变化速率ROC的python实现过程
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# Rate of Change code
# Load the necessary packages and modules
import pandas as pd
import pandas.io.data as web
import matplotlib.pyplot as plt
# Rate of Change (ROC)
def ROC(data,n):
N = data['Close'].diff(n)
D = data['Close'].shift(n)
ROC = pd.Series(N/D,name='Rate of Change')
data = data.join(ROC)
return data
# Retrieve the NIFTY data from Yahoo finance:
data = web.DataReader('^NSEI',data_source='yahoo',start='6/1/2015',end='1/1/2016')
data = pd.DataFrame(data)
# Compute the 5-period Rate of Change for NIFTY
n = 5
NIFTY_ROC = ROC(data,n)
ROC = NIFTY_ROC['Rate of Change']
# Plotting the Price Series chart and the Ease Of Movement below
fig = plt.figure(figsize=(7,5))
ax = fig.add_subplot(2, 1, 1)
ax.set_xticklabels([])
plt.plot(data['Close'],lw=1)
plt.title('NSE Price Chart')
plt.ylabel('Close Price')
plt.grid(True)
bx = fig.add_subplot(2, 1, 2)
plt.plot(ROC,'k',lw=0.75,linestyle='-',label='ROC')
plt.legend(loc=2,prop={'size':9})
plt.ylabel('ROC values')
plt.grid(True)
plt.setp(plt.gca().get_xticklabels(), rotation=30)
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