Publications
207 results found
RUSTEM B, 1986, SPECIAL PROCEEDINGS ISSUE OF THE 7TH CONFERENCE OF THE SOCIETY-OF-ECONOMIC-DYNAMICS-AND-CONTROL - FOREWORD, JOURNAL OF ECONOMIC DYNAMICS & CONTROL, Vol: 10, Pages: 5-9, ISSN: 0165-1889
RUSTEM B, VELUPILLAI K, 1986, ON RATIONALIZING EXPECTATIONS USING RANK-ONE UPDATES OF THE KALMAN FILTER, JOURNAL OF ECONOMIC DYNAMICS & CONTROL, Vol: 10, Pages: 119-124, ISSN: 0165-1889
BECKER R, DWOLATZKY B, KARAKITSOS E, et al., 1986, RIVAL MODELS IN POLICY OPTIMIZATION, JOURNAL OF ECONOMIC DYNAMICS & CONTROL, Vol: 10, Pages: 75-81, ISSN: 0165-1889
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- Citations: 1
RUSTEM B, 1986, CONVERGENT STEPSIZES FOR CONSTRAINED OPTIMIZATION ALGORITHMS, JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS, Vol: 49, Pages: 135-160, ISSN: 0022-3239
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- Citations: 3
Rustem B, Velupillai K, 1985, ON RATIONALIZING EXPECTATIONS USING RANK-ONE UPDATES OF THE KALMAN FILTER., IFAC Proceedings Series, Pages: 1373-1378, ISSN: 0741-1146
The problem of maintaining the consistency of state estimates with a decision maker's expectations, is considered. The discrepancy between the estimate and its expectation defines a jump in the state estimate. The jump makes the estimate consistent with its expectation. A method is described for generating corresponding covariance matrices for the Kalman filter in order to make the filter consistent with such a jump. The method is based on appropriate rank-one modifications to these convariances. It is shown that the method is able to alter the estimates in the precise direction indicated by the expectations. The corresponding alteration to the Kalman gain is also discussed. Convergence becomes evident if expectations become, through learning, increasingly accurate estimates of the corresponding state vector.
KARAKITSOS E, RUSTEM B, 1985, OPTIMAL FIXED RULES AND SIMPLE FEEDBACK LAWS IN THE DESIGN OF ECONOMIC-POLICY, AUTOMATICA, Vol: 21, Pages: 169-180, ISSN: 0005-1098
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- Citations: 7
RUSTEM B, 1985, OPTIMIZATION OVER TIME - DYNAMIC-PROGRAMMING AND STOCHASTIC-CONTROL - WHITTLE,P, ECONOMICA, Vol: 52, Pages: 275-276, ISSN: 0013-0427
RUSTEM B, 1984, A CLASS OF SUPERLINEARLY CONVERGENT PROJECTION ALGORITHMS WITH RELAXED STEPSIZES, APPLIED MATHEMATICS AND OPTIMIZATION, Vol: 12, Pages: 29-43, ISSN: 0095-4616
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- Citations: 9
RUSTEM B, VELUPILLAI K, 1984, COOPERATION BETWEEN POLITICIANS AND ECONOMETRICIANS AND THE SEARCH FOR OPTIMAL ECONOMIC-POLICY, JOURNAL OF POLICY MODELING, Vol: 6, Pages: 341-350, ISSN: 0161-8938
KARAKITSOS E, RUSTEM B, 1984, OPTIMALLY DERIVED FIXED RULES AND INDICATORS, JOURNAL OF ECONOMIC DYNAMICS & CONTROL, Vol: 8, Pages: 33-64, ISSN: 0165-1889
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- Citations: 12
Rustem B, 1982, Applied stochastic control and management science : A. Bensoussan, P. Kleindorfer and C. S. Tapiero, eds., (North-Holland Publishing Company, Amsterdam, 1980) pp. xv + 304, $53.75, Vol: 4, Pages: 123-124
RUSTEM B, 1982, APPLIED STOCHASTIC-CONTROL AND MANAGEMENT SCIENCE - BENSOUSSAN,A, KLEINDORFER,P, TAPIERO,CS, JOURNAL OF ECONOMIC DYNAMICS & CONTROL, Vol: 4, Pages: 123-124, ISSN: 0165-1889
KARAKITSOS E, RUSTEM B, 1982, INFLATION, UNEMPLOYMENT AND INTERMEDIATE TARGETS, APPLIED ECONOMICS, Vol: 14, Pages: 421-436, ISSN: 0003-6846
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- Citations: 1
WESTCOTT JH, RUSTEM B, KARAKITSOS E, 1982, MACROECONOMIC POLICY FORMULATION - A CONTRIBUTION FROM CONTROL-THEORY, IEE PROCEEDINGS-D CONTROL THEORY AND APPLICATIONS, Vol: 129, Pages: 151-162, ISSN: 0143-7054
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- Citations: 3
Karakitsos E, Rustem B, Zarrop MB, 1981, THE INDICATOR SYSTEM AND U.K. MONETARY POLICY, Bulletin of Economic Research, Vol: 33, Pages: 91-101, ISSN: 0307-3378
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- Citations: 1
RUSTEM B, ZARROP MB, 1981, A QUASI-NEWTON ALGORITHM FOR THE CONTROL OF LARGE NON-LINEAR ECONOMETRIC-MODELS, LARGE SCALE SYSTEMS IN INFORMATION AND DECISION TECHNOLOGIES, Vol: 2, Pages: 105-111, ISSN: 0167-420X
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- Citations: 6
Rustem B, Zarrop MB, 1979, A newton-type method for the optimization and control of non-linear econometric models, Journal of Economic Dynamics and Control, Vol: 1, Pages: 283-300, ISSN: 0165-1889
The optimal control of any large and non-linear econometric model is often constrained by the computational complexity demanded by the optimisation algorithm and the size of the model. A simple Newton-type algorithm is described that is easily implementable and computationally fairly efficient. Numerical results using the macroeconomic model developed by the London Business School are reported. © 1979 North-Holland.
