Re: equity curving

["Daniel Posmik" <daniel.posmik@xxxxxx>]

Hi

I hope you will understand this:
Chande wrote in his book:
"We will use linear regression analysis to determine smoothness. One of the
outputs of linear regression analysis is the residual sum squares (RSS). RSS
is the sum of the squared vertical distance between the actual data and the
fitted regression line at each point. The next step is to divide the BSS by
the number of data points minus two, and then to take the square root, to
calculate the standard error. The standard error measures the smoothness. If
all the points fall exactly on the best fit linear regression line, then RSS
is automatically zero, and the standard error is also zero, for the ultimate
smoothness in an equity curve."

Regards

----- Original Message -----
From: "c" <camacazi@xxxxxxxxxxx>
To: "Daniel Posmik" <daniel.posmik@xxxxxx>; "omega-list@xxxxxxx com"
<omega-list@xxxxxxxxxx>
Sent: Tuesday, November 11, 2003 6:51 AM
Subject: RE: equity curving


> Hi All
>
> i have decided to impliment the sugestion below into my anlysis
> .......ummmmmmm but i dont know how to do the "slope of regression line"
> thingo.... Anybody got any ideas?
>
> Cheers
> Cameron
>
> -----Original Message-----
> From: Daniel Posmik [mailto:daniel.posmik@xxxxxx]
> Sent: Wednesday, November 05, 2003 1:51 AM
> To: c; omega-list@xxxxxxx com
> Subject: Re: equity curving
>
>
> Hi Cameron
>
> Tushar Chande described in his book a method to compare the
> "smoothness" of equity curves.  First you have to calculate the
> slope of the regression line of the equity curve.  Then you must
> calculate the average distance of equity points from that
> regression line.  He calls this "Standard Error". Last you devide
> slope/ Standard Error. The higher the value the smoother your
> equity curve.... 
>
> Regards
> Daniel