215 research outputs found
Possibilistic risk aversion with many parameters
AbstractThe study of risk aversion of an agent confronted by a risk situations with several parameters is an important topic of risk theory. It is tackled traditionally with probabilistic methods. When these do not offer an appropriate shaping we can use Zadeh's possibility theory. In this paper a possibilistic model of risk aversion with several parameters is proposed. The notion of possibilistic risk premium vector is introduced as a measure of an agent's risk aversion to a situation with several risk parameters. The main result of the paper is an approximate calculation formula of this indicator. The way we can apply this model in risk aversion evaluation in grid computing is sketched out
A Possibilistic and Probabilistic Approach to Precautionary Saving
This paper proposes two mixed models to study a consumer's optimal saving in
the presence of two types of risk.Comment: Panoeconomicus, 201
Robust portfolio management with multiple financial analysts
Portfolio selection theory, developed by Markowitz (1952), is one of the best known and widely applied methods for allocating funds among possible investment choices, where investment decision making is a trade-off between the expected return and risk of the portfolio. Many portfolio selection models have been developed on the basis of Markowitzâs theory. Most of them assume that complete investment information is available and that it can be accurately extracted from the historical data. However, this complete information never exists in reality. There are many kinds of ambiguity and vagueness which cannot be dealt with in the historical data but still need to be considered in portfolio selection. For example, to address the issue of uncertainty caused by estimation errors, the robust counterpart approach of Ben-Tal and Nemirovski (1998) has been employed frequently in recent years. Robustification, however, often leads to a more conservative solution. As a consequence, one of the most common critiques against the robust counterpart approach is the excessively pessimistic character of the robust asset allocation.
This thesis attempts to develop new approaches to improve on the respective performances of the robust counterpart approach by incorporating additional investment information sources, so that the optimal portfolio can be more reliable and, at the same time, achieve a greater return. [Continues.
Precautionary Culture and the Rise of Possibilistic Risk Assessment
The shift from probabilistic to possibilistic risk management characterises contemporary cultural attitudes towards uncertainty. This shift in attitude is paralleled by the growing influence of the belief that future risks are not only unknown but are also unknowable. Scepticism about the capacity of knowledge to help manage risks has encouraged the dramatisation of uncertainty. One consequence of this development has been the advocacy of a precautionary response to threats. This article examines the way in which precautionary attitudes have shaped the response to the threat of terrorism and to the millennium bug. The main accomplishment of this response has been to intensify the sense of existential insecurity
Strict Solution Method for Linear Programming Problem with Ellipsoidal Distributions under Fuzziness
This paper considers a linear programming problem with ellipsoidal distributions including fuzziness. Since this problem is not well-defined due to randomness and fuzziness, it is hard to solve it directly. Therefore, introducing chance constraints, fuzzy goals and possibility measures, the proposed model is transformed into the deterministic equivalent problems. Furthermore, since it is difficult to solve the main problem analytically and efficiently due to nonlinear programming, the solution method is constructed introducing an appropriate parameter and performing the equivalent transformations
Asset allocation with multiple analystsâ views: a robust approach
Retail investors often make decisions based on professional analystsâ investment recommendations. Although these recommendations contain up-to-date financial information, they are usually expressed in sophisticated but vague forms. In addition, the quality differs from analyst to analyst and recommendations may even be mutually conflicting. This paper addresses these issues by extending the BlackâLitterman (BL) method and developing a multi-analyst portfolio selection method, balanced against any over-optimistic forecasts. Our methods accommodate analystsâ ambiguous investment recommendations and the heterogeneity of data from disparate sources. We prove the validity of our model, using an empirical analysis of around 1000 daily financial newsletters collected from two top 10 Taiwanese brokerage firms over a 2-year period. We conclude that analystsâ views contribute to the investment allocation process and enhance the portfolio performance. We confirm that the degree of investorsâ confidence in these views influences the portfolio outcome, thus extending the idea of the BL model and improving the practicality of robust optimisation
A framework of distributionally robust possibilistic optimization
In this paper, an optimization problem with uncertain constraint coefficients
is considered. Possibility theory is used to model the uncertainty. Namely, a
joint possibility distribution in constraint coefficient realizations, called
scenarios, is specified. This possibility distribution induces a necessity
measure in scenario set, which in turn describes an ambiguity set of
probability distributions in scenario set. The distributionally robust approach
is then used to convert the imprecise constraints into deterministic
equivalents. Namely, the left-hand side of an imprecise constraint is evaluated
by using a risk measure with respect to the worst probability distribution that
can occur. In this paper, the Conditional Value at Risk is used as the risk
measure, which generalizes the strict robust and expected value approaches,
commonly used in literature. A general framework for solving such a class of
problems is described. Some cases which can be solved in polynomial time are
identified
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