A MULTINOMIAL APPROXIMATION FOR AMERICAN OPTION PRICES IN LÉVY PROCESS MODELS

This paper gives a tree-based method for pricing American options in models where the stock price follows a general exponential Lévy process. A multinomial model for approximating the stock price process, which can be viewed as generalizing the binomial model of Cox, Ross, and Rubinstein (1979) for geometric Brownian motion, is developed. Under mild conditions, it is proved that the stock price process and the prices of American-type options on the stock, calculated from the multinomial model, converge to the corresponding prices under the continuous time Lévy process model. Explicit illustrations are given for the variance gamma model and the normal inverse Gaussian process when the option is an American put, but the procedure is applicable to a much wider class of derivatives including some path-dependent options. Our approach overcomes some practical difficulties that have previously been encountered when the Lévy process has infinite activity.     

Strategies to reduce product proliferation

Major problems associated with product proliferation include higher production, inventory, and record-keeping costs; increased expenses associated with trade promotions and slotting fees; added consumer confusion and stress; and increased susceptibility to stockouts. This article describes how a firm can limit product proliferation without incurring reduced sales or lowering consumer loyalty. An effective product proliferation reduction program needs to be based on several principles: resisting the temptation of asking consumers if a greater assortment is required; classifying goods into consumer behavior-based tiers; using interfunctional product pruning teams; practicing mass customization, where appropriate; placing absolute limits on product choice; and implementing effective strategies for product pruning.     

Accelerating the Durable Replacement Cycle with Marketing Mix Variables

In many established product categories, a large component of sales is due to the replacement of existing units. Because of the long expected lifetime of durables, replacement decisions can often be postponed by the consumer. In light of this, one marketing strategy for manufacturers of such products may be to accelerate the timing of product replacement decisions for buyers planning to replace. In this article, Barry Bayus presents the results of his investigation of the effect of marketing efforts on shortening the replacement cycle. Such information can be used by new product managers to forecast more accurately long-term sales and to help decide when to introduce new products (e.g., with enhanced features). Using data on color television purchases, he shows that the marketing variables of price, advertising, new features and styling are related to the timing of discretionary replacements. Further, these data suggest that price has the most impact in accelerating replacement purchases.     

Empirically Testing the Law of One Price in an International Commodity Market: A Rational Expectations Application to the Natural Rubber Market

The Law of One Price (LOP) is an important ingredient in theories of international trade and exchange rate determination. An important shortcoming of the existing empirical literature is that parity is typically assumed to hold contemporaneously. This overlooks the fact that international commodity arbitrage takes place over time as well as across spatially separated markets. Recognizing this fact, we expect to see parity holding for expected prices. A model which incorporates the expectations of commodity arbitragers is constructed and used to test the LOP in the natural rubber market. Results indicate that the inclusion of expectations may be of value when considering the LOP.     

On the informational content of advice: a theoretical and experimental study

This paper examines the market for advice and the underlying perception that advice is useful and informative. We do this by first providing a theoretical examination of the informational content of advice and then by setting up a series of experimental markets where this advice is sold. In these markets we provide bidders with a demographic profile of the “experts” offering advice.The results of our experiment generate several interesting findings. The raw bid data suggest that subjects bid significantly more for data than they do for advice. Second, in the market for advice there appears to be no consensus as to who are the best advisors although on average economists demand the highest mean price and women suffer a discount. In addition, we find that whether a subject suffers from a representativeness bias in the way he or she processes data has an impact on how he or she bids for advice and on his or her willingness to follow it once offered. Finally, we find that on average people impute a low level of informativeness onto advice, consistent with their bidding behavior for data versus advice.This work was done under grant number SES-0425118 of the National Science Foundation. The authors would like to recognize the Center for Experimental Social Science at New York University for its additional support. We also acknowledge the help of Elizabeth Potamites for her research assistance.