Multi-step forecasts from threshold ARMA models using asymmetric loss functions

被引:5
作者
Niglio, Marcella [1 ]
机构
[1] Univ Salerno, Dipartimento Sci Econ & Stat, I-84084 Fisciano, SA, Italy
关键词
nonlinear prediction; general loss functions; SETARMA; Linex;
D O I
10.1007/s10260-007-0044-x
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
The forecasts generation from nonlinear time series models is investigated under general loss functions. After presenting the main results and some relevant features of these functions, the Linex loss has been used to generate multi-step forecasts from threshold autoregressive moving average models showing their main properties and some results connected to a proper transformation of the forecast errors. A simulation exercise highlights interesting properties of the proposed predictors, both in terms of their bias and their distribution, further clarifying how the Linex predictor can be helpful in empirical applications.
引用
收藏
页码:395 / 410
页数:16
相关论文
共 21 条
[11]  
GOOIJER J., 1998, J TIME SER ANAL, V19, P1
[12]  
Granger C. W. J., 1999, SPAN ECON REV, V1, P161, DOI DOI 10.1007/s101080050007
[13]   PREDICTION WITH A GENERALIZED COST OF ERROR FUNCTION [J].
GRANGER, CWJ .
OPERATIONAL RESEARCH QUARTERLY, 1969, 20 (02) :199-&
[14]  
Hendry, 2002, COMPANION EC FORECAS, P241
[15]  
Hwang S., 2001, ANN ECON FINANC, V2, P187
[16]   HIGHEST-DENSITY FORECAST REGIONS FOR NONLINEAR AND NONNORMAL TIME-SERIES MODELS [J].
HYNDMAN, RJ .
JOURNAL OF FORECASTING, 1995, 14 (05) :431-441
[17]  
PATTON AJ, 2006, IN PRESS J AM STAT A
[18]   Properties of optimal forecasts under asymmetric loss and nonlinearity [J].
Patton, Andrew J. ;
Timmermann, Allan .
JOURNAL OF ECONOMETRICS, 2007, 140 (02) :884-918
[19]   Conditional minimum volume predictive regions for stochastic processes [J].
Polonik, W ;
Yao, QW .
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2000, 95 (450) :509-519
[20]  
Tong H., 1990, NONLINEAR TIME SERIE