Paul Tetlock’s latest paper on the subject of prediction markets “Does Liquidity Affect Securities Markets Efficiency?” follows the lines of the other authors whose model starts with the concept of first generation prediction markets, designed in such a way that their prices express probabilities.
First: We should not be surprised that those markets “underprice high probability events and overprice low probability events”. This is a consequence of continuous information arrival. Any binary option MUST show this behaviour, mathematically, depending on its In-the-money or Out-of-the money state.
In the framework of Price Information Theory, with continuous information arrival, you “lose” probability until the prediction horizon sigma sqrt T of the price differential. No “irrationality” there. (Remember: “Austrians” start on the premise that man is rational.)
Second: The immediate analogy from such binary contracts to behaviour of securities markets is not permissible. Securities markets price discounted future cash-flows in consideration of the two risks (ex-ante volatility and noise) affecting them. Applying the problematic binary framework to securities prices does not make binary options a security, they stay what they are. (Price predictions on rice in China does not make them edible.)
Third: Based on this, it is easy to explain why the conclusions of the paper appear overdrawn: The better the probability of a binary follows the information decay, the more mispricing the presented model would detect. Mr. Tetlock final thoughts appear to run in a similar vein by stating in the end that “…, liquidity may only appear to be a priced risk factor because it captures some systematic element of mispricing.”
So: On this one, let’s stay with the cited conventional models (Kyle) plus some empirical evidence from “real” securities markets: Mispricing is greater in illiquid markets.