Re: [libreoffice-users] intercept and slope -- is there a problem?

On 06/14/2012 08:47 PM, Robert Peirce wrote:
> If I use a small amount (3 pairs) of dummy information, the intercept, 
> slope and R^2 are exactly what I expect them to be.  If I use something 
> on the order of 400 pairs it makes no sense at all.  When I use Linest, 
> the results are reasonable.
>
> I am evaluating stock trading systems against holding the market.  The 
> data pairs are the monthly percentage change in the model vs. the 
> market.  A regression produces the y-intercept (called alpha), the slope 
> (called beta) and R^2.
>
> Generally, if I know the total return for the model and the market the 
> calculation
>
>    "total model return" = "total market return" * beta + alpha
>       or
>    y = mx + b
>
> is fairly close if I get the results from linest.  They are way off from 
> intercept and slope.
>
> If the dependent variable is in A and the independent in B and there are 
> 400 pairs, I can use INTERCEPT|SLOPE(A1:A400; B1:B400).  The results 
> aren't even close and I don't know why.  Plugging the average returns 
> for the market into the equation to calculate the expected return for 
> the model produces nothing reasonable.
>
> Any ideas?  I am probably missing something really obvious.
What are your R^2 values? Near 1 indicates a high correlation between x
and y.

-- 
Jay Lozier
jslozier@gmail.com


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