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Evaluating the magnitudes of financial transactions costs on risk behavior

AGRICULTURAL SYSTEMS 2003年第2-3期75卷 235-249页

作者： Atwood, JA Buschena, DE Montana State Univ Dept Agr Econ & Econ Bozeman MT 59717 USA

The model presented in this paper relies on financial constraints and transactions costs to operationalize model of behavior akin to safety rules. The decision maker is taken to maximize long term (40 period) expected wealth in the presence of financial transactions costs. The model allows exploration of the implications of these constraints and transactions costs for measurable choice patterns over risk. The optimization analysis demonstrates very rich behavior despite the restrictive assumption of risk neutral preferences. The optimal decisions show instances of "risk aversion" with willingness to pay less than a risky option's expected value, and of "risk preference" or plunging with willingness to pay greater than a risky option's expected value. These varied behavioral patterns in the presence of risk depend on the individual's financial standing, the magnitude of the random outcomes, the underlying distribution, and the farm policy environment. (C) 2002 Elsevier Science Ltd. All rights reserved.

关键词： risk transaction costs plunging stochastic dynamic programming safety rules

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The value of information in a long-term hydro-thermal electrical planning model

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International Transactions in Operational Research 2003年第1期10卷 89-100页

作者： Contesse, Luis Donoso, Patricio Prina, José Pontificia Universidad Católica de Chile Chile

This article presents the analysis, comparison, and application of two alternative models to the optimal long-term operation planning of an hydro-thermal power system under conditions of uncertainty. The electrical system considered comprises one large reservoir, with interannual regulation capacity, and several smaller ones. The analyzed models employ stochastic dynamic programming as the solution methodology. The fundamental problem is to decide, on every temporal stage, how much water to use for generating purposes and how much to store, in order to minimize the total thermal and shortage costs. The original version of the studied model, created originally to forecast fuel consumption, assumes that the decision regarding the water release from the main reservoir is taken knowing the future hydrologic conditions. This criterion is known as wait-and-see. On the contrary, the new versions of the model, proposed in this article, consider a here-and-now criterion. Specifically, it is assumed that the future hydrologic conditions are not known at the time of making the operational decisions. The difference between the optimal cost of the proposed models and the original model defines the value of having the information regarding future hydrologic conditions before taking any decision. This value is generally known as the expected value of perfect information. © 2003 International Federation of Operational Research Societies.

关键词： Hydro-thermal power system planning Long-term planning under uncertainty stochastic dynamic programming

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Optimal market timing strategies under transaction costs

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OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE 2002年第2期30卷 97-108页

作者： Li, W Lam, K Hong Kong Polytech Univ Fac Business & Informat Syst Dept Business Studies Kowloon Hong Kong Peoples R China Hong Kong Baptist Univ Sch Business Dept Finance & Decis Sci Kowloon Tong Peoples R China

In this paper, we consider optimal market timing, strategies under transaction costs. We assume that the asset's return follows an auto-regressive model and use long-term investment growth as the objective of a market timing strategy which entails the shifting of funds between a risky asset and a riskless asset. We give the optimal trading strategy for a finite investment horizon, and analyze its limiting behavior. For a finite horizon, the optimal decision in each step depends on two threshold values. If the return today is between the two values, nothing needs to be done, otherwise funds will be shifted from one asset to another, depending on which threshold value is being exceeded. When investment horizon tends to infinity, the optimal strategy converges to a stationary policy, which is shown to be closely related to a well-known technical trading rule, called Momentum Index trading rule. An integral equation of them two threshold values is given. Numerical results for the limiting stationary strategy are presented. The results confirm the obvious guess that the no-transaction region increases as the transaction cost increase. Finally, the limiting stationary strategy is applied to data in the Hang Seng Index Futures market in Hong Kong. The out-of-sample performance of the limiting stationary strategy is found to be better than the simple strategy sed in literature, which is based on an 1-step ahead forecast of return. (C) 2002 Elsevier Science Ltd. All rights reserved.

