Showing posts with label Entropy. Show all posts
Showing posts with label Entropy. Show all posts

Wednesday, August 03, 2016

Wisdom Of Crowd Market Index (WCMI)

WCMI Wisdom Of Crowd Market Index (WCMI)

In sports markets, the probabilities implied by the prices on offer are a proxy for the wisdom of the crowd for that particular event. By adapting Shannon's Entropy formula, we can generate our own "Wisdom Of Crowd Market Index" (WCMI) to represent this information on a scale from 0 - 1.

First, calculate implied probabilities of prices: x = 1.00 / d (where d = decimal odds). Next, calculate log probabilities: y = log(x, n) (where n = number of runners). Then, multiply probabilities by log probabilities: z = x * y. Finally, sum products and subtract from one for final index: wcmi = 1 - (-sum(z)).


Note that the index is at a minimum (0.00) when the market is completely uninformed about the outcome (all prices are the same) and at a maximum (1.00) when the market has closed (no price for winner and maximum price for all others). In the realistic exchange market above (snapshot of prices taken one minute before going in-play), the crowd is relatively uninformed (0.03) about the likely outcome and presents an excellent opportunity for the informed sports trader. Personally, I do not trade in any market with an index above 0.13 (approx).

It is very gratifying to note that FlatStats are now (29-Dec-2017) using our WCMI as a guide to those markets in which the crowd is less well-informed!

Sunday, August 16, 2015

Doubling Rate Entropy And Kullback-Leibler Divergence

Cover and Thomas (2006) show that, in a horse race, a handicapper has an expected wealth growth-rate equal to that of an investor who wins every race minus a measure of uncertainty of the race and minus the difference in the win probability distribution used by the handicapper and the distribution of true win probabilities. Intuitively, this makes sense. To reduce the race uncertainty, we should focus on open betting markets with as few runners as possible. To reduce the win estimates difference, we should meld our betting line estimates with that of the crowd (Benter, 2004). In terms of a simplistic equation:

   Long-Term Profit = Clairvoyance – Race Uncertainty – Market Divergence.

My experience is that most handicappers focus too much on trying to become clairvoyant and not enough on selecting open races and factoring in the “wisdom of crowds”.