What explains long memory in futures price volatility?

Authors: Power, G. J.1; Turvey, C.2

Source: Applied Economics, Volume 43, Number 24, 1 September 2011 , pp. 3395-3404(10)

Publisher: Routledge, part of the Taylor & Francis Group

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Long memory in futures price volatility is a well-documented stylized fact with implications for market efficiency, risk management, forecasting and option pricing bias. The implications of long-memory differ, however, based on whether it is of a ‘fractional’ or of a ‘stochastic’ type. The aims of this article are to determine, in the case of agricultural commodity futures data, which type better describes price volatility and also to evaluate several competing explanations for findings of long memory. The evidence presented here finds little support for three out of four potential explanations, namely, excessive noise in the volatility measure, bias in the long-memory estimator and understated SEs of the long-memory parameter. For the data considered, price volatility appears to be most likely generated by a nonfractional long-memory process such as a stochastic break or stochastic unit root.

Document Type: Research Article

DOI: http://dx.doi.org/10.1080/00036841003636300

Affiliations: 1: Department of Agricultural Economics,Texas A&M University, College StationTexas 77840, USA 2: Department of Applied Economics and Management,Cornell University, IthacaNY 14850, USA

Publication date: September 1, 2011

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