关键词： market timing autoregressive models growth-optimal investment strategy stochastic dynamic programming

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The importance of functional form in optimal control solutions of problems in population dynamics

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ECOLOGY 2002年第5期83卷 1357-1371页

作者： Runge, MC Johnson, FA Univ Georgia Warnell Sch Forest Resources Athens GA 30602 USA US Fish & Wildlife Serv Patuxent Wildlife Res Ctr Off Migratory Bird Management Laurel MD 20708 USA

Optimal control theory is finding increased application in both theoretical and applied ecology, and it is a central element of adaptive resource management. One of the steps in an adaptive management process is to develop alternative models of system dynamics, models that are all reasonable in light of available data, but that differ substantially in their implications for optimal control of the resource. We explored how the form of the recruitment and survival functions in a general population model for ducks affected the patterns in the optimal harvest strategy, using a combination of analytical, numerical, and simulation techniques. We compared three relationships between recruitment and population density (linear, exponential, and hyperbolic) and three relationships between survival during the nonharvest season and population density (constant, logistic, and one related to the compensatory harvest mortality hypothesis). We found that the form of the component functions had a dramatic influence on the optimal harvest strategy and the ultimate equilibrium state of the system. For instance, while it is commonly assumed that a compensatory hypothesis leads to higher optimal harvest rates than an additive hypothesis, we found this to depend on the form of the recruitment function, in part because of differences in the optimal steady-state population density. This work has strong direct consequences for those developing alternative models to describe harvested systems, but it is relevant to a larger class of problems applying optimal control at the population level. Often, different functional forms will not be statistically distinguishable in the range of the data. Nevertheless, differences between the functions outside the range of the data can have an important impact on the optimal harvest strategy. Thus, development of alternative models by identifying a single functional form, then choosing different parameter combinations from extremes on the likelihood profil

关键词： adaptive management compensatory mortality density-dependence equilibrium analysis harvest theory optimal control theory population dynamics reproductive function stochastic dynamic programming survival function

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stochastic discrete-time Nash games with constrained state estimators

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JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 2002年第1期114卷 171-188页

作者： Kian, AR Cruz, JB Simaan, MA Ohio State Univ Dept Elect Engn Columbus OH 43210 USA Univ Pittsburgh Dept Elect Engn Pittsburgh PA USA

In this paper, we consider stochastic linear-quadratic discrete-time Nash games in which two players have access only to noise-corrupted output measurements. We assume that each player is constrained to use a linear Kalman filter-like state estimator to implement his optimal strategies. Two information structures available to the players in their state estimators are investigated. The first has access to one-step delayed output and a one-step delayed control input of the player. The second has access to the current output and a one-step delayed control input of the player. In both cases, statistics of the process and statistics of the measurements of each player are known to both players. A simple example of a two-zone energy trading system is considered to illustrate the developed Nash strategies. In this example, the Nash strategies are calculated for the two cases of unlimited and limited transmission capacity constraints.

关键词： stochastic linear-quadratic systems nonzero-sum discrete-time Nash games optimal Nash strategies estimator-controller stochastic dynamic programming Nash equilibrium

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Scheduling in multiclass networks with deterministic service times

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QUEUEING SYSTEMS 2002年第4期41卷 305-319页

作者： Righter, R Santa Clara Univ Dept Operat & Management Informat Syst Santa Clara CA 95053 USA

We consider general feed-forward networks of queues with deterministic service times and arbitrary arrival processes. There are holding costs at each queue, idling may or may not be permitted, and servers may fail. We partially characterize the optimal policy and give conditions under which lower priority should be given to jobs that would be delayed later in the network if they were processed now.

关键词： scheduling stochastic dynamic programming restless bandits mobile communications

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Algorithms for optimal scheduling and management of Hidden Markov model sensors

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2002年第6期50卷 1382-1397页

作者： Krishnamurthy, V Univ Melbourne Dept Elect & Elect Engn Parkville Vic 3052 Australia

Consider a Hidden Markov model (HMM) where a single Markov chain is observed by a number of noisy sensors. Due to computational or communication constraints, at each time instant, one can select only one of the noisy sensors. The sensor scheduling problem involves designing algorithms for choosing dynamically at each time instant which sensor to select to provide the next measurement. Each measurement has an associated measurement cost. The problem is to select an optimal measurement scheduling policy to minimize a cost function of estimation errors and measurement costs. The optimal measurement policy is solved via stochastic dynamic programming. Sensor management issues and suboptimal scheduling algorithms are also presented. A numerical example that deals with the aircraft identification problem is presented.

