Put | EPFL Graph Search

Le put ou l'option de vente est une option contractuelle de vente par laquelle deux parties s'accordent pour échanger un actif (appelé sous-jacent) à un prix fixé (appelé prix d'exercice ou strike) à une date prédéterminée (dite date de maturité). Une partie, l'acheteur du put, a le droit (non l'obligation) de vendre l'actif sous-jacent au prix d'exercice dans les délais spécifiés tandis que l'autre partie, le vendeur du put, a l'obligation de racheter cet actif au prix d'exercice si l'acheteur décide d'exercer l'option. On parle de « put européen » si le souscripteur peut exercer son droit uniquement à la date de maturité et de « put américain » s'il peut l'exercer à tout moment avant la date de maturité inclusivement. Il permet à l'acheteur du put de se prémunir contre, ou de parier sur, une baisse du prix de ce sous-jacent en dessous du prix d'exercice. La vente d'un put correspond à l'objectif inverse. Son contraire est loption d'achat ou call. Exemple chiffré Le ,

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

Variance Risk Premia in Energy Commodities

Anders Trolle

This paper investigates variance risk premia in energy commodities, particularly crude oil and natural gas, using a robust model-independent approach. Over a period of 11 years, we find that the average variance risk premia are significantly negative for both energy commodities. However, it is difficult to explain the level and variation in energy variance risk premia with systematic or commodity specific factors. The return profile of a natural gas variance swap resembles that of a call option, while the return profile of a crude oil variance swap, if anything, resembles the return profile of a put option. The annualized Sharpe ratios from shorting energy variance are sizable; although not nearly as high as the annualized Sharpe ratio of shorting S&P 500 index variance, they are comparable to those of shorting interest rate volatility or variance on individual stocks.

2010

An Option Pricing Formula for the GARCH Diffusion Model

Giovanni Barone-Adesi, Claudia Ravanelli

We derive analytically the first four conditional moments of the integrated variance implied by the GARCH diffusion process. From these moments we obtain an analytical closed-form approximation formula to price European options under the GARCH diffusion model. Using Monte Carlo simulations, we show that this approximation formula is accurate for a large set of reasonable parameters. Finally, we use the closed-form option pricing solution to shed light on the qualitative properties of implied volatility surfaces induced by GARCH diffusion models.

Elsevier2005

Three Essays on Asset Pricing

Emmanuel Leclercq

EPFL2014