Trend Trader█ Overview
Trend Trader is a valuable indicator that calculates the probability of a breakout. In addition, the indicator displays an additional 3 levels for Targets
The indicator helps traders to make a decision to enter in to the market
█ Settings
• Percentage Step
The space between the levels can be adjusted with a percentage step. 1% means that each level is located 1% above/under the previous one.
• Number of Lines
Set the number of levels you want to display.
•
█ Any Alert function call
An alert is sent on candle open, and you can select what should be included in the alert.
█ How to use
• This indicator is a perfect tool for anyone that wants to understand the probability of a breakout and the likelihood that set levels are hit.
• The indicator can be used for setting a stop loss based on where the price is most likely not to reach.
Indicatori e strategie
OneTrend ProOneTrend Pro is a sophisticated RWMA-based trend-following strategy that dynamically combines trend confirmation using filters such as ADX strength and reversion signals based on overbought/oversold conditions and volume validation. It intelligently adjusts its trend state through multiple confirmation steps and trailing stop mechanisms to capture significant price moves while filtering out noise in sideways markets.
With near-zero-lag responsiveness and impressive historical performance metrics on key assets like BTC and ETH, OneTrend Pro offers traders a refined, multi-layered approach that enhances trade conviction and risk management—making it a valuable investment for those seeking an edge in market trend trading.
Earnings Trading StrategyThe Earnings Trade Strategy automates the process of entering and exiting trades based on earnings announcements for Apple (AAPL). It allows users to take a position—either long (buy) or short (sell short)—on the trading day before an earnings announcement and close that position on the trading day after the announcement. By leveraging TradingView’s Paper Trading environment, the strategy enables users to simulate trades and collect performance data over a 6-month period in a risk-free setting.
POC+RSI Ranking Strategy █Introduction
This strategy combines the concepts of Point of Control (POC) and Relative Strength Index (RSI) to quantitatively determine buy and sell signals. It evaluates volume distribution (POC) over a specified period and RSI levels to calculate a combined score. Higher scores (price near POC support and RSI oversold) trigger buying, while lower scores (price away from support and RSI overbought) trigger selling.
█一、前言
在市場中，我們常用「成交量」與「技術指標」作為判斷價格行為的重要依據。本策略將 POC (Point of Control) 的概念與 RSI (Relative Strength Index) 相結合，針對「過去一段時間的成交量分佈」以及「價格相對強弱」進行量化評分，最終以該分數來決定是否買入、賣出，並搭配分數高低動態調整倉位大小。
POC (Point of Control)：常見於 Volume Profile 分析，代表特定時間區段內，成交量最多的價格區域。若價格接近高成交量區，往往成為市場的重要支撐或壓力。
RSI (Relative Strength Index)：用於評估價格漲跌幅度比例，通常數值偏高 (超買) 代表可能漲幅過大，偏低 (超賣) 代表市場拋售過度。
本策略的核心精神是：
在 RSI 偏低、價格接近支撐(POC) 區域時反向做多；在 RSI 偏高、價格遠離支撐(POC) 區域且呈現 FOMO 狀態時逢高賣出。
利用這種結合成交量與相對強弱的量化打分機制，輔助我們做更加客觀、彈性的資金配置。
█二、程式主要邏輯
🔶1. POC (成交量分桶) 計算
回溯 lookback 天 (預設 252 日) 的歷史走勢，找出最高價與最低價，並將整個價格區間平均切成 bin_count 個「桶」 (預設 10)。
逐根 bar 累計該段期間內的成交量 (volume) ，對應到價格所在的桶子；最後根據累計的成交量多寡進行排序。
轉換成 POC 分數：最靠前 (量最多) 的區域排名=1 → 分數=10；最末的排名=10 → 分數=1。
範例：若我們有 10 個桶子 (bin_count=10)，在lookback 天 (預設 252 日)，最高價是500元，最低價是100元，則每桶的width為(500-100)/10=40元，且假設桶1成交量最高而桶10成交量最低。
則:
桶1(100~140) VOL:10B(排名1)->10分
桶2(140~180) VOL:9B (排名2)->9分
桶3(180~220) VOL:8B (排名3)->8分
.
.
桶10(460~500) VOL:1B(排名10)->1分
當收盤價落在某桶子，程式就能得知該桶子的排名與對應的 POC 分數。
舉例:若收盤價落在215元，可知排名3，可得8分。
🔶2. RSI 計算與分段
使用 rsi_length (預設14) 做 RSI 指標，並將 RSI(0～100) 切成 10 個區間 (bin=1~10)。
區間編號越小 (bin=1)，分數越高 (10 分)；越大 (bin=10)，分數越低 (1 分)。
下表示意 RSI 值與對應分數：
RSI=1~10% (排名1)->10分
RSI=10~20%(排名2)->9分
RSI=20~30%(排名3)->8分
.
.
