Catastrophe forecasting: seeing “gray” among the “black boxes”

Abstract

Purpose

The purpose of this paper is to consider the problem of using “black‐box” methods to forecast catastrophe events, and illustrate the value of independent peer review.

Design/methodology/approach

The problem with black‐box catastrophe forecasts is the absence of both extensive validation data and impartial peer review. These issues may be addressed by comparing black‐box forecasts with a set of naïve alternative forecasts provided by an independent party. To illustrate this approach, the historical hurricane forecasts of Dr William M. Gray, professor at Colorado State University, are considered and a simple ARIMA analysis is offered as a naïve alternative.

Findings

The analysis shows that Dr Gray's complex forecasting methodology does in fact provide reasonable forecasts, and may indeed offer value beyond a naïve alternative model.

Originality/value

The editorial identifies a major problem in catastrophe forecasting, and suggests one way to address this problem.

Citation

Powers, M.R. (2006), "Catastrophe forecasting: seeing “gray” among the “black boxes”", Journal of Risk Finance, Vol. 7 No. 5, pp. 458-462. https://doi.org/10.1108/15265940610712632