Trend Following Strategy Based on Multi Timeframe Moving Average and RSI

Pine ScriptTrend following Multi-timeframe Mean reversion RSI EMA Bollinger Bands

Author: ChaoZhang
Complexity: Intermediate · 68 lines
Parameters: 8
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

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Overview

This strategy identifies trend direction based on multi timeframe moving average and judges overbought/oversold situation with RSI to generate trading signals. When the long, medium and short MA lines are in the same direction, it is considered as a trend. At this point, RSI is used to determine if it is overbought/oversold and trading signals are generated. In addition, the strategy also adopts trailing stop loss to control risks.

Strategy Logic

The basic logic is to judge the trend through golden cross and death cross of fast and slow moving averages. When the fast line crosses above the slow line, it is a golden cross indicating a bull market. When the fast line crosses below the slow line, it is a death cross indicating a bear market. This strategy applies such logic in different timeframes to see if the long, medium and short terms are in the same direction. If they are all bull or bear, trading signals are generated. In addition, RSI helps avoid missing stop loss at inflection points. Trailing stop loss sets certain offset to let profits run while controlling risks.

Advantage Analysis

Using multiple timeframes to determine trends can effectively filter out short-term market noise and identify medium-long term trends.
RSI helps avoid insisting on original direction at inflection points and missing stop loss.
Trailing stop loss considers both profit growth and risk control, leading to high return/risk ratio.

Risk Analysis

Multi timeframe determination may have time lag, resulting in late entry and missing early phase of the trend.
RSI only judges overbought/oversold status. It does not perform well in determining inflection points when sharp reversal happens.
Improper setup of trailing stop loss offset may lead to too aggressive or conservative behaviors. Parameter tuning is needed.

Optimization Directions

Consider combining more indicators such as Bollinger Bands and KDJ to generate more precise trading signals.
Adopt dynamic trailing stop loss that adjusts offset based on market volatility and risk appetite.
Apply similar logic in even shorter timeframes to better utilize capital.

Summary

In general, this strategy has more pros than cons. It accurately determines medium-long term trends and delivers high return/risk payoff. As a trend following system, it can identify the major trend direction amid consolidations. Further improvements on parameters and indicators can enhance its stability and profitability.

Parameters

Name	Default	What it controls
v_input_1_close	0	kaynak: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_2	21	hızlıbarlar
v_input_3	34	yavaşbarlar
v_input_4	240	uzunvade
v_input_5	60	ortavade
v_input_6	5	kısavade
v_input_7	60	aşırıalım
v_input_8	25	aşırısatış

Source Pine Script

/*backtest
start: 2023-01-01 00:00:00
end: 2024-01-07 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4
//Cryptocurrency Trading Tools by XMAXPRO
//ATA INDIKATORU
//Test 4.0v Tarih:23.02.2020
//

strategy("MTF+MA+RSI+TSL", overlay=false, shorttitle="ATA v4 Strategy")
src = input(title="kaynak", type=input.source, defval=close)
fast = input(title="hızlıbarlar", type=input.integer, defval=21)
slow = input(title="yavaşbarlar", type=input.integer, defval=34)

//MTF source
long = input(title="uzunvade", type=input.resolution, defval="240")
mid = input(title="ortavade", type=input.resolution, defval="60")
short = input(title="kısavade", type=input.resolution, defval="5")

//MTF Grafikleri
ln = security(syminfo.ticker, long, src)
md = security(syminfo.ticker, mid, src)
sh = security(syminfo.ticker, short, src)

//0
lnma = ema(ln, fast) - ema(ln, slow)
mdma = ema(sh, fast) - ema(md, slow)
shma = ema(sh, fast) - ema(sh, slow)

//Makeup
uzunrenk = lnma > 0 ? color.white : color.red
ortarenk = mdma > 0 ? color.white : color.red
kisarenk = shma > 0 ? color.white : color.red

l1 = 1
m1 = 2
s1 = 3

plot(l1, style=plot.style_line, color=uzunrenk, linewidth=25)
plot(m1, style=plot.style_line, color=ortarenk, linewidth=25)
plot(s1, style=plot.style_line, color=kisarenk, linewidth=25)

atarsi = rsi(close, 14)
rsiob = input(title="aşırıalım", type=input.integer, defval=60)
rsios = input(title="aşırısatış", type=input.integer, defval=25)

sell = atarsi > rsiob and lnma > 0 and mdma > 0 and shma > 0
buy = atarsi < rsios and lnma < 0 and mdma < 0 and shma < 0

barcolor(sell ? color.white : color.red)
barcolor(buy ? color.white : color.red)

//strateji
strategy.entry("long", strategy.long, comment = "BULL", when = sell)
strategy.entry("short", strategy.short, comment = "BEAR", when = buy)

//kompleks alarm
//alertcondition(sell, title = "ATA LONG SIGNAL", message = "btc/usd ata long sinyali")
//alertcondition(buy, title = "ATA SHORT SIGNAL", message = "btc/usd ata short sinyali")

//iz sürücü TSL
strategy.exit ("Bull TSL", "long", trail_points=close * 0.02 / syminfo.mintick, trail_offset=close * 0.02/syminfo.mintick)
strategy.exit ("Bear TSL", "short", trail_points=close * 0.02 / syminfo.mintick, trail_offset=close * 0.02/syminfo.mintick)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-01-08. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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