Buy Sell Magic Rework📌 Purpose
This script is a reworked version of the Parabolic SAR strategy, with an optional ZigZag filter to confirm reversal points.
It helps traders identify potential trend reversals with reduced noise compared to the standard SAR.
🧠 How It Works
1. Parabolic SAR Flip Signals
Buy Signal: Triggered when SAR flips from above price to below price.
Sell Signal: Triggered when SAR flips from below price to above price.
(Default SAR parameters: Start = 0.02, Increment = 0.02, Max = 0.2)
2. ZigZag Filter (Optional)
When Use ZigZag Filter = true:
The script confirms reversals only at significant pivots (swing highs/lows) detected by the ZigZag algorithm over the selected ZigZag Period (default = 14 bars).
Buy Signal: Appears only when a new pivot low is detected.
Sell Signal: Appears only when a new pivot high is detected.
3. Trade-Off
Without ZigZag: More signals, more noise.
With ZigZag: Fewer signals, but stronger confirmation and reduced false entries.
📈 How to Use
Signals appear as green arrows for buy and red arrows for sell.
Works well for:
Trend reversal detection.
Swing trading confirmation.
Filtering entries for other systems.
Recommended Timeframes: 15m, 1h, 4h.
Markets: Forex, Crypto, Stocks.
⚙️ Inputs
ZigZag Period (bars for pivot detection)
SAR Start / Increment / Max (SAR parameters)
Use ZigZag Filter (toggle for confirmation)
⚠️ Disclaimer
This script is for educational purposes only. It does not constitute financial advice.
Always test thoroughly before live trading.
Trend Analizi
Master Trend Navigator/趋势大师导航仪[4H] by mrlazycat趋势大师导航仪使用说明
⚠ 非常重要，使用指标前请认真阅读这个使用说明
指标核心功能 本指标通过分析比特币的成交量、动能指标（MACD）、相对强弱指数（RSI）、趋势强度和成交量比率，生成在-1到1之间波动的趋势大师导航仪，帮助判断买卖时机。指标最佳适用场为4小时（4H）图表，适合1-2周的中短期交易。该趋势大师导航仪适用于 BTC,ETH, DOGE 等现货成交量大的虚拟货币
趋势曲线解读指南
① 市场状态（曲线颜色）
暗紫色：区间震荡市场 浅红色：弱多头趋势 深红色：强多头趋势 浅绿色：弱空头趋势 深绿色：强空头趋势
② 关键信号区域
红色区域（超买）：趋势曲线 ≥ 0.6 时，可能出现回调风险
绿色区域（超卖）：趋势曲线 ≤ -0.615 时，可能出现反弹机会
③ 锁定机制
在强多头趋势（深红色）和深绿色（强空头趋势）和部分弱趋势期间：
如果趋势曲线突破红色区域（超买）且市场趋势强度保持在强趋势或较强的弱趋势，趋势曲线会锁定在0.7附近（原始曲线以灰色继续）。
如果趋势曲线跌破绿色区域（超卖）且市场趋势强度保持在强趋势或较强的弱趋势，趋势曲线会锁定在-0.7附近（原始曲线以灰色继续）。 这表示趋势可能继续发展，建议等待锁定期结束后再进行操作。
✅ 极端多头趋势的特殊案例：（如ETH在2025年7月10日到20日，趋势曲线一直维持红色，意味着多头趋势不变。但这段时间ETH的趋势曲线曾跌到超卖区，因此曲线曾在底部锁定3个K线的时间，这意味着是多头右侧追多的机会。）
交易信号
① 超买超卖信号
红色区域（超买）：趋势曲线 ≥ 0.6 时，可能出现回调风险
绿色区域（超卖）：趋势曲线 ≤ -0.615 时，可能出现反弹机会
② 成交量爆发信号
顶部红色圆圈：代表成交量比率的爆发期，可能在当前或未来1-6根K线内出现阶段性高点。
底部黄色圆圈：代表成交量比率的潜在底部机会，可能在当前或未来1-6根K线内出现阶段性低点。
✅ 注意连续大量的顶部红色圆圈和底部黄色圆圈的出现，这意味着极端行情的出现。
③ 背离信号
顶背离（卖出信号）：红色倒三角图标（标记为Bearish divergence\Sell）出现在趋势曲线顶部，当价格创新高但趋势曲线未创新高时触发，预示大幅回调风险。
底背离（买入信号）：绿色正三角图标（标记为Bullish divergence\Buy）出现在趋势曲线底部，当价格创新低但趋势曲线未创新低时触发，预示底部反弹机会。
使用注意事项
① 交易所推荐：同时使用币安(Binance)和OKX的BTC/USDT现货数据（不同交易所的量能差异可能影响信号准确性）。
② 特殊行情优化：已针对2024-2025年比特币ETF上市后的低波动行情调整参数，未来将持续根据市场变化优化。
③ 强趋势操作提示：当趋势曲线锁定在超买或超卖区，应减少逆势操作。
④ 首次使用建议：观察历史行情以验证信号特征，震荡市捕捉反转点，趋势市识别延续信号。
最简单操作要诀
✅ 底部抄底组合：强空头趋势转弱空头 + 绿色超卖区 + 底背离绿色三角 + 底部黄色成交量圈
✅ 顶部逃顶组合：强多头趋势转弱多头趋势转换 + 红色超买区 + 顶背离红色三角 + 顶部红色成交量圈
✅ 趋势延续信号：趋势曲线锁定在 ±0.7 时，耐心等待锁定解除
推特联系：Jeffmo0769
Trend Master Navigator User Guide
⚠ Important: Please read this guide carefully before using the indicator
Core Functionality
This indicator analyzes Bitcoin's trading volume, MACD, RSI, trend strength, and volume ratio to generate the Trend Master Navigator, which oscillates between -1 and 1 to assist in buy/sell decisions. The indicator is best suited for 4-hour (4H) charts and is ideal for 1-2 week swing trading.The Trend Master Navigator is suitable for cryptocurrencies with high spot trading volumes, such as BTC ， ETH , and DOGE .
