nep-cmp New Economics Papers
on Computational Economics
Issue of 2010‒05‒29
nine papers chosen by
Stan Miles
Thompson Rivers University

  1. Asset Allocation under Hierarchical Clustering By Jin Zhang; Dietmar Maringer
  2. A Social Network System for Analyzing Publication Activities of Researchers By Alireza Abbasi; Jorn Altmann
  3. Does vertical integration reduce investment reluctance in production chains? An agent-based real options approach By Balmann, Alfons; Musshoff, Oliver; Larsen, Karin
  4. Forecasting Realized Volatility with Linear and Nonlinear Univariate Models By Michael McAleer; Marcelo C. Medeiros
  5. Environmental tax reform and double dividend evidence By Maurizio Ciaschini, Rosita Pretaroli, Francesca Severini, Claudio Socci
  6. Robust and Adaptive Algorithms for Online Portfolio Selection By Theodoros Tsagaris; Ajay Jasra; Niall Adams
  7. Cross-Border Financial Surveillance: A Network Perspective By Marco Espinosa-Vega; Juan Sole
  8. The EAGLE. A model for policy analysis of macroeconomic interdependence in the Euro area By Sandra Gomes; Pascal Jacquinot; Massimiliano Pisani
  9. On downloading and using COIN-OR for solving lineal/integer optimization problems. By Gloria Pérez Sainz de Rozas; María Araceli Garín Martín

