This paper investigates Value at Risk and Expected Shortfall for CAC 40, S&P 500, Wheat and Crude Oil indexes during the 2008 financial crisis. We show an underestimation of the risk of loss for the unconditional VaR models as compared with the conditional models. This underestimation is stronger using the historical VaR approach than when using the extreme values theory VaR model. Even in 2008 financial crisis, the conditional EVT model is more accurate and reliable for predicting the asset risk losses. Banks have no interest in using it because the Basel II agreement penalizes banks using accuracy models like the conditional EVT model, and this is the case for the assets being studied in this paper.
The spatial reconstruction of the production, trade, transformation and consumption flows of a specific material, can become an important decision-help tool for improving resource management and for studying environmental pressures from the producer's to the consumer's viewpoint. One of the obstacles preventing its actual use in the decision-making process is that building such studies at various geographical scales proves to be costly both in time and manpower. In this article, we propose a semi-automatic methodology to overcome this issue: we describe our multi-scalar model and its data-reconciliation component and apply it to cereals flows. Namely, using o cial databases (Insee, Agreste, FranceAgriMer, SitraM) as well as corporate sources, we reconstructed the supply chain flows of the 22 French regions as well as the flows of four nested territories: France, the Rhône-Alpes région, the Isère département and the territory of the SCOT of Grenoble. We display the results using Sankey diagrams and discuss the intervals of confidence of the model's outputs. We conclude on the perspectives of coupling this model with economic, social and environmental aspects that would provide key information to decision-makers.
International audienceFrance is the second largest exporter of cereals in the world. Although the cereals supply chain is an asset for the country's economy and employment, it is at the same time responsible for a number of pressures on the local and global environment including greenhouse gases (GHG) emissions and stresses on water quality and quantity. This article aims at evaluating this situation from an environmental point of view by linking productions occurring in French regions with consumption occurring in France and abroad. Based on previous work on Material Flow Analysis, we use an Absorbing Markov Chain model to study the fate of French cereals and link worldwide consumption to environmental pressures along the supply chain, that is, induced by production, transformation or transport. The model is based on physical supply and use tables and distinguishes between 21 industries, 22 products, 38 regions of various spatial resolution (22 French regions, 10 countries, 6 continents) and 4 modes of transport. Energy use, GHG emissions, land use, use of pesticides and blue water footprint are studied. Illustrative examples are taken in order to demonstrate the versatility of the results produced, for instance: Where and under what form does local production end up? How do regions compare relatively to their production and consumption footprints? These results are designed to be a first step towards scenario analysis for decision-aiding that would also include socioeconomic indicators. Examples of such scenarios are discussed in the conclusion
L'investissement socialement responsable connaît une croissance rapide ces dernières années, ceci traduisant une préoccupation réelle des investisseurs. Cette étude propose une modélisation théorique formalisant les implications de ce goût nouveau pour l'investissement socialement responsable sur le prix des actions. Nous retraçons les différentes phases d'introduction de l'éthique sur les marchés financiers. Nous montrons, en particulier, que l'émergence d'une notation éthique entraîne une hausse du prix des titres éthiques, et donc une diminution du coût du capital de ces entreprises. Cet avantage peut inciter des entreprises à s'adapter à la demande des investisseurs en adoptant un comportement éthique, et ce jusqu'à ce que la baisse du coût du capital induite s'équilibre avec le coût supporté pour investir dans des programmes de mise en conformité aux normes sociales.
Freight statistics are at the core of many studies in the field of industrial ecology because they depict the physical inter-dependencies of territories and allow to link worldwide productions and consumptions. Recent studies have been increasingly focusing on subnational scales, often relying on domestic freight data. In this perspective, this article analyses the uncertainties of the French domestic road freight survey, road being by far the most common mode of transport in the country. Based on a statistical analysis of the survey, we propose a model to estimate the uncertainty of any given domestic road transport flow. We also assess uncertainty reduction when averaging the flows over several years, and obtain for instance a 30% reduction for a 3-year average. We then study the impact of the uncertainties on regional material flow studies such as the Economy-Wide Material Flow Analysis of the Bourgogne region. Overall the case studies advocate for a systematic assessment of freight uncertainties, as neither the disaggregation level nor the quantities traded are good enough predictors. This justifies the need for an easy-to-implement estimation model. Finally, basic comparison with the German and Swedish surveys tend to indicate that the main conclusions presented in this article are likely to be valid in other European countries.
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