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Ternary decision rules allowing for abstentions,besides Yea- and Nay-votes, are analyzed. The German Bundesrat serves as a prime example. We show that the decision-making efficiency of the Bundesrat would increase if abstentions were allowed. A general formula for the mean success margin of a ternary decision rule is derived assuming selfdual and permutationally invariant distributions. The ternary Penrose–Banzhaf model is discussed in detail, and the influence probabilities of voters and a rule´s influence sensitivity are evaluated.

This paper deals with pricing and hedging based on utility indifference for exponential utility. We consider the limit for vanishing risk aversion or, equivalently, small quantities of the contingent claim. In first order approximation the utility indifference price and the corresponding hedge can be determined from the corresponding quadratic hedging problem relative to the minimal entropy martingale measure. This extends similar results obtained by Mania and Schweizer [21], Becherer [3], and Kramkov and Sîrbu [20,19].

We consider the robust hedging problem in the framework of model uncertainty, where the log-returns of the stock price are Gaussian and H -self-similar with H ∈(1/2,1). These assumptions lead to two natural but mutually exclusive hypotheses, both being self-contained to fix the probabilistic model for the stock price. Namely, the investor may assume that either the market is efficient, that is the stock price process is a continuous semimartingale, or that the centred log-returns have stationary distributions. We show that to be able to super-hedge a European contingent claim with a convex payoff robustly, the investor must assume that the markets are efficient. If it turns out that the stationarity hypothesis is true, then the investor can actually super-hedge the option and thereby receive some net profit.

This paper studies the consistency of bootstrap moment estimators for a general M-estimator. We establish a theorem on the uniform integrability of the bootstrap M-estimator, thereby giving sufficient conditions for the consistency of the bootstrap moment estimators. As an application of our theorem, we provide sufficient conditions for the consistency of the bootstrap variance estimator for the quantile regression estimator, which has been considered as an important unsolved problem in the literature. We also discuss a justification of a bootstrap information criterion.

We introduce mixtures of probability distributions to model empirical distributions of financial asset returns. In this framework, we examine the problem of maximizing performance measures. For this purpose, we consider a large class of reward/risk ratios such as the Kappa measures and in particular the Omega ratio. This latter measure is associated to a downside risk measure based on a put component. All these measures can take account of the asymmetry of the probability distribution, which is important when dealing with mixture of distributions. We examine first a fundamental example: the ranking and maximization of Gaussian mixture distributions, according to the Omega performance measure. Then we provide a general result for the maximization of mixture distributions with respect to a very large family of performance measures, including Kappa measures.