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- Title
Optimal Inference for Spot Regressions.
- Authors
Bollerslev, Tim; Li, Jia; Ren, Yuexuan
- Abstract
Betas from return regressions are commonly used to measure systematic financial market risks. "Good" beta measurements are essential for a range of empirical inquiries in finance and macroeconomics. We introduce a novel econometric framework for the nonparametric estimation of time-varying betas with high-frequency data. The "local Gaussian" property of the generic continuous-time benchmark model enables optimal "finite-sample" inference in a well-defined sense. It also affords more reliable inference in empirically realistic settings compared to conventional large-sample approaches. Two applications pertaining to the tracking performance of leveraged ETFs and an intraday event study illustrate the practical usefulness of the new procedures. (JEL C22, C58, G12, G23)
- Subjects
EXCHANGE traded funds; NONPARAMETRIC estimation; FINANCIAL risk; FINANCIAL markets; MACROECONOMICS
- Publication
American Economic Review, 2024, Vol 114, Issue 3, p678
- ISSN
0002-8282
- Publication type
Article
- DOI
10.1257/aer.20221338