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Libros sobre el tema "Computational economics"

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Autor: Grafiati
Publicado: 4 de junio de 2021
Última modificación: 21 de febrero de 2023

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1

Ruben, Mercado P. y Amman Hans M, eds. Computational economics. Princeton: Princeton University Press, 2006.

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2

Kendrick, David A. Computational economics. Princeton, N.J: Princeton University Press, 2006.

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3

Tesfatsion, Leigh. Handbook of Computational Economics: Agent-Based Computational Economics. Burlington: Elsevier, 2006.

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4

1959-, Chen Shu-Heng, Jain L. C y Tai Chung-Ching, eds. Computational economics: A perspective from computational intelligence. Hershey PA: Idea Group Pub., 2006.

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5

M, Amman Hans, Belsley David A y Pau L. F. 1948-, eds. Computational economics and econometrics. Dordrecht: Kluwer Academic Publishers, 1992.

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6

Amman, Hans M., David A. Belsley y Louis F. Pau, eds. Computational Economics and Econometrics. Dordrecht: Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-011-3162-9.

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7

Varian, Hal R., ed. Computational Economics and Finance. New York, NY: Springer New York, 1996. http://dx.doi.org/10.1007/978-1-4612-2340-5.

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8

1914-, Cooper William W. y Whinston Andrew B, eds. New directions in computational economics. Dordrecht: Kluwer Academic Publishers, 1994.

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9

Dadkhah, Kamran. Foundations of mathematical & computational economics. Mason, OH: Thomson South-Western, 2007.

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10

Cooper, W. W. y A. B. Whinston, eds. New Directions in Computational Economics. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-0770-9.

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11

Dadkhah, Kamran. Foundations of Mathematical and Computational Economics. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2011.

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12

Zopounidis, Constantin. Computational techniques in economics and finance. Hauppauge, N.Y: Nova Science Publishers, 2011.

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13

Chen, Shu-Heng. Computational Intelligence in Economics and Finance. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004.

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14

Chen, Shu-Heng y Paul P. Wang, eds. Computational Intelligence in Economics and Finance. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-662-06373-6.

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15

Dadkhah, Kamran. Foundations of Mathematical and Computational Economics. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-13748-8.

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16

Chen, Shu-Heng, Paul P. Wang y Tzu-Wen Kuo, eds. Computational Intelligence in Economics and Finance. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-72821-4.

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17

Willi, Semmler y SpringerLink (Online service), eds. Computational Methods in Economic Dynamics. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2011.

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18

Grassmann, Winfried K. Computational Probability. Boston, MA: Springer US, 2000.

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19

Brenner, Thomas, ed. Computational Techniques for Modelling Learning in Economics. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-5029-7.

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20

A, Barnett William, Deissenberg Christophe y Feichtinger Gustav 1940-, eds. Economic complexity: Non-linear dynamics, multi-agents economies, and learning. Amsterdam: Elsevier, 2004.

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21

Dynamic General Equilibrium Modelling: Computational Methods and Applications. Berlin: Springer, 2005.

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22

Heer, Burkhard. Dynamic general equilibrium modeling: Computational methods and applications. 2a ed. Berlin: Springer, 2009.

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23

A, Belsley David, ed. Computational techniques for econometrics and economic analysis. Dordrecht [Netherlands]: Kluwer Academic Publishers, 1994.

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24

Gil-Lafuente, Anna Maria, Josefa Boria, Agustín Torres, José M. Merigó y Janusz Kacprzyk, eds. Computational and Decision Methods in Economics and Business. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-93787-4.

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25

Kontoghiorghes, Erricos John, Berc Rustem y Stavros Siokos, eds. Computational Methods in Decision-Making, Economics and Finance. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4757-3613-7.

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26

John, Kontoghiorghes Erricos, Rustem Berc y Siokos Stavros, eds. Computational methods in decision-making, economics and finance. Dordrecht: Kluwer Academic Publishers, 2002.

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27

Computational optimization in economics and finance research compendium. Hauppauge, N.Y: Nova Science Publisher's, 2012.

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28

Baba, Norio. Computational Intelligence in Games. Heidelberg: Physica-Verlag HD, 2001.

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29

A, Belsley David y Kontoghiorghes Erricos John, eds. Handbook of computational econometrics. Chichester, U.K: Wiley, 2009.

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30

Kendrick, David A., P. Ruben Mercado y Hans M. Amman. Computational Economics. Princeton University Press, 2005.

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31

Humphreys, Paul. Computational Economics. Editado por Don Ross y Harold Kincaid. Oxford University Press, 2009. http://dx.doi.org/10.1093/oxfordhb/9780195189254.003.0013.

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Computational economics is a relatively new research technique in economics, but it is inexorably taking its place alongside the more traditional methods of general theory, abstract modeling, data analysis, and the more recent experimental economics. Perhaps because of its relative newness, the term computational economics currently has no determinate meaning. In contemporary use, it refers to a heterogeneous cluster of techniques implemented on concrete digital computers ranging from the numerical solution of the Black-Scholes partial differential equation for pricing options through automated trading strategies to agent-based computer simulations of the evolution of cooperation. Because of this heterogeneity, it is not possible to provide a comprehensive coverage of the topic in this article. Another reason for this restricted scope is that many of the methods used in computational economics have considerable technical interest but no particular philosophical relevance.
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32

Afonso, Oscar y Paulo B. Vasconcelos. Computational Economics. Routledge, 2015. http://dx.doi.org/10.4324/9781315716992.

