Four Indicator Momentum Reversal Strategy

Pine ScriptMean reversion Momentum Machine learning RSI EMA Heikin Ashi CCI

Author: ChaoZhang
Complexity: Intermediate · 135 lines
Parameters: 13
Backtest bar: 45m · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This strategy utilizes three mainstream technical indicators: the moving average EMA, the relative strength index RSI and the commodity channel index CCI to identify price momentum through EMA crossovers and further entries confirmed by oversold/overbought readings from RSI and CCI. This intermediate-term trading strategy aims to capture momentum reversals.

Strategy Logic

Use crossovers between 4-period and 8-period EMA to determine price momentum – the faster 4-period EMA to swiftly react and the slower 8-period EMA to confirm;
When EMAs turn upward, i.e. the 4-period EMA crossing above the 8-period EMA, check that RSI (over 65) and CCI (above 0) are not overbought to give a long signal;
When EMAs turn downward, i.e. the 4-period EMA crossing below the 8-period EMA, check that RSI (below 35) and CCI (below 0) are oversold to give a short signal;
Set stop loss and take profit prices based on input distances once trade signals are triggered.

In summary, this strategy considers medium-term trend and short-term overbought/oversold levels to form relatively stable signals, while stop losses and take profits effectively limit loss per trade.

Advantage Analysis

Multiple indicators mitigate false signals from individual oscillators;
EMAs determine the main trend while RSI and CCI avoid overheated areas to improve win rate;
Automatic stop loss and take profit setup constrains loss in extreme moves;
Purely technical nature makes this strategy easily implementable across any timeframe.

Risk Analysis

Major fundamental news can override technical levels;
Stop loss may be taken out by huge volatility calls for wider stops;
Frequent trading drives higher transaction costs thus best left for high frequency algorithms.

Enhancement Opportunities

Incorporate machine learning models to auto-adjust parameters based on fundamentals;
Build adaptive stops reacting to volatility rather than fixed distances.

Conclusion

This multifaceted strategy can deliver consistent medium-term profits under optimized parameters, making it an accessible technical system. Still, allowance needs to be given to black swan events via expanded stops etc, presenting areas for ongoing refinements.

Parameters

Name	Default	What it controls
v_input_1	4	Length_MA4
v_input_2_close	0	Source: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_3	false	Offset
v_input_4	8	Length_MA8
v_input_5_close	0	Source: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_6	false	Offset
v_input_7	14	Length
v_input_8	6	CCI Turbo Length
v_input_9	14	CCI 14 Length
v_input_10	12	a
v_input_11	15	b
v_input_12	120	tp
v_input_13	96	sl

Source Pine Script

/*backtest
start: 2023-11-19 00:00:00
end: 2023-11-26 00:00:00
period: 45m
basePeriod: 5m
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/
// © SoftKill21

//@version=4


strategy(title="Moving Average Exponential", shorttitle="EMA", overlay=true)


len4 = input(4, minval=1, title="Length_MA4")
src4 = input(close, title="Source")
offset4 = input(title="Offset", type=input.integer, defval=0, minval=-500, maxval=500)
out4 = ema(src4, len4)
plot(out4, title="EMA", color=color.blue, offset=offset4)

len8 = input(8, minval=1, title="Length_MA8")
src8 = input(close, title="Source")
offset8 = input(title="Offset", type=input.integer, defval=0, minval=-500, maxval=500)
out8 = ema(src8, len8)
plot(out8, title="EMA", color=color.blue, offset=offset8)


//rsioma
src = close, len = input(14, minval=1, title="Length")
up = rma(max(change(ema(src, len)), 0), len)
down = rma(-min(change(ema(src, len)), 0), len)
rsi = down == 0 ? 100 : up == 0 ? 0 : 100 - (100 / (1 + up / down))
//plot(rsi, color=color.blue)
//band1 = hline(80)
//band0 = hline(20)
//fill(band1, band0, color=color.purple, transp=90)
//hline(50, color=color.gray, linestyle=plot.style_line)
sig = ema(rsi, 21)
//plot(sig, color=color.purple)

