Work detail

Analysis of Interdependencies among Central European Stock Markets

Author: Mgr. Mašková Jana
Year: 2012 - winter
Leaders: doc. PhDr. Jozef Baruník Ph.D.
Consultants:
Work type: Doctoral
Language: English
Pages: 86
Awards and prizes:
Link:
Abstract: The objective of the thesis is to examine interdependencies among the stock markets
of the Czech Republic, Hungary, Poland and Germany in the period 2008-2010. Two main
methods are applied in the analysis. The first method is based on the use of high-frequency
data and consists in the computation of realized correlations, which are then modeled using
the heterogeneous autoregressive (HAR) model. In addition, we employ realized bipower
correlations, which should be robust to the presence of jumps in prices. The second method
involves modeling of correlations by means of the Dynamic Conditional Correlation
GARCH (DCC-GARCH) model, which is applied to daily data. The results indicate that
when high-frequency data are used, the correlations are biased towards zero (the so-called
“Epps effect”). We also find quite significant differences between the dynamics of the
correlations from the DCC-GARCH models and those of the realized correlations. Finally,
we show that accuracy of the forecasts of correlations can be improved by combining
results obtained from different models (HAR models for realized correlations, HAR models
for realized bipower correlations, DCC-GARCH models).
Downloadable: Rigorous Thesis Mašková

Partners

Deloitte

Sponsors

CRIF
McKinsey
Patria Finance