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Discrete time hedging produces a residual risk, namely, the tracking error. The major problem is to get valuation/hedging policies minimizing this error. We evaluate the risk between trading dates through a function penalizing asymmetrically profits and losses. After deriving the asymptotics within a discrete time risk measurement for a large number of trading dates, we derive the optimal strategies minimizing the asymptotic risk in the continuous time setting. We characterize the optimality through Read more [...]

A new method based on nesting Monte Carlo is developed to solve highdimensional semi-linear PDEs. Convergence of the method is proved and its convergence rate studied. Results in high dimension for different kind of non-linearities show its efficiency.

Corinne Chaton, Anna Creti, and Maria-Eugenia Sanin, Abstract In October 2015 the European Parliament has established a market stability reserve (MSR) in the Phase 4 of the EU-ETS, as part of the 2030 framework for climate policies. In this paper we model the EU-ETS in presence of the Market Stability Reserve (MSR) as it is dened by that decision and investigate the impact that such a measure has in terms of permits price, output production and banking strategies. To do so we build an inter-temporal Read more [...]

Clémence Alasseur, Ivar Ekeland, Romuald Élie, Nicolás Hernández Santibáñez and Dylan Possamaï We study the optimal design of electricity contracts among a population of consumers with different needs. This question is tackled within the framework of Principal-Agent problem in presence of adverse selection. The particular features of electricity induce an unusual structure on the production cost, with no decreasing return to scale. We are nevertheless able to provide an explicit solution Read more [...]

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R. Aid, L. Li, M. Ludkovski, We consider competitive capacity investment for a duopoly of two distinct producers. The producers are exposed to stochastically uctuating costs and interact through aggregate supply. Capacity expansion is irreversible and modeled in terms of timing strategies characterized through threshold rules. Because the impact of changing costs on the producers is asymmetric, we are led to a nonzerosum timing game describing the transitions among the discrete investment Read more [...]

Edouard Jaeck In this paper, I examine how financialization affects the term structure of risk premia by using an equilibrium model for commodity futures markets. I define financialization as the entry of cross-asset investors, who are exposed to a commodity risk, into a commodity market. Qualitatively, the model shows that the financialization decreases the segmentation between commodity markets and the stock market. It also shows that speculators and investors both provide and consume liquidity Read more [...]

Mahamadou Doumbia, Nadia Oudjane,  Xavier Warin  We propose an unbiased Monte Carlo method to compute E(g(XT ))  where g is a Lipschitz function and X an Ito process. This approach extends the method proposed in [16] to the case where X is solution of a multidimensional stochastic differential equation with varying drift and diffusion coefficients. A variance reduction method relying on interacting particle systems is also developed. Key words: unbiased estimate, linear parabolic PDEs, interacting Read more [...]

Romuald Elie, Dylan Possamaï In a framework close to the one developed by Holmstrom and Milgrom [44], we study the optimal contracting scheme between a Principal and several Agents. Each hired Agent is in charge of one project, and can make efforts towards managing his own project, as well as impact (positively or negatively) the projects of the other Agents. Considering economic agents in competition with relative performance concerns, we derive the optimal contracts in both first best and moral Read more [...]

EMMANUEL GOBET, GANG LIU, AND JORGE P. ZUBELLI Abstract. Our goal is to solve certain dynamic programming equations associated to a given Markov chain X, using a regression-based Monte Carlo algorithm. More specically, we assume that the model for X is not known in full detail and only a root sample X1; : : : ;XM of such process is available. By a stratication of the space and a suitable choice of a probability measure , we design a new resampling scheme that allows to compute local regressions Read more [...]