Hybrid EMA Momentum Trading System with Trend Persistence Analysis Strategy

Pine ScriptMomentum Trend following Breakout RSI EMA ATR Supertrend

Author: ChaoZhang
Complexity: Starter · 65 lines
Parameters: 0
Backtest bar: 2h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This strategy is a hybrid trading system that combines multiple technical indicators, including Exponential Moving Averages (EMA), Relative Strength Index (RSI), and SuperTrend to capture market trends. The strategy uses fixed parameters optimized for 2-hour timeframes, employing a 21/55/200 EMA system for trend identification, combined with RSI(14) momentum filter and SuperTrend(3,14) stop-loss for risk management. It also requires a 1.5x volume surge and ATR volatility confirmation to enhance trading reliability.

Strategy Principles

The core logic is built on a multi-layered technical analysis framework:

Trend identification system uses triple EMAs (21/55/200 periods) to determine trend direction through crossovers and relative positions
Momentum confirmation system employs RSI(14) indicator combined with its EMA to filter false breakouts
Risk control system integrates SuperTrend indicator as dynamic stop-loss and implements a 6-hour trade cooldown period
Trade trigger conditions require volume exceeding 1.5x of 20-period average volume and ATR above its 48-period EMA

Strategy Advantages

Parameter Optimization: Uses pre-optimized fixed parameters requiring no frequent adjustments
Trend Capture: Effectively captures persistent trends through multiple technical indicator coordination
Risk Control: Built-in trade cooldown mechanism prevents overtrading
Market Adaptability: Performs well in highly volatile markets
Trade Confirmation: Multiple condition filters enhance trading signal reliability

Strategy Risks

Gap Risk: Potential losses from gaps in 24-hour trading markets
News Impact: Major news events may cause severe price volatility affecting strategy performance
Stop-Loss Rigidity: Fixed stop-loss settings may lack flexibility
Market Environment Dependence: May generate frequent false signals in ranging markets
Slippage Risk: Potential significant slippage in markets with poor liquidity

Strategy Optimization Directions

Dynamic Parameter Adjustment: Implement automatic SuperTrend parameter adjustment based on market volatility
Market Environment Recognition: Add market state identification module for different parameter settings in various market conditions
Stop-Loss Optimization: Introduce dynamic stop-loss mechanism adapting to market volatility
Volume Analysis Enhancement: Incorporate more sophisticated volume analysis models to improve signal accuracy
Risk Management Optimization: Implement dynamic position sizing system based on market conditions

Summary

This strategy constructs a relatively complete trading system through the combination of multiple technical indicators. Its strength lies in effective trend capture and enhanced trading reliability through multiple condition filters. While inherent risks exist, the strategy's overall performance can be improved through optimization and refinement. It is particularly suitable for volatile markets but requires attention to market environment changes and risk control.

Source Pine Script

/*backtest
start: 2024-02-19 00:00:00
end: 2025-02-16 08:00:00
period: 2h
basePeriod: 2h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=6
strategy("Hybrid Trend Momentum Strategy by Biege ver. 1.0", overlay=true)

// ---- SUPERTREND FIX ----
supertrendWrapper(factor, atrPeriod) =>
    [stLine, stDir] = ta.supertrend(factor, atrPeriod)
    [stLine, stDir]

// ---- GLOBAL EMA CALCULATIONS ----
fastEMA = ta.ema(close, 21)
slowEMA = ta.ema(close, 55)
trendEMA = ta.ema(close, 200)
atrVal = ta.atr(14)
atrEMA = ta.ema(atrVal, 48)
rsiVal = ta.rsi(close, 14)
rsiEMA = ta.ema(rsiVal, 14)
volumeEMA = ta.ema(volume, 20)
[supertrendLine, supertrendDir] = supertrendWrapper(3, 14)

// ---- TRADE THROTTLING SYSTEM ----
var int lastTradeTime = na
tradeCooldown = input.int(360, "Cooldown (minutes)", minval=60, step=15) * 60 * 1000

// ---- ENHANCED ENTRY CONDITIONS ----
entryCondition = 
     ta.crossover(fastEMA, slowEMA) and
     rsiVal > rsiEMA + 10 and
     close > supertrendLine and
     close > trendEMA and
     volume > volumeEMA * 1.5 and
     atrVal > atrEMA and
     (na(lastTradeTime) or time - lastTradeTime >= tradeCooldown)

// ---- ULTRA-OPTIMIZED EXIT CONDITIONS ----
exitCondition = 
     ta.crossunder(fastEMA, slowEMA) or                   // Main EMA cross remains
     ta.crossunder(rsiVal, rsiEMA - 15) or                // Increased from -10 to -15 (harder trigger)
     ta.crossunder(close, supertrendLine * 0.98)          // Changed from 1.01 to 0.98 (2% buffer below)

// ---- TRADE EXECUTION ----
if entryCondition
    strategy.entry("Buy", strategy.long)
    lastTradeTime := time

if exitCondition
    strategy.close("Buy")

// ---- VISUALS ----
plot(fastEMA, "Fast EMA", color.new(#2962FF, 0), 2)
plot(slowEMA, "Slow EMA", color.new(#FF6D00, 0), 2)
plot(trendEMA, "Trend EMA", color.new(#AA00FF, 0), 2)
plot(supertrendLine, "SuperTrend", color.new(#00C853, 0), 2)

plotshape(entryCondition, "Buy", shape.triangleup, 
  location.belowbar, color.new(#00E676, 0), size=size.small)
plotshape(exitCondition, "Sell", shape.triangledown, 
  location.abovebar, color.new(#FF1744, 0), size=size.small)

Published by ChaoZhang on the FMZ strategy square · last modified 2025-02-18. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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