Momentum and Moving Average Combination Long Strategy

This strategy combines the MACD momentum indicator and the DMI trend indicator to go long when conditions are met. Its exits set a fixed take profit and a custom volatility trailing stop to lock in profits.

Pine ScriptMomentum Mean reversion Trend following MACD ATR ADX / DMI

Author: ChaoZhang
Complexity: Intermediate · 70 lines
Parameters: 11
Backtest bar: 2h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Principles

The entries of this strategy rely on the MACD and DMI indicators:

When MACD is positive (MACD line above Signal line), it indicates strengthening upside momentum in the market
When DI+ is higher than DI- in DMI, it indicates the market is in an uptrend

When both conditions are met at the same time, go long.

There are two standards for position exits:

Fixed take profit: close price rises to a set percentage for profit taking
Volatility trailing stop loss: use ATR and recent highest price to calculate a dynamically adjusted stop loss position. This can trailing stop loss according to market volatility

Advantages

The combination of MACD and DMI can more reliably determine the trend direction of the market and reduce erroneous operations
The profit taking conditions combine fixed take profit and volatility stop loss, which can flexibly lock in profits

Risks

Both MACD and DMI may produce false signals, leading to unnecessary losses
Fixed take profit may prevent profits from being maximized
The trailing speed of volatility stops may be improperly adjusted, too aggressive or conservative

Optimization Directions

Consider adding other indicators to filter entry signals, such as using the KDJ indicator to determine whether it is overbought or oversold
Different parameters can be tested for better take profit and stop loss effects
Parameters such as moving averages can be adjusted according to specific trading varieties to optimize the system

Summary

This strategy synthesizes multiple indicators to judge market trends and conditions, and intervenes in situations with a relatively large probability of favor. The profit taking conditions have also been optimally designed to ensure a certain profit while considering the flexibility of locking in gains. Through parameter adjustment and further risk management, this strategy can become a stable quantitative trading system.

Parameters

Name	Default	What it controls
v_input_1	true	From Month
v_input_2	true	From Day
v_input_3	2021	From Year
v_input_4	true	Thru Month
v_input_5	true	Thru Day
v_input_6	2112	Thru Year
v_input_7	true	Show Date Range
v_input_8	3	v_input_8
v_input_9	20	Length
v_input_10_close	0	Source: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_11	2	vStop Multiplier

Source Pine Script

/*backtest
start: 2024-01-29 00:00:00
end: 2024-02-28 00:00:00
period: 2h
basePeriod: 15m
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/
//@version=4
strategy(shorttitle='(MACD + DMI Scalping with Volatility Stop',title='MACD + DMI Scalping with Volatility Stop by (Coinrule)', overlay=true, initial_capital = 100, process_orders_on_close=true, default_qty_type = strategy.percent_of_equity, default_qty_value = 100, commission_type=strategy.commission.percent, commission_value=0.1)

// Works better on 3h, 1h, 2h, 4h

//Backtest dates
fromMonth = input(defval = 1,    title = "From Month",      type = input.integer, minval = 1, maxval = 12)
fromDay   = input(defval = 1,    title = "From Day",        type = input.integer, minval = 1, maxval = 31)
fromYear  = input(defval = 2021, title = "From Year",       type = input.integer, minval = 1970)
thruMonth = input(defval = 1,    title = "Thru Month",      type = input.integer, minval = 1, maxval = 12)
thruDay   = input(defval = 1,    title = "Thru Day",        type = input.integer, minval = 1, maxval = 31)
thruYear  = input(defval = 2112, title = "Thru Year",       type = input.integer, minval = 1970)

showDate  = input(defval = true, title = "Show Date Range", type = input.bool)

start     = timestamp(fromYear, fromMonth, fromDay, 00, 00)        // backtest start window
finish    = timestamp(thruYear, thruMonth, thruDay, 23, 59)        // backtest finish window
window()  => true

// DMI and MACD inputs and calculations

[pos_dm, neg_dm, avg_dm] = dmi(14, 14)
[macd, macd_signal, macd_histogram] = macd(close, 12, 26, 9)


Take_profit= ((input (3))/100)

longTakeProfit = strategy.position_avg_price * (1 + Take_profit)

length = input(20, "Length", minval = 2)
src = input(close, "Source")
factor = input(2.0, "vStop Multiplier", minval = 0.25, step = 0.25)
volStop(src, atrlen, atrfactor) =>
    var max     = src
    var min     = src
    var uptrend = true
    var stop    = 0.0
    atrM        = nz(atr(atrlen) * atrfactor, tr)
    max         := max(max, src)
    min         := min(min, src)
    stop        := nz(uptrend ? max(stop, max - atrM) : min(stop, min + atrM), src)
    uptrend     := src - stop >= 0.0
    if uptrend != nz(uptrend[1], true)
        max    := src
        min    := src
        stop   := uptrend ? max - atrM : min + atrM
    [stop, uptrend]

[vStop, uptrend] = volStop(src, length, factor)


closeLong = close > longTakeProfit or crossunder(close, vStop)


//Entry 
strategy.entry(id="long", long = true, when = crossover(macd, macd_signal) and pos_dm > neg_dm and window())


//Exit
strategy.close("long", when = closeLong and window())

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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