Knowledge that Transforms

Robert H. Litzenberger, Some Observations on Capital Structure and the Impact of Recent Recapitalizations on Share Prices, The Journal of Financial and Quantitative Analysis, Vol. 21, No. 1 (Mar., 1986), pp. 59-71

Richard A. Ashley, Douglas M. Patterson, A Nonparametric, Distribution-Free Test for Serial Independence in Stock Returns, The Journal of Financial and Quantitative Analysis, Vol. 21, No. 2 (Jun., 1986), pp. 221-227

Recent studies indicate that the widespread assumption of parameter stationarity in empirical applications of asset pricing models may be inappropriate. This paper investigates the feasibility of modeling parameter instability as a sequence of persistent stable regimes. Recursive residual and log likelihood techniques are combined to detect and locate shift points. The results indicate that regime shifts are widespread, frequent, and often large enough to significantly effect empirical findings. The nature of the shifts appears to be a rotation of the regression line, indicating that correction of both alpha and beta parameters is required.

Sanjai Bhagat, The Effect of Management's Choice between Negotiated and Competitive Equity Offerings on Shareholder Wealth, The Journal of Financial and Quantitative Analysis, Vol. 21, No. 2 (Jun., 1986), pp. 181-196

The following paper presents a general derivation of the jump process option pricing formula. In particular, a general jump process formula is derived via an analysis of the limiting behavior of the binomial option pricing formula. In deriving the formula, a very simple central limit theorem known as Poisson's Limit Theorem is applied. The simplicity of the analysis allows the establishment of precisely the connections between the specification of the underlying binomial stock return process and the specific form of the corresponding continuous-time jump process formula. Several examples are provided to illustrate these connections.

This paper examines whether investors with power utility functions choose mean-variance-(MV) efficient portfolios when returns are approximately normally distributed and there is borrowing or lending at a riskless interest rate. The results show that the unlevered portfolios of power utility investors plot very closely to the MV-efficient frontier. However, there are marked differences in the mix of risky assets, regardless of whether the portfolios are highly concentrated or widely diversified. Such differences allow power investors to remain solvent even when they lever their optimal portfolios to a greater extent than “less risk-averse” MV investors who risk bankruptcy. It is concluded that the investment policies of power utility and MV investors with similar risk aversion measures are not as similar as is commonly believed. This is particularly true for high power investors, unless explicit solvency constraints are imposed on the MV problem, and for low power investors when quadratic utility approximations are made to the power utility functions. These differences in the investment policies of power utility and MV investors lead us to question the widely-accepted assertion that the assumptions of homogeneous beliefs, normality, a riskless asset, and risk-averse investors imply the simple MV CAPM where all investors, including power utility investors, hold combinations of the market portfolio and the riskless asset.

Portfolios of stocks issued by small firms are well known to earn rates of return in excess of those commensurate with their market sensitivities. One common explanation for this phenomenon is that small firm stocks are riskier than large firm stocks because less information is available about the former than about the latter. A necessary condition for such an explanation to be valid is that the information effect not be eliminated by combining the individual stocks into portfolios. This paper uses jump-diffusion return models to gauge the impact of information by firm size. The results show that portfolios of small firm stocks are no more prone to information surprises than are portfolios of large firm stocks. However, portfolios of small firm stocks are found to react more severely than portfolios of large firm stocks when surprises do occur.

Frank J. Fabozzi, Thom B. Thurston, State Taxes and Reserve Requirements as Major Determinants of Yield Spreads Among Money Market Instruments, The Journal of Financial and Quantitative Analysis, Vol. 21, No. 4 (Dec., 1986), pp. 427-436

Richard R. Simonds, Lynn Roy LaMotte, Archer McWhorter, Jr., Testing for Nonstationarity of Market: An Exact Test and Power Considerations, The Journal of Financial and Quantitative Analysis, Vol. 21, No. 2 (Jun., 1986), pp. 209-220

Alan J. Marcus, David M. Modest, The Valuation of a Random Number of Put Options: An Application to Agricultural Price Supports, The Journal of Financial and Quantitative Analysis, Vol. 21, No. 1 (Mar., 1986), pp. 73-86