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杠杆化马丁格尔期货交易策略Leveraged-Martingale-Futures-Trading-Strategy.md

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Name

杠杆化马丁格尔期货交易策略Leveraged-Martingale-Futures-Trading-Strategy

Author

ChaoZhang

Strategy Description

IMG [trans]

概述

本策略是一个利用杠杆效应实现高收益的马丁格尔期货交易策略。它通过动态调整仓位规模,在亏损时加大仓位来实现盈利目标。

策略原理

该策略的核心逻辑是:当价格触发止损线时,用更大的仓位重新入场,同时将止损线下调一定幅度。这样通过加大仓位规模来减少平均入场价。当仓位数量达到设定的最大订单数时,等待价格反转突破止盈线止损。

具体来说,策略首先在当前价格入场,设定仓位大小和止盈止损位。当价格向不利方向移动达到止损线时,策略以更大的仓位重新入场,同时将止损线下移一定百分比。这种补仓和移仓操作每次会使得开仓均价变低,从而增加了盈利机会。补仓次数达到设定最大订单数量后,等待价格反转回升突破止盈位时止盈。

优势分析

该策略最大的优势是可以通过杠杆化补仓来减少开仓成本,在行情不利时仍有向有利方向反转的可能。同时设定合理的止盈止损条件,可以有效控制风险。

该策略也适用于大宗商品等高波动率市场。通过杠杆放大盈亏来获取更高收益。

风险分析

策略的主要风险在于价格可能在补仓后继续不利运行,甚至跌破之前的止损位。这时可能面临较大的损失。可以通过设定较宽的止损幅度、较小的杠杆倍数等方法来控制这种风险。

另一个风险是在反转前资金可能已无法支撑最多订单量的加仓。这需要投资者具备足够的资金实力。

优化方向

可以从以下几个方面继续优化该策略:

  1. 动态调整杠杆倍数,在盈利时适当减小,亏损时适当加大

  2. 结合均线指标判断行情趋势,在趋势不明时止损退出

  3. 根据市场波动率设定止损幅度,波动大时扩大幅度

  4. 增加自动止损模块,避免极端行情下的巨额亏损

总结

本策略是一个典型的杠杆化马丁格尔交易策略。它通过加仓降低成本的方法追求更高收益,但也带有一定程度的风险。通过参数调节和功能扩展仍有优化空间,能适应更多市场环境。

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Overview

This is a futures trading strategy that leverages the martingale mechanism to achieve high returns. It dynamically adjusts position sizes to increase positions when losing to meet profit targets.

Principles

The core logic of this strategy is: when price triggers the stop loss line, reopen positions with larger sizes while lowering the stop loss line by a certain percentage. By increasing position sizes, it aims to lower average entry price. When number of positions reaches the set maximum orders, it waits for price reversal to take profit.

Specifically, it first enters at current price with set position size and take profit/loss levels. When price moves to the stop loss line, larger positions will be reopened and stop loss line is lowered by a set percentage. Such reopening and stop loss lowering operations will lower the average opening price, increasing profit potential. After number of added orders reaches maximum, it waits for price reversal to hit take profit.

Advantage Analysis

The biggest advantage is the ability to lower cost basis through leveraged reopening, while still having the chance of favorable reversal when trends are negative. Also by setting proper stop loss/profit levels, it effectively controls risks.

It also works well for commodities and other high volatility markets, amplifying gains/losses through leverage.

Risk Analysis

Main risk is price may continue downward trend after reopening, even breaking previous stop loss levels, leading to heavy losses. This can be mitigated by setting wider stop loss percentage, smaller leverage ratio etc.

Another risk is insufficient capital to support max order quantity before reversal. It requires adequate funding.

Improvement Areas

Some ways to further optimize the strategy:

  1. Dynamically adjust leverage level, lower when profiting and higher when losing

  2. Incorporate trend indicators to stop loss when trend unclear

  3. Set stop loss width based on market volatility, wider when volatile

  4. Add auto stop loss modules to limit extreme losses

Summary

This is a typical leveraged martingale trading strategy. By lowering cost through added orders, it pursues higher returns but also introduces risks. There is still room for optimization through parameter tuning and feature expansion to suit more market conditions.

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Strategy Arguments

Argument Default Description
v_input_1 2 Take Profit Percentage
v_input_2 2 Position Size Multiplier
v_input_3 10 Maximum Number of Reinforced Orders
v_input_4 10000 Trade Size in USD
v_input_5 true Drop Percentage for Next Trade
v_input_6 5 Leverage Factor
v_input_7 true Enter First Trade at Current Price
v_input_8 0.1 Taker Order Fee Percentage

Source (PineScript)

/*backtest
start: 2023-01-19 00:00:00
end: 2024-01-25 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4
strategy("Leveraged Martingale Strategy with Fees", overlay=true)

// User-defined input parameters
var float takeProfitPct = input(2.0, title="Take Profit Percentage") / 100.0
var float positionMultiplier = input(2.0, title="Position Size Multiplier")
var int maxOrders = input(10, title="Maximum Number of Reinforced Orders")
var float tradeSizeUSD = input(10000.0, title="Trade Size in USD")
var float dropPctForNextTrade = input(1.0, title="Drop Percentage for Next Trade") / 100.0
var float leverage = input(5.0, title="Leverage Factor")
var bool enterAtCurrentPrice = input(true, title="Enter First Trade at Current Price")
var float takerFeePct = input(0.1, title="Taker Order Fee Percentage") / 100.0

// State variables
var float last_entry_price = na
var float avg_entry_price = na
var float total_position_size = 0.0
var int num_trades = 0

// Entry logic
if (num_trades == 0)
    if (enterAtCurrentPrice or close < last_entry_price * (1 - dropPctForNextTrade))
        float size = tradeSizeUSD / close * leverage
        strategy.entry("Long", strategy.long, qty=size)
        avg_entry_price := close
        total_position_size := size
        last_entry_price := close
        num_trades := 1
else if (close < last_entry_price * (1 - dropPctForNextTrade) and num_trades < maxOrders)
    float size = tradeSizeUSD / close * leverage * pow(positionMultiplier, num_trades)
    strategy.entry("Double Long" + tostring(num_trades), strategy.long, qty=size)
    avg_entry_price := ((avg_entry_price * total_position_size) + (close * size)) / (total_position_size + size)
    total_position_size := total_position_size + size
    last_entry_price := close
    num_trades := num_trades + 1

// Take profit logic adjusted for leverage and fees
var float take_profit_price = na
var float fee_deduction = na
if (num_trades > 0)
    take_profit_price := avg_entry_price * (1 + takeProfitPct / leverage)
    fee_deduction := total_position_size * close * takerFeePct
    if (close > take_profit_price + fee_deduction / total_position_size)
        strategy.close_all()
        num_trades := 0

Detail

https://www.fmz.com/strategy/440058

Last Modified

2024-01-26 11:12:23