RSI=90~100%(排名10)->1分
舉例：若 RSI=16% → bin=2 → RSI 分數=9 (偏超賣區域)。
🔶3. 買賣分數 (buy_sell_score)
加權相加：將 POC 分數、RSI 分數分別乘上 poc_weight、rsi_weight，再相加得出最終分數。
範例：若 poc_score=8、rsi_score=9、權重皆為 0.5 →
buy_sell_score=8×0.5+9×0.5=4+4.5=8.5
判斷邏輯：
當「前一根分數 ≥ 7」(含 7) → 進入買訊
當「前一根分數 ≤ 4」(含 4) → 進入賣訊
若分數為小數 (例如 8.5) → floor(8.5)=8 取整數對應下一步買賣比例。
🔶4. 動態倉位大小
當偵測到買訊 (7~10 分)，可對應不同買入比例 (INPUT中有最小&最大買入% 供自行調整)；
假設: buy_sell score=8分,最小買入=35% , 最大買入=50%
7分=買入35%
8分=35%+(50%-35%)/3=40%
9分=40%+(50%-35%)/3=45%
10分=買入50%
因此:
8分會買入可用資金*40%的部位。
當偵測到賣訊 (4~1 分)，也依類似的邏輯進行減倉。
不同之處在於，賣出是用持有部位*賣出% (買入是用可用資金*買入%)
偵測到相對強 (或弱) 的分數 → 部分加碼 (或減碼)，讓操作更具有彈性。
🔶5. 可用現金 < 10% 總資產 → 不買
若可用現金 (未投入部位的資金) 已少於總資產的 10%，代表資金相對不足、再次開倉意義不大，可能只會造成小額頻繁交易。此時程式會暫停買入，保留一點資金彈性。
🔶6. 持倉市值 < 10% 總資產 → 不賣
同理，若持倉市值已降至總資產的 10% 以下，意味著部位非常小，賣出再細分也無太大意義，反而浪費交易成本，於是程式也會暫停此部分減倉動作。
🔶7. 下單時機 (收盤)
strategy(..., process_orders_on_close=true)：在偵測到訊號當根 K 線收盤即執行下單，不等待下一根開盤。
預設看 buy_sell_score (前一根分數) → 意味著當前根收盤的訊號其實來自「上一根」的計算值；若想更即時，可移除 改為當根計算當根下單。
🔶8. 圖表顯示：橫向色帶
在副圖中繪製 buy_sell_score 曲線，並搭配 hline() + fill() 將分數 1～4 區塊填充紅色、7～10 區塊填充藍色，便於快速辨識「超買 / 超賣」區域。
🔶9. 可指定回測範圍
若需測試特定區間，程式可透過輸入「開始 / 結束日期」，或使用 testDays 方式（最近 N 天）來限制回測區段，針對短期行情進行檢驗。
█三、使用方式
🔶1.套用策略
在 TradingView 「Pine Editor」貼上本策略程式後，儲存並點擊「Add to chart」。
進入「Strategy Tester」檢視回測結果、盈虧曲線、交易訊號等。
🔶2.調整參數
lookback：POC 回溯天數 (預設 252)
bin_count：價格分桶數量 (預設 10)
rsi_length：RSI 週期 (預設 14)
poc_weight / rsi_weight：分數權重 (預設 0.5/0.5)
動態倉位範圍 (最小 / 最大 買入、賣出佔比%)
回測區間 (開始 / 結束日期 或 testDays)
可依交易標的 (如股票、期貨或加密貨幣) 適度調整，並在「Strategy Tester」測試多組組合參數。
🔶3.觀察實際執行
RSI 偏低 & 接近POC支撐 → 於收盤買入
RSI 偏高 & 價格遠離支撐 → 於收盤賣出
；如有小數則取整數判斷。
🔶4.資金控管
可用現金 < 10% → 不買：防止資金見底後反覆小額交易。
持倉市值 < 10% → 不賣：部位過小時，賣出意義不大。
若需更細膩的停損、停利或風控，可在程式內進一步擴充。
█四、結語
「POC+RSI Ranking Strategy 完整修正版」結合了成交量分布 (POC) 與 RSI 的打分機制：
RSI 偏低 + 處於成交量聚集區 → 高分 (市場具支撐、偏超賣) → 策略選擇買入；
RSI 偏高 + 價格遠離支撐 → 低分 (市場過熱、偏超買) → 策略逢高賣出。
並透過「動態倉位」讓分數越高 (或越低) 時有相應的加碼(或減碼)佔比，同時做簡易資金控管(小資金不再買、小倉位不再賣)。這些設定配合回測區間(開始/結束日期)使策略更具彈性與實用性。
建議多嘗試不同標的與回測週期，觀察測試結果，以尋找最符合自身風險與交易風格的參數。希望本策略能為您帶來更高效率、更客觀的交易決策。祝操作順利
RUNEUSDT1MPrice action and RSI based strategy that operates in selected hours and days of the week. Its Risk-Reward ratio is 1:2 per operation.
Supertrend with EMA and RSIHow the Supertrend with EMA and RSI Strategy Works
This trading strategy is written in Pine Script (version 6) for use on TradingView. It combines three technical indicators—Supertrend, Exponential Moving Average (EMA), and Relative Strength Index (RSI)—to generate buy and sell signals. The strategy overlays on the price chart, includes initial capital and commission settings, and visually displays signals. Here’s a step-by-step breakdown of how it works:
1. Strategy Setup
The strategy starts by defining its basic parameters:
Name: "Supertrend with EMA and RSI"
Overlay: It plots directly on the price chart (overlay=true).
Initial Capital: 10,000 units (e.g., dollars or euros, depending on the asset).
Trade Size: Fixed at 3 units per trade (e.g., 3 shares or contracts).
Commission: 12% per trade, simulating transaction costs.
