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指标和策略

Crypto Breakout Buy/Sell Sequence ⚙️ Components & Sequence Multiple Timeframe (What It Does) 1. Bollinger Bands – Form the foundation by measuring volatility and creating the dynamic range where squeezes and breakouts occur. 2. Squeeze Dots – Show when price compresses inside the bands, signaling reduced volatility before expansion. 3. Breakout Event (Brk Dot) – Fires when price expands beyond the squeeze zone, confirming volatility expansion. (This paints Intra, before candle close) 4. Buy Signal – Confirms entry after a breakout is validated. (This paints at candle close) 5. Pump Signal – Flags sudden surges that extend sharply from the bands, often linked to strong inflows. 6. Momentum Stream – Tracks the strength of movement following the breakout, from continuation (🟢) to slowing (🟡) to exhaustion (🔴). (Resets at Pump Signal) 7. Overbought Indicator – Confirms when momentum has reached overheated conditions, often aligning with band extremes. 8. Sell Signal – Prints when exhaustion/reversal conditions are met, closing the trade cycle. The Crypto Breakout Buy/Sell Sequence is a no-repaint event indicator that maps a full trade cycle using Bollinger-band-based volatility states: Bollinger Bands → Squeeze → Breakout → Buy → Pump → Momentum → Top Test → Overbought → Sell. Each stage is rule-based and designed to be read on standard candlesticks. How It Works (System Logic) Volatility framework: Bollinger Bands define dynamic range and compression/expansion. Initiation: Squeeze → Breakout confirms expansion; Buy validates participation after expansion begins. Management: Pump highlights unusual acceleration; Momentum stream tracks continuation → slowing → exhaustion. Exhaustion/Exit: Top Testing + Overbought build the exhaustion case; Sell marks the sequence end. How To Use (Quick Guide) Wait for Squeeze → Breakout → Buy to establish a structured start. Manage with Momentum: 🟢 continuation, 🟡 slowing, 🔴 exhaustion pressure. Monitor extremes: Top Testing and/or Overbought = tighten risk. Exit on Sell or on your risk rules when exhaustion builds. Limitations & Good Practice Signals reflect price/volatility behavior, not certainty. Strong trends can remain extended; Overbought/Top Test ≠ instant reversal. Always confirm with your own risk rules, position sizing, and market context. Initial public release: integrated Squeeze/Breakout/Buy → Momentum → Exhaustion → Sell cycle; improved label clarity; cleaned defaults. Disclaimer For educational purposes only. Not financial advice. Past performance does not guarantee future results. Test before live use. Thank You
Pine Script®指标
由ictc3d提供
VHB by bigmmVolume-Based Support/Resistance Levels Indicator identifies significant price levels based on high-volume trading activity across three timeframes (4H, D, W). The script draws horizontal lines at key support/resistance levels where trading volume exceeded 60% of the maximum volume observed over the previous 499 periods. Analyzes volume spikes on 4-hour, daily, and weekly timeframes Displays colored lines (green for bullish candles, red for bearish candles) Maintains only the 5 most recent significant levels to avoid chart clutter Labels each line with its respective timeframe (4H, 1D, 1W) Lines extend in real-time to show current relevance of each level Traders can use these volume-based levels to identify potential support/resistance zones and make informed decisions about entry/exit points, recognizing areas where significant trading activity previously occurred.
