Applications of Artificial Intelligence in Finance and - download pdf or read online

By Binner, J. M. Binner, G. Kendall

ISBN-10: 0762311509

ISBN-13: 9780762311507

ISBN-10: 1865843830

ISBN-13: 9781865843834

ISBN-10: 2076315500

ISBN-13: 9782076315509

Synthetic intelligence is a consortium of data-driven methodologies which include man made neural networks, genetic algorithms, fuzzy common sense, probabilistic trust networks and computing device studying as its elements. we now have witnessed a stupendous impression of this data-driven consortium of methodologies in lots of parts of experiences, the commercial and monetary fields being of no exception. specifically, this quantity of accumulated works will provide examples of its effect at the box of economics and finance. This quantity is the results of the choice of top quality papers awarded at a unique consultation entitled 'Applications of man-made Intelligence in Economics and Finance' on the '2003 foreign convention on synthetic Intelligence' (IC-AI '03) held on the Monte Carlo inn, Las Vegas, Nevada, united states, June 23-26 2003. The distinct consultation, organised through Jane Binner, Graham Kendall and Shu-Heng Chen, was once offered on the way to draw realization to the great variety and richness of the functions of man-made intelligence to difficulties in Economics and Finance. This quantity may still attract economists attracted to adopting an interdisciplinary method of the learn of monetary difficulties, machine scientists who're searching for capability purposes of man-made intelligence and practitioners who're searching for new views on how one can construct types for daily operations.

There are nonetheless many very important man made Intelligence disciplines but to be lined. between them are the methodologies of self sufficient part research, reinforcement studying, inductive logical programming, classifier structures and Bayesian networks, let alone many ongoing and hugely interesting hybrid structures. how to make up for his or her omission is to go to this topic back later. We definitely desire that we will be able to achieve this within the close to destiny with one other quantity of 'Applications of synthetic Intelligence in Economics and Finance'.

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Extra resources for Applications of Artificial Intelligence in Finance and Economics, Volume 19 (Advances in Econometrics)

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Gottingen and Zurich: Vandenhoech & Ruprecht. Holland, J. H. (1975). Adaptation in natural and artificial systems. Ann Arbor, MI: University of Michigan Press. Jarque, C. , & Bera, A. K. (1980). Efficient tests for normality, homoscedasticity and serial independence of regression residuals. Economic Letters, 6, 255–259. Jobson, J. , & Korkie, B. M. (1981). Performance hypothesis testing with the Sharpe and Treynor measures. Journal of Finance, 36(4), 889–908. , & Wu, L. (1997). What is the “true price”?

5. Chaotic Processes Chaotic processes are also nonlinear, but they differ from the previous four nonlinear processes in that they are deterministic rather than stochastic. These processes can behave quite erratically without any discernible pattern. Can the GA survive well with this type of nonlinear process? The answer is a resounding yes. All the statistics in Table 11 are sending us this message. The winning probabilities are all higher than 85%. In the case of the Henon map (C-2), the GA even beats B&H in all of the 1000 trials.

For a general coverage of this subject, interested readers are referred to Chen (1998a), Chen (2002) and Chen and Wang (2003). As opposed to the conventional technical analysis, the advantages of using GAs and GP are well discussed in Allen and Karjalainen (1999), and is also briefly reviewed in another paper of this special issue. , 2004). 3. For example, Chen (1998b) sorted out three stochastic properties which may impinge upon the performance of GAs in financial data mining. These are the no-free-lunch property, the well-ordered property and the existence of temporal correlation.

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Applications of Artificial Intelligence in Finance and Economics, Volume 19 (Advances in Econometrics) by Binner, J. M. Binner, G. Kendall

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