  1. By: Jin Zhang; Dietmar Maringer
    Abstract: This paper proposes a clustering asset allocation scheme which provides better risk-adjusted portfolio performance than those obtained from traditional asset allocation approaches such as the equal weight strategy and the Markowitz minimum variance allocation. The clustering criterion used, which involves maximization of the in-sample Sharpe ratio (SR), is different from traditional clustering criteria reported in the literature. Two evolutionary methods, namely Differential Evolution and Genetic Algorithm, are employed to search for such an optimal clustering structure given a cluster number. To explore the clustering impact on the SR, the in-sample and the out-of-sample SR distributions of the portfolios are studied using bootstrapped data as well as simulated paths from the single index market model. It was found that the SR distributions of the portfolios under the clustering asset allocation structure have higher mean values and skewness but approximately the same standard deviation and kurtosis than those in the non-clustered case. Genetic Algorithm is suggested as a more efficient approach than Differential Evolution for the purpose of solving the clustering problem.
    Keywords: Asset Allocation, Clustering Technique, Sharpe Ratio, Evolutionary Approach, Heuristic Optimization
    Date: 2010–05–17
  2. By: Alireza Abbasi; Jorn Altmann (Technology Management, Economics and Policy Program (TEMEP), Seoul National University)
    Abstract: Social networks play an increasingly important role in knowledge management, information retrieval, and collaboration. In order to leverage the full potential of social networks, social networks need to be supported through technical systems. Within this paper, we introduce such a technical system. It is called AcaSoNet. It is a system for identifying and managing social networks of researchers. In particular, AcaSoNet employs a combination of techniques to extract co-author relationships between researchers and to detect groups of persons with similar interest. Past systems have used either search engines to extract information about social networks from the Web (Web mining) or have required people¡¯s effort to enter their relationships to others into the system (as being done by most social network services). AcaSoNet, instead, uses a combination of these two types, thereby achieving data reliability and scalability. It extracts and collects data of researchers from the Web but allows researchers to modify the data. In the current version, our system can identify the social network based on publication lists and evaluate the publication activities of users within an academic community.
    Keywords: Social network systems, academic community, co-author relationship, publication analysis, productivity analysis, knowledge sharing, knowledge transfer, Web mining, performance analysis, and social network analysis.
    JEL: C43 C88 D83 L86
    Date: 2010–04
  3. By: Balmann, Alfons; Musshoff, Oliver; Larsen, Karin
    Abstract: This paper uses an agent-based real options approach to analyze whether stronger vertical integration reduces investment reluctance in pork production. A competitive model in which firms identify optimal investment strategies by using genetic algorithms is developed. Two production systems are compared: a perfectly integrated system and a system in which firms produce either the intermediate product (piglets) or the final product (pork). Simulations show that the spot market solution and the perfectly integrated system lead to a very similar production dynamics even with limited information on production capacities. The results suggest that, from a pure real options perspective, spot markets are not significantly inferior to perfectly integrated supply chains.
    Keywords: real options, supply chain, agent-based models, genetic algorithms, Agribusiness, Agricultural and Food Policy, Agricultural Finance, Institutional and Behavioral Economics, Productivity Analysis,
    Date: 2009–09
  4. By: Michael McAleer (University of Canterbury); Marcelo C. Medeiros
    Abstract: In this paper we consider a nonlinear model based on neural networks as well as linear models to forecast the daily volatility of the S&P 500 and FTSE 100 futures. As a proxy for daily volatility, we consider a consistent and unbiased estimator of the integrated volatility that is computed from high frequency intra-day returns. We also consider a simple algorithm based on bagging (bootstrap aggregation) in order to specify the models analyzed.
    Keywords: Financial econometrics; volatility forecasting; neural networks; nonlinear models; realized volatility; bagging
    Date: 2010–05–01
  5. By: Maurizio Ciaschini, Rosita Pretaroli, Francesca Severini, Claudio Socci (University of Macerata, Politechnical University of Marche)
    Abstract: <div style="text-align: justify;">The increasing attention to environmental damage and the problem of climate changes have led many studies to concentrate on environmental taxation as an incentive-based instrument of environmental policy. Focusing on the relationship among environmental, labour market policies and institutional sectors, this paper aims to investigate the economic effects of a fiscal reform designed with the intent of reducing the Greenhouse Gas (GHG) emissions, according to Kyoto Protocol. For this purpose, a Computable General Equilibrium (CGE) model is used with imperfection market for labour factor and a green tax on commodity output depending on the level of CO2 emission is introduced. Tax revenues are than completely distributed to the economy in order to reduce the income tax or to cut the regional tax on commodity value added. In this way a revenue-neutral environmental policy is tested and the double dividend and any other effect on national economy are assessed. The application will be done on a Social Accounting Matrix (SAM) for Italy for the 2003 year.</div>
    Keywords: Environmental taxation,CGE model,SAM
    JEL: O1 O11
    Date: 2010–05
  6. By: Theodoros Tsagaris; Ajay Jasra; Niall Adams
    Abstract: We present an online approach to portfolio selection. The motivation is within the context of algorithmic trading, which demands fast and recursive updates of portfolio allocations, as new data arrives. In particular, we look at two online algorithms: Robust-Exponentially Weighted Least Squares (R-EWRLS) and a regularized Online minimum Variance algorithm (O-VAR). Our methods use simple ideas from signal processing and statistics, which are sometimes overlooked in the empirical financial literature. The two approaches are evaluated against benchmark allocation techniques using 4 real datasets. Our methods outperform the benchmark allocation techniques in these datasets, in terms of both computational demand and financial performance.
    Date: 2010–05
  7. By: Marco Espinosa-Vega; Juan Sole
    Abstract: Effective cross-border financial surveillance requires the monitoring of direct and indirect systemic linkages. This paper illustrates how network analysis could make a significant contribution in this regard by simulating different credit and funding shocks to the banking systems of a number of selected countries. After that, we show that the inclusion of risk transfers could modify the risk profile of entire financial systems, and thus an enriched simulation algorithm able to account for risk transfers is proposed. Finally, we discuss how some of the limitations of our simulations are a reflection of existing information and data gaps, and thus view these shortcomings as a call to improve the collection and analysis of data on cross-border financial exposures.
    Keywords: Bank credit , Banking systems , Chile , Credit risk , Cross country analysis , Economic models , External shocks , Financial crisis , Financial risk , Financial sector , Global Financial Crisis 2008-2009 , Risk management ,
    Date: 2010–04–23
  8. By: Sandra Gomes (Bank of Portugal, Economic Research Department, Av. Almirante Reis 71, 1150-012 Lisbon, Portugal.); Pascal Jacquinot (European Central Bank, Directorate General of Research, Kaiserstrasse 29, 60311 Frankfurt am Main, Germany.); Massimiliano Pisani (Bank of Italy, Research Department, Via Nazionale 91, 00184 Rome, Italy.)
    Abstract: Building on the New Area Wide Model, we develop a 4-region macroeconomic model of the euro area and the world economy. The model (EAGLE, Euro Area and Global Economy model) is microfounded and designed for conducting quantitative policy analysis of macroeconomic interdependence across regions belonging to the euro area and between euro area regions and the world economy. Simulation analysis shows the transmission mechanism of region-specific or common shocks, originating in the euro area and abroad. JEL Classification: C53, E32, E52, F47.
    Keywords: Open-economy macroeconomics, DSGE models, econometric models, policy analysis.
    Date: 2010–05
  9. By: Gloria Pérez Sainz de Rozas (Dpto. Matemática Aplicada y Estadística e I.O. (UPV/EHU)); María Araceli Garín Martín (Dpto. Economía Aplicada III. (UPV/EHU))
    Abstract: The aim of this technical report is to present some detailed explanations in order to help to use the open source software for optimization COIN-OR. In particular, we describe how to download, install and use the corresponding solvers under Windows and Linux operating systems. We will use an example taken from the literature, with the corresponding source code written in C++, to describe the whole process of editing, compiling and running the executable, to solve this optimization problem by using this software.
    Keywords: COIN-OR, source code, optimization software
    JEL: C6 C61 C63
    Date: 2010–05–20

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