Conference on “Banking, Finance, Money and Institutions: The Post Crisis Era” to be held at the University of Surrey, Guildford, Surrey, UK.

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Dr Ekaterini Panopoulou from Kent Business School will present a working paper entitled “Hedge fund return predictability; To combine forecasts or combine information?” at the Conference on “Banking, Finance, Money and Institutions: The Post Crisis Era” to be held at the University of Surrey, between the 2nd and 3rd November 2013.

The conference is jointly organised by the Centre for Money, Banking & Institutions (University of Surrey, UK) and the Centre for Research in contemporary Finance (Fordham University, USA). It aims to provide a forum for debate among researchers and policy makers from around the world on the performance of banking and financial markets, financial stability and risk management, and the monetary, regulatory and institutional environment, in light of the recent financial crisis. Keynote Speakers include Anthony Saunders (New York University, USA) and Hans Degryse (University of Leuven, Belgium & Tilburg University, Netherlands).

Dr Ekaterini Panopoulou from Kent Business School will present a working paper entitled “Hedge fund return predictability; To combine forecasts or combine information?”

While the majority of the predictability literature has been devoted to the predictability of traditional asset classes, the literature on the predictability of hedge fund returns is quite scanty. This is rather awkward since hedge funds have attracted much interest not only for their ability to generate relatively high average returns, but also for the large losses that they can incur. We consider various combining methods (CF) ranging from simple averaging schemes to more sophisticated ones, such as discounting forecast errors, cluster combining and principal components combining. Our second approach combines information (CI) by applying the Kitchen Sink, Lasso, Ridge, and Elastic Net regressions, pre-testing and bootstrap aggregating (bagging). Our findings suggest that combining forecasts performs better than combining information. An aggressive portfolio aiming at maximizing expected returns constructed on the basis of simple combining schemes (mean, median, trimmed mean) leads to significant benefits when compared to the naive equally-weighted portfolio and the benchmark HFR fund of hedge funds.

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