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动量指标与SuperTrend组合交易策略Momentum-and-SuperTrend-Combination-Trading-Strategy.md

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Name

动量指标与SuperTrend组合交易策略Momentum-and-SuperTrend-Combination-Trading-Strategy

Author

ChaoZhang

Strategy Description

IMG [trans]

一、策略概述

本策略名称为“动量指标与SuperTrend组合交易策略”。该策略主要思想是将动量指标与SuperTrend指标进行组合,利用两种指标的优势实现更准确的 Entries 和 Exits。

具体来说,动量指标用于判断价格运动的加速或减速,判断趋势的变化。SuperTrend 用于判断价格是否突破上升或下降通道,判断趋势的变化。两者组合可以更准确地捕捉趋势的转折点。

二、策略详细原理

  1. 动量指标部分

    计算价格的 N 日动量值,并计算动量值的 1 日动量。当 N 日动量 > 0 且 1 日动量 > 0 时,为做多信号;当 N 日动量 < 0 且 1 日动量 < 0 时,为做空信号。

  2. SuperTrend 指标部分

    计算价格的 ATR 值,并根据 ATR 绘制上升通道线和下降通道线。当价格从下方突破上升通道时为做多信号,当价格从上方突破下降通道时为做空信号。

  3. entry logic

将动量指标的做多信号与 SuperTrend 的做多信号进行“与”操作,同时发生时为最终做多Entry信号;将动量指标的做空信号与 SuperTrend 的做空信号进行“与”操作,同时发生时为最终做空Entry信号。

三、策略优势分析

  1. 利用动量指标判断价格运动加速或减速,捕捉趋势转折点。

  2. 利用 SuperTrend 指标判断价格突破通道,捕捉突破点。

  3. 两种指标互相验证,可以减少假信号,提高 Entries 准确性。

  4. 结合两种指标的 Exit logic,可以实现趋势追踪退出,避免 premature exit。

四、策略风险分析

  1. N 日动量指标参数设置不当可能导致错失趋势转折点。

  2. SuperTrend 参数设置不当,通道绘制不准确,可能产生假信号。

  3. 两种指标互相验证,可能错过部分机会。

  4. 需调整参数组合找到最优参数对,最大程度发掘策略潜力。

对应的解决方法:

  1. 利用 walk-forward analysis 方法找到最优参数。

  2. 增加参数优化模块,实时优化参数。

  3. 调整两种指标的组合逻辑,综合考虑。

五、策略优化方向

  1. 增加参数自适应优化模块,使参数能根据市场环境实时调整

  2. 增加机器学习模型,辅助判断指标信号的准确性

  3. 扩展更多指标,组成指标集,利用投票机制产生 Entry 信号

  4. 利用深度学习模型替代传统指标,以数据驱动方法判断 Entry 和 Exit 时机

六、总结

本策略综合运用动量指标和 SuperTrend 指标的优势,通过双重验证提高 Entry 准确性,并利用指标判断 Exit 时机。相比单一使用指标,能够减少假信号,获取更高胜率。通过参数优化、机器学习等技术扩展,策略效果还有进一步提升空间,值得深入研究与应用。

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1. Strategy Overview

The strategy is named "Momentum and SuperTrend Combination Trading Strategy". The main idea of this strategy is to combine the Momentum indicator with the SuperTrend indicator to take advantage of both indicators for more accurate Entries and Exits.

Specifically, the Momentum indicator is used to judge the acceleration or deceleration of price movements and changes in trends. SuperTrend is used to judge whether prices break through upward or downward channels and changes in trends. The combination of the two can more accurately capture trend reversal points.

2. Detailed Strategy Principle

  1. Momentum indicator part

    Calculate the N-day momentum value of the price and calculate the 1-day momentum of the momentum value. When N-day momentum > 0 and 1-day momentum > 0, it is a long signal; when N-day momentum < 0 and 1-day momentum < 0, it is a short signal.

  2. SuperTrend indicator part

    Calculate the ATR value of the price, and draw the upward channel line and downward channel line based on ATR. When the price breaks through the upward channel from the bottom, it is a long signal, and when the price breaks through the downward channel from the top, it is a short signal.

  3. Entry logic

    Take the AND operation of the long signal from the momentum indicator and the long signal from the SuperTrend to generate the final long entry signal when both happen at the same time; Take the AND operation of the short signal from the momentum indicator and the short signal from the SuperTrend to generate the final short entry signal when both happen at the same time.

3. Advantage Analysis

  1. Use momentum indicators to determine acceleration or deceleration of price movements to capture trend reversal points.

