends on your chosen length and bandwidth. Adaptive envelope construction (what makes it “adaptive”) A normal envelope uses a constant width (like ±k*ATR or ±k*stdev). This script does something different: it estimates a local envelope width based on smoothed residual magnitude. 1) Smooth residual magnitude locally It computes a residual averaging window: rWin = max(3, int(h * 0.8)) So the residual smoothing window is linked to the LOWESS locality. If the fit is local, the envelope adapts locally. If the fit is global, the envelope adapts more slowly. Then for each i: envW = mean(absRes over ) * envMult Interpretation: The envelope width is proportional to how much price typically deviates from the fit around that region. envMult is your “how many spreads” multiplier. This creates an envelope that expands and contracts along the curve, not a single constant band. 2) Upper and lower envelopes For each i: upper = fitted + envW lower = fitted - envW This is a model-driven channel. It is not ATR-based directly, it is “error-based.” That makes it very effective at responding to the actual behavior of the market relative to the fitted structure. How to interpret the envelope The centerline is the best local structural estimate. The envelope is the expected deviation range around that structure. Typical readings: Price near centerline: balanced relative to structure. Price riding upper band: strong bullish pressure, trend continuation or overextension depending on context. Price riding lower band: strong bearish pressure, continuation or overextension. Repeated band rejections: mean-reversion regime around the structural fit. Envelope widening: instability rising, volatility expanding, structure less reliable. Envelope tightening: compression, cleaner trend or coiling behavior. Because the band width is based on residuals, widening often coincides with “trend breaks” and regime transitions, not just higher ATR. Color logic and visual encoding The envelope fill color is based on price relative to the most recent fitted value: If close > fitted , bullish color. Else bearish color. So color is a regime/bias cue, not a volatility cue. The bands themselves are drawn with translucent versions of the same regime color, while the fit line is a subtle white. The fill polygon is constructed by: Walking forward through upper points. Then walking backward through lower points. So the shape is closed and can be filled cleanly using polyline fills. Extrapolation: forward projection with widening uncertainty This script can project the fitted line into future bars. This is not forecasting in a statistical sense, it is a deterministic extension based on the current slope. How it extrapolates It takes: slope = fitted - fitted lastFit = fitted Then for i = 1..extrapBars: futureFit = lastFit + slope * i This is a linear continuation of the most recent fit direction. It is meant as a visual guide for “if the current local trend continues.” Why the forward envelope widens The script also grows the envelope slightly with each projected bar: envGrow = lastEnv * 0.01 futureEnv = lastEnv + envGrow * i This is a simple uncertainty widening mechanism. As you move further into the future, you should assume less confidence. The envelope expansion encodes that visually without claiming statistical rigor. Info label: what it reports and how to read it When enabled, the label shows: 1) Direction arrow It computes a slope over the last few fitted points: recentSlope = fitted - fitted (or closest valid index) ▲ if slope >= 0 ▼ if slope < 0 This gives a slightly more stable direction read than one-bar slope. 2) R² Displayed as R²: 0.xxx, representing how well the LOWESS curve explains window variation. 3) Envelope Position (Env Pos) It measures where the current close sits inside the latest envelope: 0% = at lower band 50% = at centerline 100% = at upper band This is extremely useful as a normalized “over/under extension” metric because it is scaled by the adaptive band width, not raw price units. How to use it properly Trend structure and regime filtering Use the fit line as structural trend direction. Use the fill color as quick bias context. Use R² as a “trend quality” read: high R² tends to mean cleaner structure, low R² tends to mean chop or instability. Mean reversion vs continuation This tool can support both styles, but interpretation differs: Mean reversion framing If market repeatedly returns to the fit line, the fit is acting like value. Upper band touches can be “overbought relative to structure.” Lower band touches can be “oversold relative to structure.” Envelope position becomes your normalized stretch gauge. Trend continuation framing In strong trends, price can ride a band rather than revert to centerline. Band riding plus rising fit slope suggests persistence. A sudden failure to hold the band plus falling R² can flag transition risk. Breakdown/transition identification Because the envelope width is residual-driven: If price starts producing large residuals, the envelope expands. That expansion is often a signature of regime change, not just volatility. Combine expansion with slope flattening to identify trend exhaustion. Parameter tuning (what each input really does) Length Defines how much historical data is used for the full fit. Larger length: More stable curve. More computational load. Tends to represent macro structure. Bandwidth Controls locality: Low bandwidth (0.10–0.25): more reactive, tracks curvature and micro-structure, more sensitive to noise. Higher bandwidth (0.30–0.50+): smoother, more stable, more lag in fast turns. Envelope Width (envMult) Scales how wide the adaptive band is relative to the local residual spread: Lower values create a tighter channel, more band interactions. Higher values create a wider channel, fewer touches, better for regime filtering. Extrapolation Bars Purely visual. More bars gives a longer projected structure line and uncertainty region. Limitations and correct expectations LOWESS is powerful, but it is not a magic predictor. LOWESS is descriptive, it fits what happened, then projects linearly if extrapolation is enabled. In sudden shocks or gaps, the fit will update only after the new data is inside the window. Very small bandwidth can overfit local noise, producing misleading curvature. Very large bandwidth can underfit, behaving like a slow regression and missing turning points. R² is window-dependent, a low value does not mean “bad indicator,” it often means “market is not smooth right now.” Summary LOWESS Adaptive Envelope applies locally weighted linear regression (LOWESS) with a tricube kernel to build a smooth, structure-following fitted price curve that adapts to regime changes without relying on a fixed moving-average form. It then converts the model’s local residual spread into a dynamic envelope that expands and contracts with real deviation behavior, provides fit quality via R², normalizes price position inside the band, and optionally extrapolates the latest structural slope forward with widening uncertainty. The result is a robust trend-structure and deviation framework that is equally useful for regime filtering, mean-reversion context, and trend persistence assessment.
