Matching Supply and Demand: The Value of a Second Chance in Producing Seed Corn

This paper analyzes the supply chain for hybrid seed corn in which there are two sequential production periods with random yields before demand occurs. We show that the problem of managing the supply chain can be viewed as a multiperiod optimization model that is easily solved. By examining data that represents actual costs, prices, and yields encountered in the seed corn industry, we gain some insight into the value that the second production period provides. Using a representative sample of hybrids from a major seed corn producer, we show that margins could be enhanced considerably by using the model.     

Liquidity risk and arbitrage pricing theory

Classical theories of financial markets assume an infinitely liquid market and that all traders act as price takers. This theory is a good approximation for highly liquid stocks, although even there it does not apply well for large traders or for modelling transaction costs. We extend the classical approach by formulating a new model that takes into account illiquidities. Our approach hypothesizes a stochastic supply curve for a securitys price as a function of trade size. This leads to a new definition of a self-financing trading strategy, additional restrictions on hedging strategies, and some interesting mathematical issues.Received: 1 November 2003, Mathematics Subject Classification: 60G44, 60H05, 90A09JEL Classification: G11, G12, G13Umut Çetin: This work was performed while Dr. Çetin was at the Center for Applied Mathematics, Cornell UniversityPhilip Protter: Supported in part by NSF grant DMS-0202958 and NSA grant MDA-904-03-1-0092 The authors wish to thank M. Warachka and Kiseop Lee for helpful comments, as well as the anonymous referee and Associate Editor for numerous helpful suggestions, which have made this a much improved paper.     

Detection of Financial Time Series Turning Points: A New CUSUM Approach Applied to IPO Cycles

This paper presents a new Cumulative Sum approach for the detection of turning points in financial time series that are subject to cyclical mean level and volatility regime shifts. The new CUSUM approach is applied to the problem of detecting turning points in hot issue markets for Initial Public Offerings (IPOs), thus providing a multi-dimensional characterization of states of the IPO cycle.