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Applications of artificial intelligence in finance and economics

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Applications of artificial intelligence in finance and economics/ edited by Jane M. Binner, Graham Kendall, and Shu-Heng Chen.{me_controlnum}
其他作者:	Binner, Jane M.,
出版者:	Bingley, U.K. :Emerald, : 2004.,
面頁冊數:	1 online resource (xiii, 275 p.).
內容註:	Statistical analysis of genetic algorithms in discovering technical trading strategies / Chueh-Yung Tsao, Shu-Heng Chen -- Co-evolving neural networks with evolutionary strategies : a new application to divisiamoney / Jane M. Binner, Graham Kendall, Alicia Gazely -- Forecasting the EMU inflation rate : linear econometric vs. non-linear computationalmodels using genetic neural fuzzy systems / Stefan Kooths, Timo Mitze,Eric Ringhut -- Finding or not finding rules in time series / Jessica Lin, Eamonn Keogh -- A comparison of var and neural networks with genetic algorithm in forecasting price of oil / Sam Mirmirani, Hsi Cheng Li -- Searching for divisia/inflation relationships with the aggregate feedforward neural network / Vincent A. Schmidt, Jane M. Binner -- Predicting housing value : genetic algorithm attribute selection and dependence modelling utilising the gamma test / Ian D. Wilson, Antonia J. Jones,David H. Jenkins, J.A. Ware -- A genetic programming approach to modelinternational short-term capital flow / Tina Yu, Shu-Heng Chen, Tzu-Wen Kuo -- Tools for non-linear time series forecasting in economics : anempirical comparison of regime switching vector autoregressive models and recurrent neural networks / Jane M. Binner, Thomas Elger, Birger Nilsson, Jonathan A. Tepper -- Using non-parametric search algorithms to forecast daily excess stock returns / Nathan Lael Joseph, David S. Bre, Efstathios Kalyvas.
標題:	Business & Economics - Econometrics. -
電子資源:	http://www.emeraldinsight.com/0731-9053/19
ISBN:	9781849503037 (electronic bk.)

Applications of artificial intelligence in finance and economics
Applications of artificial intelligence in finance and economics[electronic resource] /edited by Jane M. Binner, Graham Kendall, and Shu-Heng Chen.{me_controlnum} - Bingley, U.K. :Emerald,2004. - 1 online resource (xiii, 275 p.). - Advances in econometrics,v. 190731-9053 ;. - Advances in econometrics ;v. 12..

Statistical analysis of genetic algorithms in discovering technical trading strategies / Chueh-Yung Tsao, Shu-Heng Chen -- Co-evolving neural networks with evolutionary strategies : a new application to divisiamoney / Jane M. Binner, Graham Kendall, Alicia Gazely -- Forecasting the EMU inflation rate : linear econometric vs. non-linear computationalmodels using genetic neural fuzzy systems / Stefan Kooths, Timo Mitze,Eric Ringhut -- Finding or not finding rules in time series / Jessica Lin, Eamonn Keogh -- A comparison of var and neural networks with genetic algorithm in forecasting price of oil / Sam Mirmirani, Hsi Cheng Li -- Searching for divisia/inflation relationships with the aggregate feedforward neural network / Vincent A. Schmidt, Jane M. Binner -- Predicting housing value : genetic algorithm attribute selection and dependence modelling utilising the gamma test / Ian D. Wilson, Antonia J. Jones,David H. Jenkins, J.A. Ware -- A genetic programming approach to modelinternational short-term capital flow / Tina Yu, Shu-Heng Chen, Tzu-Wen Kuo -- Tools for non-linear time series forecasting in economics : anempirical comparison of regime switching vector autoregressive models and recurrent neural networks / Jane M. Binner, Thomas Elger, Birger Nilsson, Jonathan A. Tepper -- Using non-parametric search algorithms to forecast daily excess stock returns / Nathan Lael Joseph, David S. Bre, Efstathios Kalyvas.

Artificial intelligence is a consortium of data-driven methodologieswhich includes artificialneural networks, genetic algorithms, fuzzy logic, probabilistic belief networks and machine learning as its components. We have witnessed a phenomenal impact of this data-driven consortium of methodologies in many areas of studies, the economic and financial fields being of no exception. In particular, this volume of collectedworks will give examples of its impact on the field of economics and finance. This volume is the result of the selection of high-quality papers presented at a special session entitled 'Applications of Artificial Intelligence in Economics and Finance' at the '2003 International Conference on Artificial Intelligence' (IC-AI '03) held at the Monte Carlo Resort, Las Vegas,Nevada, USA, June 23-26 2003. The special session, organised by Jane Binner, Graham Kendall and Shu-Heng Chen, was presentedin order to draw attention to the tremendous diversity and richness ofthe applications of artificial intelligence to problems in Economics and Finance. This volume should appeal to economists interested in adopting an interdisciplinary approach to the study of economic problems, computer scientists who are looking for potential applications of artificial intelligence and practitioners who are looking for new perspectiveson how to build models for everyday operations. There are still many important Artificial Intelligence disciplines yet to be covered. Among them are the methodologies of independent component analysis, reinforcement learning, inductive logical programming, classifier systems and Bayesian networks, not to mention many ongoing and highly fascinating hybrid systems. A way to make up for their omission is to visit this subject again later. We certainly hope that we can do so in the near future with another volume of Applications of Artificial Intelligence in Economics and Finance.

ISBN: 9781849503037 (electronic bk.)Subjects--Topical Terms:

1556307
Business & Economics
--Econometrics.

LC Class. No.: HB139 / .A67 2004

Dewey Class. No.: 330.015195

Universal Decimal Class. No.: 330.43

Applications of artificial intelligence in finance and economics
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