This study tests the popular claim that the DJIA's movements around key reference points affect “investor sentiment” and thus price behavior. It is found that the DJIA's rise and fall is indeed restrained by “support” and “resistance” levels at multiples of 100 (e.g., 2800, 2900, 3000, etc.) but that, having broken through a 100-level, the DJIA then moves by more than otherwise warranted. A Monte Carlo study and comparisons with other indices confirm the significance of these findings. This suggests that some agents may trade on the basis of the DJIA but does not necessarily suggest that the market is inefficient.

This paper uses an autoregressive approach to test a multi-factor model with time-varying risk premiums. A quasi-differencing approach is used to eliminate the unobservable factors in the model. It is found that the model is capable of capturing the “size effect” and the “dividend yield effect,” but is incapable of explaining the “book-to-market effect” and the “earnings-price ratio effect.” Thus, it is concluded that a constant-beta multi-factor model will not be able to explain the cross-sectional variation in expected returns.

Three major motives have been suggested for takeovers: synergy, agency, and hubris. Existing empirical evidence is unable to clearly distinguish among these motives probably due to the simultaneous existence of all three in any sample of takeovers. This paper suggests a way of distinguishing among these competing hypotheses by looking at the correlation between target and total gains. It is argued that this correlation should be positive if synergy is the motive, negative if agency is the motive, and zero if hubris is the motive. The empirical results show that synergy is the primary motive in takeovers with positive total gains even though the evidence is consistent with the simultaneous existence of hubris in this sample. It is also found that agency is the primary motive in takeovers with negative total gains.

This paper presents evidence on how the Williams Act affected the corporate acquisitions market. The acquisition process is modeled and three hypotheses about the Act's effects are discussed. These hypotheses imply differing restrictions on how the Act changes the model's parameters. Parameter changes are estimated but we are unable to reliably discriminate between two of the three hypotheses using the classical statistical testing approach, though the third hypothesis is reliably rejected. Bayesian analysis using a diffuse prior is employed to make formal probability comparisons among the hypotheses. The most probable hypothesis, according to the results, implies that the Williams Act reduced the expected gross present value of acquisition attempts.

This paper examines the cross-sectional distribution of bid-ask spreads in the S&P 100 index options market. Cross-sectional differences in bid-ask spreads are found to be directly related to differences in market-making costs and trading activity across options. We also examine the relation of an option's bid-ask spread and trading activity to the spread and trading activity in other options. Call option trading activity is inversely related to the call option bid-ask spread but positively related to the spread of the put option having the same strike price and maturity, and vice versa. These findings suggest that traders view call and put options as substitutes.

This paper examines the signalling implications of sinking funds and shows that under information asymmetry the sinking fund amortization rate provides a credible signal for the quality of the firm. In a separating equilibrium, better quality firms choose higher sinking fund amortization rates in their bond issues. A latent index model is proposed for testing the hypothesis of sinking fund signalling. Empirical evidence indicates that the sinking fund amortization rate signals the credit quality of the firm.

Rogalski-Tinic have reported a monthly pattern in ex post stock return variances that differs between small and large market capitalization firms. Maloney-Rogalski find that option prices reflect these monthly patterns ex ante. This study extends Maloney-Rogalski's work by devising an expiration-specific weighted implied standard deviation (WISD). It is found that: i) the monthly patterns in one-month WISDs are basically similar to the monthly patterns in ex post variances detected by Rogalski-Tinic for both large and small size firms, and ii) use of expiration-specific WISDs, as opposed to standard composite WISDs, results in improved performance of option pricing models.

A vector autoregressive (VAR) model is used to examine the relation between aggregate insider transactions and stock market returns. Consistent with the extant literature, there is some predictive content associated with aggregate insider transactions, but its magnitude is slight. In contrast, market returns have substantial influence on the aggregate purchases and sales of corporate insiders. The findings suggest that: 1) the degree of mispricing observed by insiders is small; 2) very little of the mispricing is associated with unanticipated macroeconomic factors; and 3) investors cannot use aggregate insider transactions to profitably predict future market returns over the following eight weeks.