Pricing Options on an Asset with Bernoulli Jump-Diffusion Returns

The price movements of certain assets can be modeled by stochastic processes that combine continuous diffusion with discrete jumps. This paper compares values of options on assets with no jumps, jumps of fixed size, and jumps drawn from a lognormal distribution. It is shown that not only the magnitude but also the direction of the mispricing of the Black-Scholes model relative to jump models can vary with the distribution family of the jump component. This paper also discusses a methodology for the numerical valuation, via a backward induction algorithm, of American options on a jump-diffusion asset whose early exercise may be profitable. These cannot, in general, be accurately priced using analytic models. The procedure has the further advantage of being easily adaptable to nonanalytic, empirical distributions of period returns and to nonstationarity in the underlying diffusion process.     

Further Ambiguity When Performance Is Measured by the Security Market Line

This paper employs the optimality conditions for expected utility and mean-variance portfolio problems to examine the ambiguities associated with the security market line criterion both at a point in time and through time. At a point in time, we show that the security market line criterion can be irrelevant, even in meanvariance economies. In a multiperiod setting, we show that the analysis of performance based on portfolio choice is inconsistent with the analysis based on return generating models. Empirical work suggests that the inconsistency can lead to dramatically different estimates of a security's required return.     

The local economic impact of construction projects in a small and relatively self-contained economy: The case of Lancaster University

Whilst the local multiplier impacts of the annual operation of universities has been the subject of intensive research, the economic impacts of capital construction projects have been almost completely ignored. This paper presents the results of detailed analysis of capital projects at Lancaster University in 1993-The reasons for the radically different annual operation and construction multipliers estimated in the Lancaster study are examined. Despite the smaller size of construction multipliers it is argued that it is a serious mistake to estimate local construction multipliers by making simplifying assumptions on the size of the key parameters in the multiplier equations.     

BOOK REVIEW

Emerging Financial Markets, by David O. Beim and Charles W. Calomiris. McGraw‐Hill/Irwin, 2001, 364 pages, price $75.00.     

STRATEGIC ORIENTATION,CAPABILITIES, AND PERFORMANCE IN MANUFACTURER — 3PL RELATIONSHIPS

This study examines how two dimensions of strategic orientation (customer and competitor orientation) influence logistics and market performance. Two capabilities, operational flexibility and collaboration, are studied. Data were collected from manufacturers working with third party logistics providers. The findings suggest that customer and competitor orientations have different influences upon performance when leveraged through the capabilities. Competitor orientation, while having a detrimental direct effect on logistics performance, appears to be the better strategic approach, when supported with operational flexibility since it results in enhanced logistics (efficiency) and market (effectiveness) performance. Customer orientation, on the other hand, greatly improves logistics performance, i.e., internal efficiency.     

A Comparison of Cost of Equity Estimates of Local and Global CAPMs

Cost of equity estimates are compared for three pricing models: the traditional local CAPM, the single (market) factor global CAPM, and the two‐factor global CAPM, with both market and currency index factors. For 2989 US stocks, the average difference in the cost of equity estimates is about 48 basis points between the local CAPM and the single‐factor global CAPM, and is about 61 basis points between the two global models. For 70 developed‐market ADRs, the corresponding average differences are 76 and 47 basis points, respectively. For 48 emerging‐market ADRs, the corresponding average differences are 57 and 70 basis points.