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...

This study presents a survey on the current methodologies employed in the asset allocation industry. We review techniques from Modern Portfolio Theory and focus on the central role of the mean-variance optimization problem. The formalism of the Black-Litterman model is discussed with its...

It is well known that strategies that allow investors to allocate their wealth using return and volatility forecasts, the use of which are termed market and volatility timing, are of significant value. In this paper, we show that distribution timing, defined here as the ability to use forecasts...

We propose a novel dynamic approach to forecast the weights of the global minimum variance portfolio (GMVP). The GMVP weights are the population coefficients of a linear regression of a benchmark return on a vector of return differences. This representation enables us to derive a consistent loss...

We study the intra-horizon value at risk (iVaR) in a general jump diffusion setup and propose a new model of asset returns called displaced mixed-exponential model, which can arbitrarily closely approximate finite-activity jump-diffusions and completely monotone Levy processes. We derive...

We provide examples of pitfalls for parametric portfolio policies as introduced by Brandt, Santa Clara and Valkanov. For the leading case of constant relative risk aversion (CRRA) strong assumptions on the properties of the returns, the variables used to implement the parametric portfolio policy...

We provide examples of pitfalls for parametric portfolio policies as introduced by Brandt, Santa Clara and Valkanov (RFS 2009). For the leading case of constant relative risk aversion (CRRA) strong assumptions on the properties of the returns, the variables used to implement the parametric...

Value-at-Risk (VaR) forecasting generally relies on a parametric density function of portfolio returns that ignores higher moments or assumes them constant. In this paper, we propose a new simple approach to estimation of a portfolio VaR. We employ the Gram-Charlier expansion (GCE) augmenting...

Three concepts: stochastic discount factors, multi-beta pricing and mean-variance efficiency, are at the core of modern empirical asset pricing. This chapter reviews these paradigms and the relations among them, concentrating on conditional asset-pricing models where lagged variables serve as...

In the paper we introduce an empirical approximation of the log-optimal investment strategy that guarantees an almost optimal growth rate of investments. The proposed strategy also considers the effects of portfolio rearrangement costs on growth optimality and advises a suboptimal portfolio for...