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International audience; French grasslands support important populations of waders. Grazing intensity is a key issue since these birds are very sensitive to grass height and heterogeneity. On 1594 plots, grazing intensity was characterized as a combination of stocking rate and the proportion of days grazed on each day on which birds were observed. This made it possible to standardized stocking rates such that the various cumulative of time were minimized. We modeled the relationship between stocking rate and the proportion of days grazed on plots occupied by birds and those that did not. Birds select plots with a mean spring stocking rate that is significantly lower than the global mean and bird species richness is negatively correlated with intensity of spring grazing. Birds show a degree of specialization towards grazing intensity: redshank and curlews being two extremes of low and high intensity. Variance in the start date of grazing is only significantly lower than global variance for plots occupied by black tailed godwit and redshank and when only grazed plots are included in the analysis. Those results indicate that a diversity of grazing regimes is necessary to preserve habitat quality for birds. From such analysis useful indicators can be derived to assess positive side –effects of livestock farming systems.

National audience; Les attentes environnementales relatives à la gestion d’habitat par le pâturage invitent à analyser l’hétérogénéité des prairies à différentes échelles spatiales et temporelles. A partir de deux études, l’une privilégiant une entrée par les modes d’exploitation parcellaires, l’autre une entrée territoire, nous contribuons à la réflexion sur les souplesses et les compromis nécessaires pour gérer la prairie pâturée en fonction d’objectifs multiples. L’hétérogénéité spatiale et temporelle de des prairies est un facteur clef pour concevoir des systèmes d’élevage à finalité multiples et envisager les changements possibles dans les exploitations.

In this paper we analyse recovery rates on defaulted bonds using the Standard and Poor's / PMD database for the years 1981-1999. Due to the specific nature of the data (observations lie within 0 and 1), we must rely on nonstandard econometric techniques. The recovery rate density is estimated nonparametrically using a beta kernel method. This method is free of boundary bias, and Monte Carlo comparison with competing nonparametric estimators show that the beta kernel density estimator is particularly well suited for density estimation on the unit interval. We challenge the usual market practice to model parametrically recovery rates using a beta distribution calibrated on the empirical mean and variance. This assumption is unable to replicate multimodal distributions or concentration of data at total recovery and total loss. We evaluate the impact of choosing the beta distribution on the estimation of credit Value-at-Risk.

Special paper / FMG, 130

This paper offers an option pricing framework grounded in econometric microstructure modelling. We consider a model where stock price dynamics follow a pure jump process with constant jump size similar to a binomial setting with random time steps. Jump arrival times are described as an Autoregressive Conditional Duration (ACD) process while conditional probabilities of up-moves are given by the logistic transformation of an autoregressive process. We derive no-arbitrage pricing formulae under the minimal martingale measure and illustrate the use of our Autoregressive Conditional Binomial (ACB) option pricing model on intraday IBM stock data.

We develop a simple binomial model of liquidity and credit risk in which a bondholder has the option to time the sale of his security, given a distribution of potential buyers, bids and liquidity shocks. We examine as a benchmark the case without default and find that our model predicts a decreasing term structure of liquidity premia, in accordance with the empirical findings of AMIHUD and MENDELSON (1990). Then, we study the default risky case and show that credit risk influences liquidity spreads in a non-trivial way. We find that liquidity spreads are an increasing function of the volatility of the firm's assets and leverage - the key determinants of credit risk. Furthermore we show that bondholders are more likely to sell their holdings voluntarily when bond maturity is distant and when default becomes more probable. Finally, in a sample of US corporate bonds, we find support for the time to maturity effect and the positive correlation between credit and liquidity risks.

We study the dynamics of the spread between U.S. corporate and Treasury bonds. We focus on Aaa and Baa corporate yield indices and estimate nonparametrically the dynamics of the spreads assuming that they follow a univariate diffusion process. Using techniques developed for interest rate processes we try to infer from the data what acceptable process can be used to model aggregate credit spreads for option pricing or risk management purposes. We find that there is significant evidence of mean reversion especially for higher rated spreads and that the volatility of Aaa spreads exhibit a U-shape while the volatility of Baa spreads is monotonically increasing in the level of spreads. Based on these observations and on the evidence of jumps in the series, we propose a new model for credit spread indices (an Ornstein-Uhlenbeck with jumps) and estimate it by maximum likehood.

CIB: A61K31/44; A61K31/4427; A61K31/4433; A61K31/445; A61K31/4465; A61K31/45; A61K31/451; A61K31/4523; A61K31/4535; A61K31/4545; A61K31/55; A61P25/04; A61P25/16; A61P25/28; A61P29/00; A61P43/00; C07B61/00; C07D211/38; C07D211/46; C07D211/54; C07D211/72; C07D211/74; C07D211/84; C07D211/86; C07D223/00; C07D223/08; C07D401/04; C07D409/04; (IPC1-7): A61K31/395; A61P43/00; C07D211/38; C07D211/54; C07D211/72; C07D211/74; C07D211/86; C07D223/08; C07D401/04; C07D409/04; 1-Aza-2-alkyl-6-aryl cycloalkanes (I) are new. 1-Aza-2-alkyl-6-aryl cycloalkanes of formula (I), their isomers and acid addition salts, are new. n = 0 or 1; R1 = H, aryl-1-6C alkyl, 1-6C alkyl or acyl, 1-6C alkoxycarbonylaryl-1-6C alkoxy carbonyl, or CF3; R2 = 1-6C alkyl; X = O, Cl, OR3, SR4, or NOR5; R3 = H, 1-6C alkyl or acyl, 1-6C alkoxycarbonyl, or aryl 1-6C alkoxycarbonyl; R4 = H, 1-6C alkyl, or aryl; R5 = H, 1-6C alkyl(optionally substituted by one or more groups selected from OH, amino that may be substituted by one or two alkyl groups, or 1-6C alkoxy; the dotted line = an optional bond; and Ar = aryl or heteroaryl; with the proviso that (I) is not any of the following: 6-methyl-2-phenyl-2,3-dihydro-4-pyridinone; 2-methyl-6-phenyl-4-piperidinone; N-benzyl-2-(R'2)-6-phenyl-4-piperidinones where R'2 is methyl, ethyl, propyl, or isopropyl; or 2-(R2)-6-phenyl-4-piperidinols where R2 is isopropyl or butyl.

We consider option pricing when dynamic portfolios are discretely rebalanced. The portfolio adjustments only occur after fixed relative variation of the stock price. The stock price follows a marked point process and the market is incomplete. We first characterize the equivalent martingale measures. An explicit formula based on the minimal martingale measure is then provided together with the hedging strategy underlying portfolio adjustments. Under adequate conditions on the stock price dynamics, the minimal pricing formula converges to the Black-Scholes formula when the triggering price increment shrinks to zero. This is shown theoretically and numerically on two examples : a marked Poisson process and a jump process driven by a latent geometric Brownian motion. For the empirical application we use IBM intraday transaction data and compare option prices given by the marked Poisson model and the Black-Scholes model.