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毕达哥蜡烛图MACD指标背离趋势跟踪策略Demigod-Candlestick-MACD-Divergence-Trend-Following-Strategy.md

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Name

毕达哥蜡烛图MACD指标背离趋势跟踪策略Demigod-Candlestick-MACD-Divergence-Trend-Following-Strategy

Author

ChaoZhang

Strategy Description

IMG [trans]

概述

该策略通过计算MACD指标及其MACD柱状线,检测MACD柱状线与价格走势之间的背离信号,进而产生交易信号。当检测到价格新高但MACD柱状线没有创出新高时,产生看跌背离信号;当检测到价格新低但MACD柱状线没有创出新低时,产生看涨背离信号。结合ATR指标,设置止损位和止盈位,进行趋势跟踪交易。

策略原理

该策略的核心原理是利用MACD指标及其MACD柱状线反映价格趋势变化的特性,检测MACD柱状线与价格之间的背离信号,作为交易信号的触发条件。

具体来说,策略首先计算MACD线、Signal线和MACD柱状线。然后通过定义 fractal 函数,检测 MACD柱状线 的 peak 和 valley,提取局部极大值和极小值点。再结合价格的最高价和最低价,判断 MACD柱状线 与价格之间是否存在背离。

当价格创出新高,但 MACD柱状线没有创出新高时,产生 regulark_bearish_div 看跌背离信号;当价格创出新低,但 MACD柱状线没有创出新低时,产生 regulark_bullish_div 看涨背离信号。

最后,策略在看跌背离和看涨背离信号产生时,分别发出做空和做多指令,并以 ATR 止损、止盈退出仓位。

优势分析

该策略具有以下几个优势:

  1. 利用 MACD柱状线与价格之间的背离特征,可提前捕捉到价格趋势的转变。

  2. ATR止损止盈设置合理,可有效控制单笔交易的最大亏损。

  3. 采用趋势跟踪方法,可最大限度锁住利润。

  4. 参数设置合理,可过滤掉部分噪音交易信号。

  5. 策略逻辑清晰易懂,容易实盘验证。

风险分析

该策略也存在一些风险:

  1. MACD背离不一定会带来价格的反转,存在一定的假信号风险。

  2. 止损止盈设置不合理可能导致亏损过大或利润太小。

  3. 背离信号周期偏短,可能是噪音造成,应适当过滤。

  4. 交易品种和参数设置不匹配,也会影响策略效果。

对应解决方法:

  1. 适当增大背离长度和背离幅度要求,过滤假信号。

  2. 用 ATR 作为止损止盈指标,并调整ATR 倍数,控制单笔交易风险。

  3. 针对不同交易品种选取不同参数。进行参数优化,找到最佳参数组合。

优化方向

该策略还可从以下几个方向进行优化:

  1. 更复杂的背离确认,如 Volume 背离确认。

  2. 优化 MACD 参数,寻找最佳参数组合。

  3. 优化 ATR 止损止盈的倍数。

  4. 增加机器学习算法,辅助判断背离信号的可靠性。

  5. 增加模型预测,判断价格反转概率。

  6. 根据市场环境变化,动态调整策略参数。

总结

总的来说,该毕达哥蜡烛图MACD指标背离趋势跟踪策略,利用 MACD柱状线与价格之间的背离特征,实现趋势的捕捉。ATR 止损止盈设置合理,可控制单笔交易风险。该策略逻辑清晰易懂,值得实盘检验。后续可从多方面进行策略优化,以获得更好的效果。

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Overview

This strategy calculates the MACD indicator and its MACD histogram to detect divergence signals between the MACD histogram and price movement, thereby generating trading signals. When a new high in price but no new high in MACD histogram is detected, a bearish divergence signal is generated. When a new low in price but no new low in MACD histogram is detected, a bullish divergence signal is generated. Combined with ATR indicator for stop loss and take profit, it carries out trend following trades.

Strategy Logic

The core principle of this strategy is to utilize the MACD indicator and its MACD histogram to reflect changes in price trends, and detect divergence signals between the MACD histogram and price as the trigger condition for trading signals.

