Momentum Crossover Strategy with Dynamic Trailing Stop Loss

This strategy combines moving average indicators and directional movement index (DMI) indicators to generate buy and sell signals based on dual-indicator crossovers. It also incorporates a dynamic trailing stop loss…

Pine ScriptMomentum Trend following EMA ADX / DMI

Author: ChaoZhang
Complexity: Starter · 84 lines
Parameters: 5
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Logic

Construct moving average indicators using a short 9-day EMA and a long 21-day EMA. A buy signal is generated when the short EMA crosses above the long EMA. A sell signal is generated when the short EMA crosses below the long EMA.
Construct DMI indicators using ADX, +DI and -DI. A buy signal is triggered when +DI crosses above -DI. A sell signal is triggered when -DI crosses above +DI.
Combine the signals of EMA and DMI, requiring both indicators to satisfy conditions before issuing actual buy or sell signals.
Use a dynamic trailing stop loss to track the highest price/lowest price for stop loss.

Advantage Analysis

Dual-indicator combos filter fake signals and improve signal accuracy. Short-term indicators capture trend changes while long-term ones determine overall direction.
Momentum indicators can capture trend shifts early with some leading characteristics.
Dynamic trailing stop loss locks in profits as much as possible while controlling risks.

Risk Analysis

With dual-indicator combos, signal frequency is reduced, possibly missing some opportunities.
Poor parameter tuning of indicators may lead to over-trading or low-quality signals.
Stop loss set too wide increases loss risks while set too tight increases trend disconnection risks.

Optimization Directions

Test EMA combos with different short and long term lengths to find optimum.
Optimize ADX parameters to improve DMI signal quality.
Fine tune stop loss parameters to lock profits while managing risks.
Consider adding more filters to further boost signal quality.

Conclusion

This strategy combines the strengths of moving averages and momentum indicators for dual confirmation of signals, complementing each other to enhance profitability. Meanwhile, the dynamic trailing stop loss effectively controls risks. Further parameter optimization and strategy refinement could improve both profitability and stability.

Parameters

Name	Default	What it controls
v_input_int_1	9	Short-Term EMA Period
v_input_int_2	21	Long-Term EMA Period
v_input_float_1	true	Risk Percentage EMA
v_input_1	17	ADX Smoothing
v_input_2	17	DI Length

Source Pine Script

/*backtest
start: 2023-02-22 00:00:00
end: 2024-02-28 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5
strategy("Combined EMA and DMI Strategy with Enhanced Table", overlay=true)

// Input parameters for EMA
shortTermEMA = input.int(9, title="Short-Term EMA Period")
longTermEMA = input.int(21, title="Long-Term EMA Period")
riskPercentageEMA = input.float(1, title="Risk Percentage EMA", minval=0.1, maxval=5, step=0.1)

// Calculate EMAs
emaShort = ta.ema(close, shortTermEMA)
emaLong = ta.ema(close, longTermEMA)

// EMA Crossover Strategy
longConditionEMA = emaShort > emaLong and emaShort[1] <= emaLong[1]
shortConditionEMA = emaShort < emaLong and emaShort[1] >= emaLong[1]

// Input parameters for DMI
adxlen = input(17, title="ADX Smoothing")
dilen = input(17, title="DI Length")

// DMI Logic
dirmov(len) =>
    up = ta.change(high)
    down = -ta.change(low)
    truerange = ta.tr
    plus = fixnan(100 * ta.rma(up > down and up > 0 ? up : 0, len) / truerange)
    minus = fixnan(100 * ta.rma(down > up and down > 0 ? down : 0, len) / truerange)
    [plus, minus]

adx(dilen, adxlen) => 
    [plus, minus] = dirmov(dilen)
    sum = plus + minus
    adxValue = 100 * ta.rma(math.abs(plus - minus) / (sum == 0 ? 1 : sum), adxlen)
    [adxValue, plus, minus]

[adxValue, up, down] = adx(dilen, adxlen)

// DMI Conditions
buyConditionDMI = up > down or (up and adxValue > down)
sellConditionDMI = down > up or (down and adxValue > up)

// Combined Conditions for Entry
longEntryCondition = longConditionEMA and buyConditionDMI
shortEntryCondition = shortConditionEMA and sellConditionDMI

// Combined Conditions for Exit
longExitCondition = shortConditionEMA
shortExitCondition = longConditionEMA

// Enter long trade based on combined conditions
if (longEntryCondition)
    strategy.entry("Long", strategy.long)

// Enter short trade based on combined conditions
if (shortEntryCondition)
    strategy.entry("Short", strategy.short)

// Exit trades
if (longExitCondition)
    strategy.close("Long")

if (shortExitCondition)
    strategy.close("Short")

// Plot EMAs
plot(emaShort, color=color.blue, title="Short-Term EMA")
plot(emaLong, color=color.red, title="Long-Term EMA")

// Create and fill the enhanced table
var tbl = table.new(position.top_right, 4, 1)
if (barstate.islast)
    table.cell(tbl, 0, 0, "ADX: " + str.tostring(adxValue), bgcolor=color.new(color.red, 90), width=15, height=4)
    table.cell(tbl, 1, 0, "+DI: " + str.tostring(up), bgcolor=color.new(color.blue, 90), width=15, height=4)
    table.cell(tbl, 2, 0, "-DI: " + str.tostring(down), bgcolor=color.new(color.orange, 90), width=15, height=4)

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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