A Frequency-Domain Alternative to Long-Horizon Regressions with Application to Return Predictability

This paper aims at improved accuracy in testing for long-run predictability in noisy series, such as stock market returns. Long-horizon regressions have previously been the dominant approach in this area. We suggest an alternative method that yields more accurate results. We find evidence of predictability in S&P 500 returns even when the con fidence intervals are constructed using model-free methods based on sub-sampling

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Year of publication:	2013
Authors:	Sizova, Natalia
Publisher:	[2013]: [S.l.] : SSRN
Subject:	Regressionsanalyse \| Regression analysis \| Prognoseverfahren \| Forecasting model \| Kapitaleinkommen \| Capital income \| Theorie \| Theory \| Schätzung \| Estimation

Extent:	1 Online-Ressource (21 p)
Type of publication:	Book / Working Paper
Language:	English
Notes:	Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments July 24, 2013 erstellt
Other identifiers:	10.2139/ssrn.2297934 [DOI]
Classification:	C12 - Hypothesis Testing ; C14 - Semiparametric and Nonparametric Methods ; G12 - Asset Pricing ; G14 - Information and Market Efficiency; Event Studies ; E47 - Forecasting and Simulation
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10013078663