Maximum entropy estimator for the predictability of energy commodity market time series

Francesco Benedetto, Gaetano Giunta and Loretta Mastroeni

No 192, Departmental Working Papers of Economics - University 'Roma Tre' from Department of Economics - University Roma Tre

Abstract: This paper proposes a novel method for assessing the predictability of energy market time series, by predicting the entropy of the series. According to conventional entropy-based analysis where the entropy is always ex-post estimated), high entropy values characterize unpredictable series, while more stable series exhibits lesser entropy values. Here, we predict ex-ante the entropy regarding the future behavior of a series, based on the observation of historical data. Our prediction is performed according to the optimum least squares minimization algorithm. Preliminary results, applied to energy commodities, show the efficacy of the proposed method for application to energy market time series.

Keywords: Entropy analysis; market efficiency; energy commodity; energy time (search for similar items in EconPapers)
JEL-codes: C53 C63 G17 Q47 (search for similar items in EconPapers)
Date: 2014-07
New Economics Papers: this item is included in nep-ecm and nep-ene
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://dipeco.uniroma3.it/db/docs/wp%20192.pdf

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:rtr:wpaper:0192

Access Statistics for this paper

More papers in Departmental Working Papers of Economics - University 'Roma Tre' from Department of Economics - University Roma Tre Via Silvio d'Amico 77, - 00145 Rome Italy. Contact information at EDIRC.
Bibliographic data for series maintained by Telephone for information ().