The purpose of this thesis is to investigate different formulations of multivariate GARCH models and to apply two of the popular ones – the BEKKGARCH model and the DCCGARCH model – in evaluating the volatility of a portfolio of zero-coupon bonds. Multivariate GARCH models are considered as one of the most useful tools for analyzing and forecasting the volatility of time series when volatility f...

Financial markets are one of the most fundamental markets in any country. In the financial markets, the securities market and the foreign exchange market are sensitive sectors. These two markets are affected by fluctuations and economic cycles so reflect economic changes rapidly. Changes in the returns of one market due to arbitrage conditions during time lead to changes in the returns of other...

This paper proposes a constrained nonlinear programming view of generalized autoregressive conditional heteroskedasticity (GARCH) volatility estimation models in financial econometrics. These models are usually presented to the reader as unconstrained optimization models with recursive terms in the literature, whereas they actually fall into the domain of nonconvex nonlinear programming. Our re...

t his paper investigates the existence of possible spillover effects among four main asset markets namely foreign exchange, stock, gold, and housing markets in iran from 2002:03 to 2015:06. for this purpose, we have exploited sigma-point kalman filter (spkf) to extract the bubble component of assets prices in the aforementioned markets. then, in order to analyze the price bubbles spillover amon...

Correlations among the asset returns are the main reason for the computational and statistical complexities of the full multivariate GARCH models. We rely on the variancecorrelation separation strategy and introduce a broad class of multivariate models in the spirit of Engle’s (2002) dynamic conditional correlation models, that is univariate GARCH models are used for variances of individual ass...