Pine Script®指标
由BIGMarketMaker提供
Day Zero Fakeout Detector MTFDay Zero Template (Stacey Burke) Definition: “Day Zero” is essentially the setup day in Stacey Burke’s playbook. It’s the day when the market creates a significant inflection — often forming a Peak Formation High (PFH) or Peak Formation Low (PFL). It usually occurs after 3 days of directional movement (the classic 3-day cycle Stacey teaches). Example: Day 1: Breakout expansion. Day 2: Continuation or consolidation. Day 3: Exhaustion + reversal (forms PFH/PFL). Day Zero: The day after this reversal template begins — where traders start looking for measured moves back inside the range. 👉 Day Zero = the transition day where the new weekly cycle (up or down) begins. 2️⃣ Peak Formation Highs (PFH) and Lows (PFL) A PFH occurs when the market fails above prior highs (often with stop hunts/fakeouts). A PFL occurs when the market fails below prior lows. These PFHs/PFLs mark the anchor points for the next 3-day cycle. Once identified, they become reference levels: Above PFH → fade long traps (short bias). Below PFL → fade short traps (long bias). 👉 This is where rectangles (Peter Brandt style) can come in handy to box in the PFH/PFL area. 3️⃣ Peter L. Brandt – Rectangles & Classical Charting Peter Brandt’s approach (classical charting) complements Stacey’s playbook: Rectangles are consolidation zones (value areas). When a PFH or PFL forms, price often consolidates in a rectangle range. A breakout from that rectangle confirms direction (continuation or reversal). The measured move target is typically the height of the rectangle projected from the breakout point. 👉 Applied to Day Zero: PFH/PFL = the extreme boundary of the rectangle. A breakout from the rectangle in the opposite direction = confirmation of Day Zero reversal. 4️⃣ How They Fit Together Stacey Burke: Focus on intraday cycles, 3-day cycle, Day Zero as the reset after PFH/PFL. Peter Brandt: Focus on classical rectangle consolidation and breakout targets. Integration: Day Zero = when you’ve spotted a PFH or PFL and are preparing for the new cycle to begin. Mark the PFH/PFL → draw a rectangle around the consolidation. Wait for breakout/acceptance beyond rectangle → trade toward measured move (often aligning with Stacey’s Day 1/Day 2 directional bias). ✅ Example in practice: Monday & Tuesday rally → Wednesday exhaustion → PFH forms. Thursday = Day Zero (new short bias starting). Rectangle consolidation forms under PFH. Breakout below rectangle = signal. Target = rectangle height measured down → often aligns with yesterday’s lows or prior session value area.
Pine Script®指标
由Ross-J-Burland提供
XAUUSD Buy/Sell Alerts with SL & TPThis custom TradingView indicator identifies high-probability buy and sell signals on XAUUSD using EMA crossovers combined with RSI confirmation. Designed for precision entries, it automatically calculates optimal Stop Loss (SL) and Take Profit (TP) levels based on user-defined pip distances. Key Features: Fast and Slow EMA crossover for trend direction RSI filter for momentum confirmation Dynamic SL and TP levels to manage risk and reward Visual buy/sell signals plotted on chart Real-time alerts with detailed messages including entry price, SL, and TP Suitable for multiple timeframes and trading styles Perfect for traders seeking clear signals with built-in risk management for scalping or swing trading XAUUSD.
Pine Script®指标
由alexandrossolomou1提供
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®指标
由fts4sure提供
ConeWave MACoRa Wave is a custom-weighted moving average designed to adapt intelligently to market dynamics. It builds upon the foundational logic of the Comp_Ratio_MA by @redktrader, incorporating a compound ratio-based weighting curve that emphasizes recent price action while preserving smoothness and structure with pinescript version 6. This version introduces modular enhancements, including: A Comp Ratio Multiplier for fine-tuned responsiveness Optional Auto Smoothing based on wave length Streamlined plotting for clarity and performance Whether you're confirming market structure, identifying trend shifts, or seeking a cleaner alternative to noisy indicators, CoRa Wave offers a visually intuitive and mathematically elegant solution. 🛠 Reimagined by @atulgalande75 — optimized for traders who value precision, adaptability, and clean charting. Original concept by @redktrader.
Pine Script®指标
由AtulGalande提供
Real Close Overlay for Heiken AshiDescription: The Real Close on Heiken Ashi indicator solves one of the biggest problems traders face when using Heiken Ashi candles, the fact that the displayed close is not the true market close. By default, Heiken Ashi modifies the open, high, low, and close values to create smoother-looking candles. This makes them great for identifying trends, but it also means entries and exits can be misleading if you rely only on the chart. This tool fixes that by overlaying the real closing price (traditional candlestick close) directly onto your Heiken Ashi chart. How It Works: - Plots the true closing price of each bar (from standard candles) onto your Heiken Ashi chart. - Displays a small, unobtrusive marker (black dot by default) so you can instantly see where price actually closed. Not only does it plot the close, but it moves with real price as the candle is forming so price action is not lost. - Updates in real time with every new bar. Why It Matters: - Use Heiken Ashi for trend clarity without losing price accuracy. - Avoid entering/exiting based on inaccurate Heiken Ashi body closes. - Improves stop-loss and take-profit placement by showing where price truly ended the candle. - Essential for scalpers and short-term traders who need precision without losing true price action. Best Uses: - Combine with Heiken Ashi for momentum trading. - Verify breakout confirmations against the real close. - Use as an execution reference if you trade a HA-based system. Disclaimer: This script is for educational purposes only. It is open source and fully accessible. It does not provide financial advice. Always test thoroughly before applying to live markets.
