The Bayesian Method of Financial Forecasting
https://www.investopedia.com/articles/financial-theory/09/bayesian-methods-financial-modeling.asp
This article gives an overview of an interesting application of Bayes’ Rule: financial forecasting. An example given in the article is predicting how a change in interest rates can affect the value of a stock. If we can get accurate past data then getting this prediction is just a matter of applying Bayes’ Rule and we now have a fairly decent estimate of how changing interest rates can affect the value of a stock. We can apply the same rule to many different effectors of a stock’s price to continually get better and better estimates of how a stock’s price will change. Unfortunately, if we cannot get accurate past data, the predictions we get will be much more subjective. Oftentimes, experts in the field will be required to come up with predictions with certain estimates that can be used to build more sophisticated models. For example, say we do not know the probability of the interest rate increasing. We would then need to rely on an industry expert to come up with a prediction so we can create a model to determine the probability of a stock increasing given the probability of the interest rate increasing.
I found this article to be a very interesting application of Bayes’ Rule. I found it fascinating that such a simple formula can have an impact on so many important fields such as predicting the price of stocks. Additionally, it is cool that something that seems as complicated as predicting the price of a stock can be modeled using Bayes’ Rule with a couple of different parameters. Obviously this will not give us the best estimate but it will probably give us a somewhat accurate estimate and good baseline for creating more complex models.