Interpreting the Trend Curve
① Market States (Curve Colors)
Dark Purple: Range-bound market
Light Red: Weak bullish trend
Deep Red: Strong bullish trend
Light Green: Weak bearish trend
Deep Green: Strong bearish trend
② Key Signal Zones
Red Zone (Overbought): Trend curve ≥ 0.6 → Potential pullback risk
Green Zone (Oversold): Trend curve ≤ -0.615 → Potential rebound opportunity
③ Locking Mechanism
During strong bullish trends (deep red) and strong bearish trends (deep green), and partial weak trends:
If the trend curve breaks above the red zone (overbought) and market trend strength remains in a strong trend or robust weak trend, the trend curve will lock near 0.7 (original curve continues in gray).
If the trend curve breaks below the green zone (oversold) and market trend strength remains in a strong trend or robust weak trend, the trend curve will lock near -0.7 (original curve continues in gray).
This indicates that the trend may continue, and it is advisable to wait until the lock period ends before taking action.
✅ In the context of extreme bullish trends (e.g., ETH from July 10 to 20, 2025, where the trend curve remained red, indicating a persistent bullish trend), even though ETH's trend curve once dipped into the oversold zone, causing the curve to lock at the bottom for 3 K-line periods, this signifies a right-side buying opportunity during the bullish trend.
Trading Signals
① Overbought/Oversold Signals
Red Zone (Overbought): Trend curve ≥ 0.6 → Potential pullback risk
Green Zone (Oversold): Trend curve ≤ -0.615 → Potential rebound opportunity
② Volume Explosion Signals
Top Red Circle: Represents a volume ratio explosion period, possibly indicating a phase peak within the current or next 1-6 bars.
Bottom Yellow Circle: Represents a potential bottom opportunity in volume ratio, possibly indicating a phase trough within the current or next 1-6 bars.
✅ Pay attention to the continuous appearance of top red circles and bottom yellow circles, as this signals the emergence of extreme market conditions.
③ Divergence Signals
Bearish Divergence (Sell): Red inverted triangle icon (marked as Bearish divergence\Sell) appears at the trend curve top when the price makes a new high, but the trend curve does not; this indicates a significant pullback risk.
Bullish Divergence (Buy): Green upright triangle icon (marked as Bullish divergence\Buy) appears at the trend curve bottom when the price makes a new low, but the trend curve does not; this indicates a potential bottom rebound opportunity.
Other Usage Notes
① Exchange Recommendation: Use Binance and OKX BTC/USDT spot data simultaneously (volume discrepancies across different exchanges may affect signal accuracy).
② Special Market Optimization: Parameters have been adjusted for the low-volatility era following the Bitcoin ETF launch (2024-2025) and will continue to be optimized based on market changes.
③ Strong Trend Operation Tips: When the trend curve is locked in overbought or oversold zones, reduce counter-trend operations.
④ First Use Recommendation: Observe historical market trends to validate signal characteristics. Capture reversal points in range-bound markets and identify continuation signals in trending markets.
Simplest Trading Tactics
✅ Bottom Picking Setup: Transition from strong bearish trend to weak bearish + Green oversold zone + Bullish divergence green triangle + Bottom yellow volume circle
✅ Top Selling Setup: Transition from strong bullish trend to weak bullish trend + Red overbought zone + Bearish divergence red triangle + Top red volume circle
✅ Trend Continuation Signal: Trend curve locked at ±0.7 → Wait patiently for lock release
Contact on X: Jeffmo0769
Price-Volume Strength Meter (Color Zones)The Price-Volume Strength Meter is a custom-built tool designed to help traders assess market strength by analyzing both price action and volume behavior. It generates a smoothed strength signal and color-coded visualization for quick decision-making.
🔍 Key Features:
✅ Dual Momentum Analysis – Evaluates price and volume movements to identify strong or weak trends.
🎨 Color Zones –
🟢 Green: Bullish strength
🔴 Red: Bearish strength
🟡 Yellow: Sideways or indecisive zone
🧠 Smoothed Output – Uses internal smoothing to reduce noise and provide a cleaner trend view.
📊 Strength Range:
+100: Strong Bullish
+50: Weak Bullish
0: Neutral
-50: Weak Bearish
-100: Strong Bearish
This indicator can be used as a market strength confirmation tool for trend-following strategies or to filter out sideways/no-trade zones. Ideal for intraday to swing trading setups.
Smart Money Breakout Channels [AlgoAlpha]🟠 OVERVIEW
This script draws breakout detection zones called “Smart Money Breakout Channels” based on volatility-normalized price movement and visualizes them as dynamic boxes with volume overlays. It identifies temporary accumulation or distribution ranges using a custom normalized volatility metric and tracks when price breaks out of those zones—either upward or downward. Each channel represents a structured range where smart money may be active, helping traders anticipate key breakouts with added context from volume delta, up/down volume, and a visual gradient gauge for momentum bias.
🟠 CONCEPTS
The script calculates normalized price volatility by measuring the standard deviation of price mapped to a scale using the highest and lowest prices over a set lookback period. When normalized volatility reaches a local low and flips upward, a boxed channel is drawn between the highest and lowest prices in that zone. These boxes persist until price breaks out, either with a strong candle close (configurable) or by touching the boundary. Volume analysis enhances interpretation by rendering delta bars inside the box, showing volume distribution during the channel. Additionally, a real-time visual “gauge” shows where volume delta sits within the channel range, helping users spot pressure imbalances.
🟠 FEATURES
Automatic detection and drawing of breakout channels based on volatility-normalized price pivots.
Optional nested channels to allow multiple simultaneous zones or a clean single-zone view.
Gradient-filled volume gauge with dynamic pointer to show current delta pressure within the box.
Three volume visualization modes: raw volume, comparative up/down volume, and delta.
Alerts for new channel creation and confirmed bullish or bearish breakouts.
