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Spring 2019

Special Features

  1. Will You Become a Victim of Your Models? by Thomas Willemain
    In this feature section, Tom Willemain provokes a good deal of thought about the role of statistical models in supply chain forecasting, a field that he believes lags far behind finance in embracing algorithms over gut instinct. His article is followed by Commentaries from practitioners and researchers about the realities that can lead to ”model failure” and the conditions for successful implementation of model-based decision making.
  2. Predicting Medical Risks and Appreciating Uncertainty by Spyros Makridakis, Ann Wakefield, and Richard Kirkham
    In this paper, the authors present a number of specific examples related to risk and uncertainty in the context of clinical decision making—some more than a little alarming—including extremely high incidences of misdiagnosis, reluctance on the part of medical professionals to abandon treatment regimens that are doing patients no good and may be causing harm, and systemic flaws in medical research methodology that can impede important new data from reaching practitioners.

    • Commentaries by John P.A. Ioannidis and Nassim Nicholas Taleb


  1. The Ten Commandments of Economic Forecasting by Azhar Iqbal and John Silvia
    In this ever-evolving world, we need accurate forecasts of key economic and financial variables to help decision makers design effective policies. Azhar Iqbal and John Silvia present a framework of “ten commandments” to govern the economic-forecasting process. They begin with the need to know the forecasting objective and loss function and end with the monitoring of forecast performance and refinements to the original model.
  2. Monetized Forecast-Error Comparisons by Shaun Snapp
    Standard error metrics such as the MAPE are not effective in directing a company to make changes that will have the most significant impact. Rather, it is in the monetization of forecast error that we enable the best use of forecasting resources. This article illustrates the calculation of the monetized forecast-error metric and presents the author’s free application designed to steer improvement in forecast accuracy at specific product/locations.
  3. Medicine and Risk Transfer by Nassim Nicholas Taleb
    Whether risk comes from a misalignment of incentives between patient and practitioner, a misunderstanding of the probabilistic structure and the dynamics of the problem, or psychological biases that favor over-treatment is a matter of long discussion. This note will put the medical exposures in the context of risk management and decision theory, and presents three mechanisms of risk transfer from visible to hidden risks.


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