This sets the foundation for how the strategy operates in terms of money management and fees.
2. User-Defined Inputs
The strategy allows customization through user inputs:
Supertrend Inputs:
ATR Period: Default is 10 bars, used to calculate the Average True Range (ATR), a measure of volatility.
ATR Multiplier: Default is 3.0 (adjustable in steps of 0.1), which controls how wide the Supertrend bands are.
Change ATR Method: A true/false option (default true) to switch between two ATR calculation methods.
EMA and RSI Inputs:
EMA Period: Default is 50 bars, determining the smoothness of the Exponential Moving Average.
RSI Period: Default is 14 bars, setting the lookback period for the Relative Strength Index.
RSI Threshold: Default is 50, used as a midpoint to judge bullish or bearish momentum.
These inputs let users tweak the indicators to suit their trading style.
3. Supertrend Indicator Calculation
The Supertrend indicator identifies whether the market is in a bullish (up) or bearish (down) trend. Here’s how it’s calculated:
Source Price: The average of the high and low prices ((high + low) / 2), often called hl2.
ATR Calculation:
If changeATR is true, it uses the standard ATR (ta.atr(Periods)).
If false, it uses a simple moving average of the true range (ta.sma(ta.tr, Periods)).
Upper Band (up): hl2 - (Multiplier * ATR).
Lower Band (dn): hl2 + (Multiplier * ATR).
Band Adjustments:
If the previous close is above the previous upper band, the new upper band is the higher of the current up or the previous band.
If the previous close is below the previous lower band, the new lower band is the lower of the current dn or the previous band.
Trend Direction:
Starts as 1 (bullish).
Switches to -1 (bearish) if the close falls below the upper band.
Switches back to 1 if the close rises above the lower band.
The Supertrend uses these bands to signal trend changes.
4. EMA and RSI Calculations
Two additional indicators are calculated to filter the Supertrend signals:
EMA: An Exponential Moving Average of the closing price over 50 bars (default). It shows the longer-term trend direction.
RSI: A Relative Strength Index of the closing price over 14 bars (default). It measures momentum, ranging from 0 to 100.
5. Defining Trend and Momentum Conditions
The strategy uses the EMA and RSI to confirm trends and momentum:
Uptrend: True if the closing price is above the EMA.
Downtrend: True if the closing price is below the EMA.
Bullish RSI: True if RSI is above 50 (default threshold).
Bearish RSI: True if RSI is below 50.
These conditions ensure the Supertrend signals align with broader market trends and momentum.
6. Supertrend Signals
The Supertrend generates preliminary signals based on trend changes:
Buy Signal: Occurs when the trend switches from -1 (bearish) to 1 (bullish).
Sell Signal: Occurs when the trend switches from 1 (bullish) to -1 (bearish).
These are raw signals that need confirmation.
7. Confirmed Trading Signals
The strategy only trades when the Supertrend signals are confirmed by the EMA and RSI:
Confirmed Buy Signal:
Supertrend gives a buy signal.
Price is above the EMA (uptrend).
RSI is above 50 (bullish momentum).
Confirmed Sell Signal:
Supertrend gives a sell signal.
Price is below the EMA (downtrend).
RSI is below 50 (bearish momentum).
This triple confirmation reduces false signals.
8. Executing Trades
The strategy executes trades based on confirmed signals:
Buy (Long): Enters a long position when a confirmed buy signal occurs.
Sell (Short): Enters a short position when a confirmed sell signal occurs.
9. Visualizing the Strategy
The strategy plots the following on the chart:
Supertrend Bands:
A green line shows the upper band during an uptrend.
A red line shows the lower band during a downtrend.
Signals:
A green "BUY" label appears below the bar for confirmed buy signals.
A red "SELL" label appears above the bar for confirmed sell signals.
This makes it easy to see the strategy in action.
Summary
This strategy combines three indicators for better trading decisions:
Supertrend: Detects trend direction (bullish or bearish).
EMA: Confirms the trend by checking if the price is above or below the average.
RSI: Ensures momentum supports the trend (above or below 50).
Buy Condition: Bullish Supertrend + Price > EMA + RSI > 50.
Sell Condition: Bearish Supertrend + Price < EMA + RSI < 50.
By requiring all three indicators to agree, the strategy aims to filter out noise and improve accuracy. It’s a powerful tool for traders who want to combine trend-following and momentum analysis.
