Fund-of-funds (FoF) managers face the task of selecting a (relatively) small number of hedge funds from a large universe of candidate funds. We analyse whether such a selection can be successfully achieved by looking at the track records of the available funds alone, using advanced statistical...

In this paper, we extend the semi-nonparametric (SNP) densities of León, Mencía and Sentana (2009) through time-varying (TV) volatility, skewness and kurtosis. We derive some parametric properties, the conditional expected shortfall, quantiles and partial moments. We obtain closed-form...

We argue that the practise of valuing the portfolio is important for the calculation of the VaR. In particular, the seller (buyer) of an asset does not face horizontal demand (supply) curves. We propose a partially new approach for incorporating this fact in the VaR and in an empirical...

We examine the impact of temporal and portfolio aggregation on the quality of Value-at-Risk (VaR) forecasts over a horizon of ten trading days for a well-diversified portfolio of stocks, bonds and alternative investments. The VaR forecasts are constructed based on daily, weekly or biweekly...

We document a substantial increase in downside risk to US economic growth over the last 30 years. By modelling secular trends and cyclical changes of the predictive density of GDP growth, we find an accelerating decline in the skewness of the conditional distributions, with significant,...

The GARCH(1,1) model and its extensions have become a standard econometric tool for modeling volatility dynamics of financial returns and portfolio risk. In this paper, we propose an adjustment of GARCH implied conditional value-at-risk and expected shortfall forecasts that exploits the...

This paper compares multivariate and univariate GARCH models to forecast portfolio value-at-risk (VaR). We provide a comprehensive look at the problem by considering realistic models and diversified portfolios containing a large number of assets, using both simulated and real data. Moreover, we...

We introduce a flexible utility-based empirical approach to directly determine asset allocation decisions between risky and risk-free assets. This is in contrast to the commonly used two-step approach where least squares optimal statistical equity premium predictions are first constructed to...

We demonstrate that the parameters controlling skewness and kurtosis in popular equity return models estimated at daily frequency can be obtained almost as precisely as if volatility is observable by simply incorporating the strong information content of realized volatility measures extracted...