3EMA with Stochastic RSI Strategy

Pine ScriptMean reversion Trend following Volatility RSI EMA SMA ATR Stochastic

Author: ChaoZhang
Complexity: Intermediate · 62 lines
Parameters: 11
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This is a trend following strategy combining multiple indicators. It uses three EMAs with different periods, Stochastic RSI and ATR to identify trend direction and establish positions. It goes long when the faster EMA crosses above the slower EMA, with stop loss set at 3 times the recent ATR value and take profit at 2 times the recent ATR.

Principle

The strategy uses three EMA lines - 8-, 14- and 50-period EMAs, representing price trends over different timeframes. When the 8-period EMA crosses above the 14-period EMA, and the 14-period EMA crosses above the 50-period EMA, it signals the start of an uptrend and a long position can be initiated.

The Stochastic RSI indicator incorporates RSI and Stochastic calculations to identify overbought/oversold conditions. When the Stochastic RSI K line crosses above the D line from below, it suggests the market is transitioning from oversold to bullish outlook, allowing a long position.

ATR represents the recent volatility range. The strategy uses 3 times ATR as stop loss distance and 2 times ATR as take profit distance to lock in profits and control risk.

Advantages

EMAs filter out noise in price data and identify trend direction
Stochastic RSI identifies reversal opportunities
ATR dynamically trails stop loss/take profit based on market volatility

Risks

Multiple indicators may generate conflicting signals
Fixed stop loss/take profit ratios cannot adapt to changing market conditions
Short-term longs susceptible to reversals

Optimization can be done by adjusting EMA periods to optimize sensitivity. Making ATR ratios adjustable allows customization based on market conditions. Adding other indicators helps validate signals and avoid mistakes.

Enhancement

Adjust EMA periods to optimize sensitivity
Make ATR ratios adjustable
Add other indicators to avoid false signals

Conclusion

The strategy considers trend, overbought/oversold levels, and volatility range to identify entry timing. EMAs and Stochastic RSI combined effectively identify trends, while ATR's dynamic stop loss/take profit helps risk control. With parameter tuning and optimizations, the strategy can become a reliable trend following system. But false signals and fixed stop loss/take profit caveats need to be watched out for.

Parameters

Name	Default	What it controls
v_input_1	8	EMA1 Length
v_input_2	14	EMA2 Length
v_input_3	50	EMA3 Length
v_input_4	3	K
v_input_5	3	D
v_input_6	14	RSI Length
v_input_7	14	Stochastic Length
v_input_8_close	0	RSI Source: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_9	14	ATR Period
v_input_10	2	Take-profit Multiplier
v_input_11	3	Stop-loss Multiplier

Source Pine Script

/*backtest
start: 2023-10-15 00:00:00
end: 2023-11-14 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © FreddieChopin
 
//@version=4
strategy("3 x EMA + Stochastic RSI + ATR", overlay = true, default_qty_type = strategy.percent_of_equity, default_qty_value = 100)
 
// 3x EMA
ema1Length = input(8, "EMA1 Length", minval = 1)
ema2Length = input(14, "EMA2 Length", minval = 1)
ema3Length = input(50, "EMA3 Length", minval = 1)
ema1 = ema(close, ema1Length)
ema2 = ema(close, ema2Length)
ema3 = ema(close, ema3Length)
 
plot(ema1, color = color.green)
plot(ema2, color = color.orange)
plot(ema3, color = color.red)
 
// Stochastic RSI
smoothK = input(3, "K", minval=1)
smoothD = input(3, "D", minval=1)
lengthRSI = input(14, "RSI Length", minval=1)
lengthStoch = input(14, "Stochastic Length", minval=1)
src = input(close, title="RSI Source")
rsi1 = rsi(src, lengthRSI)
k = sma(stoch(rsi1, rsi1, rsi1, lengthStoch), smoothK)
d = sma(k, smoothD)
 
// ATR
atrPeriod = input(14, "ATR Period")
takeProfitMultiplier= input(2.0, "Take-profit Multiplier")
stopLossMultiplier= input(3.0, "Stop-loss Multiplier")
atrSeries = atr(atrPeriod)[1]
 
longCondition = ema1 > ema2 and ema2 > ema3 and crossover(k, d)
strategy.entry("long", strategy.long, when = longCondition)
 
float stopLoss = na
float takeProfit = na
 
if (strategy.position_size > 0)
    if (na(stopLoss[1]))
        stopLoss := strategy.position_avg_price - atrSeries * stopLossMultiplier
    else
        stopLoss := stopLoss[1]
    if (na(takeProfit[1]))
        takeProfit := strategy.position_avg_price + atrSeries * takeProfitMultiplier
    else
        takeProfit := takeProfit[1]
 
    strategy.exit("take profit / stop loss", limit = takeProfit, stop = stopLoss)
 
plot(stopLoss, color = color.red, linewidth = 2, style = plot.style_linebr)
plot(takeProfit, color = color.green, linewidth = 2, style = plot.style_linebr)

Published by ChaoZhang on the FMZ strategy square · last modified 2023-11-15. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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