🟠 USAGE
Apply the indicator to any chart. Wait for a new breakout box to form—this occurs when volatility behavior shifts and a stable range emerges. Once a box appears, monitor price relative to its boundaries. A breakout above suggests bullish continuation, below suggests bearish continuation; signals are stronger when “Strong Closes Only” is enabled.
Watch the internal volume candles to understand where buy/sell pressure is concentrated during the box. Use the gauge on the right to interpret whether net pressure is building upward or downward before breakout to anticipate the direction.
Use alerts to catch breakout events without needing to monitor the chart constantly 🚨.
Buy The Dip - ENGThis script implements a grid trading strategy for long positions in the USDT market. The core idea is to place a series of buy limit orders at progressively lower prices below an initial entry point, aiming to lower the average entry price as the price drops. It then aims to exit the entire position when the price rises a certain percentage above the average entry price.
Here's a detailed breakdown:
1. Strategy Setup (`strategy` function):
`'거미줄 자동매매 250227'`: The name of the strategy.
`overlay = true`: Draws plots and labels directly on the main price chart.
`pyramiding = 15`: Allows up to 15 entries in the same direction (long). This is essential for grid trading, as it needs to open multiple buy orders.
`initial_capital = 600`: Sets the starting capital for backtesting to 600 USDT.
`currency = currency.USDT`: Specifies the account currency as USDT.
`margin_long/short = 0`: Doesn't define specific margin requirements (might imply spot trading logic or rely on exchange defaults if used live).
`calc_on_order_fills = false`: Strategy calculations happen on each bar's close, not just when orders fill.
2. Inputs (`input`):
Core Settings:
`lev`: Leverage (default 10x). Used to calculate position sizes.
`Investment Percentage %`: Percentage of total capital to allocate to the initial grid (default 80%).
`final entry Percentage %`: Percentage of the *remaining* capital (100 - `Investment Percentage %`) to use for the "semifinal" entry (default 50%). The rest goes to the "final" entry.
`Price Adjustment Length`: Lookback period (default 4 bars) to determine the initial `maxPrice`.
`price range`: The total percentage range downwards from `maxPrice` where the grid orders will be placed (default -10%, meaning 10% down).
`tp`: Take profit percentage above the average entry price (default 0.45%).
`semifinal entry price percent`: Percentage drop from `maxPrice` to trigger the "semifinal" larger entry (default -12%).
`final entry price percent`: Percentage drop from `maxPrice` to trigger the "final" larger entry (default -15%).
Rounding & Display:
`roundprice`, `round`: Decimal places for rounding price and quantity calculations.
`texts`, `label_style`: User interface preferences for text size and label appearance on the chart.
Time Filter:
`startTime`, `endTime`: Defines the date range for the backtest.
3. Calculations & Grid Setup:
`maxPrice`: The highest price point for the grid setup. Calculated as the lowest low of the previous `len` bars only if no trades are open. If trades are open, it uses the entry price of the very first order placed in the current sequence (`strategy.opentrades.entry_price(0)`).
`minPrice`: The lowest price point for the grid, calculated based on `maxPrice` and `range1`.
`totalCapital`: The amount of capital (considering leverage and `per1`) allocated for the main grid orders.
`coinRatios`: An array ` `. This defines the *relative* size ratio for each of the 11 grid orders. Later orders (at lower prices) will be progressively larger.
`totalRatio`: The sum of all ratios (66).
`positionSizes`: An array calculated based on `totalCapital` and `coinRatios`. It determines the actual quantity (size) for each of the 11 grid orders.
4. Order Placement Logic (`strategy.entry`):
Initial Grid Orders:
Runs only if within the specified time range and no position is currently open (`strategy.opentrades == 0`).
A loop places 11 limit buy orders (`Buy 1` to `Buy 11`).
Prices are calculated linearly between `maxPrice` and `minPrice`.
Order sizes are taken from the `positionSizes` array.
Semifinal & Final Entries:
Two additional, larger limit buy orders are placed simultaneously with the grid orders:
`semifinal entry`: At `maxPrice * (1 - semifinal / 100)`. Size is based on `per2`% of the capital *not* used by the main grid (`1 - per1`).
`final entry`: At `maxPrice * (1 - final / 100)`. Size is based on the remaining capital (`1 - per2`% of the unused portion).
5. Visualization (`line.new`, `label.new`, `plot`, `plotshape`, `plotchar`):
Grid Lines & Labels:
When a position is open (`strategy.opentrades > 0`), horizontal lines and labels are drawn for each of the 11 grid order prices and the "final" entry price.
Lines extend from the bar where the *first* entry occurred.
Labels show the price and planned size for each level.
Dynamic Coloring: If the price drops below a grid level, the corresponding line turns green, and the label color changes, visually indicating that the level has been reached or filled.
Plotted Lines:
`maxPrice` (initial high point for the grid).
`strategy.position_avg_price` (current average entry price of the open position, shown in red).
Target Profit Price (`strategy.position_avg_price * (1 + tp / 100)`, shown in green).
Markers:
A flag marks the `startTime`.
A rocket icon (`🚀`) appears below the bar where the `final entry` triggers.
A stop icon (`🛑`) appears below the bar where the `semifinal entry` triggers.
6. Exit Logic (`strategy.exit`, `strategy.entry` with `qty=0`):
Main Take Profit (`Full Exit`):
Uses `strategy.entry('Full Exit', strategy.short, qty = 0, limit = target2)`. This places a limit order to close the entire position (`qty=0`) at the calculated take profit level (`target2 = avgPrice * (1 + tp / 100)`). Note: Using `strategy.entry` with `strategy.short` and `qty=0` is a way to close a long position, though `strategy.exit` is often clearer. This exit seems intended to apply whenever any part of the grid position is open.
First Order Trailing Stop (`1st order Full Exit`):
Conditional: Only active if `trail` input is true AND the *last* order filled was "Buy 1" (meaning only the very first grid level was entered).
Uses `strategy.exit` with `trail_points` and `trail_offset` based on ATR values to implement a trailing stop loss/profit mechanism for this specific scenario.
