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Индикаторы и стратегии
Triple Sync StrategyThe Triple Sync Strategy is a comprehensive technical analysis tool designed to combine three powerful indicators: the ADX (Average Directional Index), Stochastic RSI, and CCI (Commodity Channel Index). By synthesizing these indicators into a single line, referred to as the Snake Line, this strategy identifies strong market trends and potential reversal points with high accuracy.
Key Features:
ADX helps measure the strength of a trend, ensuring that trades are executed in trending conditions.
Stochastic RSI smoothens the RSI values to detect overbought and oversold conditions, offering entry and exit signals.
CCI highlights price deviation from the average, providing insights into potential trend changes.
Dynamic Levels automatically adjust to market conditions, with overbought and oversold levels plotted as entry and exit zones.
Entry Signals: The strategy generates buy (long) and sell (short) signals when the Snake Line crosses the defined upper or lower levels.
Performance Optimization: Designed to filter noise and focus on high-probability trade opportunities by combining multiple indicators for a holistic view of the market.
This strategy is ideal for traders looking to identify trend reversals, capitalize on strong market moves, and avoid choppy or sideways price action. With dynamic levels and multiple confirmation points, the Triple Sync Strategy aims to improve trade accuracy and enhance overall trading performance.
Multi-Indicator Trading StrategyKey Features of the Script:
Moving Averages (MA):
Uses a fast and slow SMA to identify trends.
Generates buy/sell signals based on crossovers.
Relative Strength Index (RSI):
Identifies overbought and oversold conditions.
Filters trade to avoid entering during extreme conditions.
MACD:
Confirms momentum with MACD line and signal line crossovers.
Risk Management:
Optional stop loss and take profit levels.
Customizable percentages for risk management.
Backtesting:
The script is designed to backtest historical data.
Trades are executed based on the defined conditions.
High Growth StrategyWork in progress. Looking for coins with the highest growth. Do not user this strategy with a real account. Back test on different coins and comment your best results you find. Lets work as a community to optimize this strategy!
I look forward to seeing what you come up with. If you find any code optimization please share with me via DM or comment below.
Stay Profitable,
Savvy
Gaussian Channel with Stochastic RSI StrategyKeltner Channel with Stochastic RSI Strategy
The Keltner Channel with Stochastic RSI strategy is a technical trading approach that combines the Keltner Channel, a volatility-based indicator, with the Stochastic RSI, a momentum indicator. This strategy aims to identify trading opportunities by detecting overbought and oversold conditions in conjunction with volatility contractions and expansions.
Components:
Keltner Channel: A volatility-based indicator consisting of three bands: the upper band, lower band, and middle band (20-period moving average). The bands are set at 2 x Average True Range (ATR) above and below the middle band.
Stochastic RSI: A momentum indicator that measures the relative position of the RSI (Relative Strength Index) within its own range. The Stochastic RSI is set to 14 periods with overbought and oversold levels at 80 and 20, respectively.
Strategy Rules:
Long Entry:
The price touches or breaks below the lower Keltner Channel band.
The Stochastic RSI falls below 20, indicating oversold conditions.
The RSI must be below 30 to confirm the oversold condition.
Short Entry:
The price touches or breaks above the upper Keltner Channel band.
The Stochastic RSI rises above 80, indicating overbought conditions.
The RSI must be above 70 to confirm the overbought condition.
Exit Rules:
Profit Target: Set a profit target at 1:1 or 1:2 risk-reward ratio.
Stop Loss: Set a stop loss at the opposite side of the Keltner Channel band.
Trailing Stop: Use a trailing stop to lock in profits as the trade moves in your favor.
Additional Considerations:
Trend Filter: Use a trend filter, such as a 50-period moving average, to ensure that trades are taken in the direction of the underlying trend.
Risk Management: Always use proper risk management techniques, such as position sizing and stop-loss orders, to limit potential losses.
By combining the Keltner Channel and Stochastic RSI indicators, this strategy offers a unique approach to identifying trading opportunities in various markets.
