Dynamic Moving EMAs Combination Quant Strategy

This strategy is a dynamic moving average combination strategy that works on multiple timeframes. It usesExponential Moving Averages (EMAs) of different lengths for trend judgment and entry/exit signals. The "MAX" in…

Pine ScriptBreakout Mean reversion Trend following MACD EMA ATR

Author: ChaoZhang
Complexity: Intermediate · 80 lines
Parameters: 15
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Logic

The strategy employs 7 EMAs moving at different speeds, from the fastest to the slowest: 3-period EMA, 15-period EMA, 19-period EMA, 50-period EMA, 100-period EMA, 150-period EMA and 200-period EMA. These 7 EMAs are arranged in a trapezoidal formation. To generate long and short signals, the close price needs to break through these EMAs successively to ensure a strong post-reversal trend entry.

In addition, the strategy also incorporates price breaking recent high and close price crossing historical highs to confirm long signals, and uses breaking recent low and close price crossing historical lows to confirm short signals. This helps avoid false breakouts.

The exit rules require the close price to break the faster EMAs successively towards the slower EMAs, indicating a trend reversal. Alternatively, if the latest bar's low/high breaks more than 4 EMAs, it is also an exit signal for that position.

Advantage Analysis

Using 7 EMAs of different speeds forming a trapezoid shape can identify trend reversal points more precisely
Incorporating new high/low and historical highs/lows avoids false breakout signals
The strict dual exit rules allow timely stop loss

Risk Analysis

No stop loss mechanism leads to huge loss potential
The dual exit rules may cause premature exit
Too many faster EMAs generate more noise and increase trading frequency and commission cost

Solutions:

Add fixed percentage stop loss and trailing stop loss
Adjust exit EMA lengths to lower the strictness of dual exit rules
Increase EMA lengths to reduce trading frequency

Optimization Directions

Add stop loss mechanisms like fixed percentage stop loss, trailing stop loss etc
Optimize EMA parameters to find the best combination
Add other indicators like MACD, ATR, KDJ etc to filter signals
Combine with range/channel strategies to catch secondary moves in trends
Consider adding position sizing rules

Conclusion

The strategy has a clear logic of using 7 EMAs of different speeds to determine trends and dual exit rules to detect reversals. But there is no stop loss mechanism leading to huge loss risk, and it may exit prematurely. Improvements can be made in aspects like adding stop loss, parameter tuning, indicator filtering to turn it into a solid trading system.

Parameters

Name	Default	What it controls
v_input_1	3	Length
v_input_2	15	Length2
v_input_3	19	Length3
v_input_4	50	Length4
v_input_5	100	Length44
v_input_6	150	Length5
v_input_7	171	Length6
v_input_8	172	Length66
v_input_9_close	0	xPrice: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_10	true	From Day
v_input_11	true	From Month
v_input_12	2000	From Year
v_input_13	31	To Day
v_input_14	12	To Month
v_input_15	2020	To Year

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
strategy(title="Crypto MAX Trend", shorttitle="Crypto MAX", overlay = true  )
Length = input(3, minval=1)
Length2 = input(15, minval=1)
Length3 = input(19, minval=1)
//Length33 = input(25, minval=1)
Length4 = input(50, minval=1)
Length44 = input(100, minval=1)
Length5 = input(150, minval=1)
Length6 = input(171, minval=1)
Length66 = input(172, minval=1)

xPrice = input(close)

xEMA1 = ema(xPrice, Length)
xEMA2 = ema(xPrice, Length2)
xEMA3 = ema(xPrice, Length3)
//xEMA33 = ema(xPrice, Length33)
xEMA4 = ema(xPrice, Length4)
xEMA44 = ema(xPrice, Length44)
xEMA5 = ema(xPrice, Length5)
xEMA6 = ema(xPrice, Length6)
xEMA66 = ema(xPrice, Length66)

// plot(xEMA1, color=color.white)
// plot(xEMA2, color=color.red)
// plot(xEMA3, color=color.green)
// plot(xEMA4, color=color.purple)
// plot(xEMA44, color=color.gray)
// plot(xEMA5, color=color.maroon)
// plot(xEMA6, color=color.blue)
// plot(xEMA66, color=color.orange)


fromDay = input(defval = 1, title = "From Day", minval = 1, maxval = 31)
fromMonth = input(defval = 1, title = "From Month", minval = 1, maxval = 12)
fromYear = input(defval = 2000, title = "From Year", minval = 1970)
 //monday and session 
// To Date Inputs
toDay = input(defval = 31, title = "To Day", minval = 1, maxval = 31)
toMonth = input(defval = 12, title = "To Month", minval = 1, maxval = 12)
toYear = input(defval = 2020, title = "To Year", minval = 1970)

startDate = timestamp(fromYear, fromMonth, fromDay, 00, 00)
finishDate = timestamp(toYear, toMonth, toDay, 00, 00)
time_cond = true



long = close >  xEMA1 and xEMA1 > xEMA2 and xEMA2 > xEMA3  and xEMA3 > xEMA4  and xEMA4 > xEMA44 and xEMA44 > xEMA5 and xEMA5> xEMA6  and xEMA6> xEMA66  and close > high[1] and high[1] > high[2] and close > high[3] and close > high[4] and close > high[5] and high[5] > high[6] and time_cond
short = close < xEMA1 and xEMA1 < xEMA2 and xEMA2 < xEMA3  and xEMA3 < xEMA4  and xEMA4 < xEMA44 and xEMA44 < xEMA5 and xEMA5< xEMA6 and  xEMA6< xEMA66 and close < low[1] and low[1] < low[2] and close < low[3] and close < low[4] and close< low[5] and low[5] < low[6] and time_cond

notlong = close < xEMA1
strategy.entry("long",1,when=long)
strategy.entry("short",0,when=short)


exitlong1 = xEMA1 < xEMA2 and xEMA2 < xEMA3 and xEMA3 < xEMA4
exitlong2 = crossunder(low,xEMA1) and crossunder(low,xEMA2) and crossunder(low,xEMA3) and crossunder(low,xEMA4)
exitshort1 = xEMA1 > xEMA2 and xEMA2 > xEMA3 and xEMA3 > xEMA4
exitshort2 = crossover(high,xEMA1) and crossover(high,xEMA2) and crossover(high,xEMA3) and crossover(high,xEMA4)

strategy.close("long", when = exitlong1 or exitlong2)
strategy.close("short", when= exitshort1 or exitshort2)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-01-22. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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