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Better the Devil You Know: Improved Forecasts from Imperfect Models.

Authors :
Dong Hwan Oh
Patton, Andrew J.
Source :
Working Papers: U.S. Federal Reserve Board's Finance & Economic Discussion Series; Nov2021, p1-40, 44p
Publication Year :
2021

Abstract

Many important economic decisions are based on a parametric forecasting model that is known to be good but imperfect. We propose methods to improve out-of-sample forecasts from a misspecified model by estimating its parameters using a form of local M estimation (thereby nesting local OLS and local MLE), drawing on information from a state variable that is correlated with the misspecification of the model. We theoretically consider the forecast environments in which our approach is likely to offer improvements over standard methods, and we find significant forecast improvements from applying the proposed method across distinct empirical analyses including volatility forecasting, risk management, and yield curve forecasting. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19362854
Database :
Complementary Index
Journal :
Working Papers: U.S. Federal Reserve Board's Finance & Economic Discussion Series
Publication Type :
Report
Accession number :
154063438
Full Text :
https://doi.org/10.17016/FEDS.2021.071