TIME-VARYING VOLATILITY MODELLING OF BALTIC STOCK MARKETS

Abstract

As time-varying volatility has found applications in roughly all time series modelling in economics it largely draws attention in the areas of financial markets. This study also examines the characteristics of conditional volatility in the Baltic Stock Markets (Estonia Latvia and Lithuania) by using a broad range of GARCH volatility models. Correctly forecasting the volatility leads to better understanding and managing financial market risk. Daily returns from four Baltic stock indexes are used, Estonia (TALSE index) Latvia (RIGSE index) Lithuania (VILSE index) and synthetic BALTIC benchmark index. We test a large family of GARCH models including, the basic GARCH model GARCH-in-mean model asymmetric exponential GARCH and GJR GARCH power GARCH and component GARCH model. We find strong evidence that daily returns from Baltic Stock Markets can be successfully modelled by GARCH-type models. For all Baltic markets we conclude that increased risk will not necessarily lead to a rise in the returns. All of the analysed indexes exhibit complex time series characteristics involving asymmetry long tails and complex autoregression in the returns. Results from this study are firmly recommended to financial officers and international investors.