Versijp, P.J.P.M. (Philippe)
http://repub.eur.nl/ppl/6536/
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RePub, Erasmus University RepositoryMultivariate Test for Stochastic Dominance efficiency of a Given Portfolio
http://repub.eur.nl/pub/14064/
Fri, 01 Jun 2007 00:00:01 GMT<div>Post, G.T.</div><div>Versijp, P.J.P.M.</div>
We develop empirical tests for stochastic dominance efficiency of a given investment portfolio relative to all possible portfolios formed from a given set of assets. Our tests use multivariate statistics, which result in superior statistical power properties compared to existing stochastic dominance efficiency tests and increase the comparability with existing mean-variance efficiency tests. Using our tests, we demonstrate that the mean-variance inefficiency of the CRSP all-share index relative to beta-sorted portfolios can be explained by tail risk not captured by variance.Advances in the Use of Stochastic Dominance in Asset Pricing
http://repub.eur.nl/pub/10033/
Thu, 10 May 2007 00:00:01 GMT<div>Versijp, P.J.P.M.</div>
In the trade-off between risk and reward, modelling risk has always been a major problem. Traditionally, both gains and losses are assumed to contribute to risk equally, and in a rather rigid manner. Stochastic Dominance (SD) frees the model of these problematic assumptions and allows for a broad range of risk measures which are selected in a non-parametric way. This thesis proposes new tests for the SD-efficiency of a given portfolio (for various orders), a test for two-fund separation, and contains empirical work based on these tests.A GMM Test for SSD Efficiency
http://repub.eur.nl/pub/1426/
Wed, 28 Jul 2004 00:00:01 GMT<div>Post, G.T.</div><div>Versijp, P.J.P.M.</div>
We develop an empirical test for Second-order Stochastic Dominance (SSD) efficiency of a given investment portfolio relative to all possible portfolios formed from a set of assets. Contrary to the Linear Programming test of Post, Thierry, 2003, Empirical tests for stochastic dominance efficiency, Journal of Finance 58, 1905—1932, our test is embedded in the Generalized Method of Moments (GMM) framework. The GMM test has superior statistical properties compared to the original LP test. Using this test, we demonstrate that the anomalous size effect can be explained with risk not captured by variance alone. However, the market portfolio remains SSD inefficient relative to value and momentum portfolios due to the overvaluation of growth stocks and past losers.