Quant Bitcoin Trading Strategy Combining MACD RSI and FIB

The strategy is named "Golden Cross Fibonacci Strategy". It combines the technical indicator MACD, relative strength index RSI and fibonacci retracement/extension theory based on golden ratio, realizing quantitative…

Pine ScriptMean reversion Trend following RSI MACD EMA SMA Fibonacci Pivots / S&R

Author: ChaoZhang
Complexity: Intermediate · 92 lines
Parameters: 7
Backtest bar: 10m · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Principle

MACD Indicator for Trading Signals

Set EMA periods of MACD fast line and slow line to 15 and 30
Crossing up as buying signal and crossing down as selling one

RSI Filtering False Signals

Set RSI parameter to 50 period
RSI helps filter some false signals MACD gives

Fibonacci Theory for SUPPORT/RESISTANCE

Combine recent highest/lowest price over 38 candles
Calculate 0.5 fibonacci retracement/extension level
Can be used as support and resistance

MA and RSI Judging Oversold/Overbought

50-period MA judges oversold/overbought status
RSI also helps judging

Reverse Opening Mechanism

Provide option for users to open reverse order
Flexibly adjust long/short logic according to users' choice

Advantage Analysis

The biggest advantage is operating 24x7 without manual intervention. Besides, the combination of multiple indicators increases the winning rate, especially outstanding performance in bull market. Main advantages include:

Fully automated 24x7 quant trading without manual intervention
Accurate trading signals from MACD
RSI filters some false signals
Fibonacci theory adds more reference
Judging oversold/overbought status
Flexibly adjust strategies through reverse opening

Risk Analysis

There also exist some risks, mainly from huge reverse of price that is hard for stop loss to take effect. Also, overlong holding period induces risk. Main risks contain:

Stop loss too tight to protect from huge reverse
Systematic risk from overlong holding period

Solutions accordingly are:

Set looser stop loss distance
Optimize holding period against overlong risk

Optimization Directions

Main aspects for optimization:

Optimize MACD parameters for higher accuracy
Optimize RSI parameter for better utility
Test more periods of Fibonacci theory
Add more filter indicators to further decrease false signals
Combine indicators of larger periods for market trend

Summary

The strategy combines multiple quant indicators for trade signals and realizes full automatic crypto trading. Further improving profit by optimizing parameters and adding more assistant indicators. It significantly reduces manual operation costs for users. Worth deep research and application for quant traders.

Parameters

Name	Default	What it controls
v_input_1	BINANCE:BTCUSDT	Symbol
v_input_2	2.5	Long Stop Loss (%)
v_input_3	2.5	Short Stop Loss (%)
v_input_4	7.6	Long Take Profit (%)
v_input_5	7.5	Short Take Profit (%)
v_input_6	90	Capital Percentage to Invest (%)
v_input_7	false	Reverse ?

Source Pine Script

/*backtest
start: 2023-12-18 00:00:00
end: 2023-12-25 00:00:00
period: 10m
basePeriod: 1m
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/
// © onurenginogutcu

//@version=4
strategy("STRATEGY R18-F-BTC", overlay=true, margin_long=100, margin_short=100)

///////////default girişler 1 saatlik btc grafiği için geçerli olmak üzere - stop loss'lar %2.5 - long'da %7.6 , short'ta %8.1

sym = input(title="Symbol", type=input.symbol, defval="BINANCE:BTCUSDT") /////////btc'yi indikatör olarak alıyoruz

lsl = input(title="Long Stop Loss (%)",
     minval=0.0, step=0.1, defval=2.5) * 0.01
     
ssl = input(title="Short Stop Loss (%)",
     minval=0.0, step=0.1, defval=2.5) * 0.01
     
longtp = input(title="Long Take Profit (%)",
     minval=0.0, step=0.1, defval=7.6) * 0.01
     
shorttp = input(title="Short Take Profit (%)",
     minval=0.0, step=0.1, defval=7.5) * 0.01
     
capperc = input(title="Capital Percentage to Invest (%)",
     minval=0.0, maxval=100, step=0.1, defval=90) * 0.01
     
choice = input(title="Reverse ?", type=input.bool, defval=false)

symClose = security(sym, "", close)
symHigh = security(sym, "", high)
symLow = security(sym, "", low)

i = ema (symClose , 15) - ema (symClose , 30) ///////// ema close 15 ve 30 inanılmaz iyi sonuç verdi (macd standartı 12 26)
r = ema (i , 9)

sapust = highest (i , 100) * 0.729 //////////0.729 altın oran oldu 09.01.2022
sapalt = lowest (i , 100) * 0.729  //////////0.729 altın oran oldu 09.01.2022

///////////highx = highest (close , 365) * 0.72 fibo belki dahiledilebilir
///////////lowx = lowest (close , 365) * 1.272 fibo belki dahil edilebilir
simRSI = rsi (symClose , 50 ) /////// RSI DAHİL EDİLDİ "50 MUMLUK RSI EN İYİ SONUCU VERİYOR"


//////////////fibonacci seviyesi eklenmesi amacı ile koyuldu fakat en iyi sonuç %50 seviyesinin altı ve üstü (low ve high 38 barlık) en iyi sonuç verdi
fibvar = 38
fibtop = lowest (symLow , fibvar) + ((highest (symHigh , fibvar) - lowest (symLow , fibvar)) * 0.50)
fibbottom = lowest (symLow , fibvar) + ((highest (symHigh , fibvar) - lowest (symLow , fibvar)) * 0.50)

///////////////////////////////////////////////////////////// INDICATOR CONDITIONS

longCondition = crossover(i, r) and i < sapalt and symClose < sma (symClose , 50) and simRSI < sma (simRSI , 50) and symClose < fibbottom
shortCondition = crossunder(i, r) and i > sapust and symClose > sma (symClose , 50) and simRSI > sma (simRSI , 50)  and symClose > fibtop

////////////////////////////////////////////////////////////////

///////////////////////////////////////////STRATEGY ENTRIES AND STOP LOSSES /////stratejilerde kalan capital için strategy.equity kullan (bunun üzerinden işlem yap)


if (choice == false and longCondition)
    strategy.entry("Long", strategy.long , qty = capperc * strategy.equity / close ,   when = strategy.position_size == 0)
   

if (choice == false and shortCondition)
    strategy.entry("Short" , strategy.short , qty = capperc * strategy.equity / close ,  when = strategy.position_size == 0)

if (choice == true and longCondition)
    strategy.entry("Short" , strategy.short , qty = capperc * strategy.equity / close ,  when = strategy.position_size == 0)

if (choice == true and shortCondition)
    strategy.entry("Long", strategy.long , qty = capperc * strategy.equity / close ,   when = strategy.position_size == 0)
    

if (strategy.position_size > 0)
    strategy.exit("Exit Long", "Long", stop=strategy.position_avg_price*(1 - lsl) , limit=strategy.position_avg_price*(1 + longtp))

if (strategy.position_size < 0)
    strategy.exit("Exit Short", "Short", stop=strategy.position_avg_price*(1 + ssl) , limit=strategy.position_avg_price*(1 - shorttp))


////////////////////////vertical colouring signals
bgcolor(color=longCondition ? color.new (color.green , 70) : na)
bgcolor(color=shortCondition ? color.new (color.red , 70) : na)

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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