Pine Script®指标
由One_To_Two_Trades提供
Pivot Points. High & Lows By Reversal PercentageLibrary "Pivot Points. High & Lows By Reversal Percentage" by Jal9000 This Pine Script library provides a robust function for identifying and tracking pivot points (reversal points) in price data, suitable for integration into custom trading indicators and strategies. 🛠️ Main Features: - ✅ Identifies pivot highs and lows based on configurable price movement thresholds. - ✅ Lightweight. No candle backtracing used. Much less computation heavy. - ✅ Supports multiple calls (with different values) within a single script. - ✅ Compatible with request.security for multi-timeframe analysis. - ✅ Returns both confirmed and temporary pivots for flexible integration. - ✅ Pinescript V5 and V6 compliant code. Purpose: The pivots library enables Pine Script developers to easily add pivot point detection to their scripts. It identifies significant price reversals by evaluating price movements against a minimum range threshold ( min_range_pct ) and confirming reversals based on a percentage ( reversal_pct ) of the prior trend’s magnitude. The library supports multiple simultaneous calls with different settings, making it ideal for multi-timeframe strategies. How It Works: The library’s f_calculatePivot function tracks price movements to detect pivot points: Minimum Range Threshold : A potential pivot is considered if the price moves beyond the min_range_pct percentage of the current high (for a high pivot) or low (for a low pivot), ensuring sufficient movement. Reversal Confirmation : A pivot is confirmed if the price reverses from the potential pivot by at least the reversal_pct percentage of the distance between the last confirmed pivot and the current potential pivot, measuring the retracement relative to the prior trend’s magnitude. The function alternates between tracking highs (in an uptrend) and lows (in a downtrend), updating the trend when a pivot is confirmed. State management uses an array of pivot_state objects, allowing independent calculations for different timeframes and min_range_pct values within the same script. ## Technical Reference Functions: f_calculatePivot(series float _high, series float _low, float _min_range_pct, float _reversal_pct) → - Parameters: _high : The high price series (e.g., high or math.max(open, close) ). _low : The low price series (e.g., low or math.min(open, close) ). _min_range_pct : The minimum percentage price movement to consider a potential pivot. _reversal_pct : The percentage of the prior trend’s distance required to confirm a pivot. - Returns: A tuple containing: isNewPivot : Boolean indicating if a new pivot was confirmed. last_confirmed_pivot : The most recent confirmed pivot (type pivot ). temp_pivot : The current temporary pivot (type pivot ). Pivot type: idx (series int) : Bar index of the pivot. typ (series int) : Type of pivot ( PIVOT_HIGH or PIVOT_LOW ). prc (series float) : Price of the pivot. tme (series int) : Timestamp of the pivot. Constants (internal): TREND_LONG , TREND_SHORT : Trend direction indicators (1, -1). PIVOT_HIGH , PIVOT_LOW : Pivot type indicators (1, -1). ✨ Example of Use: //@version=5 indicator("Pivot Example", overlay=true) import jal9000/pivots/1 as pivots // Inputs min_range_pct = input.float(20.0, 'Min Range %') reversal_pct = input.float(30.0, 'Reversal %') ignore_wick = input.bool(true, 'Ignore wick') h = ignore_wick ? math.max(open, close) : high l = ignore_wick ? math.min(open, close) : low // Call the function with high, low, and input parameters = pivots.f_calculatePivot(h, l, min_range_pct, reversal_pct) // Variable to store previous confirmed pivot outside the function var pivots.pivot prev_confirmed_pivot = na // Draw the line if a new pivot is confirmed and previous pivot exists if is_new_pivot if not na(prev_confirmed_pivot) and not na(new_confirmed_pivot) line.new(x1 = prev_confirmed_pivot.idx, y1 = prev_confirmed_pivot.prc, x2 = new_confirmed_pivot.idx, y2 = new_confirmed_pivot.prc, color = color.blue, width = 1) prev_confirmed_pivot := new_confirmed_pivot ## Release Notes v1 - Initial release of the pivots library with f_calculatePivot function for detecting pivot points and supporting multiple configurations and timeframes. v2 - Code is Pinescript V6 ready. Remains identified as V5, but changing the version number is the only thing that is required to be v6.
Pine Script®库
由jal9000提供
2
Secret bubbleSecret bubble Why Might It Be Called "Bubbles"? Although not officially named so, some traders or platforms might refer to Bollinger Bands as "bubbles" because: The bands visually surround the price like a bubble. During low volatility, the bands form a tight "bubble" around price. Breakouts look like the price "popping out" of a bubble. Hence, the nickname "пузырьки" (bubbles) could be a colloquial or visual metaphor for Bollinger Bands in Russian-speaking trading communities. Conclusion While there is no official technical indicator called "Bubbles", the term likely refers to Bollinger Bands due to their visual appearance and function. This powerful tool helps traders assess volatility, spot potential reversals, and time entries and exits. When combined with other analysis methods, Bollinger Bands remain a cornerstone of modern technical trading. 🔧 Tip: You can find Bollinger Bands on almost every trading platform (TradingView, MetaTrader, ThinkorSwim) by searching "Bollinger Bands" in the indicators list.
