nep-cmp New Economics Papers
on Computational Economics
Issue of 2011‒09‒22
six papers chosen by
Stan Miles
Thompson Rivers University

  1. Numerical integration of Heath-Jarrow-Morton model of interest rates By M. Krivko; M. V. Tretyakov
  2. Cost-Sensitive Decision Trees with Completion Time Requirements By Hung-Pin KAO; Kwei TANG; Jen TANG
  3. Taxing capital is not a bad idea indeed: the role of human capital and labor-market frictions By Chen, Been-Lon; Chen, Hung-Ju; Wang, Ping
  4. Econophysics: agent-based models By Anirban Chakraborti; Ioane Muni Toke; Marco Patriarca; Frédéric Abergel
  5. Using MOEAs To Outperform Stock Benchmarks In The Presence of Typical Investment Constraints By Andrew Clark; Jeff Kenyon
  6. On the informativeness of persistence for mutual funds' performance evaluation using partial frontiers By Amparo Soler Domínguez; Juan Carlos Matallín Sáez; Emili Tortosa Ausina

  1. By: M. Krivko; M. V. Tretyakov
    Abstract: We propose and analyze numerical methods for the Heath-Jarrow-Morton (HJM) model. To construct the methods, we first discretize the infinite dimensional HJM equation in maturity time variable using quadrature rules for approximating the arbitrage-free drift. This results in a finite dimensional system of stochastic differential equations (SDEs) which we approximate in the weak and mean-square sense using the general theory of numerical integration of SDEs. The proposed numerical algorithms are computationally highly efficient due to the use of high-order quadrature rules which allow us to take relatively large discretization steps in the maturity time without affecting overall accuracy of the algorithms. Convergence theorems for the methods are proved. Results of some numerical experiments with European-type interest rate derivatives are presented.
    Date: 2011–09
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1109.2557&r=cmp
  2. By: Hung-Pin KAO; Kwei TANG; Jen TANG
    Abstract: In many classification tasks, managing costs and completion times are the main concerns. In this paper, we assume that the completion time for classifying an instance is determined by its class label, and that a late penalty cost is incurred if the deadline is not met. This time requirement enriches the classification problem but posts a challenge to developing a solution algorithm. We propose an innovative approach for the decision tree induction, which produces multiple candidate trees by allowing more than one splitting attribute at each node. The user can specify the maximum number of candidate trees to control the computational efforts required to produce the final solution. In the tree-induction process, an allocation scheme is used to dynamically distribute the given number of candidate trees to splitting attributes according to their estimated contributions to cost reduction. The algorithm finds the final tree by backtracking. An extensive experiment shows that the algorithm outperforms the top-down heuristic and can effectively obtain the optimal or near-optimal decision trees without an excessive computation time.
    Keywords: classification, decision tree, cost and time sensitive learning, late penalty
    Date: 2010–09
    URL: http://d.repec.org/n?u=RePEc:pur:prukra:1264&r=cmp
  3. By: Chen, Been-Lon; Chen, Hung-Ju; Wang, Ping
    Abstract: In a second-best optimal growth setup with only factor taxes as available instruments, is it optimal to fully replace capital by labor income taxation? The answer is generally positive based on Chamley, Judd, Lucas, and many follow-up studies. In the present paper, we revisit this important tax reform-related issue by developing a human capital-based endogenous growth framework with frictional labor search and matching. We allow each firm to create multiple vacancies and each worker to determine labor market participation endogenously. We consider a benevolent fiscal authority to finance direct transfers to households and unemployment compensation only by factor taxes. We then conduct dynamic tax incidence exercises using a model calibrated to the U.S. economy with a pre-existing 20% flat tax on both the capital and labor income. Our numerical results suggest that, due to a dominant channel via the interactions between the firm's vacancy creation and the worker's market participation, it is optimal to switch partly by a modest margin from capital to labor taxation in a benchmark economy where human capital formation depends on both the physical and human capital stocks. When the human capital accumulation process is independent of physical capital, the optimal tax mix features a slightly larger shift from capital to labor taxation; when we remove the extensive margin of the labor-leisure trade-off, such a shift is much larger. In either case, however, the optimal capital tax rate is far above zero.
    Keywords: Tax Incidence; Endogenous Human Capital Accumulation; Labor-Market Search and Matching Frictions
    JEL: E62 H22 O40 J20
    Date: 2011–08–30
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:33209&r=cmp
  4. By: Anirban Chakraborti (MAS - Mathématiques Appliquées aux Systèmes - EA 4037 - Ecole Centrale Paris); Ioane Muni Toke (MAS - Mathématiques Appliquées aux Systèmes - EA 4037 - Ecole Centrale Paris); Marco Patriarca (IFISC - Instituto de Fisica Interdisciplinaire y Sistemas Complejos - Instituto de Fisica Interdisciplinaire y Sistemas Complejos); Frédéric Abergel (MAS - Mathématiques Appliquées aux Systèmes - EA 4037 - Ecole Centrale Paris)
