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趋势角度均线交叉策略Trend-Angle-Moving-Average-Crossover-Strategy.md

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Name

趋势角度均线交叉策略Trend-Angle-Moving-Average-Crossover-Strategy

Author

ChaoZhang

Strategy Description

IMG [trans]

概述

该策略通过计算均线的斜率角度,判断趋势方向,结合价格变化率指标,进行长短双向交易。其本质是利用均线斜率角度判定价格趋势,以及价格变化率指标过滤盘整行情的趋势跟踪策略。

策略原理

该策略主要基于以下指标进行判断:

  1. 均线角度:通过计算Jurik均线和指数移动平均线的斜率角度,来判断价格趋势方向。角度大于0为上涨趋势,小于0为下跌趋势。

  2. 价格变化率:计算最近12根K线的收盘价变化率,通过波动性来过滤无效信号。

当均线角度向上(大于0)且价格变化率满足条件时,做多;当均线角度向下(小于0)且价格变化率满足条件时,做空。

具体来说,策略首先计算出Jurik均线和EMA的斜率角度。然后计算出价格的变化率指标,用于过滤盘整时期。当均线角度指示趋势,且价格变化率符合条件时,产生交易信号。

优势分析

该策略具有以下优势:

  1. 利用均线斜率判断趋势非常可靠,胜率较高。

  2. 价格变化率指标可有效过滤盘整波动,避免无效交易。

  3. Jurik均线对突破做出迅速反应,EMA则提供稳定的趋势判断,两者互补。

  4. 采用长短双向交易方式,可在趋势行情中捕捉较大利润。

风险分析

该策略也存在一些风险:

  1. 价格剧烈震荡时,均线产生错误信号的概率较大。可通过优化参数降低此风险。

  2. 进入盘整时均线信号可能频繁切换,产生过多不必要交易。可加入附加过滤条件以减少无效交易。

  3. 突发事件造成价格跳空时,止损可能被击穿,可适当放宽止损点。

优化方向

该策略可从以下几个方面进行优化:

  1. 优化均线参数,寻找最佳参数组合,提高策略稳定性。

  2. 增加波动率、交易量等过滤条件,进一步减少无效交易。

  3. 结合其他指标判断止损点,使止损更加智能化。

  4. 开发自适应交易大小算法,让盈利更加平稳。

总结

该策略整体来说是非常实用的趋势跟踪策略。它利用均线斜率判断趋势非常可靠,而价格变化率指标可有效过滤无效信号。同时采用长短双向交易方式可获得较好收益。通过持续优化,该策略可以成为非常稳定可靠的量化策略。

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Overview

This strategy determines the trend direction by calculating the slope angle of moving averages, combined with price change rate indicator for long and short trading. Essentially it is a trend following strategy that uses the slope angle of moving averages to determine price trends, and the price change rate indicator to filter out range-bound market.

Strategy Logic

The strategy is mainly based on the following indicators for judgement:

  1. Moving Average Slope Angle: Calculate the slope angles of Jurik Moving Average and Exponential Moving Average to determine price trend direction. Angle greater than 0 indicates uptrend, less than 0 means downtrend.

  2. Price Change Rate: Calculate the rate of change of closing price over last 12 bars to filter signals by volatility.

When moving average slope goes up (greater than 0) and price change rate meets criteria, go long. When slope goes down (less than 0) and price change rate meets criteria, go short.

Specifically, the strategy first calculates the slope angles of Jurik MA and EMA. Then the price change rate indicator is calculated for filtering range-bound period. When both moving average slope signals trend and price change rate meets criteria, trading signal is generated.

Advantage Analysis

The advantages of this strategy:

  1. Using MA slope to determine trend is very reliable with good win rate.

  2. Price change rate indicator effectively filters ranging fluctuation to avoid invalid trades.

  3. Jurik MA gives quick response to breakout while EMA offers stable trend judgement, both complementary.

  4. Going both long and short in trending market could capture greater profit.

Risk Analysis

Some risks of this strategy:

  1. In extreme price whipsaw, MA may generate wrong signals. This can be reduced by parameter optimization.

  2. Signals may switch frequently during ranging causing unnecessary trades. Additional filter can be added.

  3. Stop loss could be broken in sudden price gap events. Wider stop loss can be used.

Optimization Directions

The strategy can be optimized in following aspects:

  1. Optimize MA parameters to find best parameter combination improving stability.

  2. Add volatility, volume filters etc. for further reducing invalid trades.

  3. Incorporate other indicators for smarter stop loss positioning.

  4. Develop adaptive position sizing algorithms for steadier profitability.

Conclusion

Overall this is a very practical trend following strategy. It reliably determines trend using MA slope angle, and effectively filters noise signals using price change rate indicator. Taking both long and short positions could gain nice profit. With continuous optimizations, this strategy can become a very stable and reliable quantitative strategy.

