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 consisting of man made neural networks, genetic algorithms, fuzzy common sense, probabilistic trust networks and laptop studying as its elements. we have now witnessed a gorgeous effect of this data-driven consortium of methodologies in lots of parts of reports, the commercial and fiscal fields being of no exception. specifically, this quantity of accrued 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 provided 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 hotel, Las Vegas, Nevada, united states, June 23-26 2003. The distinct consultation, organised by means of Jane Binner, Graham Kendall and Shu-Heng Chen, used to be awarded with a purpose to draw awareness to the super variety and richness of the functions of synthetic intelligence to difficulties in Economics and Finance. This quantity may still entice economists attracted to adopting an interdisciplinary method of the research of financial difficulties, laptop scientists who're searching for strength functions of man-made intelligence and practitioners who're trying to find 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 autonomous part research, reinforcement studying, inductive logical programming, classifier structures and Bayesian networks, let alone many ongoing and hugely interesting hybrid platforms. 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 accomplish that within the close to destiny with one other quantity of 'Applications of man-made Intelligence in Economics and Finance'.

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

Sample text

Karjalainen, R. (1999). Using generic algorithms to find technical trading rules. Journal of Financial Economics, 51, 245–271. Arnold, S. F. (1990). Mathematical statistics. New Jersey: Prentice-Hall. Barnett, W. , Gallant, A. , Hinich, M. , Jungeilges, J. , Kaplan, D. , & Jensen, M. J. (1997). A single-blind controlled competition among tests for nonlinearity and chaos. Paper presented at the 1997 Far Eastern Meeting of the Econometric Society (FEMES’97), Hong Kong, July 24–26, 1997 (Session 4A).

The luck coefficient l␧ is defined as the sum of the largest 100␧% returns, ␧ ∈ (0, 1), divided by the sum of total returns. In a sense, the larger the luck coefficient, the weaker the reliability of the performance. The luck coefficient, as a performance statistic, is formally described below. Let {X1 , X2 , . , Xm } be a random sample from f(x) with E(X) = ␮. The order statistic of this random sample can be enumerated as X(1) , X(2) , . , X(m) , where X (1) ≤ X (2) ≤ · · · ≤ X (m) . Then, from the order statistics, it is well known that X (m) ∼ g(x (m) ) = m[F(x (m) )]m−1 f(x (m) ) (38) iid where F is the distribution function of X.

Gallant, A. , Hinich, M. , Jungeilges, J. , Kaplan, D. , & Jensen, M. J. (1997). A single-blind controlled competition among tests for nonlinearity and chaos. Paper presented at the 1997 Far Eastern Meeting of the Econometric Society (FEMES’97), Hong Kong, July 24–26, 1997 (Session 4A). Bauer, R. J. (1994). Genetic algorithms and investment strategies. Wiley. Bollerslev, T. P. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31, 307–327. , Chou, R. , & Kroner, K.

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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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