By Apostolos Serletis
Книга Quantitative and Empirical research of strength Markets Quantitative and Empirical research of strength MarketsКниги Экономика Автор: Apostolos Serletis Год издания: 2007 Формат: pdf Издат.:World clinical Publishing corporation Страниц: 304 Размер: 3,7 Mb ISBN: 9812704744 Язык: Английский0 (голосов: zero) Оценка:Quantitative and Empirical research of strength Markets (World medical sequence on power and source Economics)By Apostolos Serletis
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Additional resources for Quantitative and Empirical Analysis of Energy Markets
Consequently, shedding some light on what these factors might be (that is, to investigate whether they are liquidity factors or information factors) could be the subject of particularly constructive future empirical work. Chapter 4 Business Cycles and the Behavior of Energy Prices Apostolos Serletis and Vaughn W. 1 Introduction The theory of storage, which postulates that the marginal convenience yield on inventory falls at a decreasing rate as aggregate inventory increases [see, for example, Brennan (1958), Telser (1958), and Working (1949)], is the dominant model of commodity futures prices.
3. 1), t is the number of days remaining until the futures contract expires, V OL(t) is the number of futures contracts traded on day t, and the error terms, ε(t) and u(t) are each assumed to be independently and identically distributed. The constant term α0 measures the price variability at maturity and should be positive under the assumption that it equals the variability of the spot price on that day. The slope coeﬃcient α1 measures the sensitivity of the variability of the futures price to changes in time to maturity.
This is a maximum likelihood approach for estimating long-run relations in multivariate vector autoregressive models. This approach, by allowing the analysis of the data in a full system of equations model, is suﬃciently ﬂexible to account for long-run properties as well as short-run dynamics. Cointegration is designed to deal explicitly with the analysis of the relationship between non-stationary time series. In particular, it allows individual time series to be non-stationary but requires a linear combination of the series to be stationary.