python3 编写K线技术指标

╰+哭是因爲堅強的太久メ 2022-12-22 14:29 111阅读 0赞

#!encoding=utf8
    
    import pandas as pd
    
    class AppliedPrice:
        open = 'open'
        close = 'close'
        high = 'high'
        low = 'low'
    
    
    def iSMA(rates_frame, sma_period, applied_price):
        """简单移动平均线技术指标
        Args:
            rates_frame (pandas.DataFrame): pandas.DataFrame 价格数据
            sma_period (int): 平均线计算周期
            applied_price (string): 价格或处理器类型, AppliedPrice 中的枚举值
        return:
            rates_frame (pandas.DataFrame) 价格数据，简单移动平均线数据
        """
        print('开始计算SMA{0}'.format(sma_period))
        rates_frame['SMA{0}'.format(sma_period)] = rates_frame[applied_price].rolling(sma_period, min_periods=sma_period).mean()  
        return rates_frame
    
    def iEMA(rates_frame, ema_period, applied_price):
        """指数移动平均线技术指标
        Args:
            rates_frame (pandas.DataFrame): pandas.DataFrame 价格数据
            ema_period (int): 平均线计算周期
            applied_price (string): 价格或处理器类型, AppliedPrice 中的枚举值
        return:
            rates_frame (pandas.DataFrame) 价格数据，指数移动平均线数据
        """
        print('开始计算EMA{0}'.format(ema_period))
        rates_frame['EMA{0}'.format(ema_period)] = rates_frame[applied_price].ewm(ema_period, span=ema_period).mean()  
        return rates_frame
    
    def iBands(rates_frame, bands_period, deviation, applied_price):
        """保力加通道技术指标, 布林带
        Args:
            rates_frame (pandas.DataFrame): pandas.DataFrame 价格数据
            bands_period (int): 平均线计算周期
            deviation (int): 标准差数
            applied_price (string): 价格或处理器类型, AppliedPrice 中的枚举值
        return:
            rates_frame (pandas.DataFrame) 价格数据，布林带数据
        """
        print('开始计算 ibands {0}, {1}'.format(bands_period, deviation))
        # 计算均线
        rates_frame['median'] = rates_frame[applied_price].rolling(bands_period, min_periods=bands_period).mean()  
        # 计算上轨、下轨道
        rates_frame['std'] = rates_frame[applied_price].rolling(bands_period, min_periods=bands_period).std(ddof=0)  # ddof代表标准差自由度
        rates_frame['upper'] = rates_frame['median'] + deviation * rates_frame['std']
        rates_frame['lower'] = rates_frame['median'] - deviation * rates_frame['std']
    
        return rates_frame

github源码：[https://github.com/lvhaiyang/python-mt5][https_github.com_lvhaiyang_python-mt5]

[https_github.com_lvhaiyang_python-mt5]: https://github.com/lvhaiyang/python-mt5