Raphael Douady Academic French Mathematician and Economist.

Raphael Douady is a French Mathematician and Economist. He holds the Robert Frey Endowed Chair for Quantitative Finance at Stony Brook, New York. He is a fellow of the Centre d’Economie de la Sorbonne (Economic Centre of Sorbonne), Paris 1 Pantheon-Sorbonne University, and academic director of the Laboratory of Excellence on Financial Regulation.

Since 1994, Professor Douady has conducted research in the field of mathematical finance, statistics and economics. He established a generalization of Heath–Jarrow–Morton interest rate model, where the yield curve is represented as a random field. With Monique Jeanblanc, he created a rating-based credit derivatives model that introduced the notion of "rating surface". In collaboration with Albert Shiryaev and Marc Yor he co-authored a theory of Brownian motions downfalls.

• Doctor of Philosophy (In fields of Hamiltonian systems.)
  Paris Diderot University

• Mathematician, Economist (n 1983, Douady was appointed to the Centre National de la Recherche Scientifique (CNRS). He was affiliated with Ecole Polytechnique (1983–87), Ecole Normale Supérieure (1987–95), the Courant Institute at New York University (1995–97), Ecole Normale Supérieure of Cachan (1997–2001), and a former visiting professor at New York University Polytechnic Institute.[1] In 2001, he founded Riskdata, a private software company, remaining with them until 2011 since when he has been affiliated to Paris 1 Pantheon-Sorbonne University. In 1994, he created and animated the Bachelier Seminar of mathematical finance at Institut Henri Poincaré in Paris. He is also the co-founder, with Marco Avellaneda, of the Seminar of Mathematical Finance held at the Courant Institute of Mathematical Science, New York University. He has advised financial institutions including Société Générale, National Westminster Bank, Canadian Imperial Bank of Commerce and Citibank.)
  NYC, Paris

Managing the Downside of Active and Passive Strategies: Convexity and Fragilities

Question of the day: how to manage a large (or small) portfolio in low interest rate conditions, while equity markets bear significant draw-down risk? More generally, how to build an “antifragile” portfolio that can weather the most extreme market scenarios without impacting long-term performances? Do active strategies systematically create or increase already existing market instabilities?

Academic Raphael Douady Jul 2024 Asset Management 253

Mathematical Definition, Mapping, and Detection of (Anti)Fragility

We provide a mathematical definition of fragility a semi-measure of dispersion and and antifragility as negative or positive sensitivity to volatility (a variant of negative or positive “vega”) and examine the link to nonlinear effects. We integrate model error (and biases) into the fragile or antifragile context. Unlike risk, which is linked to psychological notions such as subjective preferences (hence cannot apply to a coffee cup) we offer a measure that is universal and concerns any object that has a probability distribution (whether such distribution is known or, critically, unknown). We propose a detection of fragility, robustness, and antifragility using a single “fast-and-frugal”, model-free, probability free heuristic that also picks up exposure to model error.

Academic Raphael Douady Jun 2024 Derivatives 185