Quantitative Dual indicator Strategy

This strategy is a combination strategy based on dual EMA indicator and Bull Power indicator. The strategy name contains keywords like "quantitative" and "dual-indicator", highlighting its characteristic of using two…

Pine ScriptTrend following Volatility EMA SMA

Author: ChaoZhang
Complexity: Starter · 79 lines
Parameters: 6
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Logic

The strategy consists of two parts:

2/20 EMA indicator. This indicator calculates the 2-day and 20-day EMA. It generates buy signals when price crosses above EMA and sell signals when price crosses below EMA.
Bull Power indicator. This indicator calculates bullish/bearish power based on the current bar's relationship with previous bar. It generates trading signals when bull/bear power exceeds the threshold.

The two parts' signals need to trigger at the same time to open positions. For example, EMA golden cross and Bull Power being positive open long positions, while EMA dead cross and Bull Power being negative open short positions.

Advantage Analysis

Combine indicators to filter fake signals. Single indicator is prone to be influenced by external factors generating fake signals. Dual-indicator combination can verify each other and filter out fake signals, improving signal quality.
Customizable parameters. The periods of EMA and threshold of Bull Power are customizable to adapt to different market environments.
Simple and clear logic. The strategy only uses two common indicators with simple and clear logic, easy to understand and implement.

Risk Analysis

Indicator failure risk. Despite using combinational indicators, extreme market conditions may still cause indicator failure.
Parameter optimization risk. Inappropriate parameter settings may lead to insufficient or excessive trading, undermining strategy performance. Requires sufficient testing to find optimal parameters.

Optimization Directions

Add stop loss mechanisms. Set moving or lookback stop loss to control single trade loss.
Optimize parameter settings. Test different parameter combinations to find the optimal parameters for better performance.
Add filtering conditions. Adding conditions like trading volumes or volatility to filter abnormal market conditions when opening positions.

Conclusion

The strategy realizes trading decisions by combining dual EMA and Bull Power indicators. Compared to single indicator strategies, the combination eliminates fake signals effectively while retaining customizable parameters. In conclusion, this strategy features simplicity, flexibility and strong practicality as a quantitative trading strategy.

Parameters

Name	Default	What it controls
v_input_int_1	14	(?●═════ 2/20 EMA ═════●)Length
v_input_float_1	-15	(?●═════ Bull Power ═════●)SellLevel
v_input_bool_1	false	(?●═════ MISC ═════●)Trade reverse
v_input_int_2	true	(?●═════ Time Start ═════●)From Day
v_input_int_3	true	From Month
v_input_int_4	2005	From Year

Source Pine Script

/*backtest
start: 2022-12-22 00:00:00
end: 2023-12-28 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5
////////////////////////////////////////////////////////////
//  Copyright by HPotter v1.0 12/07/2022
// This is combo strategies for get a cumulative signal.  
//
// First strategy
// This indicator plots 2/20 exponential moving average. For the Mov 
// Avg X 2/20 Indicator, the EMA bar will be painted when the Alert criteria is met.
//
// Second strategy
//  Bull Power Indicator
//  To get more information please see "Bull And Bear Balance Indicator" 
//  by Vadim Gimelfarb. 
//
// WARNING:
// - For purpose educate only
// - This script to change bars colors.
////////////////////////////////////////////////////////////
EMA20(Length) =>
    pos = 0.0
    xPrice = close
    xXA = ta.ema(xPrice, Length)
    nHH = math.max(high, high[1])
    nLL = math.min(low, low[1])
    nXS = nLL > xXA or nHH < xXA ? nLL : nHH
    iff_1 = nXS < close[1] ? 1 : nz(pos[1], 0)
    pos := nXS > close[1] ? -1 : iff_1
    pos


BP(SellLevel) =>
    pos = 0.0
    value = close < open ?  
             close[1] < open ?  math.max(high - close[1], close - low): math.max(high - open, close - low):
              close > open ? 
               close[1] > open ?  high - low : math.max(open - close[1], high - low) : 
                 high - close > close - low ? 
                  close[1] < open ? math.max(high - close[1], close - low) : high - open : 
                   high - close < close - low ? 
                     close[1] > open ?  high - low : math.max(open - close, high - low) : 
                      close[1] > open ? math.max(high - open, close - low) :
                       close[1] < open? math.max(open - close, high - low): high - low
    val2 = ta.sma(value, 15)                   
    pos :=  val2 > SellLevel ? 1 : -1
    pos

strategy(title='Combo 2/20 EMA & Bull Power', shorttitle='Combo', overlay=true)
var I1 = '●═════ 2/20 EMA ═════●'
Length = input.int(14, minval=1, group=I1)
var I2 = '●═════  Bull Power ═════●'
SellLevel = input.float(-15, step=0.01, group=I2)
var misc = '●═════ MISC ═════●'
reverse = input.bool(false, title='Trade reverse', group=misc)
var timePeriodHeader = '●═════ Time Start ═════●'
d = input.int(1, title='From Day', minval=1, maxval=31, group=timePeriodHeader)
m = input.int(1, title='From Month', minval=1, maxval=12, group=timePeriodHeader)
y = input.int(2005, title='From Year', minval=0, group=timePeriodHeader)
StartTrade = time > timestamp(y, m, d, 00, 00) ? true : false
posEMA20 = EMA20(Length)
prePosBP = BP(SellLevel)
iff_1 = posEMA20 == -1 and prePosBP == -1 and StartTrade ? -1 : 0
pos = posEMA20 == 1 and prePosBP == 1 and StartTrade ? 1 : iff_1
iff_2 = reverse and pos == -1 ? 1 : pos
possig = reverse and pos == 1 ? -1 : iff_2
if possig == 1
    strategy.entry('Long', strategy.long)
if possig == -1
    strategy.entry('Short', strategy.short)
if possig == 0
    strategy.close_all()
barcolor(possig == -1 ? #b50404 : possig == 1 ? #079605 : #0536b3)

Published by ChaoZhang on the FMZ strategy square · last modified 2023-12-29. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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