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价格突破移动平均线的趋势跟踪策略Price-Crossing-Moving-Average-Trend-Following-Strategy.md

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Name

价格突破移动平均线的趋势跟踪策略Price-Crossing-Moving-Average-Trend-Following-Strategy

Author

ChaoZhang

Strategy Description

IMG [trans]

概述

这个策略基于价格与移动平均线的交叉来产生买入和卖出信号。它提供了多种类型的移动平均线以及一个公差参数来过滤假突破。该策略旨在捕捉价格趋势的转折点,实现趋势跟踪。

策略原理

该策略以价格收盘价为基础,计算出长度为N的移动平均线。典型的移动平均线类型有简单移动平均线(SMA)、指数移动平均线(EMA)、加权移动平均线(WMA)等。然后设定一个公差水平,比如5%,并计算出上轨(移动平均线的1.05倍)和下轨(移动平均线的0.95倍)。当价格收盘价上穿上轨时,产生买入信号;当价格收盘价下穿下轨时,产生卖出信号。这样可以过滤掉部分假突破。另外,该策略提供了一个布尔参数“短线操作”,启用这个参数后,只产生卖出信号,看空使用。

策略优势

  • 利用移动平均线的趋势跟踪特性,能够有效跟踪价格走势
  • 提供多种移动平均线类型,可以灵活组合使用
  • 公差参数可以过滤假突破,避免不必要的交易
  • 可仅做空,适用于跟踪下跌趋势

策略风险

  • 移动平均线具有滞后性,可能错过价格转折点
  • 不适用于价格震荡盘整的市场环境
  • 公差参数设置不当可能过滤掉部分有效信号
  • 做空风险较大,需审慎操作

优化方向

  • 优化移动平均线的类型和长度参数
  • 测试不同的公差参数设置
  • 结合其他指标过滤信号
  • 增加仓位管理策略

总结

该策略整体来说是一个较为典型的趋势跟踪策略。它使用价格与移动平均线的关系来判断趋势,并且提供了一定的灵活性。通过参数优化和适当的信号过滤,它可以成为一个效果不错的量化策略。但需要注意控制做空的风险,避免亏损过大。

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Overview

This strategy generates buy and sell signals based on the crossing of price with a moving average. It provides various types of moving averages and a tolerance parameter to filter false breakouts. The strategy aims to capture turning points in price trends for trend following.

Strategy Logic

The strategy calculates a length N moving average based on the closing price. Typical moving average types include Simple Moving Average (SMA), Exponential Moving Average (EMA), Weighted Moving Average (WMA) etc. Then a tolerance level is set, e.g. 5%, and upper band (1.05 times moving average) and lower band (0.95 times moving average) are calculated. When closing price crosses above upper band, a buy signal is generated. When closing price crosses below lower band, a sell signal is generated. This helps filter some false breakouts. Also, a Boolean parameter "Short Only" is provided. When enabled, only sell signals are generated for shorting the market.

Advantages

  • Effectively follows price trends using moving average's trend following characteristics
  • Provides various moving average types for flexible combinations
  • Tolerance parameter helps filter false breakouts and avoid unnecessary trades
  • Can go short only, suitable for catching downward trends

Risks

  • Moving averages have lagging effect, may miss price turning points
  • Not suitable for range-bound market environments
  • Improper tolerance parameter settings may filter valid signals
  • Going short has higher risks, need prudent operations

Optimization Directions

  • Optimize moving average type and length parameters
  • Test different tolerance parameter settings
  • Add other indicators to filter signals
  • Employ position sizing strategies

Conclusion

Overall this is a typical trend following strategy. It uses the relationship between price and moving average to determine trends, with some flexibility. Through parameter optimization and proper signal filtering, it can become a decent quant strategy. But controlling downside risks when shorting is important to avoid excessive losses.

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Strategy Arguments

Argument Default Description
v_input_1 0 MA Type: HMA
v_input_2 100 Length
v_input_3_close 0 Source: close
v_input_4 false Tolerance (%)
v_input_5 false Short only

Source (PineScript)

/*backtest
start: 2023-12-26 00:00:00
end: 2024-01-25 00:00:00
period: 1h
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/
// © RafaelPiccolo

//@version=4
strategy("Price X MA Cross", overlay=true)

typ = input("HMA", "MA Type", options=["SMA", "EMA", "WMA", "HMA", "VWMA", "RMA", "TEMA"])
len = input(100, minval=1, title="Length")
src = input(close, "Source", type=input.source)
tol = input(0, minval=0, title="Tolerance (%)", type=input.float)
shortOnly = input(false, "Short only")

tema(src, len)=>
    ema1 = ema(src, len)
    ema2 = ema(ema1, len)
    ema3 = ema(ema2, len)
    return = 3 * (ema1 - ema2) + ema3

getMAPoint(type, len, src)=>
    return = type == "SMA" ? sma(src, len) : type == "EMA" ? ema(src, len) : type == "WMA" ? wma(src, len) : type == "HMA" ? hma(src, len) : type == "VWMA" ? vwma(src, len) : type == "RMA" ? rma(src, len) : tema(src, len)

ma = getMAPoint(typ, len, src)
upperTol = ma * (1 + tol/100)
lowerTol = ma * (1 - tol/100)

longCondition = crossover(close, upperTol)
shortCondition = crossunder(close, lowerTol)

if (shortCondition)
    strategy.entry("Short", strategy.short)

if (longCondition)
    if (shortOnly)
        strategy.close("Short")
    else
        strategy.entry("Long", strategy.long)

plot(ma, "Moving Average", close > ma ? color.green : color.red, linewidth = 2)
t1 = plot(tol > 0 ? upperTol : na, transp = 70)
t2 = plot(tol > 0 ? lowerTol : na, transp = 70)
fill(t1, t2, color = tol > 0 ? color.blue : na)

Detail

https://www.fmz.com/strategy/440090

Last Modified

2024-01-26 15:18:29