While there is growing evidence that stock prices do not follow pure random walks, the degree of existence of temporary components in stock prices is not well known. Modeling stock prices as the sum of a random walk and a general stationary (predictable) component, the paper proposes an estimable lower bound on the proportion of total stock return variance caused by the predictable component. Contrary to the absolute value of the first-order auto-correlation coefficient estimates of Fama and French (1988a), this lower bound reasonably estimates the true variance proportion in finite samples also when the temporary component does not follow a first-order autoregressive process. The estimated mean values of the lower bound reach a maximum of 10 percent for the equal-weighted market portfolio of NYSE stocks over the post-war period 1947–1986, while the maximum is 25 percent for the pre-war period 1926–1946. The value-weighted market portfolio exhibits generally smaller variance proportion estimates. The pure random walk hypothesis is also reexamined using a standard variance ratio statistic extended to multiple return horizons.

This paper examines the relation between managerial ownership and the probability of being a target firm, and the impact of managerial ownership on target shareholder returns. The paper finds that targets have lower managerial ownership than either their industry counterparts or randomly selected nontargets. Managerial ownership is significantly lower in contested compared to uncontested offers, and in unsuccessful compared to successful cases. Managerial ownership is significantly related to abnormal returns in contested cases that are ultimately successful. The results are consistent with a positive impact of managerial ownership where it is used to negotiate, but not ultimately block, an acquisition.

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 deals with the nature of option interactions and the valuation of capital budgeting projects possessing flexibility in the form of multiple real options. It identifies situations where option interactions can be small or large, negative or positive. Interactions generally depend on the type, separation, degree of being “in the money,” and the order of the options involved. The paper illustrates, through a generic example, the importance of properly accounting for interactions among the options to defer, abandon, contract or expand investment, and switch use. It is shown that the incremental value of an additional option, in the presence of other options, is generally less than its value in isolation, and declines as more options are present. Therefore, valuation errors from ignoring a particular option may be small. However, configurations of real options exhibiting precisely the opposite behavior are identified. Comparative statics results confirm that the value of flexibility, despite interactions, manifests familiar option properties.

According to the Diamond-Verrecchia hypothesis, if increases in short interest are correlated with information that is not yet public, they should precipitate a price adjustment. Stocks with unexpected increases in short interest are found to generate statistically significant, but small, negative abnormal returns for a short period around the announcement date. When the sample is divided into stocks with and without tradable options, nonoptioned stocks closely mimic these results but the optioned stocks do not. In a cross-sectional analysis of individual firms, the short-term negative abnormal returns are found to be 1) more negative, the higher the degree of unexpected short interest and, 2) less negative if the firm has tradable options.

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.

The relations between volume, volatility, and market depth in eight physical and financial futures markets are examined. Evidence suggests that linking volatility to total volume does not extract all information. When volume is partitioned into expected and unexpected components, the paper finds that unexpected volume shocks have a larger effect on volatility. Further, the relation is asymmetric; the impact of positive unexpected volume shocks on volatility is larger than the impact of negative shocks. Finally, consistent with theories of market depth, the study shows large open interest mitigates volatility.

This paper studies the dynamic investment policies of firms under asymmetric information.Managers make decisions to maximize the wealth of existing shareholders. In equilibrium, the superior firms invest “myopically”, choosing intrinsically lower-valued projects that produce “early” cash flows. The inferior firms follow the socially preferred rule of investing in intrinsically higher-valued projects that produce “late” cash flows. In addition to explaining investment myopia, the model generates numerous predictions regarding announcement effects of equity issues and attempts by firms to stockpile cash, firms' preferences for limits on mandatory disclosure rules, and the effects of managerial entrenchment motives.

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 provides a direct test of the hypothesis that large January returns can be attributed to omitted risk factors. Data from 1926–1991 show that the January return in the smallest decile of NYSE firms dominates the January returns for all other deciles by the first-order stochastic dominance. Similarly, January returns in all deciles (with the exception of ninth and tenth deciles) dominate non-January returns by first-, second-, or third-order stochastic dominance. The presence of stochastic dominance by January returns suggests that the omitted risk factors are not likely to explain the January effect.