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Strategy Arguments

Argument Default Description
v_input_1 2017 Backtest Start Year
v_input_2 true Backtest Start Month
v_input_3 true Backtest Start Day
v_input_4 2019 Backtest Stop Year
v_input_5 12 Backtest Stop Month
v_input_6 31 Backtest Stop Day
v_input_7_ohlc4 0 source: ohlc4
v_input_8 56 v_input_8
v_input_9 12 roclength
v_input_10 2 pcntChange
v_input_11 2 Stop Loss %
v_input_12 900 Take Profit %

Source (PineScript)

/*backtest
start: 2023-12-01 00:00:00
end: 2023-12-31 23:59:59
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4
// Based on ma angles code by Duyck which also uses Everget Jurik MA calulation and angle calculation by KyJ
strategy("Trend Angle BF", overlay=false)

/////////////// Time Frame ///////////////
testStartYear = input(2017, "Backtest Start Year") 
testStartMonth = input(1, "Backtest Start Month")
testStartDay = input(1, "Backtest Start Day")
testPeriodStart = timestamp(testStartYear,testStartMonth,testStartDay, 0, 0)

testStopYear = input(2019, "Backtest Stop Year")
testStopMonth = input(12, "Backtest Stop Month")
testStopDay = input(31, "Backtest Stop Day")
testPeriodStop = timestamp(testStopYear,testStopMonth,testStopDay, 0, 0)

testPeriod() => true
    
src=input(ohlc4,title="source")

// definition of "Jurik Moving Average", by Everget
jma(_src,_length,_phase,_power) =>
    phaseRatio = _phase < -100 ? 0.5 : _phase > 100 ? 2.5 : _phase / 100 + 1.5
    beta = 0.45 * (_length - 1) / (0.45 * (_length - 1) + 2)
    alpha = pow(beta, _power)
    jma = 0.0
    e0 = 0.0
    e0 := (1 - alpha) * _src + alpha * nz(e0[1])
    e1 = 0.0
    e1 := (_src - e0) * (1 - beta) + beta * nz(e1[1])
    e2 = 0.0
    e2 := (e0 + phaseRatio * e1 - nz(jma[1])) * pow(1 - alpha, 2) + pow(alpha, 2) * nz(e2[1])
    jma := e2 + nz(jma[1])

//// //// Determine Angle by KyJ //// //// 
angle(_src) =>
    rad2degree=180/3.14159265359  //pi 
    ang=rad2degree*atan((_src[0] - _src[1])/atr(14)) 

jma_line=jma(src,10,50,1)
ma=ema(src,input(56))
jma_slope=angle(jma_line)
ma_slope=angle(ma)

///////////// Rate Of Change ///////////// 
source = close
roclength = input(12, minval=1)
pcntChange = input(2, minval=1)
roc = 100 * (source - source[roclength]) / source[roclength]
emaroc = ema(roc, roclength / 2)
isMoving() => emaroc > (pcntChange / 2) or emaroc < (0 - (pcntChange / 2))

/////////////// Strategy ///////////////
long = ma_slope>=0 and isMoving()
short = ma_slope<=0 and isMoving()

last_long = 0.0
last_short = 0.0
last_long := long ? time : nz(last_long[1])
last_short := short ? time : nz(last_short[1])

long_signal = crossover(last_long, last_short)
short_signal = crossover(last_short, last_long)

last_open_long_signal = 0.0
last_open_short_signal = 0.0
last_open_long_signal := long_signal ? open : nz(last_open_long_signal[1])
last_open_short_signal := short_signal ? open : nz(last_open_short_signal[1])

last_long_signal = 0.0
last_short_signal = 0.0
last_long_signal := long_signal ? time : nz(last_long_signal[1])
last_short_signal := short_signal ? time : nz(last_short_signal[1])

in_long_signal = last_long_signal > last_short_signal
in_short_signal = last_short_signal > last_long_signal

last_high = 0.0
last_low = 0.0
last_high := not in_long_signal ? na : in_long_signal and (na(last_high[1]) or high > nz(last_high[1])) ? high : nz(last_high[1])
last_low := not in_short_signal ? na : in_short_signal and (na(last_low[1]) or low < nz(last_low[1])) ? low : nz(last_low[1])
sl_inp = input(2.0, title='Stop Loss %') / 100
tp_inp = input(900.0, title='Take Profit %') / 100 
 
take_level_l = strategy.position_avg_price * (1 + tp_inp)
take_level_s = strategy.position_avg_price * (1 - tp_inp) 

since_longEntry = barssince(last_open_long_signal != last_open_long_signal[1]) 
since_shortEntry = barssince(last_open_short_signal != last_open_short_signal[1]) 

slLong = in_long_signal ? strategy.position_avg_price * (1 - sl_inp) : na
slShort = strategy.position_avg_price * (1 + sl_inp)
long_sl = in_long_signal ? slLong : na
short_sl = in_short_signal ? slShort : na

/////////////// Execution /////////////// 
if testPeriod()
    strategy.entry("Long",  strategy.long, when=long)
    strategy.entry("Short", strategy.short, when=short)
    strategy.exit("Long Ex", "Long", stop=long_sl, limit=take_level_l, when=since_longEntry > 0)
    strategy.exit("Short Ex", "Short", stop=short_sl, limit=take_level_s, when=since_shortEntry > 0)
    
///////////// Plotting /////////////
hline(0, title='Zero line', color=color.purple, linewidth=1)
plot(ma_slope,title="ma slope", linewidth=2,color=ma_slope>=0?color.lime:color.red)
bgcolor(isMoving() ? long ? color.green : short ? color.red : na : color.white, transp=80)
bgcolor(long_signal ? color.lime : short_signal ? color.red : na, transp=30)

Detail

https://www.fmz.com/strategy/439979

Last Modified

2024-01-25 14:35:13