On Market Timing And Investment Performance Part Ii Statistical Procedures for

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On Market Timing And Investment Performance Part Ii Statistical Procedures for
Roy Henriksson
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= x|N. , p) = p^'ci - p) "- ; i = 1, 2 . (5) Given the null hypothesis, we can use Bayes' Theorem to determine the probability that n = x given N, , N, and n, i. E. , PCn = x|N, ,N„, n). Denote the event that our market timer forecasts m times that Z„ < R (i. E. , n = m) as "A" and the event that of the M — times he forecasts that Z _< R, he is correct x times and incorrect m - X times (i. E. , n = x and n- = m - x) as "B. " P(n = x|N^, N„, m) = P(b|A), and by Bayes' Theorem, we have that p(BlA) = P(B_ + ^^ P(B). ^^^J^-* P(A) P(A) N- \ / N„ \ N -X N. -m-hc ' ' ' ' ' P"(l - P) ' P"-"(1 - P) ' X / \ m - X, (6) N', m, T, N-m ^ . P (1 - P) m ^1 ^2 \ X / \m - X Hence, under the null hypothesis, the probability distribution for n, the number of correct forecasts, given that Z < R, has the form of a hypergeometric distribution and is independent of both p and p„. Therefore to test the null hypothesis, it is unnecessary to -12- estiinate either of the conditional probabilities. So, provided that che forecasts are known, all the variables necessary for the test are directly observable.

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