//woodie
cciTurboLength = input(title="CCI Turbo Length", type=input.integer, defval=6, minval=3, maxval=14)
cci14Length = input(title="CCI 14 Length", type=input.integer, defval=14, minval=7, maxval=20)

source = close

cciTurbo = cci(source, cciTurboLength)
cci14 = cci(source, cci14Length)

last5IsDown = cci14[5] < 0 and cci14[4] < 0 and cci14[3] < 0 and cci14[2] < 0 and cci14[1] < 0
last5IsUp = cci14[5] > 0 and cci14[4] > 0 and cci14[3] > 0 and cci14[2] > 0 and cci14[1] > 0
histogramColor = last5IsUp ? color.green : last5IsDown ? color.red : cci14 < 0 ? color.green : color.red


// Exit Condition
// Exit Condition
a = input(12)*10
b = input(15)*10
c = a*syminfo.mintick
d = b*syminfo.mintick


longCondition = crossover(out4, out8) and (rsi >= 65 and cci14>=0)
shortCondition = crossunder(out4, out8) and (rsi <=35 and cci14<=0)


long_stop_level     = float(na)
long_profit_level1  = float(na)
long_profit_level2  = float(na)
long_even_level     = float(na)

short_stop_level    = float(na)
short_profit_level1 = float(na)
short_profit_level2 = float(na)
short_even_level    = float(na)

long_stop_level     := longCondition  ? close - c : long_stop_level     [1]
long_profit_level1  := longCondition  ? close + d : long_profit_level1  [1]
//long_profit_level2  := longCondition  ? close + d : long_profit_level2  [1]
//long_even_level     := longCondition  ? close + 0 : long_even_level     [1]

short_stop_level    := shortCondition ? close + c : short_stop_level    [1]
short_profit_level1 := shortCondition ? close - d : short_profit_level1 [1]
//short_profit_level2 := shortCondition ? close - d : short_profit_level2 [1]
//short_even_level    := shortCondition ? close + 0 : short_even_level    [1] 


//ha
// === Input ===
//ma1_len = input(1, title="MA 01")
//ma2_len = input(40, title="MA 02")

// === MA 01 Filter ===
//o=ema(open,ma1_len)
//cc=ema(close,ma1_len)
//h=ema(high,ma1_len)
//l=ema(low,ma1_len)

// === HA calculator ===
//ha_t = heikinashi(syminfo.tickerid)
//ha_o = security(ha_t, timeframe.period, o)
//ha_c = security(ha_t, timeframe.period, cc)
//ha_h = security(ha_t, timeframe.period, h)
//ha_l = security(ha_t, timeframe.period, l)

// === MA 02 Filter ===
//o2=ema(ha_o, ma2_len)
//c2=ema(ha_c, ma2_len)
//h2=ema(ha_h, ma2_len)
//l2=ema(ha_l, ma2_len)

// === Color def ===
//ha_col=o2>c2 ? color.red : color.lime

// ===  PLOTITING===
//plotcandle(o2, h2, l2, c2, title="HA Smoothed", color=ha_col)

tp=input(120)
sl=input(96)
    
strategy.entry("long", strategy.long, when = longCondition)
//strategy.close("long", when = o2>c2 , comment="ha_long")
strategy.entry("short", strategy.short , when =shortCondition )
//strategy.close("short", when = o2<=c2 , comment = "ha_short" )

//strategy.close("long",when=long_profit_level1 or long_stop_level  , comment="tp/sl")
//strategy.close("short",when=short_profit_level1 or short_stop_level , comment="tp/sl")

strategy.exit("x_long","long",profit = tp, loss = sl) //when = o2>c2)
strategy.exit("x_short","short",profit = tp, loss = sl) //when = o2<c2)

Published by ChaoZhang on the FMZ strategy square · last modified 2023-11-27. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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