Stop losses and Liquidity ZoneThis strategy works best with hiken aishi candles. This strategy is used as a confluence to predict where stop losses are in the market. Pair this with candle range theory to get profitable trades. Blue zones on the map are where retail traders lie and red zones are where market makers are. light red zones are less likely to be attacked but darker red zones are more likely to be attacked in the future. The blue box shows the previous day open and close, Once price hit the last day price, price reversed and went upwards. (candle range theory)
Bank Nifty Buy/Sell Strategyits a low risk strategy where it shows when to buy for scalping a quick 50 to 100 points
Demo GPT - #Moving Average Crossoverdsfsdfsdf fsdfsadfv fewdsfadfs fewasdfasd fasdgdsfgsdf bx fwsdvasdgsfdb fasdgdsfgsdf fsadfsdgdfsg fsadgsdfgsdfg
Multi-Timeframe RSI Grid Strategy with ArrowsKey Features of the Strategy
Multi-Timeframe RSI Analysis:
The strategy calculates RSI values for three different timeframes:
The current chart's timeframe.
Two higher timeframes (configurable via higher_tf1 and higher_tf2 inputs).
It uses these RSI values to identify overbought (sell) and oversold (buy) conditions.
Grid Trading System:
The strategy uses a grid-based approach to scale into trades. It adds positions at predefined intervals (grid_space) based on the ATR (Average True Range) and a grid multiplication factor (grid_factor).
The grid system allows for pyramiding (adding to positions) up to a maximum number of grid levels (max_grid).
Daily Profit Target:
The strategy has a daily profit target (daily_target). Once the target is reached, it closes all open positions and stops trading for the day.
Drawdown Protection:
If the open drawdown exceeds 2% of the account equity, the strategy closes all positions to limit losses.
Reverse Signals:
If the RSI conditions reverse (e.g., from buy to sell or vice versa), the strategy closes all open positions and resets the grid.
Visualization:
The script plots buy and sell signals as arrows on the chart.
It also plots the RSI values for the current and higher timeframes, along with overbought and oversold levels.
How It Works
Inputs:
The user can configure parameters like RSI length, overbought/oversold levels, higher timeframes, grid spacing, lot size multiplier, maximum grid levels, daily profit target, and ATR length.
RSI Calculation:
The RSI is calculated for the current timeframe and the two higher timeframes using ta.rsi().
Grid System:
The grid system uses the ATR to determine the spacing between grid levels (grid_space).
When the price moves in the desired direction, the strategy adds positions at intervals of grid_space, increasing the lot size by a multiplier (lot_multiplier) for each new grid level.
Entry Conditions:
A buy signal is generated when the RSI is below the oversold level on all three timeframes.
A sell signal is generated when the RSI is above the overbought level on all three timeframes.
Position Management:
The strategy scales into positions using the grid system.
It closes all positions if the daily profit target is reached or if a reverse signal is detected.
Visualization:
Buy and sell signals are plotted as arrows on the chart.
RSI values for all timeframes are plotted, along with overbought and oversold levels.
Example Scenario
Suppose the current RSI is below 30 (oversold), and the RSI on the 60-minute and 240-minute charts is also below 30. This triggers a buy signal.
The strategy enters a long position with a base lot size.
If the price moves against the position by grid_space, the strategy adds another long position with a larger lot size (scaled by lot_multiplier).
This process continues until the maximum grid level (max_grid) is reached or the daily profit target is achieved.
Key Variables
grid_level: Tracks the current grid level (number of positions added).
last_entry_price: Tracks the price of the last entry.
base_size: The base lot size for the initial position.
daily_profit_target: The daily profit target in percentage terms.
target_reached: A flag to indicate whether the daily profit target has been achieved.
Potential Use Cases
This strategy is suitable for traders who want to combine RSI-based signals with a grid trading approach to capitalize on mean-reverting price movements.
It can be used in trending or ranging markets, depending on the RSI settings and grid parameters.
Limitations
The grid trading system can lead to significant drawdowns if the market moves strongly against the initial position.
The strategy relies heavily on RSI, which may produce false signals in strongly trending markets.
The daily profit target may limit potential gains in highly volatile markets.
Customization
You can adjust the input parameters (e.g., RSI length, overbought/oversold levels, grid spacing, lot multiplier) to suit your trading style and market conditions.
You can also modify the drawdown protection threshold or add additional filters (e.g., volume, moving averages) to improve the strategy's performance.
In summary, this script is a sophisticated trading strategy that combines RSI-based signals with a grid trading system to manage entries, exits, and position sizing. It includes features like daily profit targets, drawdown protection, and multi-timeframe analysis to enhance its robustnes
SuperTrend on SteroidsSuperTrend on Steroids 🚀
Overview
SuperTrend on Steroids is a **powerful intraday trading strategy designed for high-accuracy trend-following signals. It combines SuperTrend, VWAP, EMA, and ADX to provide **optimized entry and exit points. This script helps traders identify strong momentum-based trades while minimizing false signals.