    Abstract: This article is the second part of a review of recent empirical and theoretical developments usually grouped under the heading Econophysics. In the first part, we reviewed the statistical properties of financial time series, the statistics exhibited in order books and discussed some studies of correlations of asset prices and returns. This second part deals with models in Econophysics from the point of view of agent-based modeling. Of the large number of multiagent- based models, we have identified three representative areas. First, using previous work originally presented in the fields of behavioral finance and market microstructure theory, econophysicists have developed agent-based models of order-driven markets that we discuss extensively here. Second, kinetic theory models designed to explain certain empirical facts concerning wealth distribution are reviewed. Third, we briefly summarize game theory models by reviewing the now classic minority game and related problems.
    Date: 2011–06–24
    URL: http://d.repec.org/n?u=RePEc:hal:journl:hal-00621059&r=cmp
  5. By: Andrew Clark; Jeff Kenyon
    Abstract: Portfolio managers are often constrained by turnover limits, minimum and maximum stock positions, cardinality, a target market capitalization and sometimes the need to hew to a style (growth or value). In addition, many portfolio managers choose stocks based upon fundamental data, e.g. price-to-earnings and dividend yield in an effort to maximize return. All of these are typical real-world constraints a portfolio manager faces. Another constraint, of sorts, is the need to outperform a stock index benchmark. Performance higher than the benchmark means a better compensation package. Underperforming the benchmark means a lesser compensation package. We use MOEAs to satisfy the above real-world constraints and consistently outperform typical performance benchmarks. Our first MOEA solves all the constraints (except turnover and position limits) and generates feasible portfolios. The second MOEA tests each of the potential feasible portfolios of the first MOEA by trading off mean return, variance, turnover and position limits. The best portfolio is chosen from these feasible portfolios and becomes the portfolio of choice for the next quarter. The MOEAs are applied to the following problems -- generate a series of monthly portfolios that outperform the S&P 500 over the past 30 years and generate a set of monthly portfolios that outperform the Russell 1000 Growth index over the last 15 years. Our two MOEAs accomplish both these goals on a risk adjusted and non-risk adjusted return basis
    Date: 2011–09
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1109.3488&r=cmp
  6. By: Amparo Soler Domínguez (Dpt. Finances i Comptabilitat); Juan Carlos Matallín Sáez (Dpt. Finances i Comptabilitat); Emili Tortosa Ausina (Universitat Jaume I)
    Abstract: The last few years have witnessed a rapid evolution in the literature evaluating mutual fund performance using frontier techniques. The instruments applied, mostly DEA (Data Envelopment Analysis) and, to a lesser extent, FDH (Free Disposal Hull), are able to encompass several dimensions of performance, but they also have some disadvantages that might be preventing a wider acceptance. The recently developed order-m and order-a partial frontiers overcome some of the disadvantages (they are robust with respect to extreme values and noise, and do not suffer from the well-known curse of dimensionality) while keeping the main virtues of DEA and FDH (they are fully-nonparametric). In this article we apply not only the non-convex counterpart of DEA, namely, FDH but also order-m and order-a partial frontiers to a sample of Spanish mutual funds. The results obtained for both order-m and order-a are useful, since a full ranking of mutual funds’ performance is obtained. We combine these methods with the literature on mutual fund performance persistence. By combining the two literatures we derive an algorithm for guiding the choice of m and a parameters intrinsic to order-m and order-a (respectively) based on mutual fund performance persistence. Los últimos años han sido testigos de una rápida evolución de la literatura que evalúa el rendimiento de fondos de inversión utilizando la metodología del enfoque frontera. Los instrumentos aplicados, principalmente DEA (Data Envelopment Analysis) y, en menor medida, FDH (Free Disposable Hull), son capaces de abarcar varios aspectos del rendimiento, pero también poseen algunas desventajas que podrían impedir una mayor aceptación. El recientemente desarrollado enfoque de las fronteras parciales de orden-m y de orden-alfa supera algunos de los inconvenientes (estos procedimientos son robustos con respecto a los valores extremos y perturbaciones aleatorias o ruido, y no sufren la conocida “maldición de la dimensionalidad” o curse of dimensionality), manteniendo las principales virtudes de DEA y FDH (ambas técnicas son absolutamente no paramétricas). En este artículo se aplica no sólo la versión no convexa de DEA, es decir, FDH, sino también para fronteras de orden-m y de orden-alfa cuya utilidad es notable, ya que se obtiene una clasificación completa del rendimiento de los fondos de inversión. En este trabajo se combinan estos métodos con la literatura existente relativa a la persistencia en el rendimiento de los fondos de inversión. Mediante la combinación de ambas literaturas deducimos un algoritmo capaz de guiar (o que sirva de referencia) en la elección de los parámetros intrínsecos m y alfa correspondientes a orden-m y a orden-alfa (respectivamente) en base a la persistencia en el rendimiento de los fondos de inversión.
    Keywords: eficiencia, fondos de inversión, enfoque de fronteras parciales, persistencia. efficiency, mutual funds, partial frontiers, persistence.
    Date: 2011–01
    URL: http://d.repec.org/n?u=RePEc:ivi:wpasec:2011-08&r=cmp

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