Comparing Density Forecasts Using Threshold- and Quantile-Weighted Scoring Rules

被引:283
作者
Gneiting, Tilmann [1 ]
Ranjan, Roopesh [2 ]
机构
[1] Heidelberg Univ, Inst Appl Math, D-69120 Heidelberg, Germany
[2] GE Global Res, Comp & Decis Sci, Bangalore 560066, Karnataka, India
基金
美国国家科学基金会;
关键词
Continuous ranked probability score; Predictive ability testing; Probabilistic forecast; Proper scoring rule; Quantile; Weighted likelihood ratio test; BANK-OF-ENGLAND; PROBABILISTIC FORECASTS; PREDICTION; MODELS; TESTS;
D O I
10.1198/jbes.2010.08110
中图分类号
F [经济];
学科分类号
02 ;
摘要
We propose a method for comparing density forecasts that is based on weighted versions of the continuous ranked probability score. The weighting emphasizes regions of interest, such as the tails or the center of a variable's range, while retaining propriety, as opposed to a recently developed weighted likelihood ratio test, which can be hedged. Threshold- and quantile-based decompositions of the continuous ranked probability score can be illustrated graphically and provide insight into the strengths and deficiencies of a forecasting method. We illustrate the use of the test and graphical tools in case studies on the Bank of England's density forecasts of quarterly inflation rates in the United Kingdom, and probabilistic predictions of wind resources in the Pacific Northwest.
引用
收藏
页码:411 / 422
页数:12
相关论文
共 40 条
[1]   Comparing density forecasts via weighted likelihood ratio tests [J].
Amisano, Gianni ;
Giacomini, Raffaella .
JOURNAL OF BUSINESS & ECONOMIC STATISTICS, 2007, 25 (02) :177-190
[2]  
[Anonymous], 2000, Statistics and Finance: An Interface
[3]   Comparing density forecast models [J].
Bao, Yong ;
Lee, Tae-Hwy ;
Saltoglu, Burak .
JOURNAL OF FORECASTING, 2007, 26 (03) :203-225
[4]   GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSKEDASTICITY [J].
BOLLERSLEV, T .
JOURNAL OF ECONOMETRICS, 1986, 31 (03) :307-327
[5]  
BROWN BG, 1984, J CLIM APPL METEOROL, V23, P1184, DOI 10.1175/1520-0450(1984)023<1184:TSMTSA>2.0.CO
[6]  
2
[7]  
Cervera J. L., 1996, Bayesian Statistics, P513, DOI DOI 10.1093/OSO/9780198523567.003.0029
[8]  
Christoffersen PF, 1996, J APPL ECONOM, V11, P561, DOI 10.1002/(SICI)1099-1255(199609)11:5<561::AID-JAE406>3.3.CO
[9]  
2-J
[10]   Evaluating the Bank of England density forecasts of inflation [J].
Clements, MP .
ECONOMIC JOURNAL, 2004, 114 (498) :844-866