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Rolling betas for multiple regression WITHOUT data analysis

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    Rolling betas for multiple regression WITHOUT data analysis

    Hi, as the title suggests, I'm looking to calculate rolling betas from a multiple regression for multiple variables. I'd like to subsequently translate those to standardized figures so that they can be converted to a percentage and charted (i'm not posting for that reason at this point). I'm really just looking at how best to construct the rolling betas piece. I've attached a sample workbook. I'd like to regress column G against columns B-F on a rolling basis. For starters I'm using last 20 trading days, rolling. Does anybody have a good idea as to how I might be able to do this?

    Thanks for the help.
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    Re: Rolling betas for multiple regression WITHOUT data analysis

    In I27 and copy across and down,

    (deleted -- see post #5)
    Last edited by shg; 01-25-2018 at 04:18 PM.
    Entia non sunt multiplicanda sine necessitate

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    Re: Rolling betas for multiple regression WITHOUT data analysis

    hi, thanks for the suggestion.

    I'm actually looking to calculate the betas for each individual variable, conditional on the other variables being included in the model, similar to the way in which data analysis does it. The only issue is I'm trying to create rolling figures that I can chart and as such am unable to use the data analysis toolpak.

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    Forum Expert shg's Avatar
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    Re: Rolling betas for multiple regression WITHOUT data analysis

    I can't parse that, sorry.

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    Re: Rolling betas for multiple regression WITHOUT data analysis

    My prior post is incorrect:

    H
    I
    J
    K
    L
    M
    N
    O
    26
    Var(IXM)
    Beta(IXM, MS702789)
    Beta(IXM, MS705973)
    Beta(IXM, MS139133)
    Beta(IXM, MS129788)
    Beta(IXM, MS703025)
    27
    0.000273
    87%
    90%
    69%
    80%
    81%
    H27 and down: =VAR.S(G8:G27)
    28
    0.000285
    85%
    93%
    67%
    79%
    78%
    I27 and across and down: =COVARIANCE.S($G8:$G27, B8:B27) / $H27
    29
    0.000283
    86%
    94%
    67%
    80%
    77%
    30
    0.000287
    83%
    93%
    64%
    76%
    73%
    31
    0.000259
    83%
    94%
    65%
    77%
    76%

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