MACD and Martingale Combination Strategy for Optimized Long Trading

Pine ScriptMartingale Trend following MACD

Author: ChaoZhang
Complexity: Starter · 58 lines
Parameters: 0
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This strategy combines the MACD indicator and the Martingale money management method to optimize long trading. The strategy determines buy and sell signals by comparing the relative positions of the MACD line and the signal line, as well as the ratio between them. At the same time, the strategy uses the Martingale method to dynamically adjust the contract size, aiming to achieve profitability by increasing the order quantity when losing. The main advantage of this strategy is its ability to capture strong upward trends and improve profitability through the Martingale method. However, the strategy also has certain risks. If there are consecutive losses, it may face a large drawdown.

Strategy Principle

The core of this strategy is the MACD indicator and the Martingale money management method. The MACD indicator consists of two moving averages (fast line and slow line). By comparing the position relationship between the fast line and the slow line, the current trend direction can be determined. When the fast line crosses above the slow line and the ratio of the fast line to the slow line is greater than or equal to 1.07, a buy signal is generated; when the fast line crosses below the slow line and the ratio of the slow line to the fast line is greater than or equal to 1.07, a sell signal is generated.

The Martingale method is used to dynamically adjust the contract size. When the previous trade is losing, the strategy will double the contract size, up to a maximum of 5 times. If the consecutive losses exceed 5 times or there is a profit, the contract size will be reset to the initial value. The purpose of this method is to compensate for previous losses by increasing the order quantity, but it also increases the risk.

Strategy Advantages

Ability to capture strong upward trends: By comparing the position relationship between the MACD fast line and slow line, as well as the ratio between them, the strategy can identify strong upward trends and buy in a timely manner.
Martingale method can improve profitability: When losing, by increasing the order quantity, the strategy has the opportunity to make up for previous losses in subsequent profitable trades, thereby improving overall profitability.
Reasonable take profit and stop loss settings: The strategy sets clear take profit and stop loss conditions. When the price reaches a certain level, the position is closed, which can both lock in profits and control risks.

Strategy Risks

Consecutive losses may lead to large losses: If the strategy encounters consecutive losing trades, the Martingale method will continuously increase the order quantity, which may lead to large losses. Although the strategy sets a maximum doubling times, it may still face considerable risks in extreme cases.
Trend judgment may be wrong: The strategy relies on the MACD indicator to judge the trend, but in some cases, the indicator may send false signals, causing the strategy to make wrong decisions.
Frequent adjustments to contract size may increase transaction costs: Due to the need for frequent adjustments to contract size in the Martingale method, transaction costs may increase, affecting the overall performance of the strategy.

Strategy Optimization Directions

Combine with other technical indicators: In addition to MACD, the strategy can also be combined with other technical indicators, such as RSI and BOLL, to improve the accuracy of trend judgment.
Optimize the Martingale method: Consider introducing risk control measures in the Martingale method, such as setting a maximum loss limit or dynamically adjusting the doubling ratio based on market volatility, to reduce the risk of consecutive losses.
Introduce market sentiment analysis: The strategy can incorporate market sentiment indicators, such as the Volatility Index (VIX), to determine the market's risk appetite and adjust strategy parameters accordingly.

Summary

This strategy combines the MACD indicator and the Martingale money management method to implement a quantitative trading strategy for optimizing long trades. The main advantage of the strategy is its ability to capture strong upward trends and improve profitability through the Martingale method. However, the strategy also has the risk of large losses due to consecutive losses. To further optimize the strategy, one can consider combining other technical indicators, optimizing the Martingale method, and introducing market sentiment analysis. Overall, this strategy provides a feasible idea for long trading, but in practical application, it needs to be appropriately adjusted and optimized according to specific market conditions.

Source Pine Script

/*backtest
start: 2024-05-01 00:00:00
end: 2024-05-31 23:59:59
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
//@version=5
strategy("Advanced MACD Strategy with Limited Martingale", overlay=true)

// MACD settings
fastLength = 15
slowLength = 30
signalSmoothing = 9
[macdLine, signalLine, _] = ta.macd(close, fastLength, slowLength, signalSmoothing)

// Contract size and previous trade result tracking
var float contractSize = 1
var int martingaleCount = 0 // Martingale count
var float lastTradeResult = 0

// Buy and sell conditions
longCondition = ta.crossover(macdLine, signalLine) and ( signalLine / macdLine >= 1.07)
shortCondition = ta.crossunder(macdLine, signalLine) and ( macdLine / signalLine >= 1.07)

// Buy signal
if (longCondition)
    strategy.entry("Long", strategy.long, qty=contractSize)
    lastTradeResult := strategy.netprofit

// Sell signal
if (shortCondition)
    strategy.entry("Short", strategy.short, qty=contractSize)
    lastTradeResult := strategy.netprofit

// Take profit and stop loss conditions
strategy.close("Long", when=(close / strategy.position_avg_price >= 1.005))
strategy.close("Short", when=(strategy.position_avg_price / close >= 1.005))
strategy.close("Long", when=(close / strategy.position_avg_price <= 0.99))
strategy.close("Short", when=(strategy.position_avg_price / close <= 0.99))

// Martingale strategy implementation
if (strategy.netprofit < lastTradeResult)
    if (martingaleCount < 5)
        contractSize := contractSize * 2
        martingaleCount := martingaleCount + 1
    else
        contractSize := 1
        martingaleCount := 0
else
    contractSize := 1
    martingaleCount := 0

// Plot buy and sell points as arrows
plotshape(series=longCondition, location=location.belowbar, color=color.green, style=shape.labelup, text="Buy")
plotshape(series=shortCondition, location=location.abovebar, color=color.red, style=shape.labeldown, text="Sell")

Published by ChaoZhang on the FMZ strategy square · last modified 2024-06-07. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

Build this with AgenKit

A spec is not a trading system. Paste this into your coding agent and AgenKit runs a specialist team — architecture, test-first build, risk gates, review — with paper trading on by default.

in Claude Code, Cursor, Codex & 4 more

/agenkit build a production-grade trading bot with a backtest engine, risk controls and paper trading by default from strategies/MACD-and-Martingale-Combination-Strategy-for-Optimized-Long-Trading.md

npx agenkit install engineering-kit in your project
Paste the command into your agent and approve each phase
Get tests, backtest, risk controls and a paper-trading switch

Get AgenKit How /agenkit works

Understand it first

Before you run this, read the lesson behind the idea and how to backtest it honestly. Specs like this one are the survivors of an unknown number of trials; deflate their results accordingly.