THE SQUARED ORNSTEIN-UHLENBECK MARKET

We study a complete market containing J assets, each asset contributing to the production of a single commodity at a rate that is a solution to the squared Ornstein-Uhlenbeck (Cox-Ingersoll-Ross) SDE. The assets are owned by K agents with CRRA utility functions, who follow feasible consumption/investment regimes so as to maximize their expected time-additive utility from consumption. We compute the equilibrium for this economy and determine the state-price density process from market clearing. Reducing to a single (representative) agent, and exploiting the relation between the squared-OU and squared-Bessel SDEs, we obtain closed-form expressions for the values of bonds, assets, and options on the total asset value. Typical model parameters are estimated by fitting bond price data, and we use these parameters to price the assets and options numerically. Implications for the total asset price itself as a diffusion are discussed. We also estimate implied volatility surfaces for options and bond yields.     

Volatility Estimation with Price Quanta

Volatility estimators based on high, low, opening and closing prices have been developed, and perform well on simulated data, but on real data they frequently give lower values for volatility than the simple open–close estimator. This may be due to the fact that for real data, the maximum (or minimum) price is often at the beginning or end of the day. While this could not happen if the observed process was log Brownian, it could happen if the observed process were log Brownian, but observed only to the nearest penny. We develop the theory of such approximations to derive the corrected versions of the basic estimators.     

MODELING LIQUIDITY EFFECTS IN DISCRETE TIME

We study optimal portfolio choices for an agent with the aim of maximizing utility from terminal wealth within a market with liquidity costs. Under some mild conditions, we show the existence of optimal portfolios and that the marginal utility of the optimal terminal wealth serves as a change of measure to turn the marginal price process of the optimal strategy into a martingale. Finally, we illustrate our results numerically in a Cox–Ross–Rubinstein binomial model with liquidity costs and find the reservation ask prices for simple European put options.     

Technology Strategy and Innovation: The Use of Derivative Strategies in the Aerospace Industry

Strategy has become an increasingly important theme within the management of innovation. This is reflected in the increasing amount of attention given to topics such as technology strategy within the innovation literature. However research into technology strategy has tended to focus on technology acquisition rather than technology exploitation. This paper focuses on one often neglected way in which companies can exploit the technological resources at their disposal, namely through the use of a derivative strategy where new technology is combined with old products or parts of old products in order to develop new products. The paper explores this type of strategy by means of a case study from the commercial jet engine sector of the aerospace industry. The case study provides an opportunity not only to explore the nature of derivative strategies in detail it also highlights the benefits, both direct and indirect, to be gained from this type of strategy as a means of exploiting an organisation's technological resources. The paper shows how a derivative strategy can contribute to the broader strategic goals of companies in technology based industries through strategies designed to ensure the most effective utilisation of the technology base.     

The minimum optimal steel plant and the survivor technique of cost estimation

The survivor technique is used to examine economies of scale in the U.S. steel industry, and the results are compared to an earlier engineering approach study by Tarr. Specifically, the paper focuses on the conventional fully-integrated steel mill with capacities of over 1 million tons (MT) per year. The results are consistent with Tarr's estimate of a conventional integrated steel mill Minimum Optimal Scale of 6 MT a year. The analysis and conclusions set forth are those of the author and do not necessarily reflect the views of other members of the Bureau of Economics, other Commission staff, or the Commission itself. The author would like to thank the following people: Morris Morkre, Joseph Mulholland, Pauline Ippolito, John Rolfe, and an anonymous referee for helpful comments and suggestions on the various drafts and Ty D. Weisendanger and Barry R. Sherman for help in the data collection.