📌 Key Features
✔ SuperTrend Indicator – Identifies trend direction using ATR-based volatility
✔ VWAP (Volume Weighted Average Price) – Confirms institutional buying/selling pressure
✔ EMA (Exponential Moving Average) – Smooths price action for better trend confirmation
✔ ADX (Average Directional Index) – Measures trend strength to avoid weak signals
✔ Buy/Sell Alerts – Clearly marked "BUY" and "SELL" signals for easy trade execution
✔ Trend Highlighting – Background changes color to indicate trend shifts
📈 How It Works
1. SuperTrend Calculation:
- Uses ATR period (10) and multiplier (3.0) to determine trend direction
- Green trend = Bullish, Red trend = Bearish
2. **VWAP & EMA Confirmation:
- VWAP above EMA = Bullish bias, VWAP below EMA = Bearish bias
- EMA (21) acts as a dynamic support/resistance level
3. ADX Filtering (Optional for Strong Trends):
- ADX above 25 = Strong trend, signals are more reliable
- ADX below 25 = Weak trend, caution is advised
4. Entry Conditions:
✅ BUY Signal:
- SuperTrend turns green (Uptrend confirmation)
- Price closes above VWAP and EMA
- ADX shows trend strength
❌ SELL Signal:
- SuperTrend turns red (Downtrend confirmation)
- Price closes below VWAP and EMA
- ADX confirms downtrend strength
🔍 Best Timeframes & Markets
⏳ Ideal for intraday & short-term trading(5 min, 15 min, 1 hour)
📊 Works best on trending assets (Crypto, Stocks, Forex)
⚠ Avoid using in sideways/choppy markets
🔔 Alerts & Optimization
📢 Set TradingView alerts for buy/sell signals to automate trade execution.
⚙ Customize ATR period, ADX smoothing, EMA length to fit different asset classes.
🚀 Why Use This Strategy?
✔ Combines multiple indicators for high accuracy
✔ Reduces false breakouts using ADX filter
✔ Clear buy/sell signals with visual trend confirmation
✔ Easy to customize for different markets & timeframes
🔹 Disclaimer: No strategy is 100% perfect. Always use proper risk management and test in a demo before live trading. Happy Trading! 🚀📊
Let me know if you need any modifications! 🚀🔥
SAVE ORDER'S STRATEGY V - 1
This Strategy is Using Save Order's Instate of Stop Loss to Profit of the Assets
in this case bitcoin
There is no stop loss
What is Save Order ?
SAVE ORDER IS WHEN IS IN LONG POSITION LIMIT SAVE ORDERS ARE PLACED BELOW -
THE LONG POSITION ON SET DISTANCE TO LOWER THE AVERAGE PRICE OF ALL POSITIONS
WHEN THE ASSET PRICE GO UP LIKE BITCOIN THIS STRATEGY WILL TAKE PROFIT ON -
AVERAGE PRICE FOR ALL ORDER'S
TAKE PROFIT IS TRIALING OR AVERAGE PRICE + TAKE PROFIT %
IF % TRIALING IS USE - AND THE PRACE IS >= TO AVERAGE PRICE + TAKE PROFIT % -
IN REAL TIME THE % TRAILING WILL WORK
UNFORTUNATELY ON BACK TESTING IS NOT REALISTIC
GETTING LONG IS CROSSUNDER FAST HMA - SLOW HMA - THE LENGTHS' CAN BE CHANGE
ALL THE DISTANCE IS DETERMINED BY MAIN SMOOTHED DYNAMIC MA
ONE'S IT GET ON THE FIRST POSITION THE LIMIT ORDER'S ARE SET STATICALLY -
and plot 1 by one
The SUM in Cash for Base Order and All Save orders can be Adjusted
The Distance of the Save orders can be Adjusted
Fast and Slow HMA are plotted
Take Profit and Average Price of the position are plotted
MR-AI-US30 Short-Term RSI StrategyStrategy is based on AI for short term trading less than 4 hours
it is designed for US30
No signals during news (1 hour before and 1 hour after news)
Candle Emotion Index (CEI) StrategyThe Candle Emotion Index (CEI) Strategy is an innovative sentiment-based trading approach designed to help traders identify and capitalize on market psychology. By analyzing candlestick patterns and combining them into a unified metric, the CEI Strategy provides clear entry and exit signals while dynamically managing risk. This strategy is ideal for traders looking to leverage market sentiment to identify high-probability trading opportunities.
