Raphaël Douady

ORCID: 0000-0003-4931-1806
Publications
Citations
Views
---
Saved
---
About
Contact & Profiles
Research Areas
  • Complex Systems and Time Series Analysis
  • Stochastic processes and financial applications
  • Market Dynamics and Volatility
  • Financial Risk and Volatility Modeling
  • Banking stability, regulation, efficiency
  • Financial Markets and Investment Strategies
  • Stock Market Forecasting Methods
  • Economic theories and models
  • Credit Risk and Financial Regulations
  • Global Financial Crisis and Policies
  • Monetary Policy and Economic Impact
  • Insurance and Financial Risk Management
  • Capital Investment and Risk Analysis
  • Advanced Statistical Methods and Models
  • Global Financial Regulation and Crises
  • Chaos control and synchronization
  • Chemical Thermodynamics and Molecular Structure
  • Risk Perception and Management
  • Distributed and Parallel Computing Systems
  • Statistical Methods and Inference
  • Quantum chaos and dynamical systems
  • Computational Physics and Python Applications
  • Advanced Materials Characterization Techniques
  • Housing Market and Economics
  • Advanced Differential Equations and Dynamical Systems

Université Paris 1 Panthéon-Sorbonne
2009-2022

Centre National de la Recherche Scientifique
2002-2022

Centre d'Économie de la Sorbonne
2012-2022

Sorbonne Université
2021

Universidad CES
2002-2020

Stony Brook University
2008-2020

Canadian Nautical Research Society
2019

State University of New York
2018

Laboratory of Excellence for Financial Regulation
2017

Université Paris Cité
2013-2015

Click to increase image sizeClick decrease size AcknowledgmentsBruno Dupire, Emanuel Derman, Jean-Philippe Bouchaud, Elie Canetti, Marco Avellaneda, Michal Kolano, IMF Staff. JP Morgan, New York, June 16, 2011; CFM, Paris, 17, GAIM Conference, Monaco, 21, Max Planck Institute, Berlin, 23, Eighth International Conference on Complex Systems, Boston, July 1, 2011, Columbia University September 24, 2011.

10.1080/14697688.2013.800219 article EN Quantitative Finance 2013-11-01

The impact of increasing leverage in the economy produces hyperreaction market participants to variations their revenues. If income banks decreases, they mass-reduce lendings; if corporations sales drop, and cannot adjust liquidities by further borrowing due existing debt, then must immediately reduce expenses, lay off staff, cancel investments. This a bifurcation mechanism, eventually strong dynamical instability capital markets that is commonly called systemic risk. In this article, we...

10.1080/14697688.2011.627880 article EN Quantitative Finance 2012-02-06

We present a non-naive version of the Precautionary (PP) that allows us to avoid paranoia and paralysis by confining precaution specific domains problems. PP is intended deal with uncertainty risk in cases where absence evidence incompleteness scientific knowledge carries profound implications presence risks "black swans", unforeseen unforeseable events extreme consequence. formalize PP, placing it within statistical probabilistic structure ruin problems, which system at total failure, place...

10.48550/arxiv.1410.5787 preprint EN other-oa arXiv (Cornell University) 2014-01-01

This paper presents a novel approach to financial network analysis by leveraging PolyModel theory. Traditional networks often rely on correlation matrices represent relationships between assets, but these fail capture the complex, non-linear interactions prevalent in markets. In response, we propose method that quantifies relationship time series comparing their reactions broad set of environmental risk factors. constructs based inherent similarities how assets respond external risks,...

10.20944/preprints202409.1453.v2 preprint EN 2025-03-25

For a Brownian motion $B=(B_t)_{t\le 1}$ with $B_0=0$, {\bf E}$B_t=0$, E}$B_t^2=t$ problems of probability distributions and their characteristics are considered for the variables $$ \begin{array}{c} {\mathbb D} =\displaystyle\sup_{0\le t\le t'\le 1}(B_t-B_{t'}),\qquad D}_1=B_\sigma-\inf_{\sigma\le 1}B_{t'}, \\ D}_2=\displaystyle\sup_{0\le t\le\sigma'}B_{t}-B_{\sigma'}, \end{array} where $\sigma$ $\sigma'$ times (non-Markov) absolute maximum minimum on $[0,1]$ (i.e., $B_\sigma=\sup_{0\le...

10.1137/s0040585x97977306 article EN Theory of Probability and Its Applications 2000-01-01

ce fichier doit contenir la présente mention de copyright.

10.24033/asens.1549 article FR Annales Scientifiques de l École Normale Supérieure 1988-01-01

10.1016/j.physa.2015.02.038 article EN Physica A Statistical Mechanics and its Applications 2015-02-10

We first recall the well-known expression of price barrier options, and compute double options by mean iterated mirror principle. The formula for barriers provides an intraday volatility estimator from information high-low-close prices. Then we give explicit formulas probability distribution function expectation exit time single options. These allow to independent dependent rebates. They are also helpful hedge when taking into account variations term structure interest rates volatility....

10.1142/s0219024999000030 article EN International Journal of Theoretical and Applied Finance 1999-01-01

The aim of this work is to build a class financial crisis indicators based on the spectral properties dynamics market data. After choosing an appropriate size for rolling window, historical data inside window are seen every trading day as random matrix from which correlation obtained. Our goal study correlations between assets that constitute and look reproducible patterns indicative impending crisis. A weighting in then introduced proportional daily traded volumes. This manipulation...

10.1142/s021902491850022x article EN International Journal of Theoretical and Applied Finance 2018-04-23

10.1016/j.physa.2019.122962 article EN Physica A Statistical Mechanics and its Applications 2019-09-26

The 2007-2009 financial crisis provided need to investigate the causes of systemic risk - also known as contagion and cures avoid it. In this article, we use well-established theories in dynamical systems, bifurcation, symbolic dynamics, chaos, explain mechanism behind crisis, provide insight on why conventional economic stimulus including quantitative easing cannot improve sluggish economy resolve liquidity shortage well expected. We further suggest how future should be executed, whether...

10.2139/ssrn.1733706 article EN SSRN Electronic Journal 2011-01-01

Download This Paper Open PDF in Browser Add to My Library Share: Permalink Using these links will ensure access this page indefinitely Copy URL DOI

10.2139/ssrn.1113620 article EN SSRN Electronic Journal 2008-01-01

The global financial market has become extremely interconnected as it demonstrates strong nonlinear contagion in times of crisis. As a result, is necessary to measure systemic risk comprehensive and approach. By establishing large set factors the main bones network applying factor analysis form so-called PolyModel, this paper proposes two indicators that can prognosticate advent trace development crises. Through analysis, theoretical simulation, empirical data final validation, we argue...

10.3390/jrfm12010002 article EN Journal of risk and financial management 2018-12-20
Coming Soon ...