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基于移动平均线和平均真实波动率的趋势追踪策略Trend-Tracking-Strategy-Based-on-Moving-Average-and-Average-True-Range.md

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Name

基于移动平均线和平均真实波动率的趋势追踪策略Trend-Tracking-Strategy-Based-on-Moving-Average-and-Average-True-Range

Author

ChaoZhang

Strategy Description

IMG [trans]

概述

该策略采用移动平均线和平均真实波动率来判断市场趋势方向,根据趋势方向进行趋势追踪交易。

策略原理

该策略使用len周期的移动平均线ma和2倍的len周期平均真实波动率atr来判断市场趋势。具体判断规则是:

当最低价大于移动平均线加上平均真实波动率时(low > ma + atr),判断为上升趋势。
当最高价小于移动平均线减去平均真实波动率时(high < ma - atr),判断为下降趋势。

其他情况则保持之前的判断。

在判断出上升趋势时,当允许做多时,按照一定比例做多。
在判断出下降趋势时,当允许做空时,按照一定比例做空。

平仓条件为到达指定的交易结束日期。

优势分析

该策略具有以下优势:

  1. 使用移动平均线判断大致趋势方向,避免被市场短期波动误导。
  2. 借助平均真实波动率来设置动态止损,有利于控制风险。
  3. 能够顺势而为,及时捕捉趋势机会,收益潜力较大。
  4. 规则相对简单易操作。

风险分析

该策略面临以下主要风险:

  1. 大幅震荡市场中,容易出现多次亏损。
  2. 无法有效判断趋势反转点,可能出现追高杀跌的风险。
  3. 平均真实波动率参数设置不当可能导致退出点过于宽松或过于严格。

解决方法:

  1. 适当调整移动平均线参数,使用更稳定的参数。
  2. 结合其它指标确认信号,避免追高杀跌。
  3. 对平均真实波动率参数进行优化测试,设置合适参数。

优化方向

该策略可以从以下几个方面进行优化:

  1. 测试不同平均线系统,寻找更稳定的参数组合。
  2. 加入其它辅助指标判断信号的可靠性。
  3. 对平均真实波动率参数进行测试,找到最佳参数。
  4. 优化资金利用率,通过杠杆提高收益率。
  5. 结合机器学习等方法实现参数的动态优化。

总结

该策略整体思路清晰、易于理解,使用移动平均线判断趋势方向,并利用平均真实波动率设定止损,能够有效跟踪趋势。但存在一定的风险,需要进一步优化参数设定以及加入其他判断指标。总的来说,该策略为趋势追踪交易提供了一个可行的思路。

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Overview

This strategy uses moving average and average true range to determine the market trend direction for trend tracking trading.

Principles

This strategy uses the moving average ma of len periods and 2 times the average true range atr of len periods to determine the market trend. The specific rules are:

When the low is greater than the moving average plus the average true range (low > ma + atr), it is judged as an upward trend. When the high is less than the moving average minus the average true range (high < ma - atr), it is judged as a downward trend.

In other cases, the previous judgment is maintained.

When an upward trend is determined, go long at a certain percentage when allowed to go long. When a downward trend is determined, go short at a certain percentage when allowed to go short.

The closing condition is to reach the specified trading end date.

Advantage Analysis

The advantages of this strategy are:

  1. Use moving average to determine general trend direction and avoid being misled by short-term market fluctuations.
  2. Use average true range to set dynamic stop loss, which is conducive to risk control.
  3. Can capture trend opportunities in a timely manner following the trend, with high profit potential.
  4. Simple and easy to operate rules.

Risk Analysis

The main risks faced by this strategy are:

  1. It is prone to multiple losses in a sharply fluctuating market.
  2. Unable to effectively determine trend reversal points, there is a risk of chasing highs and killing lows.
  3. Improper parameter settings of average true range may result in exit points that are too loose or too strict.

Solutions:

  1. Adjust moving average parameters appropriately to use more stable parameters.
  2. Confirm signals with other indicators to avoid chasing highs and killing lows.
  3. Optimize and test the average true range parameters to set appropriate parameters.

Optimization Directions

The strategy can be optimized from the following aspects:

  1. Test different moving average systems to find more stable parameter combinations.
  2. Add other auxiliary indicators to judge the reliability of signals.
  3. Test the average true range parameters to find the optimal parameters.
  4. Optimize capital utilization through leverage to increase return on capital.
  5. Combine machine learning and other methods to achieve dynamic parameter optimization.

Summary

The overall idea of ​​this strategy is clear and easy to understand. It uses moving averages to determine trend direction and uses average true range to set stops. It can effectively track trends. But there are certain risks, and further optimization of parameter settings and adding other judgment indicators are needed. In general, this strategy provides a viable approach for trend tracking trading.

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Strategy Arguments

Argument Default Description
v_input_1 true Long
v_input_2 true Short
v_input_3 100 Capital, %
v_input_4 30 MA Length
v_input_5_ohlc4 0 MA Source: ohlc4
v_input_6 false limitmode
v_input_7 1900 From Year
v_input_8 2100 To Year
v_input_9 true From Month
v_input_10 12 To Month
v_input_11 true From day
v_input_12 31 To day

Source (PineScript)

/*backtest
start: 2024-01-04 00:00:00
end: 2024-01-11 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//2019
//Noro

//@version=4
strategy(title = "Noro's MA+ATR Strategy", shorttitle = "MA+ATR str", overlay = true, default_qty_type = strategy.percent_of_equity, default_qty_value = 100, pyramiding = 0)

//Settings
needlong = input(true, defval = true, title = "Long")
needshort = input(true, defval = true, title = "Short")
capital = input(100, defval = 100, minval = 1, maxval = 10000, title = "Capital, %")
len = input(30, minval = 2, title = "MA Length")
src = input(ohlc4, title = "MA Source")
limitmode = input(false)
fromyear = input(1900, defval = 1900, minval = 1900, maxval = 2100, title = "From Year")
toyear = input(2100, defval = 2100, minval = 1900, maxval = 2100, title = "To Year")
frommonth = input(01, defval = 01, minval = 01, maxval = 12, title = "From Month")
tomonth = input(12, defval = 12, minval = 01, maxval = 12, title = "To Month")
fromday = input(01, defval = 01, minval = 01, maxval = 31, title = "From day")
today = input(31, defval = 31, minval = 01, maxval = 31, title = "To day")

//MA + BG
atr = sma(tr, len) * 2
ma = sma(src, len)
plot(ma, color = color.blue, linewidth = 4)
trend = 0
trend := low > ma + atr ? 1 : high < ma - atr ? -1 : trend[1]
col = trend == 1 ? color.lime : color.red
bgcolor(col, transp = 70)

//Trading
lot = 0.0
lot := strategy.position_size != strategy.position_size[1] ? strategy.equity / close * capital / 100 : lot[1]
if trend == 1 and limitmode == false
    strategy.entry("Long", strategy.long, needlong == false ? 0 : lot)
if trend == -1 and limitmode == false
    strategy.entry("Short", strategy.short, needshort == false ? 0 : lot)
if trend == 1 and limitmode
    strategy.entry("Long", strategy.long, needlong == false ? 0 : lot)
if trend == -1 and limitmode
    strategy.entry("Short", strategy.short, needshort == false ? 0 : lot)
// if time > timestamp(toyear, tomonth, today, 23, 59)
//     strategy.close_all()

Detail

https://www.fmz.com/strategy/438456

Last Modified

2024-01-12 11:14:01