How It Works
The CEI Strategy is built around three core oscillators that reflect key emotional states in the market:
Indecision Oscillator . Measures market uncertainty using patterns like Doji and Spinning Tops. High values indicate hesitation, signaling potential turning points.
Fear Oscillator . Tracks bearish sentiment through patterns like Shooting Star, Hanging Man, and Bearish Engulfing. Helps identify moments of intense selling pressure.
Greed Oscillator . Detects bullish sentiment using patterns like Marubozu, Hammer, Bullish Engulfing, and Three White Soldiers. Highlights periods of strong buying interest.
These oscillators are averaged into the Candle Emotion Index (CEI):
CEI = (Indecision + Fear + Greed) / 3
This single value quantifies overall market sentiment and drives the strategy’s trading decisions.
Key Features
Sentiment-Based Trading Signals . Long Entry: Triggered when the CEI crosses above a lower threshold (e.g., 0.1), indicating increasing bullish sentiment. Short Entry: Triggered when the CEI crosses above a higher threshold (e.g., 0.2), signaling rising bearish sentiment.
Volume Confirmation . Trades are validated only if volume exceeds a user-defined multiplier of the average volume over the lookback period. This ensures entries are backed by significant market activity.
Break-Even Recovery Mechanism . If a trade moves into a loss, the strategy attempts to recover to break-even instead of immediately exiting at a loss. This feature provides flexibility, allowing the market to recover while maintaining disciplined risk management.
Dynamic Risk Management . Maximum Holding Period: Trades are closed after a user-defined number of candles to avoid overexposure to prolonged uncertainty. Profit-Taking Conditions: Positions are exited when favorable price moves are confirmed by increased volume, locking in gains. Loss Threshold: Trades are exited early if the price moves unfavorably beyond a set percentage of the entry price, limiting potential losses.
Cooldown Period . After a trade is closed, a cooldown period prevents immediate re-entry, reducing overtrading and improving signal quality.
Why Use This Strategy?
The CEI Strategy combines advanced sentiment analysis with robust trade management, making it a powerful tool for traders seeking to understand market psychology and identify high-probability setups. Its unique features, such as the break-even recovery mechanism and volume confirmation, add an extra layer of discipline and reliability to trading decisions.
Best Practices
Combine with Other Indicators . Use trend-following tools (e.g., moving averages, ADX) and momentum oscillators (e.g., RSI, MACD) to confirm signals.
Align with Key Levels . Incorporate support and resistance levels for refined entries and exits.
Multi-Market Compatibility . Apply this strategy to forex, crypto, stocks, or any asset class with strong volume and price action.
Grid Trading with RSI and Fibonacci SLThis script implements a grid trading strategy that buys when the "AI" confidence is high and the RSI is oversold, and sells when the "AI" confidence is high and the RSI is overbought.
It uses a Fibonacci-based stop-loss and adjusts the grid levels and trade size after each trade.
The "AI" is a very simple rule-based system, not actual artificial intelligence. The script also plots the RSI, AI confidence, grid price, and stop-loss level on the chart.
It's important to thoroughly backtest and understand the risks associated with grid trading strategies before using them with real capital.
MA Crossover with Demand/Supply Zones + Stop Loss/Take ProfitStop Loss and Take Profit Inputs:
Added stopLossPerc and takeProfitPerc as inputs to allow the user to define the stop loss and take profit levels as a percentage of the entry price.
Stop Loss and Take Profit Calculation:
For long positions, the stop loss is calculated as strategy.position_avg_price * (1 - stopLossPerc), and the take profit is calculated as strategy.position_avg_price * (1 + takeProfitPerc).
For short positions, the stop loss is calculated as strategy.position_avg_price * (1 + stopLossPerc), and the take profit is calculated as strategy.position_avg_price * (1 - takeProfitPerc).
Exit Strategy:
Added strategy.exit to define the stop loss and take profit levels for each trade. The from_entry parameter ensures that the exit is tied to the specific entry order.
Flexibility:
The stop loss and take profit levels are dynamic and adjust based on the entry price of the trade.
How It Works:
When a buy signal is generated (MA crossover near a demand zone), the strategy enters a long position and sets a stop loss and take profit level based on the input percentages.
