Work detail

Value-at-risk forecasting with the ARMA-GARCH family of models during the recent financial crisis

Author: Mgr. Ivo Jánský
Year: 2011 - winter
Leaders:
Consultants:
Work type: Finance, Financial Markets and Banking
Masters
Language: English
Pages: 123
Awards and prizes: M.A. with distinction from the Dean of the Faculty of Social Sciences for an excellent state-final examination performance.
Link:
Abstract: The thesis evaluates several hundred one{day{ahead VaR forecasting models
in the time period between the years 2004 and 2009 on data from six world
stock indices | DJI, GSPC, IXIC, FTSE, GDAXI and N225. The models model
mean using the AR and MA processes with up to two lags and variance with
one of GARCH, EGARCH or TARCH processes with up to two lags. The models
are estimated on the data from the in{sample period and their forecasting accuracy
is evaluated on the out{of{sample data, which are more volatile. The
main aim of the thesis is to test whether a model estimated on data with lower
volatility can be used in periods with higher volatility. The evaluation is based
on the conditional coverage test and is performed on each stock index separately.
Unlike other works in this eld of study, the thesis does not assume the
log{returns to be normally distributed and does not explicitly select a particular
conditional volatility process. Moreover, the thesis takes advantage of a
less known conditional coverage framework for the measurement of forecasting
accuracy.
Downloadable: Diploma Thesis of Janský

Partners

Deloitte

Sponsors

CRIF
McKinsey
Patria Finance