Bitlinc MARSI Trading Strategy

This strategy is an RSI oscillation tracking strategy based on annual adjustments. By tracking the oscillation characteristics of the RSI indicator between the set upper and lower bands, trading signals are issued…

Pine ScriptMean reversion Trend following RSI SMA

Author: ChaoZhang
Complexity: Intermediate · 68 lines
Parameters: 10
Backtest bar: 2h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Principle

Set parameters for MA length, RSI, upper/lower band, take profit/stop loss, trading cycle range.
Calculate RSI value, RSI = (Avg. Upward Change)/(Avg. Upward Change + Avg. Downward Change)*100
Plot RSI line and bands
RSI crossing below lower band is long signal, crossing above upper band is short signal
Open position with OCO orders
Execute stop loss and take profit based on settings

Advantage Analysis

Setting annual trading cycle avoids unsuitable external environments.
RSI reflects overbought/oversold efficiently. Reasonable range oscillation filters noise.
OCO orders + stop loss/profit settings enable efficient risk control.

Risk Analysis

Accuracy of RSI threshold judgement cannot be guaranteed, wrong judgements may happen.
Improper annual cycle settings may miss better opportunities or enter unsuitable environments.
Overlarge stop loss setting may lead to big losses, while too-small profit setting gives small profit.

Methods like adjusting RSI parameters, trading cycle range, stop loss/profit ratios can be used to optimize.

Optimization Directions

Test optimal RSI parameters for different markets and cycles
Analyze overall market cycle pattern, set best annual trading phase
Determine reasonable stop loss/profit ratios through backtest
Optimize trading products selection and position sizing
Combine with other better techniques for further optimization

Summary

This strategy tracks trend by RSI's annual cycle oscillation features, effectively controlling trading risks. Further performance improvement can be achieved by parameter tuning and logic optimization.

Parameters

Name	Default	What it controls
v_input_1	62	Length of MA
v_input_2	31	Length
v_input_3	89	Upper Band for RSI
v_input_4	10	Lower Band for RSI
v_input_5	1.25	Take Profit Percent
v_input_6	0.04	Stop Loss Percent
v_input_7	8	Month Start
v_input_8	12	Month End
v_input_9	true	Day Start
v_input_10	31	Day End

Source Pine Script

/*backtest
start: 2024-01-01 00:00:00
end: 2024-01-31 23:59:59
period: 2h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=3
strategy(title = "Bitlinc MARSI Study AST",shorttitle="Bitlinc MARSI Study AST",default_qty_type = strategy.percent_of_equity, default_qty_value = 100,commission_type=strategy.commission.percent,commission_value=0.1,initial_capital=1000,currency="USD",pyramiding=0, calc_on_order_fills=false)

// === General Inputs ===
lengthofma = input(62, minval=1, title="Length of MA")
len = input(31, minval=1, title="Length")
upperband = input(89, minval=1, title='Upper Band for RSI')
lowerband = input(10, minval=1, title="Lower Band for RSI")
takeprofit =input(1.25, title="Take Profit Percent")
stoploss =input(.04, title ="Stop Loss Percent")
monthfrom =input(8, title = "Month Start")
monthuntil =input(12, title = "Month End")
dayfrom=input(1, title= "Day Start")
dayuntil=input(31, title= "Day End")

// === Innput Backtest Range ===
//FromMonth = input(defval = 9, title = "From Month", minval = 1, maxval = 12)
//FromDay   = input(defval = 1, title = "From Day", minval = 1, maxval = 31)
//FromYear  = input(defval = 2018, title = "From Year", minval = 2017)
//ToMonth   = input(defval = 1, title = "To Month", minval = 1, maxval = 12)
//ToDay     = input(defval = 1, title = "To Day", minval = 1, maxval = 31)
//ToYear    = input(defval = 9999, title = "To Year", minval = 2017)

// === Create RSI ===
src=sma(close,lengthofma)
up = rma(max(change(src), 0), len)
down = rma(-min(change(src), 0), len)
rsi = down == 0 ? 100 : up == 0 ? 0 : 100 - (100 / (1 + up / down))
plot(rsi,linewidth = 2, color=purple)

// === Plot Bands ===
band1 = hline(upperband)
band0 = hline(lowerband)
fill(band1, band0, color=blue, transp=95)

// === Entry and Exit Methods ===
longCond =  crossover(rsi,lowerband)
shortCond =  crossunder(rsi,upperband)

// === Long Entry Logic ===
if (  longCond ) 
    strategy.entry("LONG", strategy.long, stop=close, oca_name="TREND", comment="LONG")
else
    strategy.cancel(id="LONG")

// === Short Entry Logic ===    
if ( shortCond   ) 
    strategy.entry("SHORT", strategy.short,stop=close, oca_name="TREND",  comment="SHORT")
else
    strategy.cancel(id="SHORT")

// === Take Profit and Stop Loss Logic ===
//strategy.exit("Take Profit LONG", "LONG", profit = close * takeprofit / syminfo.mintick, loss = close * stoploss / syminfo.mintick)
//strategy.exit("Take Profit SHORT", "SHORT", profit = close * takeprofit / syminfo.mintick, loss = close * stoploss / syminfo.mintick)
strategy.exit("LONG TAKE PROFIT", "LONG", profit = close * takeprofit / syminfo.mintick)
strategy.exit("SHORT STOP LOSS", "SHORT", profit = close * takeprofit / syminfo.mintick)
strategy.exit("LONG STOP LOSS", "LONG", loss = close * stoploss / syminfo.mintick)
strategy.exit("SHORT STOP LOSS", "SHORT", loss = close * stoploss / syminfo.mintick)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-02-29. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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