This trailing stop order is cancelled (`strategy.cancel`) if any subsequent grid orders ("Buy 2", etc.) are filled.
Final/Semifinal Take Profit (`final Full Exit`):
Conditional: Only active if more than 11 entries have occurred (meaning either the "semifinal" or "final" entry must have triggered).
Uses `strategy.exit` to place a limit order to close the entire position at the take profit level (`target3 = avgPrice * (1 + tp / 100)`).
7. Information Display (Tables & UI Label):
`statsTable` (Top Right):
A comprehensive table displaying grouped information:
Market Info (Entry Point, Current Price)
Position Info (Avg Price, Target Price, Unrealized PNL $, Unrealized PNL %, Position Size, Position Value)
Strategy Performance (Realized PNL $, Realized PNL %, Initial/Total Balance, MDD, APY, Daily Profit %)
Trade Statistics (Trade Count, Wins/Losses, Win Rate, Cumulative Profit)
`buyAvgTable` (Bottom Left):
* Shows the *theoretical* entry price and average position price if trades were filled sequentially up to each `buy` level (buy1 to buy10). It uses hardcoded percentage drops (`buyper`, `avgper`) based on the initial `maxPrice` and `coinRatios`, not the dynamically changing actual average price.
`uiLabel` (Floating Label on Last Bar):
Updates only on the most recent bar (`barstate.islast`).
Provides real-time context when a position is open: Size, Avg Price, Current Price, Open PNL ($ and %), estimated % drop needed for the *next* theoretical buy (based on `ui_gridStep` input), % rise needed to hit TP, and estimated USDT profit at TP.
Shows "No Position" and basic balance/trade info otherwise.
In Summary:
This is a sophisticated long-only grid trading strategy. It aims to:
1. Define an entry range based on recent lows (`maxPrice`).
2. Place 11 scaled-in limit buy orders within a percentage range below `maxPrice`.
3. Place two additional, larger buy orders at deeper percentage drops (`semifinal`, `final`).
4. Calculate the average entry price as orders fill.
5. Exit the entire position for a small take profit (`tp`) above the average entry price.
6. Offer a conditional ATR trailing stop if only the first order fills.
7. Provide extensive visual feedback through lines, labels, icons, and detailed information tables/UI elements.
Keep in mind that grid strategies can perform well in ranging or slowly trending markets but can incur significant drawdowns if the price trends strongly against the position without sufficient retracements to hit the take profit. The leverage (`lev`) input significantly amplifies both potential profits and losses.
多维度市场分析指标 v2 (区间框选)使用大周期MACD的能量柱作为背景用于识别趋势并且搭配上伦敦和纽约交易session
we are using a high time frame macd momentum as chart background to analysis a trend and using london and newyork session to help you trade better
Price Exhaustion Envelope [BackQuant]Price Exhaustion Envelope
Visual preview of the bands:
What it is
The Price Exhaustion Envelope (PEE) is a multi‑factor overextension detector wrapped inside a dynamic envelope framework. It measures how “tired” a move is by blending price stretch, volume surges, momentum and acceleration, plus optional RSI divergence. The result is a composite exhaustion score that drives both on‑chart signals and the adaptive width of three optional envelope bands around a smoothed baseline. When the score spikes above or below your chosen threshold, the script can flag exhaustion, paint candles, tint the background and fire alerts.
How it works under the hood
Exhaustion score
Price component: distance of close from its mean in standard deviation units.
Volume component: normalized volume pressure that highlights unusual participation.
Momentum component: rate of change and acceleration of price, scaled by their own volatility.
RSI divergence (optional): bullish and bearish divergences gently push the score lower or higher.
Mode control: choose Price, Volume, Momentum or Composite. Composite averages the main pieces for a balanced view.
Energy scale (0 to 100)
The composite score is pushed through a logistic transform to create an “energy” value. High energy (above 70 to 80) signals a move that may be running hot, while very low energy (below 20 to 30) points to exhaustion on the downside.
Envelope engine
Baseline: EMA of price over the main lookback length.
Width: base width is standard deviation times a multiplier.
Type selector:
• Static keeps the width fixed.
• Dynamic expands width in proportion to the absolute exhaustion score.
• Adaptive links width to the energy reading so bands breathe with market “heat.”
Smoothing: a short EMA on the width reduces jitter and keeps bands pleasant to trade around.
Band architecture
You can toggle up to three symmetric bands on each side of the baseline. They default to 1.0, 1.6 and 2.2 multiples of the smoothed width. Soft transparent fills create a layered thermograph of extension. The outermost band often maps to true blow‑off extremes.
On‑chart elements
Baseline line that flips color in real time depending on where price sits.
Up to three upper and lower bands with progressive opacity.
Triangle markers at fresh exhaustion triggers.
Tiny warning glyphs at extreme upper or lower breaches.
Optional bar coloring to visually tag exhausted candles.
Background halo when energy > 80 or < 20 for instant context.
A compact info table showing State, Score, Energy, Momentum score and where price sits inside the envelope (percent).
How to use it in trading
Mean reversion plays
When price pierces the outer band and an exhaustion marker prints, look for reversal candles or lower‑timeframe confirmation to fade the move back toward the baseline.
For conservative entries, wait for the composite score to roll back under the threshold or for energy to drop from extreme to neutral.
Set stops just beyond the extreme levels (use extreme_upper and extreme_lower as natural invalidation points). Targets can be the baseline or the opposite inner band.
Trend continuation with smart pullbacks
In strong trends, the first tag of Band 1 or Band 2 against the dominant direction often offers low‑risk continuation entries. Use energy readings: if energy is low on a pullback during an uptrend, a bounce is more likely.
Combine with RSI divergence: hidden bullish divergence near a lower band in an uptrend can be a powerful confirmation.
Breakout filtering
A breakout that occurs while the composite score is still moderate (not exhausted) has a higher chance of follow‑through. Skip signals when energy is already above 80 and price is punching the outer band, as the move may be late.
