BOOK REVIEW

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

From T-Bills to Stocks: Seasonal Anomalies Revisited

This paper employed eleven data series which consist of stocks, bonds, bills, equity premiums, term premiums, and various default premiums to investigate whether January seasonality reported in existing literature is robust across different states of the economy as this has important trading implications. For the periods 1926–1990, small stocks, small stock premiums, low grade bonds, and default premiums (spread between high grade, low grade and government bonds) reveal January seasonality and that the seasonality is robust across different states of the economy except for low grade bond returns and default premiums. January seasonality for low grade bond returns and low grade bond default premiums are primarily driven by results found during periods of economic expansion. Overall, January seasonality is more evident during the economic expansion periods although the magnitude of default premiums is larger during periods of economic contraction. Furthermore, prior findings of strong summer equity returns are primarily driven by the results found during the periods of economic contraction. It is also found that equity returns are generally higher during periods of economic expansion.     

A reappraisal of the forecasting performance of corn and soybean new crop futures

Forecasting performance of December corn and November soybean futures contracts during the previous spring was evaluated using the commonly specified price-level and percent-change models. These models invoke different assumptions regarding stationarity. Using Stein's analytical framework, results for the price-level model suggest avoidable social loss existed in the soybean market since 1973, because November futures provided biased forecasts. Regression R²s for both corn and soybeans declined substantially between 1952–1972 and 1973–1997, suggesting total social loss increased. By contrast, results from the percent-change model suggest only unavoidable social loss existed in the corn and soybean markets, because the futures provided unbiased forecasts. R² increased for corn but declined for soybeans, suggesting unavoidable social loss declined for corn, but increased for soybeans. The important, conflicting nature of the results from the two models underscores the importance of examining alternative model specifications when evaluating price forecasting performance. © 1999 John Wiley & Sons, Inc. Jrl Fut Mark 19: 604–618, 1999     

Technological Threat and Opportunity Assessment

One of the major challenges in the management of innovation is a practical and useful implementation of technology forecasting. This article proposes the concept of aniticpating the technological future, and that a structured approach to this concept could be an invaluable aid to technical decision-making. The notion of technological threat and opportunity assessment is presented as a useful framework for anticipating technological change. This notion is based on a dual approach.Firstly, a rapidly changing global technological landscape necessitates keeping track of technological developments. However, since we are dealing with innovation (rather than mere invention), the market implications are as important as the technological ones and have to be accounted for as such. Secondly, any organisation could be considered to be technology-based to some or other degree, implying that technologies have the ability to affect the bottom line of the organisation in some way. It is thus required to assess the business impact of such technologies, typically through a technology or innovation audit.Having assessed specific technological threats and opportunities facing the organisation, an innovation strategy needs to be developed in response to the identified threats and opportunities. Various possible offensive and/or defensive responses should be considered, culminating in the selection and implementation of an optimal strategy.     

Espoused drum-buffer-rope flow control in serial lines: A comparative study of simulation models

This paper documents an investigation of drum-buffer-rope (DBR) scheduling and flow control methodology in single-product serial production lines. In particular, DBR flow control is reviewed and the importance of correctly representing this type of flow control mechanism in serial lines is discussed. Departures from valid DBR conceptual and simulation modeling are illustrated. It is shown that the model of a previously published paper is a push system not a DBR system, and that related conclusions regarding protective capacity and constraint location are unsupported. Correct modeling of DBR flow control is shown using discrete simulation experiments that compare the DBR model and a similar push model. Suggestions for additional research are offered.