变化速率ROC的python实现过程

quant001

OC(Price Rate of Change)又称变动率指标，乃以今天的收盘价比较其N天前的收盘价的差除以N天前的收盘（本质其实是N日K线的涨幅），以比率表示之，此指标经由Gerald Apple 和 Fred Hitschler 两人于”Stock Market Trading Systems”一书中介绍，采用12天及25天周期可达到相当的效果。

计算公式

(close-ref(close,N))/ref(close,N)*100

1. # Rate of Change code
   
2. 
   
3. # Load the necessary packages and modules
   
4. import pandas as pd
   
5. import pandas.io.data as web
   
6. import matplotlib.pyplot as plt
   
7. 
   
8. # Rate of Change (ROC)
   
9. def ROC(data,n):
   
10. N = data['Close'].diff(n)
    
11. D = data['Close'].shift(n)
    
12. ROC = pd.Series(N/D,name='Rate of Change')
    
13. data = data.join(ROC)
    
14. return data
    
15. 
    
16. # Retrieve the NIFTY data from Yahoo finance:
    
17. data = web.DataReader('^NSEI',data_source='yahoo',start='6/1/2015',end='1/1/2016')
    
18. data = pd.DataFrame(data)
    
19. 
    
20. # Compute the 5-period Rate of Change for NIFTY
    
21. n = 5
    
22. NIFTY_ROC = ROC(data,n)
    
23. ROC = NIFTY_ROC['Rate of Change']
    
24. 
    
25. # Plotting the Price Series chart and the Ease Of Movement below
    
26. fig = plt.figure(figsize=(7,5))
    
27. ax = fig.add_subplot(2, 1, 1)
    
28. ax.set_xticklabels([])
    
29. plt.plot(data['Close'],lw=1)
    
30. plt.title('NSE Price Chart')
    
31. plt.ylabel('Close Price')
    
32. plt.grid(True)
    
33. bx = fig.add_subplot(2, 1, 2)
    
34. plt.plot(ROC,'k',lw=0.75,linestyle='-',label='ROC')
    
35. plt.legend(loc=2,prop={'size':9})
    
36. plt.ylabel('ROC values')
    
37. plt.grid(True)
    
38. plt.setp(plt.gca().get_xticklabels(), rotation=30)
    

复制代码