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The Fama-French (FF) five-factor model is cast into a dynamic setting to capture the impact of illiquidity over the phases of the business cycle on the returns of the passive FF twelve sector portfolios. We use two dynamic approaches, Kalman filtering and a recursive/rolling robust instrumental variables (IV) algorithm cast into a GMM framework, to determine time-varying alpha and beta estimates. Our principal result is that the Kalman filter approach supports the hypothesis that illiquidity is an important risk factor in a dynamic context. However, the only factor found to matter in the dynamic GMM approach is the market risk premium. Nevertheless, illiquidity may be prescient with respect to financial crises. Keywords: Illiquidity, Fama-French five-factor model, Kalman filter, Robust IV algorithm, JEL Classification: C58, G12

The capital asset pricing model (CAPM), Fama-French (FF), and Pastor-Stambaugh (PS) factor models are examined using a new dynamic rolling regression version of the generalized method of moments (GMM) method. This rolling regression framework not only allows us to investigate phases of the business cycle, but also permits regression estimates to vary through time due to changes in the development and efficiency of the sectors. The principal reasons for using the dynamic GMM with robust instruments is that some of these factors are measured with errors and the disturbances may be non-spherical. The CAPM appears as the most parsimonious model to explain the FF sector returns. Furthermore, the rolling GMM approach is clearly more sensitive to dynamic financial episodes than the ordinary least squares approach. In particular, liquidity has some anticipatory power, as it is able to forecast the 2007–2009 crises with heightened volatility starting in late 2005.

(1981). Bank Annual Report Disclosure Adequacy Internationally. Accounting and Business Research: Vol. 11, No. 43, pp. 189-196.

An important measure of the quality of academic programs is the publications authored by an institution’s faculty members. Studies along these lines have been made for Economics and Business Administration in Canada but not so far for Management Science / Operations Research, a field in which approximately forty Canadian universities offer courses. Publications by authors at Canadian schools in fifteen major MS / OR journals duringthe 1964–79 period were used to rank Canadian universities. For the sixteen-year period the topfive schools were Toronto, Waterloo, UBC, Montreal, and Alberta. Since not all the schools offered MS / OR courses in 1964 nor were all the journals published duringthe whole period, two subperiods were used. The trend is generally upward, indicating more intensive publishing by Canadian authors, while more Journals allow for more extensive publishing.

Most of us have encountered problems in developing an effective quantitative analysis program for our business schools in the United States. We have often found managers very reluctant to adopt QA techniques; on the other hand, students, although not reluctant, lacked the necessary mathematical background. During the academic year 1970–71, the authors assisted in the development of a QA department in the business school of a developing nation which offers both resident coursework for graduate students and executives seminars for businessmen. Both the students and the executives had the necessary mathematical background for rapid understanding of QA techniques. The executives appeared eager to use QA in their business operations and the students were highly motivated toward the application of QA to business problems. Our purpose in this article is not to convince all the QA professors to teach in underdeveloped nations, but to furnish information which is likely to be useful to those who attempt to establish similar QA programs in other developing countries.

This expository paper on the use of computers for management decision-making describes how decision models are created and used and points out some of the limitations of both models and computers. It seeks to help remove the inhibitions which some managers still have about computer assistance for top management decision-making problems. Most computers are now being used for routine cost reducing applications, but they instead should be used for complex management decision-making to enhance the profitability of the firm.