When a sell signal is generated (MA crossunder near a supply zone), the strategy enters a short position and sets a stop loss and take profit level based on the input percentages.
The trade will exit automatically if either the stop loss or take profit level is hit.
Example:
If the entry price for a long position is $100, and the stop loss is set to 1% while the take profit is set to 2%:
Stop loss level =
100
∗
(
1
−
0.01
)
=
100∗(1−0.01)=99
Take profit level =
100
∗
(
1
+
0.02
)
=
100∗(1+0.02)=102
Notes:
You can adjust the stopLossPerc and takeProfitPerc inputs to suit your risk management preferences.
Always backtest the strategy to ensure the stop loss and take profit levels are appropriate for your trading instrument and timeframe.
EMA Crossover + RSI Filter (1-Hour)//@version=5
strategy("EMA Crossover + RSI Filter (1-Hour)", overlay=true)
// Input parameters
fastLength = input.int(9, title="Fast EMA Length")
slowLength = input.int(21, title="Slow EMA Length")
rsiLength = input.int(14, title="RSI Length")
overbought = input.int(70, title="Overbought Level")
oversold = input.int(30, title="Oversold Level")
// Calculate EMAs
fastEMA = ta.ema(close, fastLength)
slowEMA = ta.ema(close, slowLength)
// Calculate RSI
rsi = ta.rsi(close, rsiLength)
// Buy Condition
buyCondition = ta.crossover(fastEMA, slowEMA) and rsi > 50 and rsi < overbought
// Sell Condition
sellCondition = ta.crossunder(fastEMA, slowEMA) and rsi < 50 and rsi > oversold
// Plot EMAs
plot(fastEMA, color=color.blue, title="Fast EMA")
plot(slowEMA, color=color.red, title="Slow EMA")
// Plot Buy/Sell Signals
plotshape(series=buyCondition, title="Buy Signal", location=location.belowbar, color=color.green, style=shape.labelup, text="BUY")
plotshape(series=sellCondition, title="Sell Signal", location=location.abovebar, color=color.red, style=shape.labeldown, text="SELL")
// Execute Trades
if (buyCondition)
strategy.entry("Buy", strategy.long)
if (sellCondition)
strategy.entry("Sell", strategy.short)
Ebuka Moving Average Crossover Strategy with Volume FilterThe provided Pine Script defines a trading strategy that can generate buy and sell signals on TradingView charts. If you'd like to automate the strategy to trade on Binance while you sleep, follow these steps:
EMA and Ichimoku Baseline StrategyBest for swing trading. this strategy is made up by Baseline of ichimoku indicator and moving averages of 5ema and 34ema. It is a crossover strategy.
Demo GPT - Gold Gaussian StrategyA simple GPT stategy for XAU-USD pairs, limited success on backtasting with cryto.
Condition CheckThis script checks the following conditions:
- Latest Open < 1 day ago High
- Latest Close < 1 day ago High
- Latest Open > Latest Low
- Latest Close > 1 day ago Low
- 1 day ago Open < Latest High
- 1 day ago Open < Latest High ( duplicate condition)
- 1 day ago Open > Latest Low
- 1 day ago Close > Latest Low
KON SET By Sai"KON SET By Sai is a trend-following strategy that utilizes ATR-adjusted moving averages to determine entry and exit points. The strategy enters a long position when the price crosses above a custom moving average (adjusted by the ATR value) and exits at a defined target or stop-loss based on the ATR. Additionally, it incorporates re-entry logic, allowing the strategy to re-enter when the price reverses back to the entry point. This strategy is suitable for trend traders who want to manage risk with dynamically calculated stop-loss and target levels."
Tags:
Trend-following
ATR-based strategy
Entry and exit strategy
Stop-loss and target
Re-entry logic
Pine Script strategy
Algorithmic trading
Example Use Case:
"This strategy can be used to trade in trending markets. It provides clear entry and exit signals with automated risk management, making it ideal for traders who prefer systematic approaches to trade management. It works best on lower timeframes (like 5min) for capturing medium-term trends."
How It Works:
Entry Point: The strategy enters a long position when the price crosses above an ATR-adjusted moving average (set by the user).
Exit Points:
Stop-loss is set dynamically based on the ATR value.
Target is also based on the ATR, with an additional multiplier for customization.
Re-entry Logic: If the price retraces back to the entry level, the strategy re-enters the position.
Exit Conditions: The strategy exits when the price hits the stop-loss or target price.
