Applications of artificial intelligence in finance and economics:
Artificial intelligence is a consortium of data-driven methodologies which includes artificial neural 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...
Gespeichert in:
| Format: | Elektronisch E-Book |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
Bingley, U.K.
Emerald
2004
|
| Schriftenreihe: | Advances in econometrics
v. 19 |
| Schlagworte: | |
| Online-Zugang: | DE-634 DE-1043 DE-M347 DE-523 DE-91 DE-473 DE-19 DE-355 DE-703 DE-20 DE-706 DE-824 DE-29 DE-739 DE-1046 Volltext |
| Zusammenfassung: | Artificial intelligence is a consortium of data-driven methodologies which includes artificial neural 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 collected works 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 presented in order to draw attention to the tremendous diversity and richness of the 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 perspectives on 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 |
| Beschreibung: | 1 Online-Ressource (xiii, 275 Seiten) |
| ISBN: | 9781849503037 |
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| 505 | 8 | |a 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 divisia money / Jane M. Binner, Graham Kendall, Alicia Gazely -- Forecasting the EMU inflation rate : linear econometric vs. non-linear computational models 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 model international short-term capital flow / Tina Yu, Shu-Heng Chen, Tzu-Wen Kuo -- Tools for non-linear time series forecasting in economics : an empirical 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 | |
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| contents | 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 divisia money / Jane M. Binner, Graham Kendall, Alicia Gazely -- Forecasting the EMU inflation rate : linear econometric vs. non-linear computational models 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 model international short-term capital flow / Tina Yu, Shu-Heng Chen, Tzu-Wen Kuo -- Tools for non-linear time series forecasting in economics : an empirical 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 |
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| publishDateSearch | 2004 |
| publishDateSort | 2004 |
| publisher | Emerald |
| record_format | marc |
| series2 | Advances in econometrics |
| spelling | Applications of artificial intelligence in finance and economics edited by Jane M. Binner, Graham Kendall, and Shu-Heng Chen Bingley, U.K. Emerald 2004 1 Online-Ressource (xiii, 275 Seiten) c rdamedia cr rdacarrier Advances in econometrics v. 19 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 divisia money / Jane M. Binner, Graham Kendall, Alicia Gazely -- Forecasting the EMU inflation rate : linear econometric vs. non-linear computational models 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 model international short-term capital flow / Tina Yu, Shu-Heng Chen, Tzu-Wen Kuo -- Tools for non-linear time series forecasting in economics : an empirical 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 methodologies which includes artificial neural 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 collected works 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 presented in order to draw attention to the tremendous diversity and richness of the 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 perspectives on 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 Artificial intelligence Business & Economics Econometrics Business & Economics Economics Economics Econometrics Congresses Economics Data processing Congresses Finance Data processing Congresses Binner, Jane M. 1961- Sonstige oth Chen, Shu-Heng 1959- Sonstige oth Kendall, Graham 1961- Sonstige oth International Conference on Artificial Intelligence (2003 Las Vegas, Nev.) Sonstige oth https://www.emerald.com/insight/publication/doi/10.1016/S0731-9053(2004)19 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Applications of artificial intelligence in finance and economics 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 divisia money / Jane M. Binner, Graham Kendall, Alicia Gazely -- Forecasting the EMU inflation rate : linear econometric vs. non-linear computational models 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 model international short-term capital flow / Tina Yu, Shu-Heng Chen, Tzu-Wen Kuo -- Tools for non-linear time series forecasting in economics : an empirical 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 Business & Economics Econometrics Business & Economics Economics Economics Econometrics Congresses Economics Data processing Congresses Finance Data processing Congresses |
| title | Applications of artificial intelligence in finance and economics |
| title_auth | Applications of artificial intelligence in finance and economics |
| title_exact_search | Applications of artificial intelligence in finance and economics |
| title_exact_search_txtP | Applications of artificial intelligence in finance and economics |
| title_full | Applications of artificial intelligence in finance and economics edited by Jane M. Binner, Graham Kendall, and Shu-Heng Chen |
| title_fullStr | Applications of artificial intelligence in finance and economics edited by Jane M. Binner, Graham Kendall, and Shu-Heng Chen |
| title_full_unstemmed | Applications of artificial intelligence in finance and economics edited by Jane M. Binner, Graham Kendall, and Shu-Heng Chen |
| title_short | Applications of artificial intelligence in finance and economics |
| title_sort | applications of artificial intelligence in finance and economics |
| topic | Artificial intelligence Business & Economics Econometrics Business & Economics Economics Economics Econometrics Congresses Economics Data processing Congresses Finance Data processing Congresses |
| topic_facet | Artificial intelligence Business & Economics Economics Econometrics Congresses Economics Data processing Congresses Finance Data processing Congresses |
| url | https://www.emerald.com/insight/publication/doi/10.1016/S0731-9053(2004)19 |
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