In the first chapter, I estimate dynamic factors from the term structure of credit spreads and the term structure of equity option implied volatilities, and I provide a comprehensive characterization of the dynamic relationships among those credit spread factors and equity volatility factors. I...

This paper addresses the open debate about the usefulness of high-frequency (HF) data in large-scale portfolio allocation. Daily covariances are estimated based on HF data of the S&P 500 universe employing a blocked realized kernel estimator. We propose forecasting covariance matrices using a...

In this dissertation, I study the performance of asset-pricing models in explaining the cross section of expected stock returns. The finance literature has uncovered several potential failings of the Capital Asset Pricing Model (CAPM). I investigate the ability of additional risk factors, which...

This paper applies the Phillips and Sul (2007) method to test for convergence in stock returns to an extensive dataset including monthly stock price indices for five EU countries (Germany, France, the Netherlands, Ireland and the UK) as well as the US over the period 1973-2008. We carry out the...

The aim of the paper is to study empirically the influence of higher moments of the return distribution on conditional value at risk (CVaR). To be more exact, we attempt to reveal the extent to which the risk given by CVaR can be estimated when relying on the mean, standard deviation, skewness...

Modelling covariance structures is known to suffer from the curse of dimensionality. In order to avoid this problem for forecasting, the authors propose a new factor multivariate stochastic volatility (fMSV) model for realized covariance measures that accommodates asymmetry and long memory....

We investigate convergence in European price level, unit labor cost, income, and productivity data over the period of 1960-2006 using the non-linear time-varying coefficients factor model proposed by Phillips and Sul (2007). This approach is extremely flexible on order to model a large number of...

A standard quantitative method to access credit risk employs a factor model based on joint multivariate normal distribution properties. By extending a one-factor Gaussian copula model to make a more accurate default forecast, this paper proposes to incorporate a state-dependent recovery rate...

This paper studies the asymptotic validity of the regularized Anderson Rubin (AR) tests in linear models with large number of instruments. The regularized AR tests use informationreduction methods to provide robust inference in instrumental variable (IV) estimation for data rich environments. We...

We present a new composite leading indicator of economic activity in mainland China, estimated using a dynamic factor model.Our leading indicator is constructed from three series: exports, a real estate climate index, and the Shanghai Stock Exchange index.These series are found to share a...