Momentum Indicator Driven Trend Following Trading Strategy

This strategy builds trading signals based on momentum indicator RSI and price's Exponential Moving Average (EMA) and Simple Moving Average (SMA). It belongs to the trend following type of strategies.

Pine ScriptMomentum Trend following Mean reversion RSI MACD EMA SMA

Author: ChaoZhang
Complexity: Starter · 74 lines
Parameters: 5
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Principle

The strategy uses 3 conditions to generate trading signals:

RSI > 45: RSI value greater than 45 is considered a good buy signal
EMA(RSI) > SMA(RSI): EMA line greater than SMA line indicates RSI is accelerating upwards, which is a good momentum signal
EMA(close) > SMA(close): EMA line greater than SMA line indicates the price trend is accelerating upwards

Meeting any 2 of the above 3 conditions generates a buy signal; if none is met, a sell signal is generated.

The strategy also provides an "always buy" mode for testing the system's performance relative to the broad market.

Advantage Analysis

Using momentum indicator RSI to judge market conditions can reduce positions during market fluctuations
Combining EMA and SMA to determine trend direction can timely capture price change trends
Simple and clear conditional rules, easy to understand and optimize
Provides "always buy" mode to test system advantages

Risk Analysis

Relies on parameter settings, improper parameters will lead to frequent trading or miss good trading opportunities
Major news in the broad market can cause huge volatility in the short term, which will lead to stop loss
The strategy itself cannot judge when a trend is about to reverse, other indicators need to be used to determine

Optimization Directions

Optimize parameters of RSI, EMA and SMA to find best parameter combination
Increase other technical indicators like Volume, MACD etc. to enrich rule conditions
Increase trend reversal indicators to reduce probability of losses

Conclusion

In summary, this strategy belongs to a medium-frequency trading strategy that aims to capture mid-term price trends while avoiding short-term market fluctuations. Its advantages and risk points are quite obvious. Further enhancing stability through parameter optimization and enriching rules makes it a worthwhile high-efficiency quantitative trading strategy to research and optimize.

Parameters

Name	Default	What it controls
v_input_string_1	Unitrend	Trading Mode
v_input_bool_1	false	compoundingMode
v_input_float_1	true	leverage
v_input_float_2	true	Risk Capital per Trade unleveraged (%)
v_input_float_3	2	TPFactor

Source Pine Script

/*backtest
start: 2022-12-05 00:00:00
end: 2023-12-11 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5
strategy("I11L Unitrend",overlay=false, initial_capital=1000000,default_qty_value=1000000,default_qty_type=strategy.cash,commission_type=strategy.commission.percent,commission_value=0.00)
tradingMode = input.string("Unitrend", "Trading Mode", ["Unitrend", "Always Buy"], tooltip="Choose the Trading Mode by trying Both in your Backtesting. I use it if one is far better then the other one.")
compoundingMode = input.bool(false)
leverage = input.float(1.0,step=0.1)
SL_Factor = 1 - input.float(1,"Risk Capital per Trade unleveraged (%)", minval=0.1, maxval=100, step=0.1) / 100
TPFactor = input.float(2, step=0.1)




var disableAdditionalBuysThisDay = false
var lastTrade = time
if(time > lastTrade + 1000 * 60 * 60 * 8 or tradingMode == "Always Buy")
    disableAdditionalBuysThisDay := false

if(strategy.position_size != strategy.position_size[1])
    lastTrade := time
    disableAdditionalBuysThisDay := true

//Trade Logic
SCORE = 0

//rsi momentum
RSIFast = ta.ema(ta.rsi(close,50),24)
RSISlow = ta.sma(ta.rsi(close,50),24)
RSIMomentum = RSIFast / RSISlow
goodRSIMomentum = RSIMomentum > 1
SCORE := goodRSIMomentum ? SCORE + 1 : SCORE

//rsi trend
RSITrend = RSISlow / 45
goodRSI = RSITrend > 1
SCORE := goodRSI ? SCORE + 1 : SCORE

//price trend
normalTrend = ta.ema(close,50) / ta.sma(close,50)
goodTrend = normalTrend > 1
SCORE := goodTrend ? SCORE + 1 : SCORE



isBuy =  SCORE > 1 or tradingMode == "Always Buy"
isSell = false //SCORE == 0

//plot(SCORE, color=isBuy ? color.green : #ffffff88)
//reduced some of the values just for illustrative purposes, you can buy after the signal if the trendlines seem to grow
plot(1, color=isBuy ? #77ff7733 : SCORE == 2 ? #ffff0033 : SCORE == 1 ? #ff888833 : #ff000033,linewidth=10)
plot(1 - (1 - RSIMomentum) * 6,color=#00F569)
plot(1 - (1 - RSITrend) * 0.25,color=#00DB9B)
plot(1 - (1 - normalTrend) * 20,color=#00F5EE)


strategy.initial_capital = 50000
if(isBuy and not(disableAdditionalBuysThisDay))
    if(compoundingMode)
        strategy.entry("Long", strategy.long, (strategy.equity / close) * leverage)
    else
        strategy.entry("Long", strategy.long, (strategy.initial_capital / close) * leverage)


if(strategy.position_size != 0)
    strategy.exit("TP/SL Long", "Long", stop=strategy.position_avg_price * (1 - (1 - SL_Factor)), limit=strategy.position_avg_price * (1 + (1 - SL_Factor) * TPFactor))

Published by ChaoZhang on the FMZ strategy square · last modified 2023-12-12. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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