The Financial Times recently had an article titled “Decoding the psychology of trading” where they write about a behavioral finance based fund named MarketPsy. When I hear the words behavioral finance I often start thinking of group behavior like that shown in the video below, showing Starlings flying over Rome. We also find similar “dynamics” in groups of fish, and what I particularly associate with this type of behavior with regards to behavioral finance is how one reaction or incident in one part of the group quickly spreads across the group as a whole.
MarketPsy is using some sort of linguistics analysis on huge amonts of text data (from whatever sources they can get their hands on, I would presume), and then based on that analysis try to conclude the current (and hopefully future) investor positive/negative mood. I have on my TODO list to try something similar, using the CRM114 spam filter application as the engine needed for classifying incoming text.
I do sense however that I am a bit skeptical with regards to this approach. My reasoning is as follows:
- If you’re sampling “the complete picture”, ie all available sources out there, wouldn’t the “mood inertia” be too big to change quickly enough?
- If you instead are sampling just a selected few sources (selected on whatever flawed reasoning used), wouldn’t that be the same as doing fundamental analysis without access to the complete picture?
Would it not be better to try and do behavioral finance analysis on the actual complete picture, in other words, raw market data? For point 1, I guess maybe it’s worth something as a “mother-in-law” factor as Barton Biggs refers to contrarian indicators in the book Hedgehogging, for all I know. For point 2, too risky if you’d ask me.
Well, that’s just my 5 cents. Whatever the conclusion, if one exists, it’s interesting stuff non the less.