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The economic importance of rare earth elements volatility forecasts


The economic importance of rare earth elements volatility forecasts

Proelss, Juliane ORCID: https://orcid.org/0000-0002-9467-8220, Schweizer, Denis ORCID: https://orcid.org/0000-0001-9115-1178 and Seiler, Volker (2019) The economic importance of rare earth elements volatility forecasts. International Review of Financial Analysis . ISSN 10575219 (In Press)

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Official URL: http://dx.doi.org/10.1016/j.irfa.2019.01.010


We compare the suitability of short-memory models (ARMA), long-memory models (ARFIMA), and a GARCH model to describe the volatility of rare earth elements (REEs). We find strong support for the existence of long-memory effects. A simple long-memory ARFIMA (0, d, 0) baseline model shows generally superior accuracy both in- and out-of-sample, and is robust for various subsamples and estimation windows. Volatility forecasts produced by the baseline model also convey material forward-looking information for companies in the REEs industry. Thus, an active trading strategy based on REE volatility forecasts for these companies significantly outperforms a passive buy-and-hold strategy on both an absolute and a risk-adjusted return basis.

Divisions:Concordia University > John Molson School of Business > Finance
Item Type:Article
Authors:Proelss, Juliane and Schweizer, Denis and Seiler, Volker
Journal or Publication:International Review of Financial Analysis
Date:1 February 2019
  • Manulife Professorship
  • XJTLU Research Conference Fund
Digital Object Identifier (DOI):10.1016/j.irfa.2019.01.010
Keywords:ARFIMA; Fractional integration; Long-memory; Forecasting; Rare earth elements
ID Code:984993
Deposited By: Michael Biron
Deposited On:12 Feb 2019 23:39
Last Modified:01 Feb 2021 02:00


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