Les Cahiers de Recherche - HEC Paris
ROCKINGER Michael and URGA Giovanni
A Time Varying Parameter Model to Test for Predictability and Integration in Stock Markets of Transition Economies
Abstract: This paper introduces a model, based on the Kalman filter
framework, which allows for latent factors, time varying parameters, and a
general GARCH structure for the residuals, extending the Bekaert and Harvey
(1997) model. With this extension it is possible to test if an emerging
stock market becomes more efficient over time and more integrated with
other already established markets.
We apply this models to the Czech,
Polish, Hungarian, and Russian stock markets. We use data at daily
frequency running from April 7th 1994 to July 10th 1997. We show that those
markets have a rather heterogeneous pattern with regard to seasonalities
and exhibit significant asymmetric GARCH effects where bad news generate
greater volatility. In Hungary good news, instead, generate greater
volatility leads us to formulate a liquidity hypothesis.
factor captures macroeconomic expectations. Concerning predictability,
measured with time varying autocorrelations, Hungary reached efficiency
before 1994. Russia shows signs of ongoing convergence towards efficiency.
For Poland and the Czech Republic we find no improvements. With regard to
market integration there is evidence that the importance of Germany has
changed over time for all markets. Shocks in the UK are positively related
to the Czech and Polish market but neither with the Russian nor the
Hungarian ones. Shocks in the US have no impact on these markets but
Russia. A strong negative correlation between Russia and the US and Germany
tends to disappear.
Keywords: Central and Eastern Europe; stock indices; predictability; market integration; (follow links to similar papers)
JEL-Codes: C22; G14; G15; (follow links to similar papers)
40 pages, January 2, 1998
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