کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
998333 1481457 2011 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Quantiles as optimal point forecasts
موضوعات مرتبط
علوم انسانی و اجتماعی مدیریت، کسب و کار و حسابداری کسب و کار و مدیریت بین المللی
پیش نمایش صفحه اول مقاله
Quantiles as optimal point forecasts
چکیده انگلیسی

Loss functions play a central role in the theory and practice of forecasting. If the loss function is quadratic, the mean of the predictive distribution is the unique optimal point predictor. If the loss is symmetric piecewise linear, any median is an optimal point forecast. Quantiles arise as optimal point forecasts under a general class of economically relevant loss functions, which nests the asymmetric piecewise linear loss, and which we refer to as generalized piecewise linear (GPL). The level of the quantile depends on a generic asymmetry parameter which reflects the possibly distinct costs of underprediction and overprediction. Conversely, a loss function for which quantiles are optimal point forecasts is necessarily GPL. We review characterizations of this type in the work of Thomson, Saerens and Komunjer, and relate to proper scoring rules, incentive-compatible compensation schemes and quantile regression. In the empirical part of the paper, the relevance of decision theoretic guidance in the transition from a predictive distribution to a point forecast is illustrated using the Bank of England’s density forecasts of United Kingdom inflation rates, and probabilistic predictions of wind energy resources in the Pacific Northwest.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Forecasting - Volume 27, Issue 2, April–June 2011, Pages 197–207
نویسندگان
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