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Genetic algorithm (GA) is a search heuristic that is inspired by Charles Darwin’s theory of natural selection. This algorithm mimics the process of natural selection in order to find optimal solutions to a given problem. GA has been used in various fields such as engineering, economics, and finance. In the financial market, some practitioners claimed that GA can be used to find the best portfolio that can maximize the return while minimizing the risk and GA can also be used to predict the stock market trend.
There is an interesting discussion on quantstackexchange regarding the usefulness of GA in the financial market. The original poster asked,
There is a large body of literature on the “success” of the application of evolutionary algorithms in general, and the genetic algorithm in particular, to the financial markets.
However, I feel uncomfortable whenever reading this literature. Genetic algorithms can over-fit the existing data. With so many combinations, it is easy to come up with a few rules that work. It may not be robust and it doesn’t have a consistent explanation of why this rule works and those rules don’t beyond the mere (circular) argument that “it works because the testing shows it works”.
What is the current consensus on the application of the genetic algorithm in finance?
One poster replied,
I’ve worked at a hedge fund that allowed GA-derived strategies. For safety, it required that all models be submitted long before production to make sure that they still worked in the backtests. So there could be a delay of up to several months before a model would be allowed to run.
It’s also helpful to separate the sample universe; use a random half of the possible stocks for GA analysis and the other half for confirmation backtests.
This is a valid point. Out-of-sample and live testing should be applied not only to GA-derived strategies but to all trading strategies.
Another poster pointed out,
There is never a real consensus in finance – everybody tries to outsmart everybody else. This is why it is so interesting. (Or put another way: this is why there are still buyers AND sellers – a real consensus is a crash
We think that the poster has a point. We will never be able to design a method for forecasting the market with 100% accuracy.
In summary, the consensus is that GA is useful in the financial market, but it’s just another quantitative method and should be used with caution.
Let us know what you think in the comments below.
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