...you casually find papers like "Biological Brain-Inspired Genetic Complementary Learning for Stock Market and Bank Failure Prediction" (Tan et. al. , Computational Intelligence Vol. 23, No. 2. (May 2007), pp. 236-261). So don't even give me that "where's my jetpack and hover car!" whining because when a computer can use properties of our brains and genetic algorithms to learn when the stock market is going to crash, you can tell we've come a long way.

This paper attempts to tackle a common problem in the realm of computational finance, using computers to make millions. The use of all our super-computing power for financial applications only makes sense in order to get the maximum amount of cash-money, but when stuff like surfing the internet and word processing causes my computer to crash, it makes you wonder how hard it must be to model something like stock market strategies.

So smart computer scientists take a tip from right at home, our brains, and they use computational intelligence tools such as artificial neural networks, fuzzy logic, Bayesian statistics, and evolutionary computing to give computers a bit of a heads-up. This paper proposes a nice slurry of the tools above in the design of a neural network called a GLC (Genetic Complementary Learning Fuzzy Neural Network) and genetic algorithms to use human pattern recognition and gene selection to learn good financial decisions.

Tan et. al. analyzes the accuracy of the HAL 9000 computational finance tool for bank failure and stock market prediction in many real situations. The GLC performed competently and gave good results on both tests, which is essentially a giant leap towards the hover car. So keep your fingers crossed!

You can get the article mentioned above here or search for it using your library's journal subscriptions.