nep-cmp New Economics Papers
on Computational Economics
Issue of 2007‒04‒09
eleven papers chosen by
Stan Miles
Thompson Rivers University

  1. A branch and price algorithm for the combined vehicle routing and scheduling problem with synchronization constraints By Bredström, David; Rönnqvist, Mikael
  2. An Agent-Based Computational Laboratory for Wholesale Power Market Design By Sun, Junjie; Tesfatsion, Leigh S.
  3. Nonlinear Combination of Financial Forecast with Genetic Algorithm By Ozun, Alper; Cifter, Atilla
  4. Computable General equilibrium Models in Environmental and Resource Economics By Conrad, Klaus
  5. Textiles Protection and Poverty in South Africa/La protection du secteur des textiles et la pauvreté en Afrique du Sud: une analyse en équilibre général calculable dynamique micro-simulé By Ramos Mabugu; Margaret Chitiga
  6. Evidence-based Trade Policy Decision Making in Australia and the Development of Computable General Equilibrium Modelling By Peter B. Dixon
  7. Open-Source Software for Power Industry Research, Teaching, and Training: A DC-OPF Illustration By Sun, Junjie; Tesfatsion, Leigh S.
  8. Screening experiments for simulation : a review By Kleijnen,Jack P.C.
  9. Application of machine learning to short-term equity return prediction By Yan, Robert; Nuttall, John; Ling, Charles
  10. Multiscale Systematic Risk: An Application on ISE-30 By Cifter, Atilla; Ozun, Alper
  11. Parallel implementation of a semidefinite programming solver based on CSDP on a distributed memory cluster By Ivanov,I.D.; Klerk,E. de

  1. By: Bredström, David (Department of Mathematics, Linköping University); Rönnqvist, Mikael (Dept. of Finance and Management Science, Norwegian School of Economics and Business Administration)
    Abstract: In this paper we present a branch and price algorithm for the combined vehicle routing and scheduling problem with synchronization constraints. The synchronization constraints are used to model situations when two or more customers need simultaneous service. The synchronization constraints impose a temporal dependency between vehicles, and it follows that a classical decomposition of the vehicle routing and scheduling problem is not directly applicable. With our algorithm, we have solved 44 problems to optimality from the 60 problems used for numerical experiments. The algorithm performs time window branching, and the number of subproblem calls is kept low by adjustment of the columns service times.
    Keywords: Routing; Scheduling; Synchronization; Branch and Price
    JEL: C44 C61
    Date: 2007–03–27
  2. By: Sun, Junjie; Tesfatsion, Leigh S.
    Abstract: This study reports on the model development and open-source implementation (in Java) of an agent-based computational wholesale power market organized in accordance with core FERC-recommended design features and operating over a realistically rendered transmission grid subject to congestion effects. The traders within this market model are strategic profit-seeking agents whose learning behaviors are based on data from human-subject experiments. Our key experimental focus is the complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance. Market power findings for a dynamic 5-node transmission grid test case are presented for concrete illustration.
    Keywords: Restructured electricity markets, Market design, Learning Traders, Transmission grid congestion, Market power, Agent-based computational economics
    JEL: C0 C6 D4 D43 L1 L13 L5 Q4
    Date: 2007–03–31
  3. By: Ozun, Alper; Cifter, Atilla
    Abstract: Complexity in the financial markets requires intelligent forecasting models for return volatility. In this paper, historical simulation, GARCH, GARCH with skewed student-t distribution and asymmetric normal mixture GRJ-GARCH models are combined with Extreme Value Theory Hill by using artificial neural networks with genetic algorithm as the combination platform. By employing daily closing values of the Istanbul Stock Exchange from 01/10/1996 to 11/07/2006, Kupiec and Christoffersen tests as the back-testing mechanisms are performed for forecast comparison of the models. Empirical findings show that the fat-tails are more properly captured by the combination of GARCH with skewed student-t distribution and Extreme Value Theory Hill. Modeling return volatility in the emerging markets needs “intelligent” combinations of Value-at-Risk models to capture the extreme movements in the markets rather than individual model forecast.
