A mathematical resurgence of risk management: an extreme modeling of expert opinions

The Operational Risk Advanced Measurement Approach requires financial institutions to use scenarios to model these risks and to evaluate the pertaining capital charges. Considering that a banking group is composed of numerous entities (branches and subsidiaries), and that each one of them is represented by an Operational Risk Manager (ORM), we propose a novel scenario approach based on ORM expertise to collect information and create new data sets focusing on large losses, and the use of the Extreme Value Theory (EVT) to evaluate the corresponding capital allocation. In this paper, we highlight the importance to consider an a priori knowledge of the experts associated to a a posteriori backtesting based on collected incidents.Basel II; operational risks; EVT; AMA; expert; Value-at-Risk; expected shortfall

A new algorithm for the loss distribution function with applications to Operational Risk Management

Operational risks inside banks and insurance companies is currently an important task. The computation of a risk measure associated to these risks lies on the knowledge of the so-called Loss Distribution Function. Traditionally this distribution function is computed via the Panjer algorithm which is an iterative algorithm. In this paper, we propose an adaptation of this last algorithm in order to improve the computation of convolutions between Panjer class distributions and continuous distributions. This new approach permits to reduce drastically the variance of the estimated VAR associated to the operational risks.Operational risk, Panjer algorithm, Kernel, numerical integration, convolution.

La « merveilleuse histoire » des « disgrâces » de Dassoucy : récit de survivance et résilience ambiguë

La suite narrative rétrospective que nous livre Dassoucy de ses Aventures (1677) se donne comme un récit de survivance. L’auteur, plusieurs fois emprisonné et réputé mort, transpose dans son autofiction burlesque une partie des tribulations qui ont failli lui coûter réellement la vie, le ruiner et détruire sa réputation. La recomposition du passé, ordonné comme suite de disgrâces et des triomphes, favorise la réappropriation d’une estime de soi, associée à une méditation sur les ressorts intimes qui ont permis au héros-narrateur de résister à des épreuves mortifères. Toutefois cette résilience est incomplète et ambiguë : l’ironie libertine parasite le récit de survivance, et le retour manifeste d’un refoulé traumatique témoigne de l’insuffisante réparation des blessures d’une victime qui ne renonce pas aux bénéfices de la persécution et fait prévaloir la logique apologétique et polémique.In a way, the restrospective narrative of Dassoucy in his Adventures (1677) is the narration of a survivor. The author, who was in jail several times and was said to be dead, tells adventures that were prejudicial to his person, his fortune and his honor. Reorganizing the past as a succession of misfortunes and triumphs, the narrative helps the narrator to restore his self-esteem, and we can see how the author is very conscious of his mechanisms of defense. It is, however, difficult to consider this narrative as a text of resiliency ; self adaptation is incomplete and ambiguous : libertine irony compromises the story of survival and the traumatic experiences of prison and symbolic death are present in only a metaphorical way. Dassoucy enjoys his status of victim to some degree and the main goals of his text are polemic and promoting himself

A k- factor GIGARCH process : estimation and application to electricity market spot prices,

Some crucial time series of market data, such as electricity spot prices, exhibit long memory, in the sense of slowly-decaying correlations combined with heteroscedasticity. To e able to model such a behaviour, we consider the k-factor GIGARCH process and we propose two methods to address the related parameter estimation problem. For each method, we develop the asymptotic theory for this estimation.GIGARCH process – estimation theory – Electricity spot prices.

Forecasting electricity spot market prices with a k-factor GIGARCH process

In this article, we investigate conditional mean and variance forecasts using a dynamic model following a k-factor GIGARCH process. We are particularly interested in calculating the conditional variance of the prediction error. We apply this method to electricity prices and test spot prices forecasts until one month ahead forecast. We conclude that the k-factor GIGARCH process is a suitable tool to forecast spot prices, using the classical RMSE criteria.Conditional mean ; conditional variance ; forecast ; electricity prices ; GIGARCH process

Forecasting electricity spot market prices with a k-factor GIGARCH process

In this article, we investigate conditional mean and variance forecasts using a dynamic model following a k-factor GIGARCH process. We are particularly interested in calculating the conditional variance of the prediction error. We apply this method to electricity prices and test spot prices forecasts until one month ahead forecast. We conclude that the k-factor GIGARCH process is a suitable tool to forecast spot prices, using the classical RMSE criteria.Conditional mean - conditional variance - forecast - electricity prices - GIGARCH process

Low Temperature Oxidation of pure Iron : Growth kinetics and scale Morphologies

Isothermal oxidation of pure iron has been performed in air at atmospheric pressure between 260°C and 500°C. Growth kinetics are accurately analysed and scale morphologies are investigated by SEM and TEM observations. The calculation of the variations of the parabolic rate constant kp with scale thickness allows a better understanding of scale growth mechanisms involved at this intermediate temperature range, which have been poorly investigated up to now. These results are discussed with the objective of long term behaviour for long term interim storage of some nuclear waste containers

Numerical Model for Oxide Scale Growth with Explicit Treatment of Vacancy Fluxes

In the framework of research on behaviour of nuclear waste containers, to evaluate the effects of possible evolution of experimental conditions, as well as evolution of parameters controlling oxidation rate during long-term interim storage, a numerical model has been developed in order to take into account non-stationary states. To anticipate effects like cold working of the metal on the scale growth kinetics and risks of scale detachment by over saturation of vacancies at the metal/oxide interface in the course of scale growth, the model is based on the calculation of chemical species, but also vacancies profiles evolution in the oxide and the metal following a simple time integration. An original numerical treatment is proposed to easily describe elimination of vacancies by introducing sink strength in the metal. The first calculations are presented and discussed

Distortion Risk Measures or the Transformation of Unimodal Distributions into Multimodal Functions

URL des Documents de travail : http://ces.univ-paris1.fr/cesdp/cesdp2014.html Chapitre dans "Future Perspectives in Risk Models and Finance", eds. A. Bensoussan, D. Guegan, C. Tapiero, Volume 211 of the series International Series in Operations Research & Management Science, 89-124, 2015Documents de travail du Centre d'Economie de la Sorbonne 2014.08 - ISSN : 1955-611XThe particular subject of this paper, is to construct a general framework that can consider and analyse in the same time upside and downside risks. This paper offers a comparative analysis of concept risk measures, we focus on quantile based risk measure (ES and VaR), spectral risk measure and distortion risk measure. After introducing each measure, we investigate their interest and limit. Knowing that quantile based risk measure cannot capture correctly the risk aversion of risk manager and spectral risk measure can be inconsistent to risk aversion, we propose and develop a new distortion risk measure extending the work of Wang (2000) [38] and Sereda et al (2010) [34]. Finally, we provide a comprehensive analysis of the feasibility of this approach using the S&P500 data set from o1/01/1999 to 31/12/2011.Ce papier propose un cadre général qui permet d'analyser dans le même temps les risques à la hausse et la baisse. Après une revue (avec limites et intérêt) sur les mesures de risques classiques : VaR, ES et mesure spectrale, nous proposons et développons une nouvelle mesure du risque appeler mesure de distorsion qui étend le travail de Wang (2000) et Sereda et al (2010) pour des distributions bimodales et multimodales