1580 The Journal of finance apparently small French and roll estimate that for the average NYSe stock, he upper bound on the transitory portion of the daily variance is 11.7% spurious negative autocorrelation of daily returns due to bid-ask effects(Roll(1984)), the estimate of the transitory portion drops to 4. 1%. The smallest quintile of NYSE stocks produces the largest estimate of the transitory portion of price variation, an upper bound of 26.9%.After correction for bid-ask effects, however, the estimate drops to 4.7%-hardly a number on which to conclude that noise trading results in substantial market inefficiency. French and Roll(1986, p. 23)conclude, "pricing errors. have a trivial effect on the difference between trading and non-trading variances We conclude that this difference is caused by differences in the flow of information during trading and non-trading hours In short, with the crsp daily data back to 1962, recent research is able to show confidently that daily and weekly returns are predictable from past returns. The work thus rejects the old market efficiency-constant expected returns model on a statistical basis. The new results, however tend to confirm the conclusion of the early work that, at least for individual stocks variation in daily and weekly expected returns is a small part of the variance of returns. The more striking, but less powerful, recent evidence on the predictability of returns from past returns comes from long-horizon returns A.2. Long-Horizon Returns The early literature does not interpret the autocorrelation in daily and weekly returns as important evidence against the joint hypothesis of market efficiency and constant expected returns. The argument is that, even when the autocorrelations deviate reliably from 0(as they do in the recent tests) chey are close to 0 and thus economically insignificant The view that autocorrelations of short-horizon returns close to 0 imply economic insignificance is challenged by Shiller(1984)and Summers(1986) They present simple models in which stock prices take large slowly decaying swings away from fundamental values (fads, or irrational bubbles), but short-horizon returns have little autocorrelation. In the Shiller -Summers model, the market is highly inefficient, but in a way that is missed in tests on short-horizon returns value. Suppose daily prices are a first-order autoregression(ARl) with slope less than but close to 1. All variation in the price then results from long mean-reverting swings away from the constant fundamental value. Over short horizons, however, an ARl slope close to 1 means that the price looks like a random walk and returns have little autocorrelation. Thus in tests on short-horizon returns, all price changes seem to be permanent when funda mental value is in fact constant and all deviations of price from fundamental value are temporary In his comment on Summers(1986), Stambaugh(1986)points out that although the Shiller-Summers model can explain autocorrelations of short