Pine Script®指标
由SaNtA_1408提供
ForecastForecast (FC), indicator documentation Type: Study, not a strategy Primary timeframe: 1D chart, most plots and the on-chart table only render on daily bars Inspiration: Robert Carver’s “forecast” concept from Advanced Futures Trading Strategies, using normalized, capped signals for comparability across markets ⸻ What the indicator does FC builds a volatility-normalized momentum forecast for a chosen symbol, optionally versus a benchmark. It combines an EWMAC composite with a channel breakout composite, then caps the result to a common scale. You can run it in three data modes: • Absolute: Forecast of the selected symbol • Relative: Forecast of the ratio symbol / benchmark • Combined: Average of Absolute and Relative A compact table can summarize the current forecast, short-term direction on the forecast EMAs, correlation versus the benchmark, and ATR-scaled distances to common price EMAs. ⸻ PineScreener, relative-strength screening This indicator is excellent for screening on relative strength in PineScreener, since the forecast is volatility-normalized and capped on a common scale. Available PineScreener columns PineScreener reads the plotted series. You will see at least these columns: • FC, the capped forecast • from EMA20, (price − EMA20) / ATR in ATR multiples • from EMA50, (price − EMA50) / ATR in ATR multiples • ATR, ATR as a percent of price • Corr, weekly correlation with the chosen benchmark Relative mode and Combined mode are recommended for cross-sectional screens. In Relative mode the calculation uses symbol / benchmark, so ensure the ratio ticker exists for your data source. ⸻ How it works, step by step 1. Volatility model Compute exponentially weighted mean and variance of daily percent returns on D, annualize, optionally blend with a long lookback using 10y %, then convert to a price-scaled sigma. 2. EWMAC momentum, three legs Daily legs: EMA(8) − EMA(32), EMA(16) − EMA(64), EMA(32) − EMA(128). Divide by price-scaled sigma, multiply by leg scalars, cap to Cap = 20, average, then apply a small FDM factor. 3. Breakout momentum, three channels Smoothed position inside 40, 80, and 160 day channels, each scaled, then averaged. 4. Composite forecast Average the EWMAC composite and the breakout composite, then cap to ±20. Relative mode runs the same logic on symbol / benchmark. Combined mode averages Absolute and Relative composites. 5. Weekly correlation Pearson correlation between weekly closes of the asset and the benchmark over a user-set length. 6. Direction overlay Two EMAs on the forecast series plus optional green or red background by sign, and optional horizontal level shading around 0, ±5, ±10, ±15, ±20. ⸻ Plots • FC, capped forecast on the daily chart • 8-32 Abs, 8-32 Rel, single-leg EWMAC plus breakout view • 8-32-128 Abs, 8-32-128 Rel, three-leg composite views • from EMA20, from EMA50, (price − EMA) / ATR • ATR, ATR as a percent of price • Corr, weekly correlation with the benchmark • Forecast EMA1 and EMA2, EMAs of the forecast with an optional fill • Backgrounds and guide lines, optional sign-based background, optional 0, ±5, ±10, ±15, ±20 guides Most plots and the table are gated by timeframe.isdaily. Set the chart to 1D to see them. ⸻ Inputs Symbol selection • Absolute, Relative, Combined • Vs. benchmark for Relative mode and correlation, choices: SPY, QQQ, XLE, GLD • Ticker or Freeform, for Freeform use full TradingView notation, for example NASDAQ:AAPL Engine selection • Include: • 8-32-128, three EWMAC legs plus three breakouts • 8-32, simplified view based on the 8-32 leg plus a 40-day breakout EMA, applied to the forecast • EMA1, EMA2, with line-width controls, plus color and opacity Volatility • Span, EW volatility span for daily returns • 10y %, blend of long-run volatility • Thresh, Too volatile, placeholders in this version Background • Horizontal bg, level shading, enabled by default • Long BG, Hedge BG, colors and opacities Show • Table, Header, Direction, Gain, Extension • Corr, Length for correlation row Table settings • Position, background, opacity, text size, text color Lines • 0-lines, 10-lines, 5-lines, level guides ⸻ Reading the outputs • Forecast > 0, bullish tilt; Forecast < 0, bearish or hedge tilt • ±10 and ±20 indicate strength on a uniform scale • EMA1 vs EMA2 on the forecast, EMA1 above EMA2 suggests improving momentum • Table rows, label colored by sign, current forecast value plus a green or red dot for the forecast EMA cross, optional daily return percent, weekly correlation, and ATR-scaled EMA9, EMA20, EMA50 distances ⸻ Data handling, repainting, and performance • Daily and weekly series are fetched with request.security(). • Calculations use closed bars, values can update until the bar closes. • No lookahead, historical values do not repaint. • Weekly correlation updates during the week, it finalizes on weekly close. • On intraday charts most visuals are hidden by design. ⸻ Good practice and limitations • This is a research indicator, not a trading system. • The fixed Cap = 20 keeps a common scale, extreme moves will be clipped. • Relative mode depends on the ratio symbol / benchmark, ensure both legs have data for your feed. ⸻ Credits Concept inspired by Robert Carver’s forecast methodology in Advanced Futures Trading Strategies. Implementation details, parameters, and visuals are specific to this script. ⸻ Changelog • First version ⸻ Disclaimer For education and research only, not financial advice. Always test on your market and data feed, consider costs and slippage before using any indicator in live decisions.
