Document Type

Article

Rights

Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence

Publication Details

Journal of Signal and Information Processing, 2012

doi:10.4236/jsip.2012.

Published Online 2012

Abstract

Energy traders need to decide what markets and commodities to trade in, when to open and close trades and how to maximize profits. In this paper we consider an approach for analyzing energy commodity price data based on the Lévy index in order to develop a new short-term predictive trend indicator for the price. This is achieved by computing the unwrapped phase signal generated from the Lévy index of both the Stochastic Volatility and price and is evaluated using data from the Irish Energy Market, namely, time series for the price of Electricity, Gas and Oil. The initial results show the predictive hypothesis holds true and algorithms are developed for implementation on an open source trading platform (Alpari MetaTrader4) which includes a range of energy commodities. This is used to demonstrate the potential of the approach in support of energy commodities trading compounded in a set of prototype MetaQuotes Language 4 (MQL4) Apps which can be downloaded and evaluated further by interested readers.

DOI

10.4236/jsip.2012.

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