We tested different GARCH models in modeling the volatility of stock returns in London Stock Exchange. The monthly returns of FTSE All Share Index during the period of February 1965 and October 2002 and GARCH, TGARCH, EGARCH, and AGARCH models have been used for the analysis.

This study demonstrates the existence of economically significant information spillovers between stock markets and markets for shipping freight by sea. Using multivariate correlation models on the returns of the Dow Jones Industrial Average (DJIA) and the Baltic Dry Index (BDI), we find mutual...

The volatility of financial instruments is rarely constant, and usually varies over time. This creates a phenomenon called volatility clustering, where large price movements on one day are followed by similarly large movements on successive days, creating temporal clusters. The GARCH model,...

Appropriate modeling of the process of volatility has implications for portfolio selection, the pricing of derivative securities and risk management. Further, a large body of research has suggested that both long memory and structural changes simultaneously characterize the structure of...

We propose a two-step local polynomial and a weighted bootstrapped estimator for the parameter functions of a time varying GARCH(p,q) model. We also suggest a test statistic for testing the constancy of parameter functions of the model. Asymptotic distributions of the estimators and a test...