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Strategy vault / Momentum

Stochastic RSI Momentum Oscillation Trading Strategy

This article mainly explains a momentum oscillation trading strategy based on the Stochastic RSI indicator. The strategy adopts shorter cycle technical indicators (such as 30 minutes) to make trading decisions based…

Author
ChaoZhang
Complexity
Intermediate · 199 lines
Parameters
29
Backtest bar
1h · intraday
Tested on
BTC/USDT · futures

IMG

Overview

This article mainly explains a momentum oscillation trading strategy based on the Stochastic RSI indicator. The strategy adopts shorter cycle technical indicators (such as 30 minutes) to make trading decisions based on whether the Stochastic RSI enters the overbought/oversold region. Compared with other momentum strategies, this strategy combines the advantages of both RSI and Stochastic indicators to more accurately capture short-term market oscillations.

Strategy Principle

The core indicator of the strategy is Stochastic RSI. The calculation formula of Stochastic RSI is:

Stochastic RSI = (RSI - RSI Low) / (RSI High - RSI Low) * 100

Where RSI is calculated using the lengthRSI parameter (default 12), and Stochastic RSI is calculated using the lengthStoch parameter (default 12).

When Stochastic RSI is higher than the purple filled area, it is the overbought area, then go short; when Stochastic RSI is lower than the purple filled area, it is the oversold area, then go long.

In addition, the strategy also sets the moving average filter condition. Only when the fast EMA is higher than the slow EMA can you open a long position; only when the fast EMA is lower than the slow EMA can you open a short position. This avoids counter-trend trading.

Advantages of the Strategy

Compared with a single RSI strategy, this strategy combines the Stochastic indicator to more clearly identify overbought/oversold areas, thereby improving the reliability of signals.

Compared with a single Stochastic strategy, this strategy uses RSI as the input data source of Stochastic, which can filter out some noise and make the signal more reliable.

The moving average filter condition is set to effectively avoid counter-trend positions building, thereby reducing unnecessary losses.

The position holding time delay is set to avoid being stopped out by false breakouts.

Risks of the Strategy

The strategy mainly uses short-cycle indicators, so it is only suitable for short-term operations and may not perform well in the long run.

The Stochastic RSI indicator itself has a certain lag and may miss signals after drastic price changes in the short term.

In oscillating markets, Stochastic RSI may produce multiple penetrations of overbought/oversold areas, which may lead to overtrading and increased transaction costs.

Optimization Directions

  1. Different parameter combinations can be tested to further optimize the length, K and D values of Stochastic RSI.

  2. Different RSI length parameters can be tested to find a more appropriate RSI cycle.

  3. Try combining with other indicators to further improve signal accuracy, such as MACD, Bollinger Bands, etc.

  4. Test different position holding delay parameters to find a more appropriate exit timing.

Conclusion

This article details the construction principles, advantages, risks and optimization ideas of a momentum strategy based on the Stochastic RSI indicator. Compared with single indicator strategies, this strategy utilizes the strengths of both RSI and Stochastic to more clearly and reliably identify short-term overbought/oversold phenomena in the market for reversal trading. Further performance improvements can be expected through parameter optimization and indicator combinations.

Parameters

NameDefaultWhat it controls
v_input_1false------------------------Backtest Period------------------------
v_input_22020start year
v_input_3truestart month
v_input_4truestart day
v_input_5falseend year
v_input_6falseend month
v_input_7falseend day
v_input_8false------------------------Basic Parameters------------------------
v_input_93smoothK
v_input_106smoothD
v_input_1112lengthRSI
v_input_12_close0RSI Source: close | high | low | open | hl2 | hlc3 | hlcc4 | ohlc4
v_input_1312lengthStoch
v_input_1485.29Overbought Height
v_input_1530.6Oversold Height
v_input_166Bars delay
v_input_17trueGamble Sizing?
v_input_18deltaSizeGamble Add (%)
v_input_19sizeLimiteGamble MAX (%)
v_input_20trueFast EMA length
v_input_2160Slow EMA length
v_input_22true------------------------LONG------------------------
v_input_2310Stop Loss LONG %
v_input_248Take Profit LONG %
v_input_25trueTREND FILTER LONG?
v_input_26false------------------------SHORT------------------------
v_input_2720Stop Loss SHORT %
v_input_2835Take Profit SHORT %
v_input_29trueTREND FILTER SHORT?