Watch env_position (Envelope %) in the table. Breakouts near 40 to 60 percent of the envelope are “healthy,” while those at 95 percent are stretched.
Scaling out and risk control
Use exhaustion alerts to trim positions into strength or weakness.
Trail stops just outside Band 2 or Band 3 to stay in trends while letting the envelope expand in volatile phases.
Multi‑timeframe confluence
Run the script on a higher timeframe to locate exhaustion context, then drill down to a lower timeframe for entries.
Opposite signals across timeframes (daily exhaustion vs. 5‑minute breakout) warn you to reduce size or tighten management.
Key inputs to experiment with
Lookback Period: larger values smooth the score and envelope, ideal for swing trading. Shorter values make it reactive for scalps.
Exhaustion Threshold: raise above 2.0 in choppy assets to cut noise, drop to 1.5 for smooth FX pairs.
Envelope Type: Dynamic is great for crypto spikes, Adaptive shines in stocks where volume and volatility wave together.
RSI Divergence: turn off if you prefer a pure price/volume model or if divergence floods the score in your asset.
Alert set included
Fresh upper exhaustion
Fresh lower exhaustion
Extreme upper breach
Extreme lower breach
RSI bearish divergence
RSI bullish divergence
Hook these to TradingView notifications so you get pinged the moment a move hits exhaustion.
Best practices
Always pair exhaustion signals with structure. Support and resistance, liquidity pools and session opens matter.
Avoid blindly shorting every upper signal in a roaring bull market. Let the envelope type help you filter.
Use the table to sanity‑check: a very high score but mid‑range env_position means the band may still be wide enough to absorb more movement.
Backtest threshold combinations on your instrument. Different tickers carry different volatility fingerprints.
Final note
Price Exhaustion Envelope is a flexible framework, not a turnkey system. It excels as a context layer that tells you when the crowd is pressing too hard or when a move still has fuel. Combine it with sound execution tactics, risk limits and market awareness. Trade safe and let the envelope breathe with the market.
(MACD) 25 0122 미팅 MACD 볼린저Here is the English translation:
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"I am currently testing the upload.
The content of the test script involves utilizing Bollinger Bands by linking the Bollinger Band basis line with the MACD's '0' baseline, allowing the MACD to be visualized on the chart."
Mirror US10YThis TradingView script is designed to automatically detect the asset you are viewing (stock, commodity, or crypto) and, if it matches a long list of supported tickers, overlays a "mirror" subchart. This subchart plots the price action of a related pair—typically the asset divided by the US 10-Year Treasury yield (US10Y), or another relevant macro or sector index. The script also detects and visualizes "Imbalance Fair Value Gaps" (IFVGs) on the subchart, and can trigger alerts when these gaps are filled.
1. Automatic Subchart Detection
The script first checks which symbol you are viewing.
If it matches a list of supported stocks or commodities (e.g., NVDA, TSLA, GOLD), it sets a corresponding subchart pair (e.g., NVDA/US20Y, GOLD/US10Y).
If it’s a crypto asset, it checks both the exchange and the symbol, and sets a subchart like BINANCE:ADAUSDT/US10Y.
If a match is found, it enables plotting for the subchart.
2. Subchart Data Fetching
Once a subchart is selected, the script fetches its OHLCV data (open, high, low, close) and a 200-period ATR (Average True Range) using request.security.
It then plots the subchart’s candlesticks in white (bullish) or red (bearish).
3. IFVG (Imbalance Fair Value Gap) Detection
The script defines custom types and arrays to track bullish and bearish IFVGs and their "invalidation" (when the gap is filled).
It detects IFVGs by looking for price gaps between the current and previous candles, filtered by ATR to avoid noise.
When a gap is detected, it is stored in an array with its coordinates and direction.
4. IFVG Management and Visualization
The script manages the lifecycle of each IFVG: it tracks when a gap is filled (invalidated) and moves it to a separate array.
It draws colored boxes and dashed lines on the chart to visualize the last few IFVGs, using green for bullish and red for bearish.
When a gap is filled, it places a label (▲ or ▼) at the fill point.
5. Alerts
The script sets up two alert conditions: one for a bullish IFVG fill, and one for a bearish IFVG fill.
These can be used to trigger TradingView alerts for trading signals.
6. Debugging and Info Labels
The script displays labels on the chart showing the detected ticker and the subpair being plotted, for clarity.
This indicator is even more reliable when combined with the Mirror 2 indicator, which shows the same system but mostly with the BTC pair in crypto.
Both the Mirror US10Y and Mirror 2 also allow you to see the main inverse pairs in stocks.
J-Lines Ribbon • 4-Cycle Engine (CHOP / ANTI / LONG / SHORT)📈 J-Lines Ribbon • 4-Cycle Engine (CHOP / ANTI / LONG / SHORT)
Version: Pine Script v6
Author: Thomas Lee
Category: Trend-Following / Mean Reversion / Scalping
Timeframes: Optimized for 1–5m (but adaptable) Seems to work best on Fibb Time
🧠 Strategy Overview:
The J-Lines Ribbon 4-Cycle Engine is a precision trading algorithm designed to navigate complex market microstructure across four adaptive states:
🔁 CHOP (No Trade / Flatten)
🟡 ANTI (Legacy Layer / Under Development)
🟢 LONG (Trend-Continuation & Rebounds)
🔴 SHORT (Inverse Trend-Continuation & Rebounds)
It combines a multi-layer EMA ribbon, ADX-based CHOP detection, and smart pivot analysis to dynamically shift between market modes, entering and exiting trades with surgical precision.
🔍 Core Features:
Dynamic Market Cycle Detection
Auto-classifies each bar into one of the 4 market states using ADX + EMA 72/89 crossovers.
One-Shot Entries & Rebound Logic
Initiates base entries at the start of new trend cycles. Re-entries (ReLong/ReShort) trigger on EMA 72 and EMA 126 pullbacks with momentum resumption.