Example:
If the current ATR is 2.0, the strategy will:
Stop-loss: 2x ATR below the entry price.
Target: 5 + user-defined multiplier x ATR above the entry price.
高胜率交易策略在TradingView上创建一个高胜率的交易指标需要结合多种技术分析工具，如均线、动量指标、成交量等。以下是一个基于**均线交叉 + RSI + 成交量过滤**的复合策略指标，适用于多种市场（如加密货币、股票、外汇等）。该指标会生成买入和卖出信号，并尽量提高胜率。
---
### **指标逻辑**
1. **均线交叉**：
- 短期均线（如9周期EMA）上穿长期均线（如21周期EMA）时，生成买入信号。
- 短期均线下穿长期均线时，生成卖出信号。
2. **RSI过滤**：
- 仅在RSI（相对强弱指数）处于30-70区间时触发信号，避免超买/超卖区域的假信号。
3. **成交量过滤**：
- 买入信号需伴随成交量放大（如成交量高于过去20周期的平均值）。
4. **止损与止盈**：
- 基于ATR（平均真实波幅）设置动态止损和止盈水平。
---
### **TradingView Pine Script代码**
以下是完整的Pine Script代码，可直接复制到TradingView中使用：
```pinescript
//@version=5
indicator("高胜率交易策略", overlay=true)
// 参数设置
shortLength = input.int(9, title="短期均线周期")
longLength = input.int(21, title="长期均线周期")
rsiLength = input.int(14, title="RSI周期")
volumeFilter = input.bool(true, title="启用成交量过滤")
atrLength = input.int(14, title="ATR周期")
takeProfitMultiplier = input.float(2.0, title="止盈倍数")
stopLossMultiplier = input.float(1.0, title="止损倍数")
// 计算均线
shortMA = ta.ema(close, shortLength)
longMA = ta.ema(close, longLength)
// 计算RSI
rsi = ta.rsi(close, rsiLength)
// 计算ATR
atr = ta.atr(atrLength)
// 成交量过滤
volumeAvg = ta.sma(volume, 20)
volumeCondition = volume > volumeAvg
// 生成信号
buySignal = ta.crossover(shortMA, longMA) and rsi > 30 and rsi < 70 and (volumeFilter ? volumeCondition : true)
sellSignal = ta.crossunder(shortMA, longMA)
// 止损与止盈
if (buySignal)
strategy.entry("Buy", strategy.long)
strategy.exit("Take Profit/Stop Loss", "Buy", limit=close + atr * takeProfitMultiplier, stop=close - atr * stopLossMultiplier)
if (sellSignal)
strategy.close("Buy")
// 绘制信号
plotshape(series=buySignal, title="买入信号", location=location.belowbar, color=color.green, style=shape.labelup, text="BUY")
plotshape(series=sellSignal, title="卖出信号", location=location.abovebar, color=color.red, style=shape.labeldown, text="SELL")
// 绘制均线
plot(shortMA, color=color.blue, title="短期均线")
plot(longMA, color=color.orange, title="长期均线")
```
---
### **使用方法**
1. 打开TradingView，进入任意图表。
2. 点击“Pine Script编辑器”，将上述代码粘贴并保存。
3. 返回图表，指标会自动加载，显示买入（BUY）和卖出（SELL）信号。
---
### **参数优化建议**
1. **均线周期**：
- 短期均线：9-12周期（适合短线交易）。
- 长期均线：21-50周期（适合中长线交易）。
2. **RSI参数**：
- 默认14周期，可调整为10-20周期以适应不同市场。
3. **ATR止损止盈**：
- 止损倍数：1.0-1.5（保守型）。
- 止盈倍数：2.0-3.0（激进型）。
4. **成交量过滤**：
- 在低波动市场（如外汇）可关闭，在高波动市场（如加密货币）建议开启。
---
### **策略优势**
1. **高胜率**：通过均线交叉 + RSI过滤，减少假信号。
2. **动态止损止盈**：基于ATR设置，适应市场波动。
3. **灵活性**：参数可调，适用于不同市场和交易风格。
---
### **注意事项**
1. **回测验证**：在实盘前，务必在TradingView中进行历史回测，验证策略表现。
2. **风险管理**：单笔交易风险控制在总资金的1%-2%。
3. **市场适应性**：该策略在趋势市场中表现较好，震荡市场中可能出现连续亏损。
---
如果对代码或策略有进一步问题，欢迎随时提问！
