Santa Fe Institute

Network analysis reveals investor herding that may lead to stock valuation

Feb. 15, 2012 3:40 p.m.

In a study in the New Journal of Physics, researchers constructed a network from market transaction data that allowed them to identify investor heading behaviors, an approach they believe could lead to insights about how stock price is determined.

They say the approach may lead to identification of trading patterns and strategies that collectively determine stock price.

The international research team, which includes SFI Professor Fabrizio Lillo, based its analysis on a data from thousands of investor trades of Finnish stocks.

Read the Physorg.com article (January 27, 2012)

Read the New Journal of Physics paper (January 2012)

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terry - Feb. 21, 2012, 10:03 a.m.

This is an interesting article: Well beyond my math skills but to see the patterns of traders in this format is facinating. One thing that I find interesting is that nobody has investigated the uncretainity that exists between a seller's "ask for" price and what the potential buyers in the market will actually pay. I am developing a business that exploits that uncertainity. There is a huge opportunity to profit from that uncertianity in approximately eight ways. It has never been done before and will create a new market that has up until now been hidden within the selling and buying or barter "system." This quantification of the uncertainty also allows for detailed demographic tracking. This demographic tracking being one of the eight profit opportunities. I hope to make business available this year. But for your interests, the demographic informatin will contain age, financial, and location information in addition to other information...its very exciting and much of this idea came from Brian Arthur's book "Complexity" and his paper "Out-of-Equilibrium Economics and Agent-Based Modeling." I look forward to completing the startup process this year and introducing what has up until has never been done before.

Sincerely

Terry Moore

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