Work detail

Risk factor modeling of Hedge Funds’ strategies

Author: Aleksa Radosavčević
Year: 2017 - summer
Leaders: PhDr. Michael Princ
Consultants:
Work type: Masters
MEF
Language: English
Pages: 124
Awards and prizes:
Link: https://is.cuni.cz/webapps/zzp/detail/151882/
Abstract: This thesis aims to identify main driving market risk factors of different
strategies implemented by hedge funds by looking at correlation coefficients,
implementing Principal Component Analysis and analyzing “loadings” for first
three principal components, which explain the largest portion of the variation
of hedge funds’ returns. In the next step, a stepwise regression through
iteration process includes and excludes market risk factors for each strategy,
searching for the combination of risk factors which will offer a model with the
best “fit”, based on The Akaike Information Criterion – AIC and Bayesian
Information Criterion – BIC. Lastly, to avoid counterfeit results and overcome
model uncertainty issues a Bayesian Model Average – BMA approach was
taken.
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