We consider sel sh routing over a network consisting of m parallel links through which n sel sh users route their tra c trying to minimize their own expected latency. Westudy the class of mixed strategies in which the expected latency through each link is at most a constant multiple of the optimum maximum latency had global regulation been available. For the case of uniform links it is known that all Nash equilibria belong to this class of strategies. We areinterested in bounding the coordination ratio (or price of anarchy) of these strategies de ned as the worst-case ratio of the maximum (over all links) expected latency over the optimum maximum latency. The load balancing aspect of the problem immediately implies a lower bound; lnm ln lnm of the coordination ratio. We give a tight (uptoamultiplicative constant) upper bound. To show the upper bound, we analyze a variant ofthe classical balls and bins problem, in which balls with arbitrary weights are placed into bins according to arbitrary probability distributions. At the heart of our approach is a new probabilistic tool that we call

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Abstract. The importance of risk in trust-based systems is well established. This paper presents a novel model of risk and decision-making based on economic theory. Use of the model is illustrated by way of a collaborative spam detection application. 1

The present paper is devoted to di#erent methods of choice under risk in an actuarial setting. The classical expected utility theory is first presented, and its drawbacks are underlined. A second approach based on the so-called distorted expectation hypothesis is then described. It will be seen that the well-known stochastic dominance as well as the stop-loss order have common interpretations in both theories, while defining higher degree stochastic orders leads to di#erent concepts. The aim of this paper is to emphasize the similarities of the two approaches of choice under risk as well as to point out their major di#erences.

OF LICENTIATE THESIS Department of Engineering Physics and Mathematics P.O. Box 2200, FIN-02015 HUT, FINLAND Author: Janne Gustafsson Department: Department of Engineering Physics and Mathematics Major subject: Systems Analysis and Operations Research Minor subject: Strategy and International Business English title: Valuation of Projects and Real Options in Incomplete Markets Finnish title: Projektien ja reaalioptioiden arvonmritys eptydellisill markkinoilla Number of pages: 105 Chair: Mat-2 Applied Mathematics Supervisor: Professor Ahti Salo Instructor: Professor Ahti Salo Abstract: This thesis presents a framework for valuing risky projects and its extension for the valuation of real options and managerial flexibility. The framework is also applied in a case where the investor's probability estimates are imprecise or unknown.

doi:10.1145/1378704.1378721 The most dramatic interaction between CS and GT may involve game-theory pragmatics.

This paper examines the valuation of multi-period projects in a setting where (i) the investor maximizes her terminal wealth level, (ii) she can invest in securities and private investment opportunities, and (iii) markets are incomplete, i.e. the cash flows of private investments cannot necessarily be replicated using financial securities. Based on Gustafsson and Salo’s (2005) Contingent Portfolio Programming, we develop a multiperiod mixed asset portfolio selection model, where project management decisions are captured through project-specific decision trees. This model properly captures the opportunity costs imposed by alternative investment opportunities and determines the appropriate risk-adjustment to the projects based on their effect on the investor’s aggregate portfolio risk. The project valuation procedure is based on the concepts of breakeven selling and buying prices, which require the solution of mixed asset portfolio selection models with and without the project being valued. The valuation procedure is demonstrated through numerical experiments.

Gerd Gigerenzer is a man with a mission, and a mission that has some point to it. He wants to show that people are rational decision makers, most of the time. To understand why Gigerenzer is on this mission we have to have a bit of background. Modern ideas about rationality are very largely based on Von Neumann and Morgenstern’s (1947) Theory of Games and Economic Behavior, a masterful analysis of decision making. Von Neumann and Morgenstern assumed that life consists of choices between lotteries, where if you take action A you will receive award R1 with probability p1, award R2 with probability p2, and so forth. This depiction can be applied very widely. You can choose to invest your money in one stock or another. That is clearly a choice between lotteries. While walking on the shady side of the street you can choose to cross to the sunny side or not, and there’s a chance you might be hit by a car. You are trading “coolness for sure” against “sunny walk, probability p1 or hit by a car, probability 1-p1.” Von Neumann and Morgenstern postulated a small number of statements that

Procedures designed to select alternatives on the basis of the results of pairwise contests between them have received much attention in literature. The particular case of tournaments has been studied in depth. More recently weak tournaments and valued generalizations thereof have been investigated. The purpose of this paper is to investigate to what extent these choice procedures may be meaningfully used to define ranking procedures via their repeated use, i.e. when the equivalence classes of the ranking are determined by successive applications of the choice procedure. This is what we call "ranking by choosing". As could

In this paper, we develop a framework for valuing real options and portfolios of real options in incomplete markets and show that it is a consistent generalization of contingent claims analysis, which is conventionally used for real option valuation in complete markets. The development of a framework for incomplete markets is motivated by the difficulty to construct replicating portfolios in practice, especially for projects that lead to innovative new products, which seldom share similarities with existing market-traded assets. The framework relies on (i) a decision-tree-based mixed asset portfolio selection model, which is able to capture managerial flexibility and relevant opportunity costs, and (ii) the concepts of opportunity buying and selling prices, which are extended from the notions of breakeven buying and selling prices. The use of a portfolio model is necessary, because in incomplete markets the value of a real option depends on the investor's preference model, the available budget, and on other assets in the portfolio, including the real options they contain. We demonstrate the use of the model through a series of numerical experiments and compare the results to Capital Asset Pricing Model prices and Black-Scholes values.