Specifically, the strategy first calculates the MACD line, Signal line and MACD histogram. Then by defining the fractal function to detect peaks and valleys of the MACD histogram to extract local maximums and minimums. Combined with the highest price and lowest price, it determines whether there is a divergence between the MACD histogram and price.

When price reaches a new high but MACD histogram does not reach a new high, a regular_bearish_div bearish divergence signal is generated. When price drops to a new low but MACD histogram does not drop to a new low, a regular_bullish_div bullish divergence signal is generated.

Finally, when bearish and bullish divergence signals are generated, the strategy issues short and long orders respectively, and exits positions with ATR stop loss and take profit.

Advantage Analysis

This strategy has the following advantages:

  1. By utilizing the divergence feature between MACD histogram and price, it can capture turns in price trends early.

  2. The ATR stop loss and take profit settings are reasonable to effectively control maximum loss per trade.

  3. Using trend following method can maximize locked profit.

  4. Reasonable parameter settings filter out some noisy trading signals.

  5. The strategy logic is clear and easy to understand, easy to validate in live trading.

Risk Analysis

This strategy also has some risks:

  1. MACD divergence does not necessarily lead to price reversal, there are some false signal risks.

  2. Unreasonable stop loss and take profit settings may lead to excessive losses or insufficient profits.

  3. Divergence signals with short cycles may be caused by noise and should be filtered properly.

  4. Incompatible trading products and parameter settings will also affect strategy performance.

Corresponding solutions:

  1. Increase the length and magnitude requirements of divergence to filter false signals.

  2. Use ATR as stop loss and take profit benchmark, adjust ATR multiples to control risks per trade.

  3. Select different parameters for different trading products. Perform parameter optimization to find optimum parameter combinations.

Optimization Directions

This strategy can also be optimized in the following directions:

  1. More complex divergence confirmation, such as volume divergence confirmation.

  2. Optimize MACD parameters to find the best parameter combination.

  3. Optimize the multiples of ATR stop loss and take profit.

  4. Add machine learning algorithms to assist in judging reliability of divergence signals.

  5. Add model prediction to determine probability of price reversal.

  6. Dynamically adjust strategy parameters according to market condition changes.

Summary

In summary, this Demigod Candlestick MACD Divergence Trend Following Strategy utilizes the divergence between MACD histogram and price to capture trends. The reasonable ATR stop loss and take profit settings can control risks per trade. The strategy logic is clear and easy to understand, worth validating in live trading. Follow up optimizations can be made in many aspects to obtain better results.

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Strategy Arguments

Argument Default Description
v_input_int_1 13 (?CDMA)fast Length
v_input_int_2 34 slow Length
v_input_source_1_close 0 source: close
v_input_int_3 9 ma Length
v_input_int_4 5 (?Divergence)Divergenc Length
v_input_float_1 2 Divergenc Strength
v_input_int_5 13 (?ATR)ATR Length
v_input_float_2 true ATR multyple
v_input_color_1 teal upper color
v_input_color_2 red under color

Source (PineScript)

/*backtest
start: 2024-01-04 00:00:00
end: 2024-02-03 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © bigwin_sun
// copyright： Tradingvue Limited    

//@version = 5
strategy(title = "Demigod : CDMA histogram Divergence strategy", shorttitle = "Demigod strategy", overlay = false, pyramiding = 100)

//macd input
fastMA = input.int(13, title = "fast Length", minval = 1,     group = "CDMA")
slowMA = input.int(34, title = "slow Length", minval = 1,     group = "CDMA")
src          = input.source(title = "source", defval = close, group = "CDMA")
signalSmooth = input.int(9, title="ma Length", minval = 1,    group = "CDMA")
//Divergenc
divLength    = input.int(title = "Divergenc Length",   defval = 5, minval = 1,   maxval = 50,  inline = "ATRLength",  group = "Divergence")
divStren     = input.float(title="Divergenc Strength", defval = 2, minval = 1.0, maxval = 5.0, inline = "ATRLength",  group = "Divergence")

