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Measuring Risk for Income Streams
Authors:Georg Ch. Pflug  Andrzej Ruszczyński
Affiliation:(1) Department of Statistics and Decision Support Systems, University of Vienna, Universitaetsstrasse 5, 1090 Wien-Vienna, Austria;(2) Department of Management Science and Information Systems and RUTCOR, Rutgers University, 94 Rockefeller Rd, Piscataway, NJ 08854, USA
Abstract:A measure of risk is introduced for a sequence of random incomes adapted to some filtration. This measure is formulated as the optimal net present value of a stream of adaptively planned commitments for consumption. The new measure is calculated by solving a stochastic dynamic linear optimization problem which, for finite filtrations, reduces to a deterministic linear programming problem.We analyze properties of the new measure by exploiting the convexity and duality structure of the stochastic dynamic linear problem. The measure depends on the full distribution of the income process (not only on its marginal distributions) as well as on the filtration, which is interpreted as the available information about the future. The features of the new approach are illustrated by a numerical example.
Keywords:dynamic risk measure  multistage stochastic programming  multiperiod mean-risk models  value of perfect information  conditional value at risk
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