    Keywords: Forecast combination; Artificial neural networks; GARCH models; Extreme value theory; Christoffersen test
    JEL: G0 C52 C32
    Date: 2007–02–01
  4. By: Conrad, Klaus (Institut für Volkswirtschaft und Statistik (IVS))
    Abstract: The objective of this paper is to give a survey of the theory and application of computable general equilibrium models (CGE-models) in environmental and resource economics. Although CGE models cannot be used to forecast business cycles, they can indicate likely magnitudes of policy-induced changes from future baselines, and they are indispensable for ranking alternative policy measures in environmental policies. The paper emphasizes the important of general versus partial equilibrium models and the advantage of CGE models compared to other macroeconomic models and standard input-output models. It presents models of producer and consumer behavior, of technical change, of abatement technologies and of trade. It also presents several simulation studies in environmental economics based on the use of CGE models. It reviews environmentally related CGE analyses on topics such as global warming, the costs of environmental regulation under different instruments and the double dividend issue. It finally describes some models which look at a two-way link between the environment and economic performance.
  5. By: Ramos Mabugu; Margaret Chitiga
    Abstract: There is an important debate going on in South Africa on whether to apply safeguard trade barriers to protect textiles. This presents an interesting case of how a country might use safeguard trade barriers in order to better achieve a domestic policy objective. Much of the current discourse on textiles protection focuses on static effects of protection. The aim of this paper is to take this discussion a step further by introducing the effect of textiles protection on poverty and its dynamics. To assess these effects of protection, a sequential dynamic computable general equilibrium model linked to a nationally representative household survey of 2000 is used. The simulation involves a doubling of the import tariffs on textiles. The textile sector is, obviously, the biggest winner, followed by the service sector, which sells more than half of its production as inputs for the textile sector. All other sectors experience falling output with the worst affected being the export-oriented sectors. Because the protected sectors are relatively more labour intensive, wages increase in both the short and long terms. Capital returns are sector specific in the short run and go up markedly for textiles and services but decline for all the other sectors. Overall, welfare falls both in the short and long term as the rise in factor prices is completely offset by the increase in consumer prices. The proportion of people living below US$2 per day increases marginally in the short run following increased textiles protection because of the observed increase in consumer price index that is higher than the increase in consumption for most households. Unskilled Indians are the only group to experience a reduction in poverty and welfare increases in the short run. The average poverty gap and the squared poverty gap also follow the same pattern as poverty headcount because most households are being pushed into poverty./L'Afrique du Sud représente un cas idéal pour évaluer la pertinence de mettre en place des barrières commerciales de sauvegarde pour protéger le secteur des textiles. Cette étude évalue les impacts de la protection tarifaire du secteur sud-africain des textiles au moyen d'un modèle d'équilibre général calculable dynamique, de nature séquentielle, lié aux micro données provenant de l'enquête nationale auprès des ménages de 2000. Les résultats de la simulation démontrent que le secteur des textiles est le plus grand bénéficiaire de cette mesure, suivi du secteur des services. Tous les autres secteurs enregistrent une décroissance de leur production et, parmi eux, ceux à vocation exportatrice s'avèrent être les plus sévèrement touchés. Les salaires augmentent à court et à long terme. Le capital étant immobile à court terme entre les secteurs, son rendement augmente sensiblement dans les activités de production des textiles et des services, mais diminue dans les autres activités. Le bien-être diminue à la fois à court et à long terme alors que la pauvreté augmente de façon significative à court terme.
    Keywords: Sequential dynamic CGE, microsimulation, textiles, protection, poverty, welfare, growth, South Africa/Équilibre général calculable, MEGC dynamique séquentiel, micro simulation, textiles, protection, pauvreté, bien-être, croissance, Afrique du Sud
    JEL: D58 E27 F17 I32 O15 O55
    Date: 2006
  6. By: Peter B. Dixon
    Abstract: This paper explains why evidence-based trade policy decision making is heavily reliant on results generated by CGE models and why the development and application of these modelling has been particularly active in Australia. The paper provides a short history of CGE modelling and describes the impetus to the field provided by two factors: (a) the failures of less theoretically formal approaches; and (b) the recognition of the ability of CGE modelling to handle policy-relevant detail. The paper argues that CGE modelling flourished in Australia because Australia had the right issue, the right institutions and the right model.
    Keywords: Trade policy, CGE modeling
    JEL: A11 F14
    Date: 2006–10
  7. By: Sun, Junjie; Tesfatsion, Leigh S.
    Abstract: Software currently available for power industry studies is largely proprietary. Lack of open-source access prevents users from gaining a complete and accurate understanding of what has been implemented, restricts the ability of users to experiment with new software features, and hinders users from tailoring software to specific training scenarios. This study reports on the development of a stand-alone open-source Java solver for DC optimal power flow (DC-OPF) problems suitable for research, teaching, and training purposes. The DC-OPF solver is shown to match or exceed the accuracy of BPMPD, a proprietary third-party QP solver highly recommended by MatPower, when tested on a public repository of small to medium-sized QP problems. The capabilities of the DC-OPF solver are illustrated for a 5-node DC-OPF test case commonly used for training purposes.
