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DTSTART:20260329T010000
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DTSTART:20261025T010000
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DTSTART;TZID=Europe/Helsinki:20260305T100000
DTEND;TZID=Europe/Helsinki:20260305T230000
DTSTAMP:20260710T070550
CREATED:20260217T104945Z
LAST-MODIFIED:20260217T104945Z
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SUMMARY:Nathan LASSANCE (UCL- Louvain) "The Distribution of Out-of-Sample Performance of Estimated Portfolios"
DESCRIPTION:Finance-Insurance\nTime: 10.00 am\nDate:05th of March 2026\nRoom 3001 \nNathan LASSANCE (UCL- Louvain) “The Distribution of Out-of-Sample Performance of Estimated Portfolios” \nAbstract : We derive a parsimonious stochastic representation for the joint distribution of the out-of-sample mean and variance of a large class of portfolio rules that combines the sample mean-variance optimal portfolio with the sample global minimum-variance portfolio. Such a representation enables us to obtain the distributions and moments\, asymptotically and in finite samples\, of various out-of-sample performance measures\, e.g.\, return\, utility\, and Sharpe ratio. These results offer a comprehensive analytical toolkit that researchers can use to evaluate the out-of-sample performance of existing portfolio rules and to develop new portfolio rules in the future. We illustrate the potential use of these results by constructing and evaluating optimal two-fund rules under different out-of-sample performance criteria \nOrganizers:  Jean-Michel ZAKOIAN & Christian FRANCQ \n  \n
URL:https://crest.science/event/nathan-lassance-ucl-louvain-the-distribution-of-out-of-sample-performance-of-estimated-portfolios/
CATEGORIES:Finance-Insurance,Seminars
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DTSTART;TZID=Europe/Helsinki:20260305T110000
DTEND;TZID=Europe/Helsinki:20260305T120000
DTSTAMP:20260710T070550
CREATED:20260226T101149Z
LAST-MODIFIED:20260226T101149Z
UID:18836-1772708400-1772712000@crest.science
SUMMARY:Dario PALUMBO  (Université de Venise) "Multivariate Score-Driven Models for Strictly Positive Variables"
DESCRIPTION:Finance-Insurance\nTime: 11.00 am\nDate:05th of March 2026\nRoom 3001 \nDario PALUMBO (Université de Venise) “Multivariate Score-Driven Models for Strictly Positive Variables” \nAbstract :The paper presents a novel approach for the joint modelling of strictly positive time series. A new score-driven specification based on the multivariate GB2 (MGB2) distribution is introduced. The structure of the MGB2 implies that the joint moments depend on the marginal shape parameters\, so that allowing these parameters to evolve over time provides a flexible mechanism to capture time variation not only in scale but also in cross-sectional dependence. In this framework\, dynamics in a limited set of shape parameters can induce coherent movements in the implied correlation matrix\, offering a parsimonious alternative to fully parameterised correlation models. The paper also introduces a multivariate model for the logarithms of strictly positive variables\, based on the multivariate exponential GB2 (MEGB2) distribution. Estimation is equivalent to that of the MGB2 model\, but the log formulation facilitates comparison with multivariate models defined on the real line\, such as the Gaussian and Student’s t. The empirical performance of both the MGB2 and MEGB2 specifications is assessed using a dataset of realised volatilities. The results indicate that the implied dependence structure is broadly consistent with that obtained from multivariate Gaussian and t score-driven models\, while relying on a comparatively parsimonious dynamic specification as the cross-sectional dimension increases. \nOrganizers:  Jean-Michel ZAKOIAN & Christian FRANCQ \n  \n
URL:https://crest.science/event/dario-palumbo-universite-de-venise-multivariate-score-driven-models-for-strictly-positive-variables/
CATEGORIES:Finance-Insurance,Seminars
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