关键词： Hidden Markov models partially observed Markov decision processes sensor scheduling stochastic dynamic programming

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An optimal statistical testing policy for software reliability demonstration of safety-critical systems

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2002年第3期137卷 544-557页

作者： Tal, O McCollin, C Bendell, A Nottingham Trent Univ Dept Math Stat & Operat Res Nottingham NG1 4BU England RAFAEL IL-31021 Haifa Israel Univ Leicester Ctr Management Leicester LE1 7RH Leics England

When software reliability demonstration of safety-critical systems by statistical testing is treated as a Test, Analyse and Fix (TAAF) process, an optimal testing policy can be found, which maximises the probability of p success of the whole process, over a pre-determined period of time. The optimisation problem is formulated, solved by stochastic dynamic programming, and demonstrated by two numerical examples. (C) 2002 Elsevier Science B.V. All rights reserved.

关键词： reliability software reliability demonstration statistical testing safety-critical systems stochastic dynamic programming

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Planning and management of a complex water resource system: case of Samanalawewa and Udawalawe reservoirs in the Walawe river, Sri Lanka

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AGRICULTURAL WATER MANAGEMENT 2002年第3期57卷 207-221页

作者： Nandalal, KDW Sakthivadivel, R Int Water Management Inst Colombo Sri Lanka Univ Peradeniya Dept Civil Engn Peradeniya Sri Lanka

The Samanalawewa and Udawalawe reservoirs were built to harness the hydro-energy and irrigation potentials of the Walawe river in Sri Lanka. The recently completed Samanalawewa reservoir primarily generates hydropower while the Udawalawe reservoir, which was built in the 1960s, supplies water mainly for irrigation. With the addition of the Samanalawewa reservoir, located upstream of the Udawalawe reservoir, the Government of Sri Lanka is planning to increase the irrigated area of the Udawalawe reservoir. The Samanalawewa reservoir is expected to act as an additional storage for irrigation water supply. A study was carried out to investigate the operational behavior of these two reservoirs. The model used in the study is based on stochastic dynamic programming (SDP) and simulation techniques. Since, the direct application of SDP for two reservoirs is limited by the dimensionality of the problem, a sequential decomposition method is employed in the model. The algorithm employed breaks down the system into single-reservoir subsystems and subsequently, each subsystem's operation is individually optimized using a SDP based optimization model and then simulated using a reservoir operation simulation model. The results indicate the usefulness of optimization techniques in planning reservoirs and deriving operational policies for them. The inclusion of the Samanalawewa reservoir reduces the irrigation water supply deficits at the Udawalawe reservoir. (C) 2002 Elsevier Science B.V. All rights reserved.

关键词： optimum reservoir operation stochastic dynamic programming simulation decomposition method reservoir operational policies

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Event-driven competing risks

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ECOLOGICAL MODELLING 2002年第1-2期158卷 35-50页

作者： Ewing, B Yandell, BS Barbieri, JF Luck, RF Forster, LD Univ Wisconsin Dept Stat Madison WI 53706 USA Univ Wisconsin Dept Hort Madison WI 53706 USA Univ Calif Berkeley Dept Entomol Berkeley CA 94720 USA Univ Calif Riverside Dept Entomol Riverside CA 92521 USA NAWC WPNS Adv Syst Dev China Lake CA USA

The California red scale Aonidiella aurantii (Maskell) (Homoptera: Diaspididae) is a major pest of California citrus, with infestations causing growers significant financial losses. It has recently developed resistance to traditional insecticide sprays. An alternative suppression tactic is the release of a biological control agent, Aphytis melinus DeBach (Aphelinidae: Hymenoptera) that feeds on red scale. Although many aspects of the red scale-Aphytis interaction are now understood, it is difficult to differentiate the effects of temperature and population fluctuations in the field. To investigate such complex interactions, we propose a new stochastic modeling technique, based on event-driven competing risks, that incorporates details of life histories as well as the host-parasitoid interaction. Our continuous-time, individual-oriented modeling approach quantifies relationships among individuals and describes the resulting coupling between the interacting populations. The event-structured simulation drives time in contrast to the usual time-driven stochastic dynamic programming. Our system, developed in the public domain using the R statistical package, allows for different biological clocks, since both red scale and Aphytis development respond to temperature (degree-days) while searching female Aphytis follow a diurnal time schedule, contingent upon temperature-dependent egg maturation. (C) 2002 Elsevier Science B.V. All rights reserved.

关键词： discrete event system stochastic Petri net individual-oriented model stochastic dynamic programming

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