174 research outputs found

    Efficient Frontier for Robust Higher-order Moment Portfolio Selection

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    This article proposes a non-parametric portfolio selection criterion for the static asset allocation problem in a robust higher-moment framework. Adopting the Shortage Function approach, we generalize the multi-objective optimization technique in a four-dimensional space using L-moments, and focus on various illustrations of a four-dimensional set of the first four L-moment primal efficient portfolios. our empirical findings, using a large European stock database, mainly rediscover the earlier works by Jean (1973) and Ingersoll (1975), regarding the shape of the extended higher-order moment efficient frontier, and confirm the seminal prediction by Levy and Markowitz (1979) about the accuracy of the mean-variance criterion.Efficient frontier, portfolio selection, robust higher L-moments, shortage function, goal attainment application.

    Au large de Martigues – Épave Bonnieu 3 (EA 414)

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    Cette premiĂšre opĂ©ration de sondage a Ă©tĂ© rĂ©alisĂ©e sur le site prĂ©sumĂ© d’un naufrage au ve s. avant notre Ăšre et avait pour objectif la dĂ©couverte de l’épave. En effet, depuis les premiers prĂ©lĂšvements en 1990 de quelques amphores et mortiers massaliĂštes, datĂ©s de façon homogĂšne du troisiĂšme quart du ve s. av. J.-C, ce site avait fait l’objet de nombreuses explorations Ă  la profondeur de 20 Ă  21 m sur un fond sableux parsemĂ© de roches. Ces recherches n’avaient jamais donnĂ© d’indice du centre ..

    Au large de Martigues – L’épave Bonnieu 3 (EA 414)

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    Cette deuxiĂšme opĂ©ration sur ce site avait pour objectif de situer l’emplacement du naufrage d’un navire au ve s. avant notre Ăšre. Ce site a livrĂ© depuis sa dĂ©couverte, vieille de plus de 20 ans, des amphores de type Bertucchi 2 et des mortiers massaliĂštes. Nous avions implantĂ© en 2014 un carroyage de 400 m2 centrĂ© sur la zone oĂč ces prĂ©lĂšvements de surface avaient Ă©tĂ© faits. Cette annĂ©e deux ateliers ont Ă©tĂ© mis en place, un de prospection dĂ©taillĂ©e et l’autre de sondages. Les prospections o..

    Au large de Martigues – Littoral

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    La mĂ©tĂ©orologie exĂ©crable de la pĂ©riode choisie pour cette prospection, caractĂ©risĂ©e par un trĂšs fort vent de nord, ne nous a absolument pas permis d’accĂ©der aux sites situĂ©s en mer, mis Ă  part un situĂ© Ă  la sortie du port de Carro. Nous avons donc consacrĂ© l’essentiel de nos plongĂ©es Ă  ce site ainsi qu’à celui situĂ© au nord de Tholon dans l’étang de Berre. Un nouveau site a Ă©tĂ© dĂ©couvert Ă  l’intĂ©rieur du port de Carro en fin de pĂ©riode et nous avons pu y consacrer deux journĂ©es. Enfin nous a..

    High Watermarks of Market Risks

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    We present several estimates of measures of risk amongst the most well-known, using both high and low frequency data. The aim of the article is to show which lower frequency measures can be an acceptable substitute to the high precision measures, when transaction data is unavailable for a long history. We also study the distribution of the volatility, focusing more precisely on the slopee of the tail of the various risk measure distributions, in order to define the high watermarks of market risks. Based on estimates of the tail index of a Generalized Extreme Value density backed-out from the high frequency CAC 40 series in the period 1997-2006, using both Maximum Likelihood and L-moment Methods, we, finally find no evidence for the need of a specification with heavier tails than in the case of the traditional log-normal hypothesis.Financial crisis, volatility estimators distributions, range-based volatility, extreme value, high frequency data.

    A Risk Management Approach for Portfolio Insurance Strategies

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    Controlling and managing potential losses is one of the main objectives of the Risk Management. Following Ben Ameur and Prigent (2007) and Chen et al. (2008), and extending the first results by Hamidi et al. (2009) when adopting a risk management approach for defining insurance portfolio strategies, we analyze and illustrate a specific dynamic portfolio insurance strategy depending on the Value-at-Risk level of the covered portfolio on the French stock market. This dynamic approach is derived from the traditional and popular portfolio insurance strategy (Cf. Black and Jones, 1987 ; Black and Perold, 1992) : the so-called "Constant Proportion Portfolio Insurance" (CPPI). However, financial results produced by this strategy crucially depend upon the leverage - called the multiple - likely guaranteeing a predetermined floor value whatever the plausible market evolutions. In other words, the unconditional multiple is defined once and for all in the traditional setting. The aim of this article is to further examine an alternative to the standard CPPI method, based on the determination of a conditional multiple. In this time-varying framework, the multiple is conditionally determined in order to remain the risk exposure constant, even if it also depends upon market conditions. Furthermore, we propose to define the multiple as a function of an extended Dynamic AutoRegressive Quantile model of the Value-at-Risk (DARQ-VaR). Using a French daily stock database (CAC 40) and individual stocks in the period 1998-2008), we present the main performance and risk results of the proposed Dynamic Proportion Portfolio Insurance strategy, first on real market data and secondly on artificial bootstrapped and surrogate data. Our main conclusion strengthens the previous ones : the conditional Dynamic Strategy with Constant-risk exposure dominates most of the time the traditional Constant-asset exposure unconditional strategies.CPPI, Portfolio insurance, VaR, CAViaR, quantile regression, dynamic quantile model.

    The Riskiness of Risk Models

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    URL des Documents de travail : http://centredeconomiesorbonne.univ-paris1.fr/bandeau-haut/documents-de-travail/Documents de travail du Centre d'Economie de la Sorbonne 2011.20 - ISSN : 1955-611XWe provide an economic valuation of the riskiness of risk models by directly measuring the impact of model risks (specification and estimation risks) on VaR estimates. We find that integrating the model risk into the VaR computations implies a substantial minimum correction of the order of 10-40% of VaR levels. We also present results of a practical method - based on a backtesting framework - for incorporating the model risk into the VaR estimates.Nous proposons une évaluation économique du risque de modÚle, en mesurant directement son impact (risques d'estimation et de spécification) sur les estimations des VaR. Nous montrons que l'intégration du risque de modÚle dans les calculs de VaR implique une correction minimum relativement importante, de l'ordre de 10 à 40% du niveau des VaR. Nous présentons également une illustration de notre méthode fondée sur les résultats de backtests pour introduire le risque de modÚle dans les estimations de VaR corrigées

    Detrending Persistent Predictors

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    URL des Documents de travail : http://centredeconomiesorbonne.univ-paris1.fr/bandeau-haut/documents-de-travail/Documents de travail du Centre d'Economie de la Sorbonne 2011.19 - ISSN : 1955-611XResearchers in finance very often rely on highly persistent - nearly integrated - explanatory variables to predict returns. This paper proposes to stand up to the usual problem of persistent regressor bias, by detrending the highly auto-correlated predictors. We find that the statistical evidence of out-of-sample predictability of stock returns is stronger, once predictors are adjusted for high persistence.Les variables prédictives en finance sont souvent fortement persistantes. Cet article propose de traiter le problÚme du biais des régresseurs persistants en éliminant directement leur tendance, c'est-à-dire leur composante basse fréquence. Nous montrons empiriquement que la prévision des rendements boursiers est de meilleure qualité lorsque les variables prédictives persistantes sont préalablement ajustées
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