Using filtering techniques, spectral analysis, and Markov chain models, I document trends and cycles of factors have significantly changed over the period to December 2000 compared to the period post-January 2001. The recent weaker performance of value in the 21st century, including the value...

Linear multifactor models are of great importance in portfolio construction and risk management since they provide market dimensionality reduction, which has numerous useful implications. In particular, factor models reduce the dimensionality of the asset covariance matrix, allowing for better...

Microeconomic modeling of investors behavior in financial markets and its results crucially depends on assumptions about the mathematical shape of the underlying preference functions as well as their parameterizations. With the purpose to shed some light on the question, which preferences...

The paper proposes a framework for large-scale portfolio optimization which accounts for all the major stylized facts of multivariate financial returns, including volatility clustering, dynamics in the dependency structure, asymmetry, heavy tails, and nonellipticity. It introduces a so-called...

This paper aims to replicate the semiparametric Value-At-Risk model by Dias (2014) and to test its legitimacy. The study confirms the superiority of semiparametric estimation over classical methods such as mixture normal and Student-t approximations in estimating tail distribution of portfolios,...

Oil is perceived as a good diversification tool for stock markets. To fully understand this potential, we propose a new empirical methodology that combines generalized autoregressive score copula functions with high frequency data and allows us to capture and forecast the conditional...

What determines the risk structure of financial portfolios of German households? In this paper we estimate the determinants of the share of financial wealth invested in three broad risk classes. We employ a new econometric approach - the so called fractional multinomial logit model - which...

We solve for the optimal portfolio allocation in a setting where both conditional correlation and theclustering of extreme events are considered. We demonstrate that there is a substantial welfare loss indisregarding tail dependence, even when dynamic conditional correlation has been accounted...

The use of mixture distributions for modeling asset returns has a long history in finance. New methods of demonstrating support for the presence of mixtures in the multivariate case are provided. The use of a two-component multivariate normal mixture distribution, coupled with shrinkage via a...

It is well known that non-normality plays an important role in asset and risk management. However, handling a large number of assets has long been a challenge due to the curse of dimensionality. We describe a statistical technique, which we call Moment Component Analysis (MCA), that extends...