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Denoising the Equity Premium

Alexandridis, Antonios, Panopoulou, Ekaterini (2019) Denoising the Equity Premium. In: 39th International Symposium of Forecasters, 16-19 Jun 2019, Thessaloniki, Greece. (In press)

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Abstract

Previous studies have shown that a variety of economic variables fails to deliver consistently accurate out-of-sample forecasts for the equity premium. In this study we propose a wavelet denoising framework in the context of equity premium forecasting. First, we decompose the time-series using wavelet analysis and then we remove the noise in different frequencies. Our results show that the proposed method improves the forecasting ability of linear models indicating that wavelet denoising can successfully identify the underlying persistent signal in the equity premium time-series. Motivated by this, we apply various linear and nonlinear models such as wavelet networks and neural networks to further improve the accuracy of our forecasts.

Item Type: Conference or workshop item (Proceeding)
Subjects: H Social Sciences > HG Finance
Divisions: Faculties > Social Sciences > Kent Business School > Accounting and Finance
Depositing User: Antonis Alexandridis
Date Deposited: 25 Jun 2019 06:41 UTC
Last Modified: 26 Jun 2019 07:49 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/74564 (The current URI for this page, for reference purposes)
Alexandridis, Antonios: https://orcid.org/0000-0001-6448-1593
Panopoulou, Ekaterini: https://orcid.org/0000-0001-5080-9965
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