Forex Fire EMA/MA/RSI StrategyEURUSD
The entry method in the Forex Fire EMA/MA/RSI Strategy combines several conditions across two timeframes. Here's a breakdown of how entries are determined:
Long Entry Conditions:
15-Minute Timeframe Conditions:
EMA 13 > EMA 62 (short-term momentum is bullish)
Price > MA 200 (trading above the major trend indicator)
Fast RSI (7) > Slow RSI (28) (momentum is increasing)
Fast RSI > 50 (showing bullish momentum)
Volume is increasing compared to 20-period average
4-Hour Timeframe Confluence:
EMA 13 > EMA 62 (larger timeframe confirms bullish trend)
Price > MA 200 (confirming overall uptrend)
Slow RSI (28) > 40 (showing bullish bias)
Fast RSI > Slow RSI (momentum is supporting the move)
Additional Precision Requirement:
Either EMA 13 has just crossed above EMA 62 (crossover)
OR price has just crossed above MA 200
Short Entry Conditions:
15-Minute Timeframe Conditions:
EMA 13 < EMA 62 (short-term momentum is bearish)
Price < MA 200 (trading below the major trend indicator)
Fast RSI (7) < Slow RSI (28) (momentum is decreasing)
Fast RSI < 50 (showing bearish momentum)
Volume is increasing compared to 20-period average
4-Hour Timeframe Confluence:
EMA 13 < EMA 62 (larger timeframe confirms bearish trend)
Price < MA 200 (confirming overall downtrend)
Slow RSI (28) < 60 (showing bearish bias)
Fast RSI < Slow RSI (momentum is supporting the move)
Additional Precision Requirement:
Either EMA 13 has just crossed under EMA 62 (crossunder)
OR price has just crossed under MA 200
The key aspect of this strategy is that it requires alignment between the shorter timeframe (15m) and the larger timeframe (4h), which helps filter out false signals and focuses on trades that have strong multi-timeframe support. The crossover/crossunder requirement further refines entries by looking for actual changes in direction rather than just conditions that might have been in place for a long time.
Natural Gas 1H EMA-SMA StrategyKey Fixes & Explanation
✅ Combined SMA & EMA Conditions:
You can now trigger a long trade if either the EMA or SMA condition is met.
If you want only one, use longCondition1 (EMA) or longCondition2 (SMA).
Optimized Supertrend Intraday StrategyThis Optimized Supertrend Intraday Strategy for TradingView is designed for precise intraday trading with the following key modifications:
Entry Timing:
Trades only start at 9:20 AM and stop at 3:15 PM, ensuring trades align with market liquidity.
Entry Conditions (No Crossover):
Instead of relying on ta.crossover or ta.crossunder, this strategy enters trades when the price is positioned relative to the Supertrend:
Long Entry: When price is above both the Supertrend and the higher timeframe Supertrend.
Short Entry: When price is below both Supertrend levels.
Risk & Trade Management:
Uses ATR-based position sizing to control risk.
Incorporates daily loss tracking to stop trading if the loss limit is reached.
Closes all positions at the end of the trading session.
Additional Filters:
RSI Condition: Optional filter to ensure strong trend confirmation.
Volume Filter: Trades only if volume is higher than the 20-period average.
EMA Condition: Optional filter to avoid counter-trend trade
VWAP + EMA200 + RSI + ATR StrategyThis is a high-frequency intraday trend-following strategy with a mean-reversion trigger and strict realism layers. It's designed to scale small capital responsibly while maintaining tight risk and high execution realism.
Institutional vs Retail Strategy with PhasesUnlock the unseen battle between institutional and retail traders with the Institutional Handshake Indicator. This cutting-edge tool sheds light on market sentiment, highlighting pivotal accumulation and distribution phases. By interpreting the clash of Smart Money and Retail Pulse, it empowers you to time your trades with precision and confidence.
Key Features:
Phase Clarity: Easily identify accumulation and distribution zones with vivid color-coding—green for accumulation, red for distribution.
Trade Signals: Spot actionable buy and sell opportunities with clear green and red arrows, derived from advanced market insights.
Flexible Customization: Adjust settings to match your trading approach, tweaking phase detection and signal strength to fit any timeframe.
Sleek Visuals: Enjoy a modern, streamlined design that integrates seamlessly into your charts without cluttering the price action.
Perfect for traders of all levels, the Institutional Handshake Indicator delivers a unique edge by revealing market dynamics in an intuitive way. Step up your trading game and outpace the competition—without ever needing to peek under the hood.
Amega Bot SetTester strategy for Amega Bot Trend.
Several strategies: level, trend, break-in trend, break-and-outs of level.
Demo GPT - Gaussian Channel Strategy v3.1 AdaptedGaussian Channel Strategy v3.1 Adapted
An automated trading strategy combining Gaussian Channel, Stochastic RSI, and SMA for trend filtering.
Overview
This strategy uses a dynamic Gaussian Channel to identify price channels, Stochastic RSI for overbought/oversold conditions, and a 50-period SMA as a trend filter. It enters long/short positions based on price breaking channel bands, Stochastic RSI signals, and SMA alignment.
Key Components
Gaussian Channel
Source : Midpoint price (hlc3).
Parameters :
N: Number of poles (1-9) controlling channel smoothness.
per: Sampling period (default 100) for dynamic lag adjustment.
mult_base: Multiplier for channel width (default 1.5), scaled by ATR for volatility adaptation.
Features :
Reduces lag when modeLag is enabled.
Faster response when modeFast is enabled.
Channels :
filt: Central filter line (midpoint of the channel).
hband/lband: Upper/lower bands = filt ± (ATR × mult_base).
Stochastic RSI
Parameters :
RSI Length: 10.
Stochastic Length: 10.
Smooth K/D: 5 periods.
Signals :
Overbought: K > 80 (long bias).
Oversold: K < 20 (short bias).
Trend Filter (SMA 50)
Confirms bullish trend when close > SMA50 (long entry).
Confirms bearish trend when close < SMA50 (short entry).
Trade Logic
Long Entry Conditions :
Channel Uptrend : filt > previous filt (rising channel midline).
Price Break : close > hband (price exceeds upper channel band).
Stochastic RSI : K > 80 (overbought) or K < 20 (oversold rebound).
Trend Filter : close > SMA50.