CHOP State Autopilot
Automatically closes open positions when CHOP begins, preventing sideways market exposure.
Precision Take-Profits & Pivots-Based Stop Losses
Real-time adaptive exits using pivot high/low swing points as dynamic SL/TP anchors.
Customizable Parameters
Pivot length (left/right)
ADX thresholds
Rebound tolerance bands
Ribbon display and state-labels
📊 Indicator Components:
📏 EMA Ribbon: 72, 89, 126, 267, 360, 445
📉 ADX Filter: Filters out sideways noise, confirms directional bias
🔁 Crossover Events: Detects trend initiations
🌀 Cycle Labels: Real-time visual display of current market state
🛠️ Ideal Use Cases:
Scalping volatile markets
Automated strategy testing & optimization
Entry/exit signal confirmation for discretionary traders
Trend filtering in algorithmic stacks
⚠️ Notes:
ANTI cycle logic is scaffolded but not fully deployed in this version. It will be extended in a future release for deep mean-reversion detection.
Tailor ADX floor and pivot sensitivity to your specific asset and timeframe for optimal performance.
Supertrend & MACD with 60 EMA Signalsthis is a great way to understand market without getting biased ...excellent for intraday entry
Enhanced Predator Suite🎯 Simple Predator Suite Guide - What You See on Your Chart
📍 What to Look For RIGHT NOW on Your BTC Chart
1. BAR COLORS (Most Important)
Look at the color of each price bar:
🟢 BRIGHT GREEN = BUY SIGNAL (Bull Strong)
🟢 LIGHT GREEN = Weak buy (be careful)
🟠 ORANGE = Weak sell (take profits)
🔴 RED = SELL SIGNAL (Bear Strong)
⚫ GRAY = DON'T TRADE (choppy market)
2. TRIANGLE SIGNALS
These are your entry points:
▲ GREEN TRIANGLE UP = Enter LONG (buy) on next bar
▼ RED TRIANGLE DOWN = Enter SHORT (sell) on next bar
3. TRAILING STOP LINES
🟢 GREEN LINE = Exit your long trades if price hits this
🔴 RED LINE = Exit your short trades if price hits this
🚀 SUPER SIMPLE TRADING METHOD
FOR LONG TRADES (BUYING)
Wait for a green triangle ▲ to appear
Buy on the next candle
Set stop loss below the green line
Take profit when bars turn orange or red
FOR SHORT TRADES (SELLING)
Wait for a red triangle ▼ to appear
Sell on the next candle
Set stop loss above the red line
Take profit when bars turn light green or bright green
WHEN TO STAY OUT
Gray bars = Market is confused, don't trade
No triangles = No clear entry signal
Price far from lines = You missed the move
🚫 COMMON MISTAKES TO AVOID
DON'T Do These Things:
❌ Trade during gray bars (choppy market)
❌ Enter without seeing a triangle signal
❌ Ignore the trailing stop lines
❌ Trade with big position sizes at first
❌ Chase price if you missed the triangle
DO These Instead:
✅ Wait patiently for clear triangle signals
✅ Always use the stop loss lines
✅ Start with tiny position sizes
✅ Take profits when bar colors change
✅ Stay out during gray bar periods
New Rsi For Entry FiltrationThis indicator, which is based on the RSI indicator, is written to prevent you from entering the wrong trade. Its operation is very simple. Enter a long trade when both the main area and the lower ribbon are green. Also, for a short trade, both the main area and the lower ribbon are red. The purple line also shows the stop loss level based on ATR. It is not advisable to enter the trade at the points indicated by R because the candlestick length is long.
100-Candle Look-Back MarkerIt simply redraws one vertical dotted line that always sits exactly 100 bars behind the current bar, so you can check at a glance that any trend-line you draw has at least 100 candles of data to the right of it.
Hawkes Volatility Exit IndicatorOverview
The Hawkes Volatility Exit Indicator is a powerful tool designed to help traders capitalize on volatility breakouts and exit positions when momentum fades. Built on the Hawkes process, it models volatility clustering to identify optimal entry points after quiet periods and exit signals during volatility cooling. Designed to be helpful for swing traders and trend followers across markets like stocks, forex, and crypto.
Key Features Volatility-Based Entries: Detects breakouts when volatility spikes above the 95th percentile (adjustable) after quiet periods (below 5th percentile).
This indicator is probably better on exits than entries.
Smart Exit Signals: Triggers exits when volatility drops below a customizable threshold (default: 30th percentile) after a minimum hold period.
Hawkes Process: Uses a decay-based model (kappa) to capture volatility clustering, making it responsive to market dynamics.
Visual Clarity: Includes a volatility line, exit threshold, percentile bands, and intuitive markers (triangles for entries, X for exits).
Status Table: Displays real-time data on position (LONG/SHORT/FLAT), volatility regime (HIGH/LOW/NORMAL), bars held, and exit readiness.
Customizable Alerts: Set alerts for breakouts and exits to stay on top of trading opportunities.
How It Works Quiet Periods: Identifies low volatility (below 5th percentile) that often precede significant moves.
Breakout Entries: Signals bullish (triangle up) or bearish (triangle down) entries when volatility spikes post-quiet period.
Exit Signals: Suggests exiting when volatility cools below the exit threshold after a minimum hold (default: 3 bars).
Visuals & Table: Tracks volatility, position status, and signals via lines, shaded zones, and a detailed status table.
Settings
Hawkes Kappa (0.1): Adjusts volatility decay (lower = smoother, higher = more sensitive).
Volatility Lookback (168): Sets the period for percentile calculations.
ATR Periods (14): Normalizes volatility using Average True Range.
Breakout Threshold (95%): Volatility percentile for entries.
Exit Threshold (30%): Volatility percentile for exits.
Quiet Threshold (5%): Defines quiet periods.
Minimum Hold Bars (3): Ensures positions are held before exiting.
Alerts: Enable/disable breakout and exit alerts.
How to Use
Entries: Look for triangle markers (up for long, down for short) and confirm with the status table showing "ENTRY" and "LONG"/"SHORT."
