Can We Scientifically Understand the Financial Markets? (Part 1)

A couple years ago I stumbled across an interesting article by Jeffrey Mishlove, Ph.D. In the article, he presents some survey responses to the question about whether scientific understanding of the financial markets is possible.

While Mishlove does not present us with the optimistic responses, he does show us some of the more pessimistic ones:


> …The future never resembles the past and persistence in
> performance for any length of time in the investment industry
> is almost unheard of.


> I am surprised that you do not know that predicting financial
> markets can’t be done. It’s a “Fool’s Game”


> “Never…” there is no useful research. The minute any useful
> research emerged (to the general public as suggested by the
> question), it would immediately be incorporated into financial
> markets, rendering that research no longer useful.


> Most of us, including myself, are all about data, but, as
> others have said, no empirical results – back, realtime or
> front, regardless of the power applied – can be the basis for
> long-term successful trading. Sadly, not even actual results
> can form such a basis – as actuals are indistinguishable
> from random.


> Back testing is essential but most of the output is a
> curve fit illusion… Forward testing is of little use
> either; especially for longer term trading….I fear that
> studying scientific research is not a route to Eldorado.
> Investors should remember that at the end of the day,
> Candide gave up the attempt and resorted to peacefully
> cultivating his garden. Most would be traders would do
> well to do the same.


> Building models incorporating genuinely objective data
> into a probability based decision chain is an
> interesting pursuit. However, no one knows what happens
> next particularly within any specified time slice.
> Seeking a useful predictive model producing near term
> efficacy is an exercise in futility.


I will conclude with the next post.