  2. Use SuperTrend indicators to determine price breakthrough channels to capture breakthrough points.

  3. Mutual verification of two types of indicators can reduce false signals and improve the accuracy of Entries.

  4. The combination of Exit logic of the two indicators enables trend tracking exit to avoid premature exit.

4. Risk Analysis

  1. Improper parameter setting of N-day momentum indicator may miss trend reversal points.

  2. Improper parameter setting of SuperTrend may lead to inaccurate channel drawing and false signals.

  3. Mutual verification of the two indicators may miss some opportunities.

  4. Parameters combination should be adjusted to find the optimal parameter pair to maximize the potential of the strategy.

Corresponding solutions:

  1. Use walk-forward analysis to find the optimal parameters.

  2. Add parameter optimization module for real-time parameter optimization.

  3. Adjust the combination logic of the two indicators and consider comprehensively.

5. Optimization Directions

  1. Add adaptive parameter optimization module for real-time adjustment according to market conditions

  2. Add machine learning model to assist in judging the accuracy of indicator signals

  3. Expand more indicators to form an indicator set, and use voting mechanism to generate entry signals

  4. Use deep learning models instead of traditional indicators for data-driven judgments of entry and exit timing

6. Summary

This strategy combines the strengths of Momentum and SuperTrend indicators through double verification to improve the accuracy of Entries, and uses indicators to judge the timing of Exits. Compared to the single use of indicators, it can reduce false signals and achieve higher win rates. Through parameter optimization, machine learning and other technologies extension, there is still room for further improvement of strategy effectiveness and it deserves in-depth research and application.

[/trans]

Strategy Arguments

Argument Default Description
v_input_1 12 length
v_input_2 10 Periods
v_input_3 3 Multiplier
v_input_4 true changeATR
v_input_5_hl2 0 src: hl2

Source (PineScript)

/*backtest
start: 2022-12-20 00:00:00
end: 2023-12-26 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4
strategy("Momentum + SuperTrend Strategy", overlay=true)

// Momentum Strategy
length = input(12)
price = close
momentum(seria, length) =>
    mom = seria - seria[length]
    mom
mom0 = momentum(price, length)
mom1 = momentum(mom0, 1)
momLongCondition = mom0 > 0 and mom1 > 0
momShortCondition = mom0 < 0 and mom1 < 0

// SuperTrend Strategy
Periods = input(10)
Multiplier = input(3.0)
changeATR = input(true)
src = input(hl2)
atr2 = sma(tr, Periods)
atr = changeATR ? atr(Periods) : atr2
up = src - (Multiplier * atr)
up1 = nz(up[1], up)
up := close[1] > up1 ? max(up, up1) : up
dn = src + (Multiplier * atr)
dn1 = nz(dn[1], dn)
dn := close[1] < dn1 ? min(dn, dn1) : dn
trend = 1
trend := nz(trend[1], trend)
trend := trend == -1 and close > dn1 ? 1 : trend == 1 and close < up1 ? -1 : trend
buySignal = trend == 1 and trend[1] == -1
sellSignal = trend == -1 and trend[1] == 1

// Combined Entry Conditions
longCondition = momLongCondition and buySignal
shortCondition = momShortCondition and sellSignal

// Strategy Entries
if (longCondition)
    strategy.entry("MomLE", strategy.long, stop=high+syminfo.mintick, comment="MomLE")
else
    strategy.cancel("MomLE")

if (shortCondition)
    strategy.entry("MomSE", strategy.short, stop=low-syminfo.mintick, comment="MomSE")
else
    strategy.cancel("MomSE")

// Plot SuperTrend on the chart
upPlot = plot(trend == 1 ? up : na, title="SuperTrend Up", color=color.green, linewidth=2)
dnPlot = plot(trend == -1 ? dn : na, title="SuperTrend Down", color=color.red, linewidth=2)

// Highlight the SuperTrend region
fill(upPlot, dnPlot, color = trend == 1 ? color.new(color.green, 90) : color.new(color.red, 90), title="SuperTrend Highlight")

// Plot SuperTrend Buy/Sell signals on the chart
plotshape(series=buySignal, title="SuperTrend Buy Signal", color=color.green, style=shape.triangleup, size=size.small)
plotshape(series=sellSignal, title="SuperTrend Sell Signal", color=color.red, style=shape.triangledown, size=size.small)
// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © naveen1119

Detail

https://www.fmz.com/strategy/436782

Last Modified

2023-12-27 16:37:58