The subject of unobservable variables encompasses this thesis. These latent (i.e., unobservable) variables must be inferred using statistical models or observable proxies. The objectives of my doctoral thesis are to develop and test new statistical models to infer these variables and link them...

This paper explores the evolving relationship in the volatility of sovereign yields in the European Economic and Monetary Union (EMU). To that end, we examine the behaviour for daily yields for 11 EMU countries (EMU-11), during the 2001-2010 period. In a first step, we decompose volatility in...

The purpose of the paper is to explore the relative biases in the estimation of the Full BEKK model as compared with the Diagonal BEKK model, which is used as a theoretical and empirical benchmark. Chang and McAleer show that univariate GARCH is not a special case of multivariate GARCH,...

We have examined the predictive power of GARCH model to forecast return volatility for Nifty 50 index. Realized volatility, which is the sum of intraday squared returns, is used as the proxy for the true volatility. Three models of the GARCH family have been used to forecast return volatility...

This paper examines the short-term dynamics, macroeconomic sensitivities, and longer-term trends in the variances and covariances of national equity market index daily returns for eleven countries in the Euro currency zone. We modify Colacito, Engle and Ghysel's Mixed Data Sampling Dynamic...

In recent years, portfolio flows to emerging markets have become increasingly large and volatile. Using weekly portfolio fund flows data, the paper finds that their short-run dynamics are driven mostly by global “push” factors. To what extent do these cross-border flows and global risk...

This paper investigates the time-varying impact of oil price uncertainty on stock prices in China using weekly data on ten sectoral indices over the period January 1997-Febraury 2014. The estimation of a bivariate VAR-GARCH-in-mean model suggests that oil price volatility affects stock returns...

We compare two EGARCH models, which belong to a new class of models in which the dynamics are driven by the score of the conditional distribution of the observations. Models of this kind are called dynamic conditional score (DCS) models and their form facilitates the development of a...

This paper investigates the time-varying impact of oil price uncertainty on stock prices in China using weekly data on ten sectoral indices over the period January 1997-February 2014. The estimation of a bivariate VAR-GARCH-in-mean model suggests that oil price volatility affects stock returns...