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Simple formula for calculating R-Squared between 2 stocks
Hello Experts, I'm a Delphi programmer writing a bit of a financial analysis program for myself and I'm having trouble with the calculation of R-Squared between the daily closing prices of 2 financial instruments. I thought I found a good formula on the net for doing it, but it doesn't yield sensible results. I'm no advanced statistics experts, but doesn't R-Squared have to be a value between 0 and 1? The formula I used yields values like 7.11 and 10.67... not making much sense. Here is the formula:
RSquared = (Covariance (x,y) * Covariance (x,y)) / (Variance(x) * Variance(y))
Could anyone offer any help please?
Thanks!
Shawn
RSquared = (Covariance (x,y) * Covariance (x,y)) / (Variance(x) * Variance(y))
Could anyone offer any help please?
Thanks!
Shawn
Asked:
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2 Solutions
Thanks Fred, yes I've come across that too on the net that the r-squared is no more than the Correlation Coefficient squared. That's simple enough - I'm already calculation correctly the Correlation Coefficient... but on some sites it describes r-squared differently and gives a different calculation. It's said that r-squared indicates of the "reliability" of the correlation coefficient... but to me, simply taking the CorrCoef and squaring it doesn't really offer any more insight. So I guess I'm just a little confused...
Thanks
Shawn
P.S: I'm not sure what you mean by "This much tracks"...?
Thanks
Shawn
P.S: I'm not sure what you mean by "This much tracks"...?
I meant by "this much tracks" is that we agree on terms as I've re-stated them.
But how in the world do you get the numbers you get? You haven't revealed the expressions being used. That does *not* track.
But how in the world do you get the numbers you get? You haven't revealed the expressions being used. That does *not* track.
Well Fred, googling around some time ago, here was a formula for RSquared I found in a financial analyiss article - so I figured it was what I wanted:
StockRsquared := Sqr(Covariance(x,y)) / ( Sqr(StdDev(x)) * Sqr(StdDev(y)));
That's the one that yielded the crazy numbers. But really - if RSquared is nothing more than Correlation Coefficient (...which I'm already calculating) squared, then I don't think I'm going to bang my head against the wall about this any more!
Thanks
Shawn
StockRsquared := Sqr(Covariance(x,y)) / ( Sqr(StdDev(x)) * Sqr(StdDev(y)));
That's the one that yielded the crazy numbers. But really - if RSquared is nothing more than Correlation Coefficient (...which I'm already calculating) squared, then I don't think I'm going to bang my head against the wall about this any more!
Thanks
Shawn
Then I guess we might look at some real numbers because the correlation coefficient can't be greater than 1.0 in magnitude. I don't see anything wrong with the expressions.
While it may seem a bit simplisitic: Here is a web page where one can calculate some cases and envision how it should go;
http://www.socscistatistics.com/tests/pearson/Default2.aspx
While it may seem a bit simplisitic: Here is a web page where one can calculate some cases and envision how it should go;
http://www.socscistatistics.com/tests/pearson/Default2.aspx
Sometimes there are scaling factors that need to be taken into account.
When you do a help on Covariance (x,y)) and (Variance(x) in your programming language, what precisely are the equations that these functions boil down to. I just went through an exercise at work where in one language, the scaling factor were different than in a library.
When you do a help on Covariance (x,y)) and (Variance(x) in your programming language, what precisely are the equations that these functions boil down to. I just went through an exercise at work where in one language, the scaling factor were different than in a library.
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So, yes, r squared would be in the range 0 > +1.
This much tracks.
If your "formula" yields other values then one would have to know the formula and the data being put into it wouldn't one?