talib实现与通达信、同花顺一致的MACD、KDJ指标

最新推荐文章于 2025-05-21 16:33:27 发布

夜魔009

最新推荐文章于 2025-05-21 16:33:27 发布

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分类专栏：金融分析技术文章标签： python talib 通达信指标 MACD

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本文详细介绍了如何使用Talib库在Python中调整通达信和同花顺风格的MACD、SMA和KDJ技术指标，并提供了对应的代码示例。适合理解和定制技术指标的开发者参考。

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talib实现的MACD与国内软件厂商实现的不太一致，需要自行定义和调整。提供通达信、同花顺 MACD Talib实现。

同花顺和通达信等软件中的SMA，是KDJ_CN和RSI_CN的基础依赖

注意：使用前引用talib

首先实现SMA，然后才是其它MACD、KDJ等：

import talib
def SMA_CN(close, timeperiod):
    close = np.nan_to_num(close)
    return reduce(lambda x, y: ((timeperiod - 1) * x + y) / timeperiod, close)

import talib
def MACD_CN(close, fastperiod, slowperiod, signalperiod):
    macdDIFF, macdDEA, macd = talib.MACDEXT(close, fastperiod=fastperiod, fastmatype=1,slowperiod=slowperiod, slowmatype=1, signalperiod=signalperiod, signalmatype=1)
    macd = macd * 2
    return macdDIFF, macdDEA, macd

import talib
def RSI_CN(close, timeperiod) :
    diff = map(lambda x, y : x - y, close[1:], close[:-1])
    diffGt0 = map(lambda x : 0 if x < 0 else x, diff)
    diffABS = map(lambda x : abs(x), diff)
    diff = np.array(diff)
    diffGt0 = np.array(diffGt0)
    diffABS = np.array(diffABS)
    diff = np.append(diff[0], diff)
    diffGt0 = np.append(diffGt0[0], diffGt0)
    diffABS = np.append(diffABS[0], diffABS)
    rsi = map(lambda x : SMA_CN(diffGt0[:x], timeperiod) / SMA_CN(diffABS[:x], timeperiod) * 100, range(1, len(diffGt0) + 1) )
    
    return np.array(rsi)

import talib
def KDJ_CN(high, low, close, fastk_period, slowk_period, fastd_period):
    kValue, dValue = talib.STOCHF(high, low, close, fastk_period, fastd_period=1, fastd_matype=0)
    
    kValue = np.array(map(lambda x : SMA_CN(kValue[:x], slowk_period), range(1, len(kValue) + 1)))
    dValue = np.array(map(lambda x : SMA_CN(kValue[:x], fastd_period), range(1, len(kValue) + 1)))
    
    jValue = 3 * kValue - 2 * dValue
    
    func = lambda arr : np.array([0 if x < 0 else (100 if x > 100 else x) for x in arr])
    
    kValue = func(kValue)
    dValue = func(dValue)
    jValue = func(jValue)
    return kValue, dValue, jValue