Terry Marsh, Equilibrium Term Structure Models: Test Methodology, The Journal of Finance, Vol. 35, No. 2, Papers and Proceedings Thirty-Eighth Annual Meeting American Finance Association, Atlanta, Georgia, December 28-30, 1979 (May, 1980), pp. 421-435

We examine the effects of market making and intermittent trading on estimates of stock price volatility. When observed price changes are correctly tied to a stock's true price dynamics, it is found that non-trading per se causes a loss of efficiency but no bias in traditional volatility estimates. Non-trading induces substancial inefficiency in the extreme value estimator of volatility which it biases downward. Market making's effects add to the non-trading induced inefficiency in the traditional estimator, while information trading causes a downward bias, and liquidity trading a potentially removable upward bias, in that estimator.

HD28 .M414 no.1584-, 84, Stocks Prices,

Market betas have a strong and positive relation with average stock returns on a handful of days every year. Such unique days, defined as leading earnings announcement days (LEADs), are times when an aggregate of influential S&P 500 firms disclose quarterly earnings news early in the earnings season. The positive return-to-beta relation holds for various test portfolios, individual stocks, and Treasuries; and is robust to different data frequencies and testing procedures. On days other than LEADs, the beta-return relation is flat. We conclude that waves of early earnings announcements by large firms clustered on LEADs significantly influence asset pricing.

This study attests to the important role of US midterm elections in asset pricing, even more important than presidential elections. In months following the midterms, equity premiums, mutual fund flows, and real investment growth rates are significantly higher and Treasury premiums are lower. This is consistent with theoretical models relating higher asset prices to lower future discount rates when post-election political uncertainty decreases. The results are robust to different measures of uncertainty. Also, market betas relate positively to the cross section of average returns in post-midterm months, but the relation is flat in other months.

This paper is concerned with the size-related anomalies in stock returns reported by Banz (1981) and Reinganum (1981). They showed that small firms have tended to yield returns greater than those predicted by the traditional CAPM. We find that the size effect is linear in the logarithm of size, but reject the hypothesis that the ex ante excess return attributable to size is stable through time. We briefly analyze the Seemingly Unrelated Regression Model (SURM) and a two-step procedure as two alternative estimators of the size effect. Due to the instability of the effect, we find that the estimates are sensitive to the time period studied.