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33

Computational Economics. Routledge, 2015.

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34

(Editor), Leigh Tesfatsion y Kenneth L. Judd (Editor), eds. Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics (Handbook of Computational Economics). North Holland, 2006.

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35

Chang, Myong-Hun. Computational Industrial Economics. Editado por Shu-Heng Chen, Mak Kaboudan y Ye-Rong Du. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199844371.013.42.

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Approach to Dynamic Analysis in Industrial Organization This chapter offers a basic agent-based computational model of industry dynamics that allows us to study the evolving industry structure through entry and exit of heterogeneous firms. The field of modern industrial economics focuses on the structure and performance of the industry in equilibrium when firms make decisions in an optimizing way, typically with perfect foresight. The patterns that arise in the process of adjustment, induced by persistent external shocks, are often ignored for lack of a proper tool for analysis. The model introduced here induces turbulence in market structure through unpredictable shocks to the firms' technological environment. The base model presented here enables the analysis of interactive dynamics between firms as they compete in a changing environment with limited rationality and foresight. A possible extension of the base model, allowing for R&D by firms, is also discussed.
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36

Chen, Shu-Heng, Mak Kaboudan y Ye-Rong Du. Computational Economics in the Era of Natural Computationalism. Editado por Shu-Heng Chen, Mak Kaboudan y Ye-Rong Du. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199844371.013.1.

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After a brief review of natural computationalism, this introductory chapter presents a new skeleton of computational economics and finance (CEF) along with an overview of the handbook. It begins with a conventional pursuit focusing on the algorithmic or numerical aspect of CEF such as computational efforts devoted to rational expectations, (dynamic) general equilibrium, and volatility. It then moves toward an automata- or organism-based perspective of CEF, involving nature-inspired intelligence, algorithmic trading, automated markets, network- and agent-based computing, and neural computing. As an alternative way to introduce this novel skeleton, the chapter starts with a view of computation or computing, addressing what computational economics intends to compute and what kinds of economics make computation so hard, and then it turns to a view of computing systems in which the Walrasian kind of computational economics is replaced by the Wolframian kind due to computational irreducibility.
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37

Belsley, D. A. Computational Techniques for Econometrics and Economic Analysis (Advances in Computational Economics). Springer, 1993.

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38

Judd, Kenneth L. y Karl Schmedders. Handbook of Computational Economics. Elsevier Science & Technology Books, 2013.

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39

Computational Economics/3.5 Disk. 3a ed. Course Technology, 1992.

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40

M, Amman Hans, Kendrick David A y Rust John 1955-, eds. Handbook of computational economics. Amsterdam: Elsevier, 1996.

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41

Judd, Kenneth L. y Karl Schmedders. Handbook of Computational Economics. Elsevier Science & Technology Books, 2013.

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42

Chen, Shu-Heng. Agent-Based Computational Economics. Routledge, 2017. http://dx.doi.org/10.4324/9781315734422.

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43

Thompson, Gerald. Computational Economics/5.25 Disk. 5a ed. Course Technology, 1992.

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44

Agent-Based Computational Economics. Taylor & Francis Group, 2015.

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45

Amman, H. M., D. A. Kendrick y J. Rust. Handbook of Computational Economics. Elsevier Science & Technology Books, 1996.

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46

Pau, L. F., H. Amman y D. A. Belsley. Computational Economics and Econometrics. Springer Netherlands, 2012.

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47

Pau, L. F., H. Amman y D. A. Belsley. Computational Economics and Econometrics. Springer, 2012.

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48

Computational Techniques for Modelling Learning in Economics (Advances in Computational Economics). Springer, 1999.

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49

Fehr, Hans y Fabian Kindermann. Introduction to Computational Economics Using Fortran. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198804390.001.0001.

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Introduction to Computational Economics Using Fortran is the essential guide to conducting economic research on a computer. Aimed at students of all levels of education as well as advanced economic researchers, it facilitates the first steps into writing programs using Fortran. Introduction to Computational Economics Using Fortran assumes no prior experience as it introduces the reader to this programming language. It shows the reader how to apply the most important numerical methods conducted by computational economists using the toolbox that accompanies this text. It offers various examples from economics and finance organized in self-contained chapters that speak to a diverse range of levels and academic backgrounds. Each topic is supported by an explanation of the theoretical background, a demonstration of how to implement the problem on the computer, and a discussion of simulation results. Readers can work through various exercises that promote practical experience and deepen their economic and technical insights. This textbook is accompanied by a website from which readers can download all program codes as well as a numerical toolbox, and receive technical information on how to install Fortran on their computer.
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50

(Editor), Shu-Heng Chen, Lakhmi Jain (Editor) y Chung-ching Tai (Editor), eds. Computational Economics: A Perspective from Computational Intelligence (Computational Intelligence and Its Applications Series) (Computational Intelligence and Its Applications Series). Idea Group Publishing, 2005.

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