Artificial Intelligence with Python - Second Edition by Alberto Artasanchez

Author:Alberto Artasanchez
Language: eng
Format: epub
Publisher: Packt
Published: 2020-01-30T10:27:17+00:00

The latter two examples rely heavily on computer algorithms to achieve market beating results.

Game theory has been a standard tool used by economists to try to understand markets but is increasingly supplemented by simulations with both human and computerized agents. GP is increasingly being used as part of these simulations of social systems.

GP algorithms are widely used in the areas of financial trading, time series prediction, and economic modeling; it would take a whole book to list all its applications.

It this section we will scratch the surface and visit a few examples. A particularly prodigious researcher that stands out in this field is Sheng-Hung Chen. Chen has written more than 60 papers on using GP in finance and economics. Some of his recent papers have looked at the modeling of agents in stock markets (Chen and Liao, 2005), game theory (Chen, Duffy, and Yeh, 2002), evolving trading rules for the S&P 500 (Yu and Chen, 2004) and forecasting the Heng-Sheng index (Chen, Wang, and Zhang, 1999).

Other applications

Optimization − GAs and GP are commonly used in optimization problems wherein values must be maximized or minimized given an objective function under a set of constraints.

Parallelization − GAs also possess parallel processing capabilities and prove to be an effective method to solve problems that require parallel processing. Parallelization is an active area of research in GA and GP.

Neural networks − GAs are used to train neural networks, particularly recurrent neural networks (RNNs).

Economics − GAs are commonly used to model economic systems such as:

The cobweb model

Game theory equilibrium resolution

Asset pricing

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