python N天擇時選股策略
- 2019 年 11 月 1 日
- 筆記
版權聲明：本文為部落客原創文章，遵循 CC 4.0 BY-SA 版權協議，轉載請附上原文出處鏈接和本聲明。
本文鏈接：https://blog.csdn.net/weixin_44580977/article/details/102317978
《海龜交易法則》中介紹了一種趨勢類的擇時策略——N日突破策略。策略的核心思想為：當天收盤價超過N1天內最高價認為上升趨勢成立，作為買入訊號；當天收盤價低於N2天內最低價格認為下跌趨勢成立，作為賣出訊號。也就是說，N日趨勢突破買入即為N日創新高買入，股價創出階段性新高或歷史新高後，一方面說明該股有資金在運作，相對比較強勢，更容易順勢而上，另一方面創新高後近期買入的投資者都有獲利，上檔的套牢盤比較少，股價上沖的阻力也較小，更容易繼續上漲。反之，N日趨勢跌破時賣出的邏輯思維一樣成立。
實現常式
# N日突破擇時策略 import pandas_datareader.data as web import pandas as pd import numpy as np import datetime import matplotlib.pyplot as plt #股票數據獲取及處理介面 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()#計算最近N1個交易日最高價 expan_max = stockdata.Close.expanding().max() stockdata['N1_High'].fillna(value=expan_max,inplace=True)#目前出現過的最大值填充前N1個nan stockdata['N2_Low'] = stockdata.Low.rolling(window=N2).min()#計算最近N2個交易日最低價 expan_min = stockdata.Close.expanding().min() stockdata['N2_Low'].fillna(value=expan_min,inplace=True)#目前出現過的最小值填充前N2個nan #收盤價超過N1最高價 買入股票持有 buy_index = stockdata[stockdata.Close > stockdata.N1_High.shift(1)].index stockdata.loc[buy_index,'signal'] = 1 #收盤價超過N2最低價 賣出股票持有 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日突破買賣訊號區間顯示 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: # 買入 skip_days = -1 start = df_stockload.index.get_loc(kl_index) plt.annotate('買入',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: # 賣出 skip_days = 0 end = df_stockload.index.get_loc(kl_index) if df_stockload.Close[end] < df_stockload.Close[start]: # 賠錢顯示綠色 plt.fill_between(df_stockload.index[start:end], 0, df_stockload.Close[start:end], color='green', alpha=0.38) else: # 賺錢顯示紅色 plt.fill_between(df_stockload.index[start:end], 0, df_stockload.Close[start:end], color='red', alpha=0.38) plt.annotate('賣出',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"華勝天成 N日突破擇時") plt.show() """ #買/賣時間 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 """
輸出
總結
介紹了N日突破擇時策略的實現，需要說明的是該策略中並未考慮風險因素、設定止損機制、倉位分配機制，並且也忽略了手續費，僅作為入門研究參考