Exits: Exit on X cross markers when the status table shows "EXIT" and "Exit Ready: YES."
Monitoring: Use the status table to track position, bars held, and volatility regime (HIGH/LOW/NORMAL).
Combine: Pair with price action, support/resistance, or other indicators for better context.
Tips : Adjust thresholds for your market: lower breakout thresholds for more signals, higher exit thresholds for earlier exits.
Test on your asset to ensure compatibility (best for markets with volatility clustering).
Use alerts to automate signal detection.
Limitations Requires sufficient data (default: 168 bars) for reliable signals. Check "Data Status" in the table.
Focuses on volatility, not price direction—combine with trend tools.
May lag slightly due to the smoothing nature of the Hawkes process.
Why Use It?
The Hawkes Volatility Exit Indicator offers a unique, data-driven approach to timing trades based on volatility dynamics. Its clear visuals, customizable settings, and real-time status table make it a valuable addition to any trader’s toolkit. Try it to catch breakouts and exit with precision!
This indicator is based on neurotrader888's python repo. All credit to him. All mistakes mine.
This conversion published for wider attention to the Hawkes method.
Fibonacci Range Detector ║ BullVision🔬 Overview
The Fibonacci Range Mapper is a dynamic technical tool designed to identify, track, and visualize price ranges using Fibonacci levels. Whether you're trading manually or prefer automated structure recognition, this indicator helps you contextualize market moves and locate key price zones with precision.
⚙️ Core Logic
🔍 Range Detection (Auto & Manual Modes)
In Auto mode, the indicator uses an advanced ZigZag system based on ATR or percentage thresholds to confirm market swings and construct Fibonacci-based ranges.
In Manual mode, traders can define their own swing low and high to generate precise custom ranges.
📐 Fibonacci Mapping
Each detected range is automatically plotted with key Fibonacci retracement levels — 0%, 25%, 50%, 75%, 100% — along with optional extensions (127.2% and 161.8%) to anticipate price continuations or reversals.
📋 Live Data Table
An integrated info panel dynamically displays crucial metrics:
• Range size
• Current price zone (Discount / Mid / Premium)
• Position within range (%)
• Distance to range extremes
• Range status (Pending or Confirmed)
🕰️ Historical Memory
Up to 20 past ranges can be stored and visualized simultaneously, helping traders recognize repeated price behaviors and contextual support/resistance levels.
🎨 Visual Highlights
Zones of interest (0–25% = Discount, 75–100% = Premium) are color-coded with custom transparency, and labels can be toggled for clarity. The current active range updates in real time as structure evolves.
🔧 User Customization
• Detection Method: Choose between ATR or % ZigZag for automated swing identification
• Confirmation Delay: Set how many bars to wait before confirming a new high
• Manual Overrides: Select exact price levels when you want full control
• Extensions & Labels: Toggle additional lines and info to suit your charting style
• Visual Table Position: Customize where the data table appears on screen
• Color Scheme: Define your own zone gradients for better visual interpretation
📈 Use Cases
This indicator is ideal for traders who want to:
• Identify value zones within local or macro price structures
• Plan trades around Fibonacci retracement and extension levels
• Detect shifts in market structure using an adaptive ZigZag logic
• Track recurring price ranges and historical reaction points
• Enhance technical confluence with clean, visual price mapping
⚠️ Important Notes
This tool is not a buy/sell signal generator — it is a visual framework for structure-based analysis.
Use it in conjunction with your existing strategy and risk management process.
Always confirm with broader context and multi-timeframe alignment.
Hypothesis TF Strategy EvaluationThis script provides a statistical evaluation framework for trend-following strategies by examining whether mean returns (measured here as 1-period Rate of Change, ROC) differ significantly across different price quantile groups.
Specifically, it:
Calculates rolling 25th (Q1) and 75th (Q3) percentile levels of price over a user-defined window.
Classifies returns into three groups based on whether price is above Q3, between Q1 and Q3, or below Q1.
Computes mean returns and sample sizes for each group.
Performs Welch's t-tests (which account for unequal variances) between groups to assess if their mean returns differ significantly.
Displays results in two tables:
Summary Table: Shows mean ROC and number of observations for each group.
Hypothesis Testing Table: Shows pairwise t-statistics with significance stars for 95% and 99% confidence levels.
Key Features
Rolling quantile calculations: Captures local price distributions dynamically.
Robust hypothesis testing: Welch's t-test allows for heteroskedasticity between groups.
Significance indicators: Easy visual interpretation with "*" (95%) and "**" (99%) significance levels.
Visual aids: Plots Q1 and Q3 levels on the price chart for intuitive understanding.
Extensible and transparent: Fully commented code that emphasizes the evaluation process rather than trading signals.
Important Notes
Not a trading strategy: This script is intended as a tool for research and validation, not as a standalone trading system.
Look-ahead bias caution: The calculation carefully avoids look-ahead bias by computing quantiles and ROC values only on past data at each point.
Users must ensure look-ahead bias is removed when applying this or similar methods, as look-ahead bias would artificially inflate performance and statistical significance.
The statistical tests rely on the assumption of independent samples, which might not fully hold in financial time series but still provide useful insights
Usage Suggestions
Use this evaluation framework to validate hypotheses about the behavior of returns under different price regimes.
Integrate with your strategy development workflow to test whether certain market conditions produce statistically distinct return distributions.
Example
In this example, the script was run with a quantile length of 20 bars and a lookback of 500 bars for ROC classification.
We consider a simple hypothetical "strategy":
Go long if the previous bar closed above Q3 the 75th percentile).
Go short if the previous bar closed below Q1 (the 25th percentile).
Stay in cash if the previous close was between Q1 and Q3.
The screenshot below demonstrates the results of this evaluation. Surprisingly, the "long" group shows a negative average return, while the "short" group has a positive average return, indicating mean reversion rather than trend following.
The hypothesis testing table confirms that the only statistically significant difference (at 95% or higher confidence) is between the above Q3 and below Q1 groups, suggesting a meaningful divergence in their return behavior.