    Keywords: AC optimal power flow, AMES wholesale power market framework, DC OPF approximation, DCOPFJ, dual active-set method, Java, Lagrangian augmentation, QuadProgJ, strictly convex quadratic programming.
    JEL: C0 Q4
    Date: 2007–03–31
  8. By: Kleijnen,Jack P.C. (Tilburg University, Center for Economic Research)
    Abstract: This article reviews so-called screening in simulation; i.e., it examines the search for the really important factors in experiments with simulation models that have very many factors (or inputs). The article focuses on a most e¢ cient and e¤ective screening method, namely Sequential Bifurcation. It ends with a discussion of possible topics for future research, and forty references for further study.
    Keywords: screening;metamodel;response surface;design
    JEL: C0 C1 C9
    Date: 2007
  9. By: Yan, Robert; Nuttall, John; Ling, Charles
    Abstract: Cooper showed how a filter method could be used to predict equity returns for the next week by using information about returns and volume for the two previous weeks. Cooper's method may be regarded as a crude method of Machine Learning. Over the last 20 years Machine Learning has been successfully applied to the modeling of large data sets, often containing a lot of noise, in many different fields. When applying the technique it is important to fit it to the specific problem under consideration. We have designed and applied to Cooper's problem a practical new method of Machine Learning, appropriate to the problem, that is based on a modification of the well-known kernel regression method. We call it the Prototype Kernel Regression method (PKR). In both the period 1978-1993 studied by Cooper, and the period 1994-2004, the PKR method leads to a clear profit improvement compared to Cooper's approach. In all of 48 different cases studied, the period pre-cost average return is larger for the PKR method than Cooper's method, on average 37% higher, and that margin would increase as costs were taken into account. Our method aims to minimize the danger of data snooping, and it could plausibly have been applied in 1994 or earlier. There may be a lesson here for proponents of the Efficient Market Hypothesis in the form that states that profitable prediction of equity returns is impossible except by chance. It is not enough for them to show that the profits from an anomaly-based trading scheme disappear after costs. The proponents should also consider what would have been plausible applications of more sophisticated Machine Learning techniques before dismissing evidence against the EMH.
    JEL: C02
    Date: 2006–04–03
  10. By: Cifter, Atilla; Ozun, Alper
    Abstract: In this study, variance changing to the scale and multi-scale Capital Asset Pricing Model (CAPM) is tested by Wavelets as a new analysis method in finance and economics. It introduces a new approach to the variance changing to the scale as a general risk indicator, and to multi-scale CAPM portfolio theory as a systematic risk indicator. In the study, variance changes to scale and systematic risk changes to scale of 10 stocks in ISE-30 have been determined. The ability of the investors to conduct risk based analysis up to 128 days allows them to determine the risk level to the scale (stock holding period). According to the study results; it is determined that the variances of 10 stocks from ISE 30 change according to the scale and variance differentiation as an expression of general risk level increase starting from the 1st scale (1 to 4 days). In multi-scale CAPM, it is determined that systematic risk of all stocks is changed to frequency (scale) and increased at higher scales. The finding as to beta and return at the high levels shall be in stronger form evidenced by Gencay et al (2005) is determined as not applicable to ISE 30. The risk and return for ISE 30 are close to the positive in the 3rd scale (32 days), but they are in the same direction for the other scales. This finding shows that the risk-return maximization of a portfolio of 10 stocks from ISE may be achieved at a level of 32 days and the risk will be higher than the return in the portfolios established at those levels different than 32 days.
    Keywords: Multiscale systematic risk; CAPM; wavelets; multiscale variance
    JEL: G0 G1
    Date: 2007–03–01
  11. By: Ivanov,I.D.; Klerk,E. de (Tilburg University, Center for Economic Research)
    Abstract: In this paper we present the algorithmic framework and practical aspects of implementing a parallel version of a primal-dual semidefinite programming solver on a distributed memory computer cluster. Our implementation is based on the CSDP solver and uses a message passing interface (MPI), and the ScaLAPACK library. A new feature is implemented to deal with problems that have rank-one constraint matrices. We show that significant improvement is obtained for a test set of problems with rank one constraint matrices. Moreover, we show that very good parallel efficiency is obtained for large-scale problems where the number of linear equality constraints is very large compared to the block sizes of the positive semidefinite matrix variables.
    Keywords: 90C22;90C51; semidefinite programming;interior point methods;parallel computing; distributed memory cluster
    JEL: C60
    Date: 2007

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