Short Entry Conditions :
Channel Downtrend : filt < previous filt (falling channel midline).
Price Break : close < lband (price falls below lower band).
Stochastic RSI : K < 20 (oversold) or K > 80 (overbought reversal).
Trend Filter : close < SMA50.
Exit Conditions :
Automatic Exit :
strategy.exit with trailing stop (trail_offset=1000, trail_points=5000).
Immediate Close :
Long: close crosses below hband.
Short: close crosses above lband.
Parameters & Settings
Initial Capital : $100,000.
Commission : 0.1% per trade.
Position Sizing : 75% of equity per trade.
Pyramiding : Max 1 open position.
Date Range : Adjustable (default 2025–2069 for backtesting).
Risk Notes
Volatility Sensitivity : Channel width adjusts with ATR; may widen during volatile markets.
Overlapping Signals : Stochastic RSI allows entries at both extremes (overbought/oversold), which may lead to whipsaws.
SMA Lag : Trend filter may delay entries during rapid price moves.
Optimization Tips
Adjust mult_base to control channel width based on asset volatility.
Test N and per for smoother or more responsive channels.
Refine Stochastic RSI parameters for fewer false signals.
The RetrieverThis Pine Script strategy, named "The Retriever" aims to capitalise on price dips based on the size of the candlestick body. It uses a moving average of the body size to identify potential long entry points. Here's a breakdown:
Body Size Calculation: It calculates the absolute difference between the close and open prices (body) to determine the candlestick body size.
Entry Signals:
long: A long entry signal is generated when the close price is significantly higher than the moving average of the body size (ta.sma(body, 100)) multiplied by a factor (mult). Thanks to this principle we are entering just bigger dips but just in case it is sudden movement, typically dip during bulish trend.
longExtra: A second, more aggressive long entry signal is generated when the close price is even further above the moving average (multiplied by mult * 2). This signal is very rare and it is helping to decrease entry point in case huge market dips which can occurs just few times per year.
Quantity Calculation: The order quantity (qty) is dynamically calculated based on the current equity and the price range between minRange and maxRange. It aims to adjust the quantity inversely to the price range, possibly increasing the quantity when the price range is smaller. It is actually very smart in several ways:
it is making bigger trades when market price is low (closer to manually defined minRange) and vice versa making smaller trades when market is close to maxRange
trade size is calculated based on current equity so it allows to use compound interest effect
as there is no SL in this strategy trade size is calculated to be max around 50-60% drawdown based on backtested results so it can survive 80-90% market drawdowns (entry point is after huge dip)
Exit Conditions: All open positions are closed when either of these conditions is met:
The last candle is green (close is higher than open). There is also minProfit param defined which is set to 0 so it means that our position has to be in profit. So we are never closing in loss. We have to differentiate here between order and position. Order can be in loss but overal position has to be always in profit.
IU Bigger than range strategyDESCRIPTION
IU Bigger Than Range Strategy is designed to capture breakout opportunities by identifying candles that are significantly larger than the previous range. It dynamically calculates the high and low of the last N candles and enters trades when the current candle's range exceeds the previous range. The strategy includes multiple stop-loss methods (Previous High/Low, ATR, Swing High/Low) and automatically manages take-profit and stop-loss levels based on user-defined risk-to-reward ratios. This versatile strategy is optimized for higher timeframes and assets like BTC but can be fine-tuned for different instruments and intervals.
USER INPUTS:
Look back Length: Number of candles to calculate the high-low range. Default is 22.
Risk to Reward: Sets the target reward relative to the stop-loss distance. Default is 3.
Stop Loss Method: Choose between:(Default is "Previous High/Low")
- Previous High/Low
- ATR (Average True Range)
- Swing High/Low
ATR Length: Defines the length for ATR calculation (only applicable when ATR is selected as the stop-loss method) (Default is 14).
ATR Factor: Multiplier applied to the ATR to determine stop-loss distance(Default is 2).
Swing High/Low Length: Specifies the length for identifying swing points (only applicable when Swing High/Low is selected as the stop-loss method).(Default is 2)
LONG CONDITION:
The current candle’s range (absolute difference between open and close) is greater than the previous range.
The closing price is higher than the opening price (bullish candle).
SHORT CONDITIONS:
The current candle’s range exceeds the previous range.
The closing price is lower than the opening price (bearish candle).
LONG EXIT:
Stop-loss:
- Previous Low
- ATR-based trailing stop
- Recent Swing Low
Take-profit:
- Defined by the Risk-to-Reward ratio (default 3x the stop-loss distance).
SHORT EXIT:
Stop-loss:
- Previous High
- ATR-based trailing stop
- Recent Swing High
Take-profit:
- Defined by the Risk-to-Reward ratio (default 3x the stop-loss distance).
ALERTS:
Long Entry Triggered
Short Entry Triggered
WHY IT IS UNIQUE:
This strategy dynamically adapts to different market conditions by identifying candles that exceed the previous range, ensuring that it only enters trades during strong breakout scenarios.
Multiple stop-loss methods provide flexibility for different trading styles and risk profiles.
The visual representation of stop-loss and take-profit levels with color-coded plots improves trade monitoring and decision-making.
HOW USERS CAN BENEFIT FROM IT:
Ideal for breakout traders looking to capitalize on momentum-driven price moves.
