The problem of quantile hedging for basket derivatives in the Black-Scholes model with correlation is considered. Explicit formulas for the probability maximizing function and the cost reduction function are derived. Applicability of the results to the widely traded derivatives like digital, quantos, outperformance and spread options is shown.
The problem of risk measures in a discrete-time market model with transaction costs is studied. Strategy effectiveness and shortfall risk are introduced. This gives a generalization of quantile hedging presented in [4].
In this paper the theoretical and practical implications of dropping -from the basic Bayesian coherence principles- the assumption of comparability of every pair of acts is examined. The resulting theory is shown to be still perfectly coherent and has Bayesian theory as a particular case. In particular we question the need of weakening or ruling out some of the axioms that constitute the coherence principles; what are their practical implications; how this drive to the notion of partial information...
Les systèmes «sériels» de représentation proportionnelle partent d'une table de quotients (des chiffres électoraux par une suite croissante de diviseurs) et attribuent les sièges disponibles aux plus grands de ces quotients. Le système Dhondt, pour lequel le n-ième diviseur vaut n, occupe une place centrale dans l'ensemble des systèmes sériels ; d'une part, il est le seul qui attribue toujours à chaque liste au moins la partie entière de son quotient électoral ; d'autre part, il sert d'étalon «naturel»...
In this work we propose a ranking procedure. This procedure uses an ordinal information about the criterion weights and a non-cardinal or mixed information for the potential actions evaluation. The advantage of this procedure is that it uses the linear programming software packages to compute the intervals of relative proximities from where the rankings are obtained.
This work deals with Random Coefficient Autoregressive models where the error process is a martingale difference sequence. A class of estimators of unknown parameter is employed. This class was originally proposed by Schick and it covers both least squares estimator and maximum likelihood estimator for instance. Asymptotic behavior of such estimators is explored, especially the rate of convergence to normal distribution is established.