Pine Script® Indikator
von BackQuant
Magnetick Prior Levels [MagnetickAI]Magnetick Prior Levels draws subtle reference lines for the key levels that intraday traders watch on 1-minute charts: prior day high/low/close, premarket range, the RTH opening print, and optionally prior week levels. When a level gets "taken out" (price closes beyond it), the line switches from solid to dotted so you can instantly see what's been tested vs. untouched. It also includes a Multi-Day H/L Stack that shows highs and lows from up to 10 prior sessions — but only the ones that have NEVER been taken out. An untouched -3 day high that has survived two full sessions of price action is a stronger reference than one that was already breached and reclaimed. THE 9 PRIMARY LEVELS - Prior Day High (PDH) — soft green line - Prior Day Low (PDL) — soft red line - Prior Day Close (PDC) — gray line, the gap-fill magnet - Prior Day Mid — gray line with 30% transparency, the equilibrium of yesterday's range - Premarket High (PMH) — purple line (requires extended hours data) - Premarket Low (PML) — purple line (requires extended hours data) - RTH Opening Print — blue line, today's 9:30 ET opening tick - Prior Week High (PWH) — light gray, off by default - Prior Week Low (PWL) — light gray, off by default MULTI-DAY H/L STACK Shows highs and lows from -1 to -N prior sessions (configurable, default 5 days). Only levels that have never been taken out in any subsequent session are drawn. Once price closes beyond a historical level during any session, that level is permanently hidden. - Highs in soft green, lows in soft red (same palette as PDH/PDL) - Older levels are progressively more transparent - Dashed line style to visually distinguish from primary levels - Labels show day offset: "-1D H", "-2D L", etc. The logic: if -4 day's high has survived 3 full sessions without being breached, it's likely a meaningful resistance level. If it was taken out 2 days ago, you don't need to see it. "TAKEN OUT" BEHAVIOR Primary levels (PDH, PDL, PDC, etc.) track whether price has closed on the opposite side from where the session opened. Once taken out: - The line style changes from solid to dotted - The color fades (extra transparency added) - The change is permanent for the rest of the session Multi-Day levels use a stricter rule: if a level was taken out at ANY point since it was established (across any session), it's hidden entirely rather than shown as dotted. The Opening Print is exempt — it's today's reference point, not a prior level to be "broken." HOW TO USE IT These levels are context, not signals. They're designed to sit quietly behind your hand-drawn levels and other indicators without competing for attention. All lines are width 1 and there are no background fills or proximity highlights. When your setup lines up near an untouched (solid) level — PDH, PMH, or PDC — that's useful confirmation. When a level has already been taken out (dotted), it's still worth watching for a retest, but it carries less weight. The Multi-Day stack helps you spot levels that have survived multiple sessions. If you see a cluster of untouched -2D, -3D, and -4D highs near the same price, that's a significant resistance zone that multiple sessions failed to break. SETTINGS - Toggle each of the 9 primary levels independently - Multi-Day H/L Stack: on/off toggle + configurable number of days (1-10) - Configurable session times (default: 9:30-16:00 ET market, 4:00-9:30 premarket) - Timezone selection (ET, CT, PT, UTC) - Label offset (how far right of current bar to place labels) - Taken-out transparency (how much to fade breached primary levels) ALERTS - Individual alerts when each primary level is first taken out during the session - "Any Level Taken Out" catch-all alert LIMITATIONS - Premarket levels require extended hours data enabled on your chart - Only draws on the current trading day — no historical levels shown - Multi-Day levels need enough chart history to populate (N+1 trading days) - Prior Week levels use request.security() on the weekly timeframe - If price opens exactly at a level (extremely rare), that level won't trigger a taken-out state - Best suited for 1-minute charts; Opening Print precision decreases on higher timeframes - Multi-Day -1D levels are automatically hidden when PDH/PDL are enabled (they're identical values) Built by MagnetickAI — open source tools for active traders.
Pine Script® Indikator
von MagnetickAI