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making sense of 100's of funds

3 messages · Davy, Krishna Kumar, Sylvain BARTHELEMY

#
John, Sylvain and colleagues,

I find both your remarks very interesting and to contain some truth, I
have included a working paper from Angela, ea (2003). Where they use a
time varying two factor model to test for contagion. They find that in
the Asian Crisis the correlations are indeed increased however no strong
evidence is found for contagion in the Mexican crisis. Now my question
is do you think that the use of time-varying models or stochastic models
(such as a Markov VAR) can reduce risk in a crisis by switching to safer
portfolios and by switching to high risk (and hopefully high yielding)
portfolios in better times?

I'm very interested to hear your opinions,

Davy Cielen
dcielen at vub.ac.be
Student Business Engineering, 
International Master in Management Science,
Solvay Business School

Angela, Bekeart and Campbell, 2003, Market Integration and contagion,
working paper, available from http://www.nber.org/papers/w9510
#
Davy wrote:
I broadly agree with what John and others have said on this but here is 
my two centavos and this is related to the other thread on Copula 
functions. We repeatedly see that the marginal distributions are 
non-normal and there is asymmetry in the returns. e.g. Markets tank 
together but go up in a de-correlated fashion that is not quite captured 
in a correlation estimate. {Also recall Correlation(Pearson's) is a 
linear measure of dependence}

So perhaps this is the sort of thing that is best modeled using Copula 
functions with non-Gaussian marginals. Someone with a little spare time 
could perhaps back-test the performance of risk models that use other 
measure of dependence besides correlation and see how they measure up.
#
Dear Davy,

Thank you the reference article.
I have many doubts that it would be helpful, especially on emerging markets,
where the quality and availability of data is low and markets are not
liquid.

But I know that there are a lot of research on that and some of my
collegues/practitioners are trying to use this kind of time varying models
and/or extended Kalman filters to do that. I think that if these models are
very helpful to understand a stochastic process and regimes ex-post, they
are very difficult to use to elaborate scenarios ex-ante, especially in case
of switching regime (during crises and large events).



---
Sylvain Barth?l?my
Research Director, TAC
www.tac-financial.com | www.sylbarth.com


-----Message d'origine-----
De?: r-sig-finance-bounces at stat.math.ethz.ch
[mailto:r-sig-finance-bounces at stat.math.ethz.ch] De la part de Davy
Envoy??: mardi 21 ao?t 2007 19:58
??: 'R-sig-finance'
Objet?: Re: [R-SIG-Finance] making sense of 100's of funds

John, Sylvain and colleagues,

I find both your remarks very interesting and to contain some truth, I
have included a working paper from Angela, ea (2003). Where they use a
time varying two factor model to test for contagion. They find that in
the Asian Crisis the correlations are indeed increased however no strong
evidence is found for contagion in the Mexican crisis. Now my question
is do you think that the use of time-varying models or stochastic models
(such as a Markov VAR) can reduce risk in a crisis by switching to safer
portfolios and by switching to high risk (and hopefully high yielding)
portfolios in better times?

I'm very interested to hear your opinions,

Davy Cielen
dcielen at vub.ac.be
Student Business Engineering, 
International Master in Management Science,
Solvay Business School

Angela, Bekeart and Campbell, 2003, Market Integration and contagion,
working paper, available from http://www.nber.org/papers/w9510

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