Rama Cont

Rama Cont is the Professor of Mathematical Finance at the

University of Oxford.

He is known for contributions to probability theory, stochastic analysis and mathematical modelling in finance, in particular mathematical models of systemic risk.

Cont started his career as a CNRS researcher in applied mathematics at Ecole Polytechnique (France) in 1998 and held academic positions at Ecole Polytechnique, Columbia University and Imperial College London.

He was appointed 'Directeur de Recherche CNRS' (CNRS Senior Research Scientist) in 2008 and was chair of mathematical finance at Imperial College London from 2012 to 2018.

He was awarded the Louis Bachelier Prize by the French Academy of Sciences in 2010.

Born in Tehran (Iran), Cont obtained his undergraduate degree from Ecole Polytechnique (France), a master's degree in theoretical physics from Ecole Normale Superieure and a degree in Chinese Language from Institut national des langues et civilisations orientales.

His doctoral thesis focused on the application of Lévy processes in financial modelling.

Cont was awarded the Louis Bachelier Prize by the French Academy of Sciences in 2010 for his work on mathematical modelling of financial markets.

He was elected Fellow of the Society for Industrial and Applied Mathematics (SIAM) in 2017 for "contributions to stochastic analysis and mathematical finance".

He received the Award for Excellence in Interdisciplinary Research (APEX) from the Royal Society in 2017 for his research on mathematical modelling of systemic risk.

He was elected Statutory Professor in Mathematical Finance at the Oxford Mathematical Institute and professorial fellow of St Hugh's College, Oxford in 2018.

Cont's research focuses on probability theory, stochastic analysis and mathematical modelling in finance.

His mathematical work focuses on pathwise methods in stochastic analysis and the Functional Ito calculus.

In quantitative finance he is known in particular for his work on models based on jump processes, the stochastic modelling of limit order books as queueing systems

, machine learning methods in finance

and the mathematical modelling of systemic risk.

He was editor in chief of the Encyclopedia of Quantitative Finance.

Cont has served as advisor to central banks and international organizations such as the International Monetary Fund and the Bank for International Settlements on stress testing and systemic risk monitoring.

His work on network models, financial stability and central clearing has influenced central banks and regulators

. He has given numerous media interviews

on issues related to systemic risk and financial regulation.

Cont is known in mathematics for his the "Causal functional calculus", a calculus for non-anticipative, or "causal", functionals on the space of paths.

Cont and collaborators built on the seminal work of German mathematician Hans Föllmer

and Bruno Dupire to construct a calculus for non-anticipative functionals, which includes as a special case the so-called Ito-Föllmer calculus, a pathwise counterpart of Ito's stochastic calculus.

Subsequent work by Cont and Nicolas Perkowski

extended

the Ito-Föllmer calculus to functions and functionals of more general irregular paths with non-zero p-th order variation.

Work by Cont and his collaborators on mathematical modeling of systemic risk and financial stability, in particular on network models of financial contagion and the modeling of indirect contagion via 'fire sales', has influenced academic research and policy in this area.

Cont's research on central clearing in over-the-counter (OTC) markets has influenced risk management practices of central counterparties and regulatory thinking on central clearing.

Cont has argued that central clearing does not eliminate counterparty risk but transforms it into liquidity risk, therefore risk management and stress testing of central counterparties should focus on liquidity risk and liquidity resources, not capital.

Cont introduced a rigorous approach for the assessment of model risk

which has been influential in the design of model risk management frameworks in financial institutions.

Cont, Deguest and Scandolo introduced the concept of 'risk measurement procedure', an empirical counterpart of the notion of risk measure, and defined a robust class of risk measurement procedures known as 'Range Value-at-risk' (RVaR), a robust alternative to Expected shortfall.

Cont, Kotlicki and Valderrama define the concept of Liquidity at risk, as the amount of liquid assets needed by a financial institution to face liquidity outflows in this scenario.