Quantitative Support and Resistance Oscillation Strategy

This strategy combines RSI crossover strategy with optimized stop loss strategy to achieve precise logic control and accurate stop loss and take profit. Meanwhile, by introducing signal optimization, it can better…

Pine ScriptMean reversion Trend following RSI SMA Stochastic Heikin Ashi Pivots / S&R

Author: ChaoZhang
Complexity: Intermediate · 93 lines
Parameters: 13
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Principle

RSI indicator determines overbought and oversold area. Combined with K and D value golden cross and dead cross to form trading signals.
Introduces candlestick pattern recognition to assist in judging trend signals to avoid wrong trades.
SMA lines assist in determining trend direction. Uptrend when short period SMA breaks out upper long period SMA.

Advantage Analysis

RSI parameter optimization determines overbought and oversold area precisely to avoid wrong trades.
STO parameter optimization, smoothness adjustment filters out noise and improves signal quality.
Heikin-Ashi technology introduced to recognize candlestick direction change and ensure accurate trading signals.
SMA lines assist judging major trend direction, avoids trading against the trend.
Stop loss strategy locks in maximum profit for each trade.

Risk Analysis

Facing greater risk when market continues going down.
High trading frequency increases trading cost and slippage cost.
RSI tends to generate false signals, needs filtering by other indicators.

Strategy Optimization

Adjust RSI parameters, optimize overbought oversold judgement.
Adjust STO parameters, smoothness and period to improve signal quality.
Adjust moving average period to optimize trend judgement.
Introduce more technical indicators to improve signal accuracy.
Optimize stop loss ratio to reduce single trade risk.

Conclusion

The strategy integrates advantages of multiple mainstream technical indicators. Through parameter optimization and logic refinement, it balances trading signal quality and stop loss. With certain versatility and steady profitability. Further optimization can improve win rate and profitability.

Parameters

Name	Default	What it controls
v_input_1	3	smoothK
v_input_2	3	smoothD
v_input_3	14	lengthRSI
v_input_4	14	lengthStoch
v_input_5	80	overbought
v_input_6	20	oversold
v_input_7	100	smaLengh
v_input_8	50	smaLengh2
v_input_9	20	smaLengh3
v_input_10_close	0	RSI Source: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_11	2017	Backtest Start Year
v_input_12	true	Backtest Start Month
v_input_13	true	Backtest Start Day

Source Pine Script

/*backtest
start: 2023-12-01 00:00:00
end: 2023-12-31 23:59:59
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4
//study(title="@sentenzal strategy", shorttitle="@sentenzal strategy", overlay=true)
strategy(title="@sentenzal strategy", shorttitle="@sentenzal strategy", overlay=true  )
smoothK = input(3, minval=1)
smoothD = input(3, minval=1)
lengthRSI = input(14, minval=1)
lengthStoch = input(14, minval=1)
overbought = input(80, minval=1)
oversold = input(20, minval=1)
smaLengh = input(100, minval=1)
smaLengh2 = input(50, minval=1)
smaLengh3 = input(20, minval=1)

src = input(close, title="RSI Source")
testStartYear = input(2017, "Backtest Start Year")
testStartMonth = input(1, "Backtest Start Month")
testStartDay = input(1, "Backtest Start Day")
testPeriodStart = timestamp(testStartYear,testStartMonth,testStartDay,0,0)
testPeriod() =>
    time >= testPeriodStart ? true : false

rsi1 = rsi(src, lengthRSI)
k = sma(stoch(rsi1, rsi1, rsi1, lengthStoch), smoothK)
d = sma(k, smoothD)
crossBuy = crossover(k, d) and k < oversold
crossSell = crossunder(k, d) and k > overbought

dcLower = lowest(low, 10)
dcUpper = highest(high, 10)


heikinashi_close = security(heikinashi(syminfo.tickerid), timeframe.period, close)
heikinashi_open = security(heikinashi(syminfo.tickerid), timeframe.period, open)
heikinashi_low = security(heikinashi(syminfo.tickerid), timeframe.period, low)
heikinashi_high = security(heikinashi(syminfo.tickerid), timeframe.period, high)
heikinashiPositive = heikinashi_close >= heikinashi_open

heikinashiBuy = heikinashiPositive == true and heikinashiPositive[1] == false  and heikinashiPositive[2] == false
heikinashiSell = heikinashiPositive == false and heikinashiPositive[1] == true and heikinashiPositive[2] == true

//plotshape(heikinashiBuy, style=shape.arrowup, color=green, location=location.belowbar, size=size.tiny)
//plotshape(heikinashiSell, style=shape.arrowdown, color=red, location=location.abovebar, size=size.tiny)

buy = (crossBuy == true or crossBuy[1] == true or crossBuy[2] == true) and (heikinashiBuy == true or heikinashiBuy[1] == true or heikinashiBuy[2] == true)
sell = (crossSell == true or crossSell[1] == true or crossSell[2] == true) and (heikinashiSell == true or heikinashiSell[1] == true or heikinashiSell[2] == true)

mult = timeframe.period == '15' ? 4 : 1
mult2 = timeframe.period == '240' ? 0.25 : mult

movingAverage = sma(close, round(smaLengh))
movingAverage2 = sma(close, round(smaLengh2))
movingAverage3 = sma(close, round(smaLengh3))

uptrend = movingAverage < movingAverage2 and movingAverage2 < movingAverage3 and close > movingAverage
downtrend = movingAverage > movingAverage2 and movingAverage2 > movingAverage3 and close < movingAverage

signalBuy = (buy[1] == false and buy[2] == false and buy == true) and uptrend
signalSell = (sell[1] == false and sell[2] == false and sell == true) and downtrend

takeProfitSell = (buy[1] == false and buy[2] == false and buy == true) and uptrend == false
takeProfitBuy = (sell[1] == false and sell[2] == false and sell == true)  and uptrend

plotshape(signalBuy, style=shape.triangleup, color=green, location=location.belowbar, size=size.tiny)
plotshape(signalSell, style=shape.triangledown, color=red, location=location.abovebar, size=size.tiny)



plot(movingAverage, linewidth=3, color=orange, transp=0)
plot(movingAverage2, linewidth=2, color=purple, transp=0)
plot(movingAverage3, linewidth=1, color=navy, transp=0)

alertcondition(signalBuy, title='Signal Buy', message='Signal Buy')
alertcondition(signalSell, title='Signal Sell', message='Signal Sell')


strategy.close("L", when=dcLower[1] > low)
strategy.close("S", when=dcUpper[1] < high)

strategy.entry("L", strategy.long, 1, when = signalBuy and testPeriod() and uptrend) 
strategy.entry("S", strategy.short, 1, when = signalSell and testPeriod() and uptrend ==false) 

//strategy.exit("Exit Long", from_entry = "L", loss = 25000000, profit=25000000)
//strategy.exit("Exit Short", from_entry = "S", loss = 25000000, profit=25000000)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-01-25. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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