三、建立一个简单的交易策略

大约 2 分钟

1.导入`pandas`和`matplotlib.pyplot`

import pandas as pd
import matplotlib.pyplot as plt

2. 修改股票数据并添加两列—MA10和MA50

#导入FB的股票数据，添加两列- MA10和MA50
#import FB's stock data, add two columns - MA10 and MA50
#使用dropna删除任何“非数字”数据
#use dropna to remove any "Not a Number" data
fb = pd.read_csv('data/facebook.csv',index_col=0)
fb.index=pd.to_datetime(fb.index)
fb['MA10'] = fb['Close'].rolling(10).mean()
fb['MA50'] = fb['Close'].rolling(50).mean()
fb = fb.dropna()
fb.head()

Date	Open	High	Low	Close	Adj Close	Volume	MA10	MA50
49	2015-03-13	22.559999	22.760000	22.250000	22.700001	22.116024	8982200	22.648
50	2015-03-16	22.879999	23.110001	22.730000	22.969999	22.379078	5923900	22.685
51	2015-03-17	22.920000	23.260000	22.760000	23.250000	22.651876	7497500	22.792
52	2015-03-18	23.250000	23.370001	22.660000	22.870001	22.281652	10337600	22.836
53	2015-03-19	22.950001	23.299999	22.780001	23.219999	22.622650	7768900	22.872

3.增加“股票”一栏，根据策略做出决策

#添加新列“Shares”，如果MA10>MA50，记为1(多头一股)，否则记为0(什么都不做)

fb['Shares'] = [1 if fb.loc[ei, 'MA10']>fb.loc[ei, 'MA50'] else 0 for ei in fb.index]

#添加一个新的列“利润”，使用列表推导，对于fb中的任何行，如果Shares=1，利润计算为收盘价
#明天-今天的收盘价。否则利润为0。

#画一个图表来显示利润/亏损

fb['Close1'] = fb['Close'].shift(-1)
fb['Profit'] = [fb.loc[ei, 'Close1'] - fb.loc[ei, 'Close'] if fb.loc[ei, 'Shares']==1 else 0 for ei in fb.index]
fb['Profit'].plot()
plt.axhline(y=0, color='red')

<matplotlib.lines.Line2D at 0x17825e2bc90>

4.如果我们遵循该策略，使用.cumsum()来显示模型的性能

#Use .cumsum() to calculate the accumulated wealth over the period
#使用.cumsum()计算一段时间内积累的财富

fb['wealth'] = fb['Profit'].cumsum()
fb.tail()

#plot the wealth to show the growth of profit over the period

fb['wealth'].plot()
plt.title('Total money you win is {}'.format(fb.loc[fb.index[-2], 'wealth']))

Text(0.5, 1.0, 'Total money you win is 145.72000500000001')