RUSTEM B, VELUPILLAI K, WESTCOTT JH, 1978, RESPECIFYING WEIGHTING MATRIX OF A QUADRATIC OBJECTIVE FUNCTION, AUTOMATICA, Vol: 14, Pages: 567-582, ISSN: 0005-1098
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- Citations: 15
CRAINE R, RUSTEM B, 2 SECTIONS FOR JOURNAL-OF-ECONOMIC-DYNAMICS-AND-CONTROL - FOREWORD, JOURNAL OF ECONOMIC DYNAMICS & CONTROL, Vol: 19, Pages: 1-2, ISSN: 0165-1889
Rustem B, WORST-CASE DESIGN IN OPTIMAL PORTFOLIOS
Optimal decisions robust to future uncertainties are considered. Both continuous and discrete sets of scenarios are discussed with algorithms for solving both cases. In the case of the former a quasi-Newton algorithm is discussed and in the case of the latter, a fast and easily implementable approach is introduced. Optimal portfolio results are used to illustrate the robustness properties of the strategy. A macroeconomic example is also considered.
Parpas P, Rustem B, Towards A Grid Market
In this paper we discuss a basic framework for a grid computing market. It has long been argued that pricing of computer resources can act as a scheduling protocol. We take this idea to its natural conclusion by discussing the basic properties of such a model. We introduce agents that own computer resources on the grid. We allow the agents to trade resources as well as consume resources for the benefit of their own computing needs. The aim is to study the behavior of such agents and discuss existence of equilibria between the price process and consumption of resources. At such an equilibrium point all the resources are consumed as soon as they are made available, and the market is at zero net supply.
Zakovic S, Rustem B, Wieland V, Optimisation of Stochastic Systems and Worst-case Analysis
Rustem B, Wieland V, Zakovic S, Stochastic Optimization and Worst Case Analysis in Monetary Policy Design
In this paper we compare expected loss minimization to worst-case or minimax analysis in the design of simple Taylor-style rules for monetary policy using a small model estimated for the euro area by Orphanides and Wieland (2000). We find that rules optimized under a minimax objective in the presence of general parameter and shock uncertainty do not imply extreme policy activism. Such rules tend to obey the Brainard principle of cautionary policy-making in much the same way as rules derived by expected loss minimization. Rules derived by means of minimax analysis are effective insurance policies limiting maximum loss over ranges of parameter values to be set by the policy-maker. In practice, we propose to set these ranges with an eye towards the cost of such insurance cover in terms of the implied increase in expected inflation variability.
Zakovic S, Wieland V, Rustem B, Stochastic Optimisation and Worst Case Analysis in Monetary Policy Design
In this paper, we show how stochastic optimisation and worst-case analysis can be used together in order to provide central banks with a straightforward tool for selecting a policy rule that limits worst-case outcomes while at the same time providing reasonably good performance on average. We conduct this analysis within a simple estimated model of the euro area with adaptive expectations. In particular, we consider not only uncertainty due to additive shocks but also uncertainty with respect to all the parameters of the model, including multiplicative parameters and potential nonlinearities in the inflation-output relationship. In terms of monetary policy we focus on the optimal choice of response coefficients in a Taylor-style interest rate rule that responds to inflation and the output gap and we evaluate the performance of this type of rule by means of a standard quadratic loss function in output and inflation. We then compare the rules obtained by the two different methods by comparing their respective performance in the worst-case scenario as well as the overall expected performance given the empirical probability distributions.
Wieland V, Rustem B, Zakovic S, Mean Variance Optimization of Forward Looking Systems and Worst-case Analysis
In this paper we consider expected value and mean variance optimization of a general forward--looking stochastic model. The problem is transformed into a general--nonlinear programming problem by adding extra constraints, which restrict the policy maker to commit to a certain policy. Based on this policy,and the rest of the economic structure, the agents can forecast future states except for random future disturbances. We present algorithms for computing optimal expected values based on iterative Taylor expansion and an interior point method for computing minimax robust policies. The results from both approaches are compared in order to assess the relative advantage of each approach and measure robustness against performance, and are also compared against DYNARE - a program for solving rational expectations models
Gulpinar N, Rustem B, Robust investment policies with bound forecasts
We present a continuous minimax model for robust portfolio optimization based on worst-case analysis. The classical Markowitz framework is extended to continuous minimax with upper and lower bounds on the return scenarios and a discrete number of rival risk scenarios. The model integrates benchmark relative computations in view of scalable (not fixed) transaction costs. It evaluates worst-case optimal strategies in view of upper and lower bounds on forecast return and a discrete set of risk scenarios. Robustness arises from the non-inferiority of the min-max strategy. The robust optimal policies are obtained simultaneously with the worst-case scenario. We apply the model to a selection of investment problem and evaluate the ex-ante performance of the strategy using historical data.
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