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      <div class="TdmEntry">Overall Objectives<ul><li class="tdmActPage"><a href="./uid3.html">Introduction</a></li><li><a href="./uid8.html">Highlights of the Year</a></li></ul></div>
      <div class="TdmEntry">Research Program<ul><li><a href="uid10.html&#10;&#9;&#9;  ">Dependence modeling</a></li><li><a href="uid11.html&#10;&#9;&#9;  ">Liquidity risk</a></li><li><a href="uid14.html&#10;&#9;&#9;  ">Contagion modeling and systemic risk</a></li><li><a href="uid15.html&#10;&#9;&#9;  ">Stochastic analysis and numerical probability</a></li></ul></div>
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      <div class="TdmEntry">New Results<ul><li><a href="uid86.html&#10;&#9;&#9;  ">Credit risk</a></li><li><a href="uid87.html&#10;&#9;&#9;  ">Liquidity risk</a></li><li><a href="uid88.html&#10;&#9;&#9;  ">Systemic Risk</a></li><li><a href="uid89.html&#10;&#9;&#9;  ">Estimation of the parameters of a Wishart process</a></li><li><a href="uid90.html&#10;&#9;&#9;  ">An Affine term structure model for interest rates that involve Wishart diffusions</a></li><li><a href="uid91.html&#10;&#9;&#9;  ">Applications of optimal transport</a></li><li><a href="uid92.html&#10;&#9;&#9;  ">Capital distribution and portfolio performance in the mean-field Atlas model</a></li><li><a href="uid93.html&#10;&#9;&#9;  ">Public Private Partnerships</a></li><li><a href="uid94.html&#10;&#9;&#9;  ">Backward Stochastic (Partial) Differential equations with jumps and stochastic control</a></li><li><a href="uid95.html&#10;&#9;&#9;  ">Utility maximization and Arbitrage Theory</a></li><li><a href="uid96.html&#10;&#9;&#9;  ">Regularity of probability laws using an interpolation method</a></li><li><a href="uid97.html&#10;&#9;&#9;  ">A stochastic parametric representation for the density of a Markov process</a></li><li><a href="uid98.html&#10;&#9;&#9;  ">Regularity of probability laws using an interpolation method</a></li></ul></div>
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        <h2>Section: 
      Overall Objectives</h2>
        <h3 class="titre3">Introduction</h3>
        <p>MathRisk is a joint Inria project-team with ENPC (CERMICS Laboratory) and the University Paris Est Marne-la-Vallée (UPEMLV, LAMA Laboratory), located in Rocquencourt and Marne-la-Vallée. <a href="https://www-rocq.inria.fr/mathfi/">https://www-rocq.inria.fr/mathfi/</a> . This project is based on the former Mathfi project team.</p>
        <p>Mathfi was founded in 2000, and was devoted to financial
mathematics. The project was focused on advanced stochastic analysis
and numerical techniques motivated by the development of increasingly
complex financial products. Main applications concerned evaluation
and hedging of derivative products, dynamic portfolio optimization in
incomplete markets, and calibration of financial models. Special
attention was paid to models with jumps, stochastic volatility models,
asymmetry of information.</p>
        <p>
          <b>Crisis, deregulation, and impact on the research in finance.</b>
        </p>
        <p>The starting point of the development of modern finance theory is
traditionally associated to the publication of the famous paper of
Black and Scholes in 1973 <a href="./bibliography.html#mathrisk-2013-bid0">[66]</a> . Since then, in spite of
sporadic crises, generally well overcome, financial markets have grown
in a exponential manner. More and more complex exotic derivative
products have appeared, on equities first, then on interest rates, and
more recently on credit markets.
The period between the end of the eighties and the
crisis of 2008 can be qualified as the “golden age of financial
mathematics”: finance became a quantitative industry, and financial
mathematics programs flourished in top universities, involving seminal
interplays between the worlds of finance and applied mathematics.
During its 12 years existence, the
Mathfi project team has extensively contributed to the development of
modeling and computational methods for the pricing and hedging of
increasingly complex financial products.</p>
        <p>Since the crisis of 2008, there has been a critical reorientation of
research priorities in quantitative finance with emphasis on risk.
In 2008, the “subprime” crisis has questioned the very existence of
some derivative products such as CDS (credit default swaps) or CDOs (collateralized debt obligations), which were accused to be
responsible for the crisis. The nature of this crisis is profoundly
different from the previous ones. It has negatively impacted the
activity on the exotic products in general, - even on equity
derivative markets-, and the interest in the modeling issues for these
products.
The perfect replication paradigm, at the origin of the
success of the Black and Scholes model became unsound, in particular
through the effects of the lack of liquidity.
The interest of quantitative finance analysts and mathematicians
shifted then to more realistic models taking into account
the multidimensional feature and the incompleteness of the markets, but as such
getting away from the “lost paradi(gm)” of perfect replication.
These models are much more demanding numerically, and require the development
of hedging risk measures, and decision procedures taking into account the
illiquidity and various defaults.</p>
        <p>Moreover, this crisis, and in particular the Lehman Brothers bankruptcy
and its consequences, has underlined a systemic risk due to the strong
interdependencies of financial institutions. The failure of one of them
can cause a cascade of failures, thus affecting the global stability
of the system. Better understanding of these interlinkage
phenomena becomes crucial.</p>
        <p>At the same time, independently from the subprime crisis, another phenomenon
has appeared: deregulation in the organization of stock markets
themselves. This has been encouraged by the Markets in Financial Instruments
Directive (MIFID) which is effective since November, 1st 2007.
This, together with the progress of the networks, and the fact that all the
computers have now a high computation power, have
induced arbitrage opportunities on the markets, by very short term
trading, often performed by automatic trading.
Using these high frequency trading possibilities,
some speculating operators benefit from the large volatility of the markets.
For example, the flash crash of May, 6 2010 has exhibited some
perverse effects of these automatic speculating trading strategies.
These phenomena are not well understood and the theme of high frequency trading
needs to be explored.</p>
        <p>To summarize, financial mathematics is facing the following new evolutions:</p>
        <ul>
          <li>
            <p class="notaparagraph"><a name="uid4"> </a>the complete market modeling has become unsatisfactory to provide
a realistic picture of the market and is replaced by incomplete and
multidimensional models which lead to new modeling and numerical challenges.</p>
          </li>
          <li>
            <p class="notaparagraph"><a name="uid5"> </a>quantitative measures of risk coming from the markets, the hedging procedures, and the lack of liquidity are crucial for banks,</p>
          </li>
          <li>
            <p class="notaparagraph"><a name="uid6"> </a>uncontrolled systemic risks may cause planetary economic disasters,
and require better understanding,</p>
          </li>
          <li>
            <p class="notaparagraph"><a name="uid7"> </a>deregulation of stock markets and its consequences lead to study
high frequency trading.</p>
          </li>
        </ul>
        <p>The new project team MathRisk is designed to address these new issues, in particular
dependence modeling, systemic risk,
market microstructure modeling and risk measures.
The research in
modeling and numerical analysis remain active in this new context,
motivated by new issues.</p>
        <p>The MathRisk project team develops the software Premia dedicated
to pricing and hedging options and calibration of financial models, in collaboration with a consortium of financial institutions.
<a href="https://www-rocq.inria.fr/mathfi/Premia/">https://www-rocq.inria.fr/mathfi/Premia/</a> .</p>
        <p>The MathRisk project is part of the
Université Paris-Est <b>“Labex” BÉZOUT</b>.</p>
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