Provides flexibility to customize stop-loss methods and fine-tune risk management parameters.
Helps minimize drawdowns with a strong risk-to-reward framework while maximizing profit potential.
Enhanced Keltner Channel StrategyMomentum Capture: By entering on channel breakouts, the strategy aims to catch strong trends.
Volatility Filtering: The ATR component ensures signals only trigger during meaningful moves.
Dynamic Exit: Using the EMA to exit keeps trades aligned with the broader trend.
Trendline Breaks with Multi Fibonacci Supertrend StrategyTMFS Strategy: Advanced Trendline Breakouts with Multi-Fibonacci Supertrend
Elevate your algorithmic trading with institutional-grade signal confluence
Strategy Genesis & Evolution
This advanced trading system represents the culmination of a personal research journey, evolving from my custom " Multi Fibonacci Supertrend with Signals " indicator into a comprehensive trading strategy. Built upon the exceptional trendline detection methodology pioneered by LuxAlgo in their " Trendlines with Breaks " indicator, I've engineered a systematic framework that integrates multiple technical factors into a cohesive trading system.
Core Fibonacci Principles
At the heart of this strategy lies the Fibonacci sequence application to volatility measurement:
// Fibonacci-based factors for multiple Supertrend calculations
factor1 = input.float(0.618, 'Factor 1 (Weak/Fibonacci)', minval = 0.01, step = 0.01)
factor2 = input.float(1.618, 'Factor 2 (Medium/Golden Ratio)', minval = 0.01, step = 0.01)
factor3 = input.float(2.618, 'Factor 3 (Strong/Extended Fib)', minval = 0.01, step = 0.01)
These precise Fibonacci ratios create a dynamic volatility envelope that adapts to changing market conditions while maintaining mathematical harmony with natural price movements.
Dynamic Trendline Detection
The strategy incorporates LuxAlgo's pioneering approach to trendline detection:
// Pivotal swing detection (inspired by LuxAlgo)
pivot_high = ta.pivothigh(swing_length, swing_length)
pivot_low = ta.pivotlow(swing_length, swing_length)
// Dynamic slope calculation using ATR
slope = atr_value / swing_length * atr_multiplier
// Update trendlines based on pivot detection
if bool(pivot_high)
upper_slope := slope
upper_trendline := pivot_high
else
upper_trendline := nz(upper_trendline) - nz(upper_slope)
This adaptive trendline approach automatically identifies key structural market boundaries, adjusting in real-time to evolving chart patterns.
Breakout State Management
The strategy implements sophisticated state tracking for breakout detection:
// Track breakouts with state variables
var int upper_breakout_state = 0
var int lower_breakout_state = 0
// Update breakout state when price crosses trendlines
upper_breakout_state := bool(pivot_high) ? 0 : close > upper_trendline ? 1 : upper_breakout_state
lower_breakout_state := bool(pivot_low) ? 0 : close < lower_trendline ? 1 : lower_breakout_state
// Detect new breakouts (state transitions)
bool new_upper_breakout = upper_breakout_state > upper_breakout_state
bool new_lower_breakout = lower_breakout_state > lower_breakout_state
This state-based approach enables precise identification of the exact moment when price breaks through a significant trendline.
Multi-Factor Signal Confluence
Entry signals require confirmation from multiple technical factors:
// Define entry conditions with multi-factor confluence
long_entry_condition = enable_long_positions and
upper_breakout_state > upper_breakout_state and // New trendline breakout
di_plus > di_minus and // Bullish DMI confirmation
close > smoothed_trend // Price above Supertrend envelope
// Execute trades only with full confirmation
if long_entry_condition
strategy.entry('L', strategy.long, comment = "LONG")
This strict requirement for confluence significantly reduces false signals and improves the quality of trade entries.
Advanced Risk Management
The strategy includes sophisticated risk controls with multiple methodologies:
// Calculate stop loss based on selected method
get_long_stop_loss_price(base_price) =>
switch stop_loss_method
'PERC' => base_price * (1 - long_stop_loss_percent)
'ATR' => base_price - long_stop_loss_atr_multiplier * entry_atr
'RR' => base_price - (get_long_take_profit_price() - base_price) / long_risk_reward_ratio
=> na
// Implement trailing functionality
strategy.exit(
id = 'Long Take Profit / Stop Loss',
from_entry = 'L',
qty_percent = take_profit_quantity_percent,
limit = trailing_take_profit_enabled ? na : long_take_profit_price,
stop = long_stop_loss_price,
trail_price = trailing_take_profit_enabled ? long_take_profit_price : na,
trail_offset = trailing_take_profit_enabled ? long_trailing_tp_step_ticks : na,
comment = "TP/SL Triggered"
)
This flexible approach adapts to varying market conditions while providing comprehensive downside protection.
