五日线金叉十日测试

 

import pandas as pd
import numpy as np
import os
import matplotlib.pyplot as plt 

all_stock_data = pd.DataFrame()

stock_code_list = []
#t = os.listdir('all_stock_data')
#for i in t:
#    print(i.split('.')[0])
for root, dirs, files in os.walk('all_stock_data1'):
    if files:
        for f in files:
            if '.csv' in f:
                stock_code_list.append(f.split('.csv')[0])
for code in stock_code_list:
    print('正在计算%s'%code)
    stock_data = pd.read_csv('all_stock_data1\\'+code+'.csv',encoding='gbk')
    stock_data = stock_data[['日期','股票代码','收盘价','成交量','涨跌幅']]#.ix[:300]
    stock_data.sort_values('日期',inplace=True)

    stock_data['五叉十'] = '无'
    stock_data['五日均线'] = stock_data['收盘价'].rolling(window=5).mean()
    stock_data['十日均线'] = stock_data['收盘价'].rolling(window=10).mean()
    tiao1 = stock_data['五日均线'] > stock_data['十日均线']
    tiao2 = stock_data['五日均线'].shift() < stock_data['十日均线'].shift()
    for i in [1,2,3,5]:
        stock_data[str(i)+'日涨幅'] = (stock_data['收盘价'].shift(-i)/stock_data['收盘价'] - 1)*100

    stock_data.ix[stock_data[(tiao1==True) & (tiao2 == True)].index,'五叉十'] = '金叉'
    
    stock_data.replace(np.inf,np.nan,inplace=True)
    stock_data.dropna(how='any', inplace=True)
    stock_data = stock_data[(stock_data['五叉十'] == '金叉')]
    all_stock_data = all_stock_data.append(stock_data, ignore_index=True)

print('-------------------------------')        
print('五日线金叉十日测试：')
print('共发出%d次买出提示'%all_stock_data.shape[0])
print('-------------------------------')

for i in [1,2,3,5]:
    print('买入'+str(i)+'日后平均涨幅%f' % all_stock_data[str(i)+'日涨幅'].mean())

print(all_stock_data)