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Strategy vault / Machine learning

Multi indicator Assisted Strategy

This strategy combines EMA, RSI, MACD, PSAR, Bollinger Bands and other technical indicators for overall trend judgment from multiple angles, finding optimal entry opportunities. It provides multiple parameter setting…

Author
ChaoZhang
Complexity
Intermediate · 193 lines
Parameters
16
Backtest bar
1d · swing
Tested on
BTC/USDT · futures

Overview

This strategy combines EMA, RSI, MACD, PSAR, Bollinger Bands and other technical indicators for overall trend judgment from multiple angles, finding optimal entry opportunities. It provides multiple parameter setting options for adjustable personalized strategies.

Strategy Logic

  1. Use 3 EMAs (5-, 9-, 21-period) to determine price trend. EMA crossovers signal trend changes.

  2. RSI judges overbought/oversold levels. RSI below lower level signifies oversold; above upper level overbought.

  3. MACD checks moving average difference. DIFF crossing above DEA is bullish signal and below is bearish.

  4. PSAR indicates current trend direction for additional context.

  5. Bollinger Bands show support/resistance levels. Price breaking bands suggests trend change.

  6. Take long/short positions when indicators give aligned signals based on user selection.

Advantages

  1. Multiple indicators avoid misleading signals from single indicator.

  2. Customizable parameters allow users to select optimal combinations.

  3. Accurate trend change detection from EMA, MACD etc.

  4. RSI efficiently identifies oversold/overbought opportunities.

  5. SAR and Bollinger Bands reveal turning points.

Risks

  1. Fewer multi-indicator signal occurrences may miss good opportunities.

  2. No filtering when single indicator gives false signal.

  3. Users may choose suboptimal parameter sets leading to over/undertrading.

  4. No risk management limits like STOP LOSS.

  5. Insufficient backtest data to fully validate strategy.

Possible solutions:

  1. Widen indicator thresholds to provide more signals.

  2. Add other indicators to filter out false signals.

  3. Provide more indicator options for users to test combinations.

  4. Incorporate stop loss and other risk management.

  5. Backtest on more markets to optimize parameters.

Optimization Directions

  1. Test more indicator combinations to find best matches.

  2. Add machine learning modules for more data-driven improvements.

  3. Incorporate trend filtering to determine trade direction.

  4. Optimize money management for more market environments.

  5. Develop auto parameter optimization for intelligent improvements.

Summary

This strategy applies multiple technical indicators for comprehensive trend analysis, avoiding overreliance on single indicators. It can be further enhanced via parameter tuning, adding validation modules, integrating AI etc, to provide more quality signals while maintaining robustness.

Parameters

NameDefaultWhat it controls
v_input_10Strategy: rsi | ema | macd | psr | off | BB | ema5
v_input_20background color: rsi | ema | macd | psr | off | exchange | BB | ema5
v_input_3falseShow ema5?
v_input_4trueShow ema9?
v_input_5trueShow ema21?
v_input_6falseShow ema50?
v_input_7falseShow ema100?
v_input_8trueShow ema200
v_input_9trueColor oversold and overbought bars?
v_input_10trueShow Parabolic Sar
v_input_11trueShow Bollinger Bands?
v_input_12falseShow Daily Pivots?
v_input_13truelinewidth
v_input_14truesar points width
v_input_1540oversold rsi
v_input_1665overbought rsi

Source Pine Script

/*backtest
start: 2022-09-17 00:00:00
end: 2023-09-23 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=3
strategy("f.society", title="f.society", overlay=true)
//@Author: rick#1414
// -----------------------------------------------------
// f.society : Pone 3EMA: 5, 9, 21, 50, 100, 200, SAR, 
// velas azules en sobreventa y velas moradas sobre compra 
// SAR 0.02, 0.02, 0.2 , Bandas de Bollinger
// estrategia de compra y venta con rsi, macd o psr
// color de fondo: ema, rsi (color azul sobreventa 35, 25 (mas intenso))
// -----------------------------------------------------
// Como agregar a Trading view:
// 1 Cerrar todos los otros indicadores antes de añadirlo
// 2. Ir a la página de inicio TradingView.com
// 3. En la parte inferior, haga clic en Editor Pine // ver imagen: // https://cdn.discordapp.com/attachments/407267549047422976/407393815112974336/unknown.png
// 4. borrar todo el texo y reemplazar con todo el contenido de este archivo
// 5. Pulse el botón "Añadir a trazar" (Add to graph)
// -----------------------------------------------------
// revisar opciones de on y off segun indicadores deseados
// https://cdn.discordapp.com/attachments/405885820114042883/412115277883506700/unknown.png
// se puede cambiar la estrategia desde este menu desplegable para señales buy/sell

