Work detail

Volatility Spillovers in New Member States: A Bayesian Model

Author: Mgr. Janhuba Radek
Year: 2013 - summer
Leaders: prof. Roman Horváth Ph.D.
Consultants:
Work type: Doctoral
Language: English
Pages: 76
Awards and prizes:
Link:
Abstract: Volatility spillovers in stock markets have become an important phenomenon, especially in times of
crises. Mechanisms of shock transmission from one market to another are important for the international
portfolio diversification. Our thesis examines impulse responses and variance decomposition of main
stock indices in emerging Central European markets (Czech Republic, Poland, Slovakia and Hungary) in
the period of January 2007 to August 2009. Two models are used: A vector autoregression (VAR) model
with constant variance of residuals and a time varying parameter vector autoregression (TVP-VAR)
model with a stochastic volatility. Opposingly of other comparable studies, Bayesian methods are used
in both models. Our results confirm the presence of volatility spillovers among all markets. Interestingly,
we find significant opposite transmission of shocks from Czech Republic to Poland and Hungary,
suggesting that investors see the Central European exchanges as separate markets.

Partners

Deloitte

Sponsors

CRIF
McKinsey
Patria Finance