Knowledge that Transforms

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 autocorrelation coefficient estimates of Fama and French (1988a), this lower bound reasonably estimates the true variance proportion in finite samples also when the temporary compo? nent 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 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.

Jaime Cuevas Dermody, Eliezer Z. Prisman, No Arbitrage and Valuation in Markets with Realistic Transaction Costs, The Journal of Financial and Quantitative Analysis, Vol. 28, No. 1 (Mar., 1993), pp. 65-80

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 investigates the warrant pricing abilities of dilution-adjusted versions of the Black-Scholes and Jump-Diffusion option pricing models. Because of the typically long lives of warrants, their pricing is hypothesized to benefit from use of the Jump-Diffusion model, which relaxes the Black-Scholes restriction against stock price jumps. Empirical results indicate that while the Black-Scholes model almost uniformly provides more efficient estimates, the Jump-Diffusion model generally provides less biased estimates of market value. Particularly for the valuation of out-of-the-money warrants and warrants on stocks with a history of large and/or frequent jumps, the Jump-Diffusion model may be preferred.

Karen C. Denning, Kuldeep Shastri, Changes in Organizational Structure and Shareholder Wealth: The Case of Limited Partnerships, The Journal of Financial and Quantitative Analysis, Vol. 28, No. 4 (Dec., 1993), pp. 553-564

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.

A simple moment-ordering condition is shown to be necessary for stochastic dominance. Closely related results on generalizations of the geometric and harmonic means are also provided. An ordering of the moment-generating functions is shown to be necessary and sufficient for stochastic dominance. The results have a straightforward and useful interpretation in terms of constant relative and absolute risk aversion utility functions. These results are used to provide necessary and sufficient conditions for optimality of distributions on an important class of utility functions.

New measures of stock return volatility are developed to increase the precision of stock option price estimates. With Bayesian statistical methods, volatility estimates for a given stock are developed using prior information on the cross-sectional patterns in return volatilities for groups of stocks sorted on size, financial leverage, and trading volume. Call option values computed with the Bayesian procedure generally improve prediction accuracy for market prices of call options relative to those computed using implied volatility, standard historical volatility, or even the actual ex post volatility that occurred during each option's life. Although the Bayesian methods produce biased call price estimators, they do reduce the systematic tendency of standard pricing approaches to overprice (underprice) options on high (low) volatility stocks. Little bias improvement is observed with respect to the time to maturity and moneyness of the call options.

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.