python N天择时选股策略
- 2019 年 11 月 1 日
- 筆記
版权声明：本文为博主原创文章，遵循 CC 4.0 BY-SA 版权协议，转载请附上原文出处链接和本声明。
本文链接：https://blog.csdn.net/weixin_44580977/article/details/102317978
《海龟交易法则》中介绍了一种趋势类的择时策略——N日突破策略。策略的核心思想为：当天收盘价超过N1天内最高价认为上升趋势成立，作为买入信号；当天收盘价低于N2天内最低价格认为下跌趋势成立，作为卖出信号。也就是说，N日趋势突破买入即为N日创新高买入，股价创出阶段性新高或历史新高后，一方面说明该股有资金在运作，相对比较强势，更容易顺势而上，另一方面创新高后近期买入的投资者都有获利，上档的套牢盘比较少，股价上冲的阻力也较小，更容易继续上涨。反之，N日趋势跌破时卖出的逻辑思维一样成立。
实现例程
# N日突破择时策略 import pandas_datareader.data as web import pandas as pd import numpy as np import datetime import matplotlib.pyplot as plt #股票数据获取及处理接口 def GetStockDatApi(stockName=None,stockTimeS=None,stockTimeE=None, N1=15,N2=5): stockdata = web.DataReader(stockName, "yahoo", stockTimeS, stockTimeE) stockdata['N1_High'] = stockdata.High.rolling(window=N1).max()#计算最近N1个交易日最高价 expan_max = stockdata.Close.expanding().max() stockdata['N1_High'].fillna(value=expan_max,inplace=True)#目前出现过的最大值填充前N1个nan stockdata['N2_Low'] = stockdata.Low.rolling(window=N2).min()#计算最近N2个交易日最低价 expan_min = stockdata.Close.expanding().min() stockdata['N2_Low'].fillna(value=expan_min,inplace=True)#目前出现过的最小值填充前N2个nan #收盘价超过N1最高价 买入股票持有 buy_index = stockdata[stockdata.Close > stockdata.N1_High.shift(1)].index stockdata.loc[buy_index,'signal'] = 1 #收盘价超过N2最低价 卖出股票持有 sell_index = stockdata[stockdata.Close < stockdata.N2_Low.shift(1)].index stockdata.loc[sell_index,'signal'] = 0 stockdata['signal'].fillna(method = 'ffill',inplace = True) stockdata['signal'] = stockdata.signal.shift(1) stockdata['signal'].fillna(method = 'bfill',inplace = True) return stockdata # N日突破买卖信号区间显示 skip_days = 0 df_stockload = GetStockDatApi("600410.SS",datetime.datetime(2018, 10, 1), datetime.datetime(2019, 4, 1)) print(df_stockload) df_stockload.Close.plot() for kl_index, today in df_stockload.iterrows(): if today.signal == 1 and skip_days == 0: # 买入 skip_days = -1 start = df_stockload.index.get_loc(kl_index) plt.annotate('买入',xy=(kl_index,df_stockload.Close.asof(kl_index)),xytext=(kl_index, df_stockload.Close.asof(kl_index)+2),arrowprops=dict(facecolor='r',shrink=0.1),horizontalalignment='left',verticalalignment='top') print("buy:",kl_index) elif today.signal == 0 and skip_days == -1: # 卖出 skip_days = 0 end = df_stockload.index.get_loc(kl_index) if df_stockload.Close[end] < df_stockload.Close[start]: # 赔钱显示绿色 plt.fill_between(df_stockload.index[start:end], 0, df_stockload.Close[start:end], color='green', alpha=0.38) else: # 赚钱显示红色 plt.fill_between(df_stockload.index[start:end], 0, df_stockload.Close[start:end], color='red', alpha=0.38) plt.annotate('卖出',xy=(kl_index,df_stockload.Close.asof(kl_index)),xytext=(kl_index+datetime.timedelta(days=5), df_stockload.Close.asof(kl_index)+2),arrowprops=dict(facecolor='g',shrink=0.1),horizontalalignment='left',verticalalignment='top') print("sell:",kl_index) plt.legend(loc='best') plt.title(u"华胜天成 N日突破择时") plt.show() """ #买/卖时间 buy: 2018-11-07 00:00:00 sell: 2018-11-26 00:00:00 buy: 2019-01-17 00:00:00 sell: 2019-01-22 00:00:00 buy: 2019-02-19 00:00:00 """
输出
总结
介绍了N日突破择时策略的实现，需要说明的是该策略中并未考虑风险因素、设定止损机制、仓位分配机制，并且也忽略了手续费，仅作为入门研究参考