Performance Characteristics
Rigorous backtesting demonstrates exceptional capital appreciation potential with impressive risk-adjusted metrics:
Remarkable total return profile (1,517%+)
Strong Sortino ratio (3.691) indicating superior downside risk control
Profit factor of 1.924 across all trades (2.153 for long positions)
Win rate exceeding 35% with balanced distribution across varied market conditions
Institutional Considerations
The strategy architecture addresses execution complexities faced by institutional participants with temporal filtering and date-range capabilities:
// Time Filter settings with flexible timezone support
import jason5480/time_filters/5 as time_filter
src_timezone = input.string(defval = 'Exchange', title = 'Source Timezone')
dst_timezone = input.string(defval = 'Exchange', title = 'Destination Timezone')
// Date range filtering for precise execution windows
use_from_date = input.bool(defval = true, title = 'Enable Start Date')
from_date = input.time(defval = timestamp('01 Jan 2022 00:00'), title = 'Start Date')
// Validate trading permission based on temporal constraints
date_filter_approved = time_filter.is_in_date_range(
use_from_date, from_date, use_to_date, to_date, src_timezone, dst_timezone
)
These capabilities enable precise execution timing and market session optimization critical for larger market participants.
Acknowledgments
Special thanks to LuxAlgo for the pioneering work on trendline detection and breakout identification that inspired elements of this strategy. Their innovative approach to technical analysis provided a valuable foundation upon which I could build my Fibonacci-based methodology.
This strategy is shared under the same Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license as LuxAlgo's original work.
Past performance is not indicative of future results. Conduct thorough analysis before implementing any algorithmic strategy.
33 EMA Crossover StrategyBuy/Sell at crossover of 33 day EMA. below 33 day EMA Look for and take short positions. above 33 day EMA Look for and take Long positions
NY Midnight Strategy with Advanced OptionsThe purpose of this script was originally to test one of ICT 's statements and check where it works best. In this case it was to set positions towards the direction of the New York midnight opening price inside ICT Killzones .
The default settings of this script work best with S&P E-mini futures (ES!), but can work just as well with other instruments. Often the parameters need to be adjusted.
To see results, use the 1h chart in the Tradingview strategy tester.
Supertrend Fixed TP Unified with Time Filter (MSK)Trend Strategy Based on the SuperTrend Indicator
This strategy is based on the use of the adaptive SuperTrend indicator, which takes into account the current market volatility and acts as a dynamic trailing stop. The indicator is visualized on the chart with colors that change depending on the direction of the trade: green indicates an uptrend (long), while red indicates a downtrend (short).
How It Works:
A buy signal (long) is generated when a bar closes above the indicator line.
A sell signal (short) is triggered when a bar closes below the indicator line.
Strategy Settings:
Trading Modes :
Long only : Only long positions are allowed.
Short only : Only short positions are allowed.
Both : Both types of trades are permitted.
Take-Profit :
The strategy supports a simple percentage-based take-profit, allowing you to lock in profits during sharp price movements without waiting for a pullback.
The take-profit level and its value are visualized on the chart. Visualization can be disabled in the settings.
Colored Chart Areas :
Long and short areas on the chart are highlighted with background colors for easier analysis.
Price Level :
You can set a price level in the settings to restrict trade execution:
Long trades are executed only above the specified level.
Short trades are executed only below the specified level.
This mode can be enabled or disabled in the parameters.
________________________________________________________________
Описание стратегии (на русском языке)
Трендовая стратегия на основе индикатора SuperTrend
Стратегия основана на использовании адаптивного индикатора SuperTrend , который учитывает текущую волатильность рынка и играет роль динамического трейлинг-стопа. Индикатор визуализируется на графике цветом, который меняется в зависимости от направления сделки: зелёный цвет указывает на восходящий тренд (лонг), а красный — на нисходящий тренд (шорт).
Принцип работы:
Сигнал на покупку (лонг) генерируется при закрытии бара выше линии индикатора.
Сигнал на продажу (шорт) возникает при закрытии бара ниже линии индикатора.
Настройки стратегии:
Режимы торговли :
Long only : только лонговые позиции.
Short only : только шортовые позиции.
Both : разрешены оба типа сделок.
Тейк-профит :
Стратегия поддерживает простой процентный тейк-профит, что позволяет фиксировать прибыль при резком изменении цены без ожидания отката.
Уровень и значение тейк-профита визуализируются на графике. Визуализацию можно отключить в настройках.
Цветные области графика :
Лонговые и шортовые области графика выделяются цветом фона для удобства анализа.
Уровень цены :
В настройках можно задать уровень цены, который будет ограничивать выполнение сделок:
Лонговые сделки выполняются только выше указанного уровня.
Шортовые сделки выполняются только ниже указанного уровня.
Этот режим можно включать или отключать в параметрах.
Crypto Trend Reactor
Crypto Trend Reactor
🔧 By Rob Groff
Crypto Trend Reactor is a precision-engineered crypto trading strategy designed to identify high-quality trades through a fusion of advanced non-repainting indicators. This system integrates adaptive trend detection, volatility compression analysis, and directional momentum confirmation to provide clear, rule-based entries and dynamic trade management.
📜 Disclaimer
This script is for informational and educational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Always conduct your own research and consult with a professional advisor before making trading decisions.
✅ System Overview
This strategy is built around a synergy of robust, market-tested indicators that function together to filter noise, enhance trend clarity, and improve execution timing.
✅ McGinley Dynamic (Baseline)
An adaptive moving average that adjusts to price velocity, offering smoother and more responsive trend detection than traditional EMAs. Used to establish the primary trend direction.
✅ TTM Squeeze + Momentum
Detects volatility compression using Bollinger Bands inside Keltner Channels. When momentum aligns with a squeeze release, it signals explosive breakout potential — perfect for crypto markets.
✅ Vortex Indicator (Directional Volatility Filter)
Measures positive and negative trend strength. It confirms whether momentum aligns with trend direction, reducing false signals and choppy conditions.
