# In investing, the crowd is wrong much more often than right

I am reading Ken Fisher's Beat the Crowd, and the second sentence in the book is this:

In investing, the crowd is wrong much more often than right.

I was wondering if there is a way to define the terms in this statement, "in investing", "crowd" and "wrong much more often than right", so that this sentence can be quantitatively tested.

My feeling is that if markets are efficient, in retail investing, this statement would imply that while crowds (assume in the simplest case that there are two sets of investors, those who bet on an index going up in the next time period, and those that bet on the index going down in the next time period, and the crowd is whichever set has larger cardinality) are wrong much more often, the volume of the gains of the crowd when they are right are far higher than when they are wrong.

$$\mathbb{E}(Y | \text{Crowd is right}) >> \mathbb{E}(Y | \text{Crowd is wrong})$$

Is this a testable theory? What data would be required to test this? Is there a strand of the literature which tests whether deliberately contrarian behaviour is more profitable?

Thanks.

• I have the feeling that if it was right you would have a 'free lunch' always betting against the market. – were_cat Jul 11 '16 at 15:04