nep-cmp New Economics Papers
on Computational Economics
Issue of 2009‒09‒11
four papers chosen by
Stan Miles
Thompson Rivers University

  1. Problems in the numerical simulation of models with heterogeneous agents and economic distortions By Adrian Peralta-Alva; Manuel S. Santos
  2. Applying a global optimisation algorithm to Fund of Hedge Funds portfolio optimisation By Thapar, Rishi; Minsky, Bernard; Obradovic, M; Tang, Qi
  3. LOLA 1.0 : Luxembourg OverLapping generation model for policy Analysis By Olivier Pierrard; Henri R. Sneessens
  4. Disruption Management of Rolling Stock in Passenger Railway Transportation By Nielsen, L.K.; Maroti, G.

  1. By: Adrian Peralta-Alva; Manuel S. Santos
    Abstract: Our work has been concerned with the numerical simulation of dynamic economies with heterogeneous agents and economic distortions. Recent research has drawn attention to inherent difficulties in the computation of competitive equilibria for these economies: A continuous Markovian solution may fail to exist, and some commonly used numerical algorithms may not deliver accurate approximations. We consider a reliable algorithm set forth in Feng et al. (2009), and discuss problems related to the existence and computation of Markovian equilibria, as well as convergence and accuracy properties. We offer new insights into numerical simulation.
    Keywords: Econometric models
    Date: 2009
  2. By: Thapar, Rishi; Minsky, Bernard; Obradovic, M; Tang, Qi
    Abstract: Portfolio optimisation for a Fund of Hedge Funds (“FoHF”) has to address the asymmetric, non-Gaussian nature of the underlying returns distributions. Furthermore, the objective functions and constraints are not necessarily convex or even smooth. Therefore traditional portfolio optimisation methods such as mean-variance optimisation are not appropriate for such problems and global search optimisation algorithms could serve better to address such problems. Also, in implementing such an approach the goal is to incorporate information as to the future expected outcomes to determine the optimised portfolio rather than optimise a portfolio on historic performance. In this paper, we consider the suitability of global search optimisation algorithms applied to FoHF portfolios, and using one of these algorithms to construct an optimal portfolio of investable hedge fund indices given forecast views of the future and our confidence in such views.
    Keywords: portfolio optimisation; optimization; fund of hedge funds; global search optimisation; direct search; pgsl; hedge fund portfolio
    JEL: G11 C63 C15 C61
    Date: 2009–08–19
  3. By: Olivier Pierrard; Henri R. Sneessens
    Abstract: We build on the DSGE literature to propose an overlapping generation model for Luxembourg.By way of illustration, the model is then used to study the consequences of the ageing of the population and the potential effects of alternative macroeconomic policies.
    Date: 2009–04
  4. By: Nielsen, L.K.; Maroti, G. (Erasmus Research Institute of Management (ERIM), RSM Erasmus University)
    Abstract: This paper deals with real-time disruption management of rolling stock in passenger railway transportation. We present a generic framework for modeling disruptions in railway rolling stock schedules. The framework is presented as an online combinatorial decision problem where the uncertainty of a disruption is modeled by a sequence of information updates. To decompose the problem we propose a rolling horizon approach where only rolling stock decisions within a certain time horizon from the time of rescheduling are taken into account. The schedules are then revised as the situation progresses and more accurate information becomes available. We extend an existing model for rolling stock scheduling to the specific requirements of the real-time case and apply it in the rolling horizon framework. We perform computational tests on instances constructed from real life cases and explore the consequences of different settings of the approach for the trade-off between solution quality and computation time.
    Keywords: passenger railway transportation;disruptions;combinatorial decision problem
    Date: 2009–08–18

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