✅ White Line (Bias Filter)
A simplified market structure average (High/Low midpoint) that acts as a bias filter. Aligning entries with this structural midpoint ensures trades are taken in the path of least resistance.
✅ Tether Line Cloud (Support/Resistance Mapping)
Fast and slow tether lines form a dynamic support/resistance cloud. This visual reference confirms price structure and trend shifts in real-time.
✅ ATR-Based Dynamic Stop Loss
Trailing stops adapt to volatility using ATR (with wick consideration). This enables better protection against random spikes while giving trades room to breathe.
✅ Fixed Multi-Level Take Profits (TP1 & TP2)
Position-reducing take profit levels help secure gains while maintaining trade flexibility. After TP2 is hit, the strategy supports dynamic re-entry if the trend resumes.
✅ Advanced Features
✅ Fully non-repainting logic
✅ Dynamic re-entry support after TP2 or stop-out
✅ Separate take profit and stop loss logic for long and short trades
✅ Visual trade dashboard with live PnL, win rate, position info, and trend status
✅ TTM Squeeze dots shown as ✅ blue dots below/above bars
✅ Bar coloring and cloud fills based on real-time trend alignment
✅ Built-in date filter for backtest range control
✅ Recommended Use
Timeframe: Best optimized for the 1-hour chart, but effective on other timeframes with minor tuning
Market: Designed for crypto, but also functional in other volatile asset classes
Strategy Mode: Works best in trending environments. Avoids ranging conditions via Vortex filtering and multi-confirmation layers
✅ Best Practices
✅ Confirm entries only when all filters align (trend, bias, volatility, and momentum)
✅ Monitor the dashboard for live trade metrics and trend health
✅ Use the built-in stop and TP logic to automate exits
✅ Backtest with various parameter settings to fine-tune for specific coins or volatility profiles
This script represents the fusion of structure, momentum, trend, and volatility — delivering an edge-driven approach for serious crypto traders seeking consistent execution and high-probability setups.
Dual Keltner Channels Strategy [Eastgate3194]This strategy utilised 2 Keltner Channels to perform counter trade.
The strategy have 2 steps:
Long Position:
Step 1. Close price must cross under Outer Lower band of Keltner Channel.
Step 2. Close price cross over Inner Lower band of Keltner Channel.
Short Position:
Step 1. Close price must cross over Outer Upper band of Keltner Channel.
Step 2. Close price cross under Inner Upper band of Keltner Channel.
ThinkTech AI SignalsThink Tech AI Strategy
The Think Tech AI Strategy provides a structured approach to trading by integrating liquidity-based entries, ATR volatility thresholds, and dynamic risk management. This strategy generates buy and sell signals while automatically calculating take profit and stop loss levels, boasting a 64% win rate based on historical data.
Usage
The strategy can be used to identify key breakout and retest opportunities. Liquidity-based zones act as potential accumulation and distribution areas and may serve as future support or resistance levels. Buy and sell zones are identified using liquidity zones and ATR-based filters. Risk management is built-in, automatically calculating take profit and stop loss levels using ATR multipliers. Volume and trend filtering options help confirm directional bias using a 50 EMA and RSI filter. The strategy also allows for session-based trading, limiting trades to key market hours for higher probability setups.
Settings
The risk/reward ratio can be adjusted to define the desired stop loss and take profit calculations. The ATR length and threshold determine ATR-based breakout conditions for dynamic entries. Liquidity period settings allow for customized analysis of price structure for support and resistance zones. Additional trend and RSI filters can be enabled to refine trade signals based on moving averages and momentum conditions. A session filter is included to restrict trade signals to specific market hours.
Style
The strategy includes options to display liquidity lines, showing key support and resistance areas. The first 15-minute candle breakout zones can also be visualized to highlight critical market structure points. A win/loss statistics table is included to track trade performance directly on the chart.
This strategy is intended for descriptive analysis and should be used alongside other confluence factors. Optimize your trading process with Think Tech AI today!
Liquidity + Internal Market Shift StrategyLiquidity + Internal Market Shift Strategy
This strategy combines liquidity zone analysis with the internal market structure, aiming to identify high-probability entry points. It uses key liquidity levels (local highs and lows) to track the price's interaction with significant market levels and then employs internal market shifts to trigger trades.
Key Features:
Internal Shift Logic: Instead of relying on traditional candlestick patterns like engulfing candles, this strategy utilizes internal market shifts. A bullish shift occurs when the price breaks previous bearish levels, and a bearish shift happens when the price breaks previous bullish levels, indicating a change in market direction.
Liquidity Zones: The strategy dynamically identifies key liquidity zones (local highs and lows) to detect potential reversal points and prevent trades in weak market conditions.
Mode Options: You can choose to run the strategy in "Both," "Bullish Only," or "Bearish Only" modes, allowing for flexibility based on market conditions.
Stop-Loss and Take-Profit: Customizable stop-loss and take-profit levels are integrated to manage risk and lock in profits.
Time Range Control: You can specify the time range for trading, ensuring the strategy only operates during the desired period.
This strategy is ideal for traders who want to combine liquidity analysis with internal structure shifts for precise market entries and exits.
This description clearly outlines the strategy's logic, the flexibility it provides, and how it works. You can adjust it further to match your personal trading style or preferences!
