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Multi-Indicator Trend Momentum Crossover Quantitative Strategy

Author: ChaoZhang, Date: 2024-12-11 15:00:51
Tags: EMARSIATRSMA

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Overview

This is a multi-indicator trading strategy that combines Supertrend, Exponential Moving Average (EMA), and Relative Strength Index (RSI). The strategy identifies market trends, momentum, and potential reversal points through the crossover signals and overbought/oversold levels of these three technical indicators, seeking optimal trading opportunities in the market. The strategy leverages the advantages of multiple indicators to enhance trading accuracy and reliability through market analysis from different dimensions.

Strategy Principles

The core logic is based on the combined analysis of three main technical indicators:

  1. Supertrend indicator determines overall trend direction using ATR volatility for dynamic trend line adjustment.
  2. Crossovers of short-term (9-period) and long-term (21-period) EMAs capture price momentum changes.
  3. RSI indicator identifies overbought or oversold market conditions.

Buy signals require all of the following conditions:

  • Supertrend shows bullish trend (price above Supertrend line)
  • Short-term EMA crosses above long-term EMA
  • RSI is not overbought (below 70)

Sell signals require all of the following conditions:

  • Supertrend shows bearish trend (price below Supertrend line)
  • Short-term EMA crosses below long-term EMA
  • RSI is not oversold (above 30)

Strategy Advantages

  1. Multi-indicator cross-validation improves signal reliability
  2. Combines benefits of trend following and momentum analysis
  3. RSI filters out potential false signals
  4. Strategy parameters can be flexibly adjusted for different market conditions
  5. Clear entry and exit rules reduce subjective judgment influence
  6. Incorporates solid risk control mechanisms

Strategy Risks

  1. May generate frequent false signals in ranging markets
  2. Multiple indicators’ lag may delay entry and exit timing
  3. Improper parameter selection can affect strategy performance
  4. Sudden market changes may lead to significant drawdowns
  5. Trading costs need to be considered for strategy profitability

Strategy Optimization Directions

  1. Introduce adaptive parameter mechanisms to dynamically adjust indicator parameters based on market volatility
  2. Add volume-price analysis indicators to enhance signal reliability
  3. Develop market environment recognition module to use different parameter combinations in different market conditions
  4. Implement stop-loss and take-profit mechanisms to optimize money management
  5. Consider adding volatility filters to avoid overtrading in low volatility environments

Summary

This is a well-structured, logically sound multi-indicator quantitative trading strategy that builds a comprehensive trading system by combining trend following, momentum analysis, and overbought/oversold indicators. The strategy’s strength lies in its multi-indicator cross-validation for improved signal reliability and clear risk control mechanisms. While inherent risks exist, continuous optimization and refinement could help maintain stable performance across different market environments.

/*backtest
start: 2019-12-23 08:00:00
end: 2024-12-09 08:00:00
period: 1d
basePeriod: 1d
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © satyakipaul3744

//@version=6
//@version=6
strategy("Supertrend + EMA Crossover + RSI Strategy", overlay=true)

// --- Input Parameters ---
supertrend_length = input.int(10, title="Supertrend Length", minval=1)
supertrend_multiplier = input.float(3.0, title="Supertrend Multiplier", step=0.1)
short_ema_length = input.int(9, title="Short EMA Length")
long_ema_length = input.int(21, title="Long EMA Length")
rsi_length = input.int(14, title="RSI Length")
rsi_overbought = input.int(70, title="RSI Overbought Level")
rsi_oversold = input.int(30, title="RSI Oversold Level")

// --- Indicator Calculations ---
// Supertrend calculation
[supertrend, direction] = ta.supertrend(supertrend_multiplier, supertrend_length)

// EMA calculations
short_ema = ta.ema(close, short_ema_length)
long_ema = ta.ema(close, long_ema_length)

// RSI calculation
rsi = ta.rsi(close, rsi_length)

// --- Buy/Sell Conditions ---
// Buy condition: Supertrend bullish, EMA crossover, RSI not overbought
buy_condition = direction > 0 and ta.crossover(short_ema, long_ema) and rsi < rsi_overbought

// Sell condition: Supertrend bearish, EMA crossunder, RSI not oversold
sell_condition = direction < 0 and ta.crossunder(short_ema, long_ema) and rsi > rsi_oversold

// --- Plot Buy/Sell signals ---
plotshape(buy_condition, title="Buy Signal", location=location.belowbar, color=color.green, style=shape.labelup, text="BUY")
plotshape(sell_condition, title="Sell Signal", location=location.abovebar, color=color.red, style=shape.labeldown, text="SELL")

// --- Strategy Orders for Backtesting ---
if buy_condition
    strategy.entry("Buy", strategy.long)

if sell_condition
    strategy.close("Buy")

// --- Plot Supertrend ---
plot(supertrend, color=direction > 0 ? color.green : color.red, linewidth=2, title="Supertrend")

// --- Plot EMAs ---
plot(short_ema, color=color.blue, title="Short EMA")
plot(long_ema, color=color.orange, title="Long EMA")

// --- Strategy Performance ---
// You can see the strategy performance in the "Strategy Tester" tab.
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