Hi all,
This question is not really R related, rather on Statistics subject itself.
Even I did not do those using R. however still I want to post it here, because
my hope is I could get help from great statisticians who are the very active
member of this group.
My problem is to interpret Variance decomposition of VAR model in layman's
language.
Using EViews I got following :
Variance Decomposition of LN_FU:
Period S.E. LN_SPOT LN_FU
1 0.024422 93.66959 6.330413
2 0.034838 94.36506 5.634938
3 0.042280 94.60712 5.392882
4 0.048540 94.30725 5.692747
5 0.054060 93.99039 6.009611
6 0.059042 93.67545 6.324554
7 0.063621 93.33405 6.665951
8 0.067885 92.99347 7.006529
9 0.071893 92.65966 7.340337
10 0.075687 92.33266 7.667341
Variance Decomposition of LN_SPOT:
Period S.E. LN_SPOT LN_FU
1 0.023745 100.0000 0.000000
2 0.033741 99.51122 0.488785
3 0.041018 99.25339 0.746605
4 0.047204 98.98354 1.016462
5 0.052660 98.62401 1.375990
6 0.057600 98.24985 1.750151
7 0.062155 97.86303 2.136970
8 0.066400 97.46197 2.538034
9 0.070394 97.05655 2.943451
10 0.074176 96.65102 3.348978
Cholesky Ordering: LN_SPOT LN_FU
Myquestion is How to interpret those result in layman language? If I
sayfollowing : "93.66959% of tomorrow's volatility in LN_FU is explainedby
LN_SPOT's today volatility and remaining 6.330413% is explained byit's today's
Volatility", is this statement correct? Then what will bethe interpretation of
remaining numbers like : 94.36506,5.634938,......etc?
And also What could be the interpretation of the SE in layman's term?
I already gone through Eviews help file however, did not get anything. If u
people here help me on this regard, I will be very very grateful.
Regards,
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