A True Expert

We suggest a test for discovering whether a potential expert is informed of the distribution of a stochastic process. In a non-Bayesian non-parametric setting, the expert is asked to make a prediction which is tested against a single realization of the stochastic process. It is shown that by asking the expert to predict a “small” set of sequences, the test will assure that any informed expert can pass the test with probability one with respect to the actual distribution. Moreover, for the uninformed non-expert it is impossible to pass this test, in the sense that for any choice of a “small” set of sequences, only a “small” set of measures will assign a positive probability to the given set. Hence for “most” measures, the non-expert will surely fail the test. We define small as category 1 sets, described in more detail in the paper. JEL Classification: D83, C14, C50 ∗We would like to thank Alvaro Sandroni, Eilon Solan and Bob Wilson for helpful comments. The first author gratefully acknowledges the support of the NSF. The second author gratefully acknowledges the support of the Center for Electronic Business and Commerce. †Department of Economics, Northwestern University, Evanston, USA and Tel-Aviv University, Tel-Aviv, Israel. e-mail: [email protected] ‡Stanford Graduate School of Business, Stanford CA 94305-5015. e-mail: [email protected]