//atr input
atrLength = input.int(13, title = "ATR Length", minval = 1,   inline = "ATRLength", group = "ATR")
m         = input.float(1.0,  "ATR multyple",   minval = 0.5, inline = "ATRLength", group = "ATR", step = 0.5)
collong   = input.color(color.teal, title = "upper color",  inline = "ATR显示", group = "ATR")
colshort  = input.color(color.red,  title = "under color",  inline = "ATR显示", group = "ATR")

// MACD---------------------------------------------------------------------------------------------------------------------------------
DivOffset = -2
macdLine   = ta.ema(src, fastMA) - ta.ema(src, slowMA)    
signalLine = ta.ema(macdLine, signalSmooth)
histogram  = macdLine - signalLine

histogramColor = if histogram > 0
    histogram > histogram[1] ? color.lime : color.green
else 
    histogram < histogram[1] ? color.maroon : color.red

// cdma histogram
plot(histogram, title = "MACD histogram", linewidth = 2, style = plot.style_histogram, color = histogramColor)
plot(0,         title = "zero line",      linewidth = 1,                               color = color.gray)

// Divergenc calculation-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
//peak / valley fundation
f_top_fractal(_src)=>_src[4] < _src[2] and _src[3] < _src[2] and _src[2] > _src[1] and _src[2] > _src[0] and _src > 0
f_bot_fractal(_src)=>_src[4] > _src[2] and _src[3] > _src[2] and _src[2] < _src[1] and _src[2] < _src[0] and _src < 0
f_fractalize(_src)=>f_top_fractal(_src) ? 1 : f_bot_fractal(_src) ? -1 : 0

//peak / valley value
fractal_top1 = f_fractalize(histogram) > 0 ? true : false //histogram[2] : na
fractal_bot1 = f_fractalize(histogram) < 0 ? true : false //histogram[2] : na

//previouse peak or valley
high_prev1  = ta.valuewhen(fractal_top1, histogram[2], 0)[2]
high_price1 = ta.valuewhen(fractal_top1, high[2], 0)[2]
low_prev1   = ta.valuewhen(fractal_bot1, histogram[2], 0)[2]
low_price1  = ta.valuewhen(fractal_bot1, low[2], 0)[2]

//Divergenc : cdma histogram against candle value
regular_bearish_div1 = high[2] > high_price1 + divStren and histogram[2] < high_prev1 / divStren and ta.barssince(fractal_top1[1]) > divLength
regular_bullish_div1 = low[2]  < low_price1 - divStren  and histogram[2] > low_prev1 / divStren  and ta.barssince(fractal_bot1[1]) > divLength

//-------------------------cdma Divergenc range------------------------------------------------
//histogramColor
col1 = regular_bearish_div1 ? color.red : na
col2 = regular_bullish_div1 ? #00FF00EB : na
//plot
plot(title='看跌背离', series= fractal_top1 ? histogram[2] : na, color=col1, linewidth=3, offset=DivOffset)
plot(title='看涨背离', series= fractal_bot1 ? histogram[2] : na, color=col2, linewidth=3, offset=DivOffset)

// calculate ATR				--------------------------------------------------------------------------------------------------------------------------------------------------
atr = ta.ema(ta.tr(true), atrLength) * m
up = atr + high
dw = low - atr

//stratety : enrty and exit---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
if regular_bearish_div1 and fractal_top1
//if regular_bullish_div1 and fractal_bot1
    //label.new(bar_index, histogram[2], text = "Short", textcolor = color.white, color = color.gray,  style = label.style_label_lower_left)
    strategy.entry("Short", strategy.short, qty = 1)
    strategy.exit("exitShort", "Short", stop = up, limit = dw - atr)
if regular_bullish_div1 and fractal_bot1
//if regular_bearish_div1 and fractal_top1   
    //label.new(bar_index, histogram[2], text = "Long", textcolor = color.white, color = color.fuchsia, style = label.style_label_upper_left)
	strategy.entry("Long", strategy.long, qty = 1)
    strategy.exit("exitLong", "Long", stop = dw, limit = up + atr)

Detail

https://www.fmz.com/strategy/440981

Last Modified

2024-02-04 15:06:58