// Options
estrategia = input(defval="rsi", title = "Strategy", options=["ema","rsi","macd","psr","off","BB","ema5"])
in_bkcolor = input(defval="rsi", title = "background color", options=["ema","rsi","macd","psr","off","exchange","BB","ema5"])
e5 = input(title="Show ema5?", type=bool, defval=false)
e9 = input(title="Show ema9?", type=bool, defval=true)
e21 = input(title="Show ema21?", type=bool, defval=true)
e50 = input(title="Show ema50?", type=bool, defval=false)
e100 = input(title="Show ema100?", type=bool, defval=false)
e200 = input(title="Show ema200", type=bool, defval=true)
in_rsi = input(title="Color oversold and overbought bars?", type=bool, defval=true)
in_sar = input(title="Show Parabolic Sar", type=bool, defval=true)
in_bb = input(title="Show Bollinger Bands?", type=bool, defval=true)
sd = input(false, title="Show Daily Pivots?")
linew = input(1, title="linewidth", minval=0)
sarw = input(1, title="sar points width", minval=0)
ovs = input(40, title="oversold rsi", minval=0)
ovb = input(65, title="overbought rsi", minval=0)



//pf = input(false,title="Show Filtered Pivots")
pf=false

// 3 ema
src = close // input(close, title="Source")
//len9 = input(9, minval=1, title="ema9 Length")
//len21 = input(21, minval=1, title="ema21 Length")
//len200 = input(200, minval=1, title="ema200 Length")
len5=5
len9=9
len21=21
len50=50
len100=100
len200=200
ema5 = ema(src, len5)
ema9 = ema(src, len9)
ema21 = ema(src, len21)
ema50= ema(src, len50)
ema100 = ema(src, len100)
ema200 = ema(src, len200)
plot(e5? ema5 : na, title="EMA5", linewidth=linew, color=purple)
plot(e9? ema9 : na, title="EMA9", linewidth=linew, color=blue)
plot(e21? ema21 : na, title="EMA21", linewidth=linew, color=red)
plot(e50? ema50 : na, title="EMA50", linewidth=linew, color=green)
plot(e100? ema100 : na, title="EMA100", linewidth=linew, color=lime)
plot(e200? ema200 : na, title="EMA200", linewidth=linew, color=yellow)

// RSI Color
//lenR = input(14, minval=1, title="RSI Length")
lenR=14
//up = rma(max(change(src), 0), lenR)
//down = rma(-min(change(src), 0), lenR)
//vrsi = down == 0 ? 100 : up == 0 ? 0 : 100 - (100 / (1 + up / down))
vrsi=rsi(close,lenR)
//plot(vrsi,title="vrsi")
oversold = vrsi < ovs
overbought = vrsi > ovb
barcolor(in_rsi? oversold? #0000FF : overbought? #ff00ff:na : na)

// SAR
plot(in_sar? sar(0.02, 0.02, 0.2): na, style=cross, linewidth=sarw, color=blue, title="sar")

// BB
//length = input(20, title="Bollinger length", minval=1)
length=20
//mult = input(2.0, title="Bollinger stdDev", minval=0.001, maxval=50)
mult=2.0
basis = sma(src, length)
dev = mult * stdev(src, length)
upper = basis + dev
lower = basis - dev
plot(in_bb? basis :na, color=red, linewidth=linew, title="BB basis")
p1 = plot(in_bb? upper :na, color=blue, linewidth=linew, title="BB upper")
p2 = plot(in_bb? lower :na, color=blue, linewidth=linew, title="BB lower")
fill(p1, p2)

//background
bgcolor(in_bkcolor=="exchange"? #0000FF40 : in_bkcolor=="rsi"? vrsi < (ovs-15) ? #0000FF50  : vrsi < ovs ? #0000FF30 :( vrsi < ovb ? #ff00ff10 : #ff00ff20): in_bkcolor=="ema"?(ema9>ema21?#ff00ff10  : #0000FF20):in_bkcolor=="BB"?(lower>close?#ff00ff10 : close>upper?#0000FF20:#ff00ff10): in_bkcolor=="ema5"?(ema5>ema21?#ff00ff10  : #0000FF20):na)


