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	    Raweb 
	    2018</a> | <a href="http://www.inria.fr/en/teams/mathrisk">Presentation of the Project-Team MATHRISK</a> | <a href="https://team.inria.fr/mathrisk/fr">MATHRISK Web Site
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        <h2>Section: 
      Overall Objectives</h2>
        <h3 class="titre3">Overall Objectives</h3>
        <p>The Inria project team
<b>MathRisk</b> team was created in 2013. It is the follow-up of the
MathFi project team founded in 2000. MathFi was focused on financial
mathematics, in particular on computational methods for pricing and hedging
increasingly complex financial products.
The 2007 global financial crisis and its “aftermath
crisis” has abruptly highlighted the critical importance of a better
understanding and management of risk. The project <b>MathRisk</b> has
been reoriented towards mathematical handling of risk, and addresses
broad research topics embracing risk measurement and risk management, modeling and
optimization in quantitative finance, but also in
other related domains where risk control is paramount.
The project team <b>MathRisk</b> aims both at producing mathematical tools and models
in these domains, and developing collaborations with various
institutions involved in risk control.
Quantitative finance remains for the project an important source of
mathematical problems and applications. Indeed, the
pressure of new legislation leads to a massive reorientation of
research priorities, and the interest of analysts shifted to risk
control preoccupation.</p>
        <p>The scientific issues related to quantitative finance we consider
include systemic risk and contagion modeling, robust finance, market frictions,
counterparty and liquidity risk, assets dependence modeling,
market micro-structure modeling and price
impact. In this context, models must take into
account the multidimensional feature and various market imperfections.
They are much more demanding mathematically and
numerically, and require the development of risk measures
taking into account incompleteness issues, model
uncertainties, interplay
between information and performance and various defaults.</p>
        <p>Besides, financial institutions, submitted to more stringent regulatory
legislations such as FRTB or XVA computation, are facing practical
implementation challenges which still need to be solved.
Research focused on numerical efficiency remains strongly needed in this context, renewing the interest for
the numerical platform Premia (<a href="http://www.premia.fr">http://www.premia.fr</a>) that Mathrisk is developing in collaboration
with a consortium of financial institutions.</p>
        <p>While these themes arise naturally in the world of quantitative
finance, a number of these issues and mathematical tools are also
relevant to the treatment of risk in other areas as economy, social
insurance and sustainable development, of fundamental importance in
today's society. In these contexts, the management of risk appears at
different time scales, from high frequency data to long term life
insurance management, raising challenging renewed modeling and
numerical issues.</p>
        <p>The <b>MathRisk</b> project is strongly involved in the development of new
mathematical methods and numerical algorithms. Mathematical tools
include stochastic modeling, stochastic analysis, in particular
stochastic (partial) differential equations and various aspects of
stochastic control and optimal stopping of these equations, nonlinear expectations, Malliavin calculus, stochastic optimization,
dynamic game theory, random graphs, martingale optimal transport
(especially in relation to numerical considerations), long time behavior
of Markov processes (with applications to Monte-Carlo methods) and
generally advanced numerical methods for effective solutions.</p>
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