Can We Scientifically Understand the Financial Markets? (Part 2)

In 2013, Jeffrey Mishlove, Ph.D. posted some responses to a very interesting survey question: “When is studying scientific research most useful for understanding financial markets?”

My last post detailed some of those responses. Here are two more:


> Have financial markets been consistent enough
> (knowing all the parts of a valid research study
> that must be there in the research), amidst how
> quickly the world has changed in the last 200 years,
> to even get the kind of research that would still
> be valid today?


> One can fiddle till doomsday with quantitative
> analyses of social reality, but since we are dealing
> with human creations and manipulations, I wouldn’t
> be inclined to believe very much in “scientific,
> empirical” research into financial markets.


To me, this question is about trading system development, which is something I consider a “pseudoscience.” I believe we can follow a methodology to do this in a valid way. I don’t believe we can ever get around some level of subjectivity, however, and that is why I use the prefix “pseudo.” What makes an acceptable trading system for one person (e.g. maximum net profits) may not be acceptable for someone else (e.g. maximal ratio of net profits to drawdown).

Legends abound regarding traders and institutions that have used algorithmic trading systems to earn millions and billions of dollars. The veneer of success and profitability is clear. At the very least, this is all good marketing and advertising. How much of those profits were retained, never to be lost, is something we will never know. If they were all lost and the firms went under then that is certainly something which may be discovered on a case-by-case basis. Most of us don’t have a research team available to help us out with that, though. I know I don’t.

One thing I like about option trading is that it gives me a margin of safety. I can start with a trading strategy that I think has potential and have a good chance to make money even if the strategy ends up being lousy. This certainly doesn’t mean I won’t lose, though, and when loss rears its ugly head I better have good risk management at the ready.