Too much Empiricism in financial Markets

 Think of anytime you have set out to research on a certain stock, currency. Usually, the first step we take is to plot and explore the historical prices. Often we are stuck in doing all sort of analysis on the past prices because quantitative data, ‘big data’, ’numbers’ is the magical source of credibility in financial analysis. This believe that knowledge can only be acquired through past experiences is called Empiricism. Empiricism is effective but has some limitations especially when we over depend on it to answer questions related to human behavior.

 ‘Numbers don’t lie’ is a big lie in some cases. Let’s start with creative accounting. It takes advantage of shareholders faith in numbers, so whatever numbers the accountants feed the investor public, they will probably believe it. Although such accounting would best be described as outright fraud rather than empiricism, it demonstrates the problem of underdetermination and bias that exist in empiricism.  Given the same dataset, two analysts will come up with stories that align with their interest using the same data. If truth is universally objective, then how can same data points produce different conclusions? Then probably one of the analyst or both are using numbers to lie.

Because empirical finance inherently assumes the future will be similar to the past, it suffers the problem of induction. The classical example of a farmer and the chicken says a chicken that receives grains each morning will assume that is the norm until Christmas day when the farmer will slaughter the chicken instead of feed it. Value at risk, volatility models, AR and ARMAs etcetera all this common finance tools seek to fit the past and project to the future but they do not warn us when ‘Christmas day’ is approaching.

So what is the way forward? Empiricism is great and probably the most effective philosophical approach to carrying out research however it has to be used in conjunction with other ways of discovering knowledge. The money culture by Michael Lewis describes some of the best deal makers in the ‘80s that relied on alternative sources of knowledge rather than historical hard data. Personally, I am unashamedly empiricist just like most finance researchers, traders however I believe combining quant data, common sense (intuition) and perspectives from smart people can yield good results.