Paris Dauphine University

About: Paris Dauphine University is a education organization based out in Paris, France. It is known for research contribution in the topics: Population & Approximation algorithm. The organization has 1766 authors who have published 6909 publications receiving 162747 citations. The organization is also known as: Paris Dauphine & Dauphine.

Stochastic equity volatility related to the leverage effect: I Equity volatility behaviour

Abstract: We propose a general framework to model equity volatility for a firm financed by equity and additional non-equity sources of funds. The stochastic nature of equity volatility is endogenous, and comes from the impact of a change in the value of the firm's assets on the financial leverage. We first present the basic model, which is an extension of the Black-Scholes model, to value corporate securities. Second, we show for the first time in the option literature, that instantaneous equity volatility is a solution of a partial differential equation similar to Black-Scholes', although it is non-linear and in general does not have any analytical solution. However, analytical approximations for equity volatility are proposed for different capital structures: (1) equity and debt, (2) equity and warrants, and (3) equity, debt and warrants. They are shown to be very accurate.

An Adaptive Interacting Wang–Landau Algorithm for Automatic Density Exploration

Abstract: While statisticians are well-accustomed to performing exploratory analysis in the modeling stage of an analysis, the notion of conducting preliminary general-purpose exploratory analysis in the Monte Carlo stage (or more generally, the model-fitting stage) of an analysis is an area that we feel deserves much further attention. Toward this aim, this article proposes a general-purpose algorithm for automatic density exploration. The proposed exploration algorithm combines and expands upon components from various adaptive Markov chain Monte Carlo methods, with the Wang–Landau algorithm at its heart. Additionally, the algorithm is run on interacting parallel chains—a feature that both decreases computational cost as well as stabilizes the algorithm, improving its ability to explore the density. Performance of this new parallel adaptive Wang–Landau algorithm is studied in several applications. Through a Bayesian variable selection example, we demonstrate the convergence gains obtained with interacting chains. ...

Eliciting population preferences for mass colorectal cancer screening organization.

Abstract: Introduction. The implementation of mass colorectal cancer (CRC) screening is a public health priority. Population participation is fundamental for the success of CRC screening as for any cancer screening program. The preferences of the population may influence their likelihood of participation. Objectives. The authors sought to elicit population preferences for CRC screening test characteristics to improve the design of CRC screening campaigns. Methods. A discrete choice experiment was used. Questionnaires were compiled with a set of pairs of hypothetical CRC screening scenarios. The survey was conducted by mail from June 2006 to October 2006 on a representative sample of 2000 inhabitants, aged 50 to 74 years from the northwest of France, who were randomly selected from electoral lists. Questionnaires were sent to 2000 individuals, each of whom made 3 or 4 discrete choices between hypothetical tests that differed in 7 attributes: how screening is offered, process, sensitivity, rate of unnecessary colonos...