This paper demonstrates that when log price changes are not IID, their conditional density may be more accurate than their unconditional density for describing short-term behavior. Using the BDS test of independence and identical distribution, daily log price changes in four currency futures contracts are found to be not IID. While there appear to be no predictable conditional mean changes, conditional variances are predictable, and can be described by an autoregressive volatility model that seems to capture all the departures from independence and identical distribution. Based on this model, daily log price changes are decomposed into a predictable part, which is described parametrically by the autoregressive volatility model, and an unpredictable part, which can be modeled by an empirical density, either parametrically or nonparametrically. This two-step seminonparametric method yields a conditional density for daily log price changes, which has a number of uses in financial risk management.

This paper presents empirical tests of the constant volatility version of the Heath, Jarrow, and Morton model, which is also the continuous time limit of the Ho and Lee model. Using a generalized method of moments (GMM) test on three years of daily data for Eurodollar futures and futures options, the model can be rejected for most subperiods. Various biases in the fitted option prices relative to the market prices are documented through a regression study. The small sample properties and power of the GMM framework to this setting are also studied through simulations.

One of the most fundamental results in finance is the equivalence of a no-arbitrage condition to the existence of a pricing operator in markets without transaction costs (see Ross (1978)). Garman and Ohlson (1981) extended this to markets with proportional transaction costs. The current paper further extends this result to markets with realistic (and nonproportional) transaction costs. These costs include all investors' market-impact and short-borrowing costs, large investors' institutional commissions, and for small investors only the additional cost of retail commissions. They are functions of the value of the trade and have increasing, increasing, constant, and decreasing marginal rates, respectively, in that value. Garman and Ohlson showed that equilibrium prices in their notion of a “corresponding” cost-free market, plus a certain factor, prevail under equilibrium in markets with proportional transaction costs. The current paper extends this to realistic transaction costs and establishes the functional relation between this factor and the form of such costs.

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.

Consistent with Connolly's (1989), (1991) evidence, this study finds that sample size and/or error term adjustments render U.S. day-of-the-week effects statistically insignificant. In contrast, day-of-the-week effects in seven European countries and in Canada and Hong Kong are robust to individual sample size or error term adjustments, and day-of-the-week effects in five European countries survive the simultaneous imposition of both types of adjustments. In most countries where day-of-the-week effects are robust, however, the effects are statistically significant in not more than two weeks out of the month. These findings are inconsistent with explanations of the day-of-the-week effect based on institutional differences or on the arrival of new information. Thus, in the absence of other potential explanations already dismissed by Jaffe and Westerfield (1985), evidence in this study further complicates the international day-of-the-week effect puzzle.

Myers and Majluf (1984) showed that in a world of asymmetric information, managers of overvalued firms issue equity, while managers of undervalued firms use cash, if available. This paper shows that, in a multiperiod world, managers of undervalued firms may find it optimal to issue stock, even though cash is available. Consequently, the market does not interpret all announcements of equity issues as signals of firm overvaluation. The paper also generates predictions regarding the effect of information asymmetry and investment opportunities on i) dividend policy, and ii) the cross-sectional distribution of market reactions when an equity issue is announced.

The 39 experiments reported here examine the impact on trading profits and on market performance of awarding special trading privileges to some traders and not others. In call market experiments, the last-mover and orderflow access privileges are both modestly profitable and neither impairs market performance. In continuous market experiments, quicker access to orderflow information is quite profitable and more detailed access is possibly profitable; both privileges seem to enhance market performance slightly. By contrast, privileged marketmaking is extremely profitable and greatly impairs market performance.

This paper considers the Arbitrage Pricing Theory when investors have incomplete information on the parameters generating asset returns. Each asset in the economy may have a different amount of information available on it. Bayesian investors use their prior beliefs in conjunction with the total available information to assign an expected return and a set of factor betas to each asset. The assigned expected returns are shown to be linear in their associated factor betas. However, the factor betas and prices of assets differ from those under complete information. Specifically, risky assets with high (low) information are priced relatively higher (lower). On the other hand, factor betas of high (low) information assets are relatively lower (higher). The analysis has econometric implications for testing the APT. In this paper's framework, maximum likelihood estimates of factor betas, which are based on normality assumptions, are too high (low) for high (low) information assets. In addition, sequentially increasing the sample size by adding new securities to a factor analysis procedure can result in the detection of apparent additional priced factors when they do not really exist.

This paper compares different approaches to developing arbitrage-free models of the term structure. It presents a numerical procedure that can be used to construct a wide range of one-factor models of the short rate that are both Markov and consistent with the initial term structure of interest rates.

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.