Source Pine Script

/*backtest
start: 2023-11-25 00:00:00
end: 2023-12-25 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/
// © Drun30 (Federico Magnani)

//@version=4
//STRATEGIA PRINCIPALE
capitaleIniziale=10000

var sizeordineInit= 50 // → % di capitale investita per ogni trade
var deltaSize = 25 // → delta% di capitale investito se trade precedente è stato in perdita
var sizeLimite = 100 //il trade non userà mai questa percentuale di capitale investito
var sizeordine = sizeordineInit

//Parametri ottimali 30 min
usiShort=false
usiLong=true
ipercomprato=85.29
ipervenduto=30.6
//

strategy("Momentum Strategy (V7.B.4)", initial_capital=capitaleIniziale, currency="USD", default_qty_type=strategy.percent_of_equity, commission_type=strategy.commission.percent, commission_value=0.1, slippage = 5, default_qty_value=sizeordineInit, overlay=false, pyramiding=0)

backtest = input(title="------------------------Backtest Period------------------------", defval = false)
start = timestamp(input(2020, "start year"), input(1, "start month"), input(1, "start day"), 00, 00)
end = timestamp(input(0, "end year"), input(0, "end month"), input(0, "end day"), 00, 00) 

siamoindata=time > start?true:false
if end > 0
    siamoindata:=time > start and time <= end?true:false

basicParameters = input(title="------------------------Basic Parameters------------------------", defval = false)
smoothK = input(3, minval=1)
smoothD = input(6, minval=1)
lengthRSI = input(12, minval=1) 
src = input(close, title="RSI Source")
rsi1 = rsi(src, lengthRSI)
lengthStoch = input(12, minval=1)
k = ema(stoch(rsi1, rsi1, rsi1, lengthStoch), smoothK)
d = ema(k, smoothD)
altezzaipercomprato= input(ipercomprato, title="Overbought Height", minval=1, type=input.float)
altezzaipervenduto= input(ipervenduto, title="Oversold Height", minval=1,type=input.float) 

BarsDelay = input(6,title="Bars delay",minval=0) 

GambleSizing = input(true, title = "Gamble Sizing?",type=input.bool)
gambleAdd = input(deltaSize,title="Gamble Add (%)",minval=0,type=input.integer)
gambleLimit = input(sizeLimite,title="Gamble MAX (%)",minval=0,type=input.integer)
if GambleSizing and strategy.closedtrades[0]>strategy.closedtrades[1]
    if strategy.losstrades[0]>strategy.losstrades[1] and sizeordine<gambleLimit
        sizeordine:=sizeordine+gambleAdd
    if strategy.wintrades[0]>strategy.wintrades[1]
        sizeordine:=sizeordineInit

periodomediamobile_fast = input(1, title="Fast EMA length",minval=1)
periodomediamobile_slow = input(60, title="Slow EMA length",minval=1)

plot(k, color=color.blue)
plot(d, color=color.orange)
h0 = hline(altezzaipercomprato)
h1 = hline(altezzaipervenduto)
fill(h0, h1, color=color.purple, transp=80)
// n=input(Vicinanzadalcentro,title="Vicinanza dal centro",minval=0) 
//sarebbe il livello di D in cui si acquista o si vende, maggiore è la vicinanza maggiore sarà la frequenza dei trades, SE 0 è DISABILITATO

//     siamoinipervenduto= d<=altezzaipervenduto and d<=d[n] and d>d[1]?true:false //and d<d[3] and d>d[1]
//     siamoinipercomprato= d>=altezzaipercomprato and d>=d[n] and d<d[1]?true:false //and d>d[3] and d<d[1]
goldencross = crossover(k,d)
deathcross = crossunder(k,d)
// METTI VARIABILE IN CUI AVVIENE CROSSOVER O CROSSUNDER
valoreoro = valuewhen(goldencross,d,0)
valoremorte = valuewhen(deathcross,d,0)

siamoinipervenduto = goldencross and valoreoro<=altezzaipervenduto?true:false//d<=altezzaipervenduto?true:false
siamoinipercomprato = deathcross and valoremorte>=altezzaipercomprato?true:false//d>=altezzaipercomprato?true:false

long_separator = input(title="------------------------LONG------------------------", defval = usiLong)

sl_long_inp = input(10, title="Stop Loss LONG %", type=input.float) 
tp_long_inp = input(8, title="Take Profit LONG %",type=input.float)
stop_level_long = strategy.position_avg_price * (1 - (sl_long_inp/100)) //strategy.position_avg_price corrisponde al prezzo con cui si è aperta la posizione
take_level_long = strategy.position_avg_price * (1 + (tp_long_inp/100))

//BINANCE
JSON_long = 'OPEN LONG: PUT THE JSON HERE FOR THE API CALL'
JSON_chiusura = 'CLOSE POSITION: PUT THE JSON HERE FOR THE API CALL' 

webhookLong = JSON_long
webhookClose= JSON_chiusura

trendFilterL = input(title="TREND FILTER LONG?", defval = true)

EMAfast=ema(close,periodomediamobile_fast)
EMAslow=ema(close,periodomediamobile_slow)

siamoinuptrend_ema=EMAfast>EMAslow?true:false //close>=EMAfast and EMAfast>EMAslow
siamoinuptrend = siamoinuptrend_ema

// CondizioneAperturaLong = siamoinipervenduto and siamoindata // and siamoinuptrend
CondizioneAperturaLong = siamoinipervenduto and siamoindata and long_separator
if trendFilterL
    CondizioneAperturaLong := siamoinipervenduto and siamoindata and long_separator and siamoinuptrend

