Imprecise linear filtering: a second step

International audienceLinear digital signal processing consists in convo- luting the input sampled signal with the discrete version of the impulse response of a filter designed by an expert. More than often, a unique impulse re- sponse does not represent the complete knowledge of the expert who should have proposed more than one appropriate filter. In a recent paper, we have proposed an extension of the finite impulse response filtering that able to represent the fact that the fil- ter is imprecisely known. This extension leads to compute an interval-valued filtered signal. In this paper, we propose a natural follow-up of this work by considering interval-valued input signals and re- placing the Choquet integral by the Šipoš integral

Decision theory under uncertainty

We review recent advances in the field of decision making under uncertainty or ambiguity.Ambiguity ; ambiguity aversion ; uncertainty ; decision

Ambiguity

Ambiguity refers to a decision situation under uncertainty when there is incomplete information about the likelihood of events. Different formal models of this notion have been developed with differing implications about the representation of ambiguity and ambiguity aversion.uncertainty, ambiguity, ambiguity attitude

Risk measurement with the equivalent utility principles.

Risk measures have been studied for several decades in the actuarial literature, where they appeared under the guise of premium calculation principles. Risk measures and properties that risk measures should satisfy have recently received considerable at- tention in the financial mathematics literature. Mathematically, a risk measure is a mapping from a class of random variables defined on some measurable space to the (extended) real line. Economically, a risk measure should capture the preferences of the decision-maker. In incomplete financial markets, prices are no more unique but depend on the agents' attitudes towards risk. This paper complements the study initiated in Denuit, Dhaene & Van Wouwe (1999) and considers several theories for decision under uncertainty: the classical expected utility paradigm, Yaari's dual approach, maximin expected utility theory, Choquet expected utility theory and Quiggin rank-dependent utility theory. Building on the actuarial equivalent utility pricing principle, broad classes of risk measures are generated, of which most classical risk measures appear to be particular cases. This approach shows that most risk measures studied recently in the financial literature disregard the utility concept (i.e. correspond to linear utilities), causing some deficiencies. Some alternatives proposed in the literature are discussed, based on exponential utilities.Actuarial; Coherence; Decision; Expected; Market; Markets; Measurement; Preference; Premium; Prices; Pricing; Principles; Random variables; Research; Risk; Risk measure; Risk measurement; Space; Studies; Theory; Uncertainty; Utilities; Variables;

The Evolutionary Stability of Optimism, Pessimism and Complete Ignorance

We provide an evolutionary foundation to evidence that in some situations humans maintain optimistic or pessimistic attitudes towards uncertainty and are ignorant to relevant aspects of the environment. Players in strategic games face Knightian uncertainty about opponents’ actions and maximize individually their Choquet expected utility. Our Choquet expected utility model allows for both an optimistic or pessimistic attitude towards uncertainty as well as ignorance to strategic dependencies. An optimist (resp. pessimist) overweights good (resp. bad) outcomes. A complete ignorant never reacts to opponents’ change of actions. With qualifications we show that optimistic (resp. pessimistic) complete ignorance is evolutionary stable / yields a strategic advantage in submodular (resp. supermodular) games with aggregate externalities. Moreover, this evolutionary stable preference leads to Walrasian behavior in those classes of games

Diversification Preferences in the Theory of Choice

Diversification represents the idea of choosing variety over uniformity. Within the theory of choice, desirability of diversification is axiomatized as preference for a convex combination of choices that are equivalently ranked. This corresponds to the notion of risk aversion when one assumes the von-Neumann-Morgenstern expected utility model, but the equivalence fails to hold in other models. This paper studies axiomatizations of the concept of diversification and their relationship to the related notions of risk aversion and convex preferences within different choice theoretic models. Implications of these notions on portfolio choice are discussed. We cover model-independent diversification preferences, preferences within models of choice under risk, including expected utility theory and the more general rank-dependent expected utility theory, as well as models of choice under uncertainty axiomatized via Choquet expected utility theory. Remarks on interpretations of diversification preferences within models of behavioral choice are given in the conclusion

Ambiguity

Ambiguity refers to a decision situation under uncertainty when there is incomplete information about the likelihood of events. Different formal models of this notion have been developed with differing implications about the representation of ambiguity and ambiguity aversion.