This highlights how this framework can help validate or challenge intuitive assumptions about strategy performance through rigorous statistical testing.
Squeeze Momentum Indicator With EMAThis is a upgraded verison of the most popular Squeeze Momentum Indicator with highlighted lines on the chart to better show entry and exits.
Also includes arrows for easy visibility.
Can also set up ALERTS easily and you can change the color of the momentum highlighted areas to your preference.
HOW TO USE :
***ENTER/EXIT WHEN***
1.Ema 56 / 112 / 672 lines up
2.WHEN CROSSOVER ABOVE = Highlighted green with arrows means bullish entry or bearish exit.
3.WHEN CROSSOVER DOWN = Highlighted red with arows means bearish entry or bullish exit.
4.Exit when black areas occur
***AVOID TRADING WHEN***
1.Arrows within black areas (Non momentum areas or non-squeeze areas)
2.Arrows not following trend(Down arrow during an upwards EMA trend)
**Caution**
You can decide to hold onto a position if you'd like durin the trend, but look at price action before exiting.
5min Table: Dark Up/Down - Supertrend, EMA50, VWAP5Min Table showing EMA 50, Supertrend(10,3) VWAP for Indices and Stocks.
UngliMulti-Indicator Confluence System
This is a **multi-indicator confluence trading signal system** called "Ungli" that combines RSI, ADX, and MACD to identify high-probability momentum opportunities when used alongside chart pattern and trend line breakouts.
## Core Concept
The script identifies moments when multiple technical indicators align to suggest potential price momentum moves, specifically looking for oversold and overbought conditions with momentum confirmation. Use green and red highlights along with chart patterns and trend line breakouts that signal a breakout for confluence for a likely momentum move.
## Technical Indicators Used
**RSI (Relative Strength Index)**
- Default 14-period RSI
- Oversold threshold: < 40
- Overbought threshold: > 60
**ADX (Average Directional Index)**
- Default 14-period ADX with DI+ and DI-
- Threshold: 21
- Looks for ADX below threshold but ticking upward (momentum building)
**MACD (Moving Average Convergence Divergence)**
- Fast: 12, Slow: 26, Signal: 9
- Uses MACD line direction as trend filter
## Signal Logic
**Green Background (Bullish Momentum Signal):**
- RSI > 60 (overbought)
- ADX < 21 AND rising
- MACD line trending upward
**Red Background (Bearish Momentum Signal):**
- RSI < 40 (oversold)
- ADX < 21 AND rising
- MACD line trending downward
## Key Strategy Elements
1. **Confluence Approach**: Requires all three indicators to align, reducing false signals
2. **Momentum Filter**: ADX must be building (rising) even if low, indicating emerging trend strength
3. **Trend Confirmation**: MACD direction must match the expected move
4. **Visual Simplicity**: Clean background highlighting without chart clutter
5. **Pattern Integration**: Designed to work with chart patterns and breakout strategies
## Use Case
This indicator is designed for swing trading and breakout strategies, identifying moments when oversold/overbought conditions coincide with building momentum in the expected direction. The ADX filter helps avoid choppy, trendless markets. Best used in conjunction with:
- Support/resistance breakouts
- Chart pattern breakouts (triangles, flags, channels)
- Trend line breaks
- Key level violations
The background highlights serve as confluence confirmation when combined with your chart analysis and breakout setups.
Markov Chain Trend ProbabilityA Markov Chain is a mathematical model that predicts future states based on the current state, assuming that the future depends only on the present (not the past). Originally developed by Russian mathematician Andrey Markov, this concept is widely used in:
Finance: Risk modeling, portfolio optimization, credit scoring, algorithmic trading
Weather Forecasting: Predicting sunny/rainy days, temperature patterns, storm tracking
Here's an example of a Markov chain: If the weather is sunny, the probability that will be sunny 30 min later is say 90%. However, if the state changes, i.e. it starts raining, how the probability that will be raining 30 min later is say 70% and only 30% sunny.
Similar concept can be applied to markets price action and trends.
Mathematical Foundation
The core principle follows the Markov Property: P(X_{t+1}|X_t, X_{t-1}, ..., X_0) = P(X_{t+1}|X_t)
Transition Matrix :
-------------Next State
Current----
--------P11 P12
-----P21 P22
Probability Calculations:
P(Up→Up) = Count(Up→Up) / Count(Up states)
P(Down→Down) = Count(Down→Down) / Count(Down states)
Steady-state probability: π = πP (where π is the stationary distribution)
State Definition:
State = UPTREND if (Price_t - Price_{t-n})/ATR > threshold
State = DOWNTREND if (Price_t - Price_{t-n})/ATR < -threshold
How It Works in Trading
This indicator applies Markov Chain theory to market trends by:
Defining States: Classifies market conditions as UPTREND or DOWNTREND based on price movement relative to ATR (Average True Range)
Learning Transitions: Analyzes historical data to calculate probabilities of moving from one state to another
Predicting Probabilities: Estimates the likelihood of future trend continuation or reversal
How to Use
Parameters:
Lookback Period: Number of bars to analyze for trend detection (default: 14)
ATR Threshold: Sensitivity multiplier for state changes (default: 0.5)
Historical Periods: Sample size for probability calculations (default: 33)
Trading Applications:
Trend confirmation for entry/exit decisions
Risk assessment through probability analysis
Market regime identification
Early warning system for potential trend reversals
The indicator works on any timeframe and asset class. Enjoy!
First Round Break TrackerA simple indicator that tracks the first-time breakouts of round number levels (psychological levels) on any chart. Clean interface with minimal configuration needed
First Breakout Only : Marks each round level only once when broken for the first time
Customizable Step Size : Adjustable round number intervals (e.g., 100, 1000, 10000 etc.)
Clean Visual Alerts : Green labels with "FIRST:" prefix appear exactly at breakout moments
Real-time Info Panel : Shows current price, next target level, and total breakouts count
