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Neutral Data Fitting by Dr Chris Tofallis, University of Hertfordshire

With an illustration relating to investment risk.


ABSTRACT:
Suppose you are interested in estimating the slope of a line fitted to
data points. How should you fit the line if you want to treat each
variable on the same basis? Least squares regression is inappropriate here
since it's purpose is the prediction of one of the variables; furthermore
it provides a different slope estimate if the variables are switched. I
shall present a method which gives a unique slope and line, and which is
invariant to changes in units of measurement. This neutral fitting method
is also of use if one is estimating scientific law-like relationships. The
extension to multiple variables will also be discussed.

By way of illustration I apply the method to the estimation of beta in
finance. An investment that has a beta exceeding unity is classified as
'aggressive', whereas a value below unity classifies it as 'defensive'.
More generally, beta values are used to rank investments for risk
purposes. We use real data to illustrate the changes in risk rankings that
are implied by our estimator. We find that formerly defensive single
stocks generally need to be re- classified as aggressive.


Speaker(s):

Dr Chris Tofallis | talks

 

Date and Time:

19 May 2004 at 4:30 pm

Duration:

1 hour 30 minutes

 

Venue:

Middlesex University Business School
The Burroughs
Hendon
London
NW4 4BT
02084116825
http://www.mdx.ac.uk

More at Middlesex University Business School...

 

Tickets:

None

Available from:

No purchase necessary, however, please email to book a place:
M.Lane@mdx.ac.uk

Additional Information:

BRIEF BIOGRAPHY
Dr. Christopher Tofallis is a senior lecturer in the Department of
Statistics, Economics, Accounting and Management Systems at the
University of Hertfordshire Business School. He holds degrees in
physics, operational research (LSE), and applied mathematics
(Queen Mary). He has published papers in the areas of
performance measurement using DEA (data envelopment
analysis), chaos theory, maximum correlation model building, and
neutral data fitting. His over-arching interest is in developing
quantitative methods which have broad application.

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