Why historical vola for short periods is almost worthless

Discussion in 'Options' started by nitro, Nov 27, 2009.

  1. nitro

    nitro

    I double checked my code and I am doing it correctly, however, somehow I pasted the wrong data.

    Try these instead:

    AdjClose 40.29
    AdjClose 41.46
    AdjClose 41.52
    AdjClose 42.71
    AdjClose 39.15
    AdjClose 40.32
    AdjClose 42.4
    AdjClose 41.23
    AdjClose 41.43
    AdjClose 41.28
    AdjClose 42.62
    AdjClose 43.21
    AdjClose 40.88
    AdjClose 37.42
    AdjClose 38.44
    AdjClose 39.16
    AdjClose 40.66
    AdjClose 41.16
    AdjClose 40.99
    AdjClose 42.64
    AdjClose 42.18
    AdjClose 41.67
    AdjClose 42.72
    AdjClose 40.9
    AdjClose 39.55
    AdjClose 40
    AdjClose 41.58

    Log returns:

    0.0566516328796593
    -0.00112464866587018
    -0.0124553412423446
    0.00794405539584352
    -0.0923003957414207
    0.0357180826020792
    0.0448330781140625
    -0.0380776381574135
    -0.006755439956649
    -0.00239521072595482
    0.0653625220831044
    0.0240440656324802
    -0.0010970928143731
    -0.00955889631376675
    0.00772772934905147
    0.0260506771999426
    0.0110105889486044
    -0.0010602580954361
    -0.015321874655079
    0.0649872534762654
    -0.00269541942167221
    -0.0111960457050852
    0.0368427469664723
    -0.0212703266615882
    -0.0570201080852208
    0.0067340321813439

    New day:

    AdjClose 41.46
    AdjClose 41.52
    AdjClose 42.71
    AdjClose 39.15
    AdjClose 40.32
    AdjClose 42.4
    AdjClose 41.23
    AdjClose 41.43
    AdjClose 41.28
    AdjClose 42.62
    AdjClose 43.21
    AdjClose 40.88
    AdjClose 37.42
    AdjClose 38.44
    AdjClose 39.16
    AdjClose 40.66
    AdjClose 41.16
    AdjClose 40.99
    AdjClose 42.64
    AdjClose 42.18
    AdjClose 41.67
    AdjClose 42.72
    AdjClose 40.9
    AdjClose 39.55
    AdjClose 40
    AdjClose 41.58
    AdjClose 41.32

    Log returns:

    0.0566516328796593
    -0.00112464866587018
    -0.0124553412423446
    0.00794405539584352
    -0.0923003957414207
    0.0357180826020792
    0.0448330781140625
    -0.0380776381574135
    -0.006755439956649
    -0.00239521072595482
    0.0653625220831044
    0.0240440656324802
    -0.0010970928143731
    -0.00955889631376675
    0.00772772934905147
    0.0260506771999426
    0.0110105889486044
    -0.0010602580954361
    -0.015321874655079
    0.0649872534762654
    -0.00269541942167221
    -0.0111960457050852
    0.0368427469664723
    -0.0212703266615882
    -0.0570201080852208
    0.0067340321813439
    0.0278666586337236
     
    #11     Nov 28, 2009
  2. nitro

    nitro

    Something is wrong with those numbers. WTF?
     
    #12     Nov 28, 2009
  3. I agree with earlier posters.

    Your new 2nd set of data has 1st log return posted twice--5.67% (should not be on 2nd set). Should be about 2% difference annulaized in this series.

    What appears odd to me, is not so much the difference in the ann HV of the two lagged sets of data, but the magnitudes of the consecutive data differences seem pretty large for a financial series.

    One reason a small sample set itself is not so great to draw conclusions, is because heteroskedasticity in small sample sets, will not be a good representation of the population.
    -------------------------------------------
    edit: seems like the data changed again.
    Series log rtns are different this time (and not correct vs. raw price data).
    Lagged series sets have about .6% diff in ann vol.
     
    #13     Nov 28, 2009
  4. nitro

    nitro

    A parentheses around the wrong function. :(

    Nothing and I mean nothing can replace unit testing.
     
    #14     Nov 28, 2009