问具有3个输入和3个输出的pandas.rolling_apply()

EN

def calculate_hedgeratio(df, xsymbol, ysymbol):

    import pandas
    from scipy import odr
    import numpy

    regression = pandas.ols(x=df[xsymbol], y=df[ysymbol])
    m = regression.beta[0]
    n = regression.beta[1]
    model = odr.Model(lambda B,x: (B[0]*x + B[1]))
    data = odr.RealData(df[xsymbol].values,df[ysymbol].values, sx=numpy.std(df[xsymbol].values), sy=numpy.std(df[ysymbol].values))
    myodr = odr.ODR(data, model, beta0=[m, n])
    myoutput = myodr.run()
    results = [myoutput.beta[0], myoutput.beta[1], myoutput.res_var]
    return results

def simple_Spreadtest(symbol1, symbol2, startdate, enddate, lookbackperiod):
    import pandas
    import numpy

    df=pandas.DataFrame()
    df[symbol1]=numpy.random.rand(1000)
    df[symbol2]=numpy.random.rand(1000)
    df['m','n','Chired'] = pandas.rolling_apply(df,lookbackperiod, lambda x: calculate_hedgeratio(x, symbol1, symbol2))

    return df

'Main Code:'


symbol1 = 'A'   
symbol2 = 'B' 
lookbackperiod = 250
import datetime
startdate = datetime.datetime(1990, 1, 1)
enddate = datetime.datetime(2015, 7, 31)

df = simple_Spreadtest(symbol1, symbol2, startdate, enddate, lookbackperiod)