Marché à terme | EPFL Graph Search

Un marché à terme, ou marché des contrats à terme, est un marché où l'engagement pris par le donneur d'ordre (qu'il s'agisse de vendre ou d'acheter) s'exécutera (produira tous ses effets) à une échéance dont la date, définitivement convenue par avance, se situe postérieurement à la date de l'engagement pris par le donneur d'ordre. Voir articles principaux : contrat à terme et dérivé Histoire Histoire des marchés à terme et bourses de commerce L'un des premiers marchés à terme est rapporté par l'encyclopédie de Diderot et d'Alembert (1751) sur la bourse de commerce d'Amsterdam. Celle-ci propose trois types de transactions, sur trois marchés différents : marché au comptant, marché à terme (les négociants échangent des marchandises qu'ils ne détiennent pas encore) et marché d'options (l'acquisition d'un droit, sans obligation, d'acheter des marchandises à terme, moyennant le paiement d'une prime). Les marchés à terme d'actions et d'obligations ont pris leur essor en Fra

Three Essays on Asset Pricing

Emmanuel Leclercq

In the first chapter,which is a joint work with Mathieu Cambou and Philippe H.A. Charmoy, we study the distribution of the hedging errors of a European call option for the delta and variance-minimizing strategies. Considering the setting proposed by Heston (1993), we assess the error distribution by computing its moments under the real-world probability measure. It turns out that one is better off implementing either a delta hedging or a variance-minimizing strategy, depending on the strike and maturity of the option under consideration. In the second paper, which is a joint work with Damir Filipovic and Loriano Mancini, we develop a practicable continuous-time dynamic arbitrage-free model for the pricing of European contingent claims. Using the framework introduced by Carmona and Nadtochiy (2011, 2012), the stock price is modeled as a semi-martingale process and, at each time t , the marginal distribution of the European option prices is coded by an auxiliary process that starts at t and follows an exponential additive process. The jump intensity that characterizes these auxiliary processes is then set in motion by means of stochastic dynamics of Itô's type. The model is a modification of the one proposed by Carmona and Nadtochiy, as only finitely many jump sizes are assumed. This crucial assumption implies that the jump intensities are taken values in only a finitedimensional space. In this setup, explicit necessary and sufficient consistency conditions that guarantee the absence of arbitrage are provided. A practicable dynamic model verifying them is proposed and estimated, using options on the S&P 500. Finally, the hedging of variance swap contracts is considered. It is shown that under certain conditions, a variance-minimizing hedging portfolio gives lower hedging errors on average, compared to a model-free hedging strategy. In the third and last chapter, which is a joint work with Rémy Praz, we concentrate on the commodity markets and try to understand the impact of financiers on the hedging decisions. We look at the changes in the spot price, variance, production and hedging choices of both producers and financiers, when the mass of financiers in the economy increases. We develop an equilibrium model of commodity spot and futures markets in which commodity production, consumption, and speculation are endogenously determined. Financiers facilitate hedging by the commodity suppliers. The entry of new financiers thus increases the supply of the commodity and decreases the expected spot prices, to the benefits of the end-users. However, this entry may be detrimental to the producers, as they do not internalize the price reduction due to greater aggregate supply. In the presence of asymmetric information, speculation on the futures market serves as a learning device. The futures price and open interest reveal different pieces of private information regarding the supply and demand side of the spot market, respectively. When the accuracy of private information is low, the entry of new financiers makes both production and spot prices more volatile. The entry of new financiers typically increases the correlation between financial and commodity markets.

EPFL2014

Unspanned Stochastic Volatility and the Pricing of Commodity Derivatives

Anders Trolle

Commodity derivatives are becoming an increasingly important part of the global derivatives market. Here we develop a tractable stochastic volatility model for pricing commodity derivatives. The model features unspanned stochastic volatility, quasi-analytical prices of options on futures contracts, and dynamics of the futures curve in terms of a low-dimensional affine state vector. We estimate the model on NYMEX crude oil derivatives using an extensive panel data set of 45,517 futures prices and 233,104 option prices, spanning 4082 business days.We find strong evidence for two predominantly unspanned volatility factors.

Oxford University Press2009

Efficient Pricing of Energy Derivatives

Anders Trolle

I present a tractable framework, first developed in Trolle and Schwartz (2009), for pricing energy derivatives in the presence of unspanned stochastic volatility. Among the model features are i) a perfect fit to the initial futures term structure, ii) a fast and accurate Fourier-based pricing formula for European-style options on futures contracts, enabling efficient calibration to liquid plain-vanilla exchange-traded derivatives, and iii) the evolution of the futures curve being described in terms of a low-dimensional affine state vector, making the model ideally suited for pricing complex energy derivatives and real options by simulation. I also consider an extension of the framework that takes jumps in spot prices into account.

Palgrave Macmillan US2014

Three Essays on Asset Pricing

Emmanuel Leclercq

EPFL2014