CondizioneChiusuraLong = siamoinipercomprato and siamoindata 

possiamoAprireLong=0
if trendFilterL and siamoinuptrend
    possiamoAprireLong:=5
plot(possiamoAprireLong,color=color.green)

sonPassateLeBarreG = barssince(CondizioneAperturaLong) == BarsDelay?true:false
sonPassateLeBarreD = barssince(CondizioneChiusuraLong) == BarsDelay?true:false

haiUnLongAncoraAperto = false
haiUnLongAncoraAperto := strategy.position_size>0?true:false

// Se l'ultimo valore della serie "CondizioneAperturaLong" è TRUE, allora hai un long ancora aperto
// Se l'ultimo valore della serie "CondizioneAperturaLong" è FALSE, allora:
//       Se l'ultimo valore della serie "CondizioneChiusuraLong" è TRUE, allora NON hai un long ancora aperto 
//       Se l'ultimo valore della serie "CondizioneChiusuraLong" è FALSE, allora restituisce l'ultimo valore della serie "haiUnLongAncoraAperto"

haiUnLongAncoraAperto_float = if(haiUnLongAncoraAperto==true)
    10
else
    0

plot(haiUnLongAncoraAperto_float,color=color.red) //FInché la linea rossa si trova a livello "1" allora c'è un ordine long in corso

quantita = (sizeordine/100*(capitaleIniziale+strategy.netprofit))/valuewhen(haiUnLongAncoraAperto==false and CondizioneAperturaLong,close,0)

plot(sizeordine,color=color.purple, linewidth=3)

if  strategy.position_size<=0 and CondizioneAperturaLong //and sonPassateLeBarreG and haiUnLongAncoraAperto==false strategy.opentrades==0
    strategy.entry("Vamonos",strategy.long, alert_message=webhookLong, comment="OPEN LONG", qty=quantita)

if  strategy.position_size>0 //and sonPassateLeBarreD // and CondizioneChiusuraLong 
    if siamoinuptrend == true and sonPassateLeBarreD
        strategy.close("Vamonos", alert_message=webhookClose, comment="CLOSE LONG")
    else if siamoinuptrend == false and CondizioneChiusuraLong
        strategy.close("Vamonos", alert_message=webhookClose, comment="CLOSE LONG")

    
if strategy.position_size>0 and siamoindata
    strategy.exit("Vamonos", stop=stop_level_long, limit=take_level_long, comment="CLOSE LONG (LIMIT/STOP)")


short_separator = input(title="------------------------SHORT------------------------", defval = usiShort)    

sl_short_inp = input(20, title="Stop Loss SHORT %")
tp_short_inp = input(35, title="Take Profit SHORT %")
stop_level_short = strategy.position_avg_price * (1 + (sl_short_inp/100))
take_level_short= strategy.position_avg_price * (1 - (tp_short_inp/100))

// BINANCE 
JSON_short = 'OPEN SHORT: PUT THE JSON HERE FOR THE API CALL'

webhookShort = JSON_short

trendFilterS = input(title="TREND FILTER SHORT?", defval = true)

siamoindowntrend_ema=EMAfast<EMAslow?true:false //close<=EMAfast and EMAfast<EMAslow
siamoindowntrend=siamoindowntrend_ema

CondizioneAperturaShort = short_separator and siamoinipercomprato and siamoindata 
if trendFilterS
    CondizioneAperturaShort:=short_separator and siamoinipercomprato and siamoindata and siamoindowntrend

CondizioneChiusuraShort = siamoinipervenduto and siamoindata

sonPassateLeBarreGs = barssince(CondizioneAperturaShort) == BarsDelay?true:false
sonPassateLeBarreDs = barssince(CondizioneChiusuraShort) == BarsDelay?true:false

haiUnoShortAncoraAperto = false
haiUnoShortAncoraAperto := strategy.position_size<0?true:false

haiUnoShortAncoraAperto_float = if(haiUnoShortAncoraAperto==true)
    15
else
    0

plot(haiUnoShortAncoraAperto_float,color=color.purple) //FInché la linea viola si trova a livello "2" allora c'è un ordine short in corso

if CondizioneAperturaShort and strategy.position_size>=0 //and haiUnoShortAncoraAperto==false
    strategy.entry("Andale",strategy.short,alert_message=webhookShort, comment="OPEN SHORT")

if  strategy.position_size<0 //and sonPassateLeBarreD // and CondizioneChiusuraLong 
    if siamoindowntrend == true and sonPassateLeBarreDs
        strategy.close("Andale",alert_message=webhookClose, comment="CLOSE SHORT")
    else if siamoindowntrend == false and CondizioneChiusuraShort
        strategy.close("Andale",alert_message=webhookClose, comment="CLOSE SHORT")

if strategy.position_size<0 and siamoindata
    strategy.exit("Andale", stop=stop_level_short, limit=take_level_short, comment="CLOSE SHORT (LIMIT/STOP)")

Published by ChaoZhang on the FMZ strategy square · last modified 2023-12-26. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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