1,193 research outputs found
Segmentation in the Crude Oil Futures Term Structure.
Whereas the spatial integration has already been examined in commodity markets, empirical tests on temporal integration have never been carried out. Relying on the âpreferred habitatâ theory, which is applied to the crude oil market, this article investigates whether this market is segmented or not. Segmentation is defined as a situation in which different parts of the prices curve are disconnected from each other. Consequently, the information conveyed by certain prices is useless when reconstituting the rest of the curve. Empirical tests are carried out with a term structure model, the performances of which depend on the informational value of the prices retained for the estimation. We show that the crude oil futures market is segmented into three parts. The first corresponds to maturities below 28 months, the second is situated between the 29th and 47th months, and the third consists of maturities ranging from the 4th to 7th years.Segmentation; Information; Future Prices; Term Structure; Crude Oil;
Convenience Yield and Commodity Markets.
This article explains the role of the convenience yield in the relationships linking spot and futures prices in commodity derivatives markets. First, this variable restores the non arbitrage relationship between the prices of the underlying asset and the derivative instrument. Second, it allows establishing connections between commodities and other assets. Third, it explains why firms store at an apparent loss. The convenience is however a controversial concept. Indeed, the absence of direct evidence for this quantity signifies, first that it is necessary to address the issue of estimating it and second, that it can be accused of being an ad hoc construction. Moreover, in spite of an early interest for this concept, there is no real consensus on its definition. This article aims at gathering all the reasonable explanations which were proposed trough time in the literature.Convenience yield; Non storable commodities; Arbitrage; Inventory; Commodity;
Term structure of crude oil futures prices : a principal component analysis.
Cet article sâappuie sur une analyse en composantes principales pour identifier les mouvements des courbes de prix du pĂ©trole brut. LâĂ©tude confirme que trois composantes permettent dâexpliquer les fluctuations des prix Ă terme : dĂ©placement parallĂšle, pentification, et courbure. De plus, deux conclusions sont obtenues, concernant, dâune part, lâĂ©volution de la dynamique des prix sur longue pĂ©riode, et dâautre part, lâinfluence de la maturitĂ© sur cette dynamique. Les composantes apparaissent comme stables, et le comportement des prix Ă long terme comme plus complexe.Crude oil; Term Structure; Future Prices;
Simple and extended Kalman filters : an application to term structures of commodity prices.
This article presents and compares two different Kalman filters. These methods provide a very interesting way to cope with the presence of non-observable variables, which is a frequent problem in finance. They are also very fast even in the presence of a large information volume. The first filter presented, which corresponds to the simplest version of a Kalman filter, can be used solely in the case of linear models. The second filter - the extended one - is a generalization of the first one, and it enables one to deal with non-linear models. However, it also introduces an approximation in the analysis, whose possible influence must be appreciated. The principles of the method and its advantages are first presented. It is then explained why it is interesting in the case of term structure models of commodity prices. Choosing a well-known term structure model, practical implementation problems are discussed and tested. Finally, in order to appreciate the impact of the approximation introduced for non-linear models, the two filters are compared.Term Structure; Commodity Future Prices; Kalman Filter;
Statistical properties of derivatives: a journey in term structures.
This article presents an empirical study of thirteen derivative markets for commodity and ïŹnancial assets. This paper goes beyond statistical analysis by including the maturity as a variable for futures contractsâs daily returns, from 1998 to 2010 and for delivery dates up to 120 months. We observe that the mean and variance of the commodities follow a scaling behavior in the maturity dimension with an exponent characteristic of the Samuelson effect. The comparison of the tails of the probability distribution according to the expiration dates shows that there is a segmentation in the fat tails exponent term structure above the LĂ©vy stable region. Finally, we compute the average tail exponent for each maturity and we observe two regimes of extreme events for derivative markets, reminding of a phase diagram with a sharp transition at the 18th delivery month.Derivatives; Econophysics; Tail exponents; Term structures;
On the spot-futures no-arbitrage relations in commodity markets
In commodity markets the convergence of futures towards spot prices, at the
expiration of the contract, is usually justified by no-arbitrage arguments. In
this article, we propose an alternative approach that relies on the expected
profit maximization problem of an agent, producing and storing a commodity
while trading in the associated futures contracts. In this framework, the
relation between the spot and the futures prices holds through the
well-posedness of the maximization problem. We show that the futures price can
still be seen as the risk-neutral expectation of the spot price at maturity and
we propose an explicit formula for the forward volatility. Moreover, we provide
an heuristic analysis of the optimal solution for the
production/storage/trading problem, in a Markovian setting. This approach is
particularly interesting in the case of energy commodities, like electricity:
this framework indeed remains suitable for commodities characterized by
storability constraints, when standard no-arbitrage arguments cannot be safely
applied
Filtering in Finance.
In this article we present an introduction to various Filtering algorithms and some of their applications to the world of Quantitative Finance. We shall first mention the fundamental case of Gaussian noises where we obtain the well-known Kalman Filter. Because of common nonlinearities, we will be discussing the Extended Kalman Filter.Commodity Prices; Term Structure; Stock Prices; Kalman Filter;
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