// Strategy
if estrategia == "ema"
    strategy.entry("buy", true, 1, when= crossover(ema9,ema21) ),
    strategy.entry("sell", false, 1, when = crossover(ema21,ema9)) 
else
    if estrategia =="rsi"
        strategy.entry("buy", true, 1, when= vrsi <ovs),
        strategy.entry("sell", false, 1, when = vrsi > ovb or crossover(close,upper)) 
    else 
        if estrategia =="macd"    
            [macdLine, signalLine, histLine] = macd(close, 12, 26, 9),
            //bgcolor(macdLine > signalLine ? #98c8ff : #ff8b94),
            strategy.entry("buy", true, 1, when= macdLine>=signalLine ),
            strategy.entry("sell", false, 1, when = macdLine<signalLine) 
        else 
            if estrategia=="psr"
                leftBars = 4 //input(4)
                rightBars = 2 //input(2)
                swh = pivothigh(leftBars, rightBars)
                swl = pivotlow(leftBars, rightBars)
                swh_cond = not na(swh)
                hprice = 0.0
                hprice := swh_cond ? swh : hprice[1]
                le = false
                le := swh_cond ? true : (le[1] and high > hprice ? false : le[1])
                if (le)
                    strategy.entry("buy", strategy.long, comment="buy", stop=hprice + syminfo.mintick)
                swl_cond = not na(swl)
                lprice = 0.0
                lprice := swl_cond ? swl : lprice[1]
                se = false
                se := swl_cond ? true : (se[1] and low < lprice ? false : se[1])
                if (se)
                    strategy.entry("sell", strategy.short, comment="sell", stop=lprice - syminfo.mintick)
            else
                if estrategia=="BB"
                    strategy.entry("buy", true, 1, when= crossover(lower,close) ),
                    strategy.entry("sell", false, 1, when = crossover(close,upper)) 
                else
                    if estrategia=="ema5"
                        strategy.entry("buy", true, 1, when= crossover(ema5,ema21) ),
                        strategy.entry("sell", false, 1, when = crossover(ema21,ema5)) 



// pivots

// Classic Pivot
pivot = (high + low + close ) / 3.0
// Filter Cr
bull= pivot > (pivot + pivot[1]) / 2 + .0025
bear= pivot < (pivot + pivot[1]) / 2 - .0025
// Classic Pivots
r1 = pf and bear ? pivot + (pivot - low) : pf and bull ? pivot + (high - low) : pivot + (pivot - low)
s1 = pf and bull ? pivot - (high - pivot) : pf and bear ? pivot - (high - low) : pivot - (high - pivot)
r2 = pf ? na : pivot + (high - low)
s2 = pf ? na : pivot - (high - low)
//Pivot Average Calculation
smaP = sma(pivot, 3)
//Daily Pivots 
dtime_pivot = security(syminfo.tickerid, 'D', pivot[1])
dtime_pivotAvg = security(syminfo.tickerid, 'D', smaP[1])
dtime_r1 = security(syminfo.tickerid, 'D', r1[1]) 
dtime_s1 = security(syminfo.tickerid, 'D', s1[1]) 
dtime_r2 = security(syminfo.tickerid, 'D', r2[1]) 
dtime_s2 = security(syminfo.tickerid, 'D', s2[1])
offs_daily = 0
plot(sd and dtime_pivot ? dtime_pivot : na, title="Daily Pivot",style=line, color=fuchsia,linewidth=linew) 
plot(sd and dtime_r1 ? dtime_r1 : na, title="Daily R1",style=line, color=#DC143C,linewidth=linew) 
plot(sd and dtime_s1 ? dtime_s1 : na, title="Daily S1",style=line, color=lime,linewidth=linew) 
plot(sd and dtime_r2 ? dtime_r2 : na, title="Daily R2",style=line, color=maroon,linewidth=linew) 
plot(sd and dtime_s2 ? dtime_s2 : na, title="Daily S2",style=line, color=#228B22,linewidth=linew) 


// References:
// get number of bars since last green bar
//plot(barssince(close >= open), linewidth=3, color=blue)
//bgcolor(close < open ? #ff8b94   : #98c8ff , transp=10)
//http://www.color-hex.com/
//   #98c8ff    light blue
//    #ff8b94   red   #b21c0e
//       #7d1d90    purple
//    #0029ff blue
//    #fffa86   yellow

Published by ChaoZhang on the FMZ strategy square · last modified 2023-09-24. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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