Pine Script®指标
由BB_9791提供
Relative Strength Heat [InvestorUnknown]The Relative Strength Heat (RSH) indicator is a relative strength of an asset across multiple RSI periods through a dynamic heatmap and provides smoothed signals for overbought and oversold conditions. The indicator is highly customizable, allowing traders to adjust RSI periods, smoothing methods, and visual settings to suit their trading strategies. The RSH indicator is particularly useful for identifying momentum shifts and potential reversal points by aggregating RSI data across a range of periods. It presents this data in a visually intuitive heatmap, with color-coded bands indicating overbought (red), oversold (green), or neutral (gray) conditions. Additionally, it includes signal lines for overbought and oversold indices, which can be smoothed using RAW, SMA, or EMA methods, and a table displaying the current index values. Features Dynamic RSI Periods: Calculates RSI across 31 periods, starting from a user-defined base period and incrementing by a specified step. Heatmap Visualization: Displays RSI strength as a color-coded heatmap, with red for overbought, green for oversold, and gray for neutral zones. Customizable Smoothing: Offers RAW, SMA, or EMA smoothing for overbought and oversold signals. Signal Lines: Plots scaled overbought (purple) and oversold (yellow) signal lines with a midline for reference. Information Table: Displays real-time overbought and oversold index values in a table at the top-right of the chart. User-Friendly Inputs: Allows customization of RSI source, period ranges, smoothing length, and colors. How It Works The RSH indicator aggregates RSI calculations across 31 periods, starting from the user-defined Starting Period and incrementing by the Period Increment. For each period, it computes the RSI and determines whether the asset is overbought (RSI > threshold_ob) or oversold (RSI < threshold_os). These states are stored in arrays (ob_array for overbought, os_array for oversold) and used to generate the following outputs: Heatmap: The indicator plots 31 horizontal bands, each representing an RSI period. The color of each band is determined by the f_col function: Red if the RSI for that period is overbought (>threshold_ob). Green if the RSI is oversold (
Pine Script®指标
由InvestorUnknown提供
Primitive Delta DivergencePrimitive Delta Divergence This indicator detects volume-price divergences by analyzing the relationship between price direction and volume bias over a rolling lookback period, revealing potential momentum shifts before they become apparent in price action alone. Instead of relying solely on price movements, you can identify moments when volume sentiment contradicts price direction — a core concept borrowed from footprint chart analysis, adapted for traditional bar charts. For example, when price moves higher but volume is predominantly bearish, or when price declines while volume shows bullish accumulation. 🔹 How it works Lookback Period (n) → defines the rolling window for analyzing price and volume relationships Creates a "meta-candle" from the lookback period, comparing its open vs. close for price bias Volume classification → separates each bar's volume into bullish (green candles), bearish (red candles), or neutral (doji candles) Volume bias calculation → generates a continuous score (-1 to +1) representing the directional volume pressure Plots divergence signals when price direction and volume bias disagree 🔹 Use cases Spot early momentum exhaustion when price and volume move in opposite directions Identify potential reversal zones where volume suggests underlying weakness or strength Enhance entry/exit timing by incorporating volume-based confirmation alongside price action Apply footprint-style analysis to any timeframe without specialized charting tools ✨ Primitive Delta Divergence reveals the hidden story volume tells about price, uncovering divergences that traditional indicators might miss.
Pine Script®指标
由bfoster238提供
2