Univ.-Prof. Dr. Christa Cuchiero

I am professor for Quantitative Risk Management at the Department of Statistics and Operations Research.

Previously, I was professor at the University of Paris (Paris VII, Diderot), Assistant Professor at the Vienna University of Economics and Business as well as University Assistant at the Faculty of Mathematics and Post Doc at the ETH Zurich. At the beginning of my career, I worked as Risk Analyst at Allianz France in Paris.

I studied Technical Mathematics at TU Wien and received my PhD in Mathematics in 2011 at the ETH Zurich. In 2018 followed my habilitation in Mathematics at the University of Vienna.

I am co-organizer of several international conferences, most recently the "13th Summer School in Financial Mathematics" in 2020 in Vienna. I also act as associate editor for some leading journals in Mathematical Finance  and Stochastics (Mathematical Finance, Finance and Stochastics, Journal of Computational Finance and Stochastics). 

In June 2019, I received the FWF START-Award for my project "Universal Structures in Financial Mathematics".


  • Mathematical Finance and Quantitative Riskmanagement (data driven risk inference, stochastic volatility, stochastic portfolio theory, robust portfolio optimization, arbitrage theory, interest rate theory, systemic risk)
  • Machine Learning in Finance, Insurance and Economics
  • Stochastic processes in finite and infinite dimensions
  • McKean Vlasov equations, interacting particle systems and mean field games
  • Statistics of stochastic processes, statistics with high-frequency data, covariance estimation, robust model calibration
  • Universal approximation theorems in dynamic situations


  • C. Cuchiero, L. Gonon, L. Grigoryeva, Lyudmila, J.P. Ortega and J. Teichmann, Discrete-time signatures and randomness in reservoir computing, IEEE Transactions on Neural Networks and Learning Systems 2021, arxiv.org/abs/2010.14615
  • C. Cuchiero, W. Khosrawi and J. Teichmann, A generative adversarial net-work approach to calibration of local stochastic volatility models, Risk 2020, arxiv.org/abs/2005.02505
  • Cuchiero and S. Svaluto-Ferro, Infinite dimensional poly-nomial processes, Finance and Stochastics 2020,
  • C. Cuchiero, M. Larsson and J. Teichmann, Deep neural networks, genericuniversal interpolation, and controlled ODEs, SIAM Journal on Mathemat-ics of Data Science, 2(3):901-919, 2020, arxiv.org/abs/1908.07838
  • C. Cuchiero and J. Teichmann, Generalized Feller processes and Markovian lifts of stochastic Volterra processes: the affine case, Journal of Evo-lution Equations, 1-48, 2020, doi.org/10.1007/s00028-020-00557-2,
  • E. Abi Jaber, C. Cuchiero, M. Larsson and S. Pulido, A weak solutiontheory for stochastic Volterra equations of convolution type, 2019, to appear in Annals of Applied Probability, arxiv.org/abs/1909.01166
  • C. Cuchiero and J. Teichmann, Markovian lifts of positive semidefinite affineVolterra type processes, Decisions in Economics and Finance, 42(2):407-448, 2019, arxiv.org/abs/1907.0191
  • C. Cuchiero, M. Larsson and S. Svaluto-Ferro, Probability measure-valued polynomial diffusions, Electronic Journal of Probability, 24, 2019, arxiv.org/abs/1807.0322
  • C. Cuchiero, I. Klein, J. Josef Teichmann, A fundamental theorem of as-set pricing for continuous time large financial markets in a two filtrationsetting, Theory of Probability and its Applications, 2019, arxiv.org/abs/1705.02087
  • C. Cuchiero, Polynomial processes in stochastic portfolio theory, Stochastic processes and their applications, 129(5):1829-1872, 2019, arxiv.org/abs/1705.03647
  • C. Cuchiero, M. Larsson and S. Svaluto-Ferro, Polynomial jump-diffusionson the unit simplex, Annals of Applied Probability, 28(4):2451-2500, 2018, arxiv.org/abs/1612.04266v1
  • C. Cuchiero, W. Schachermayer and L. Wong, Cover’s universal portfolio, stochastic portfolio theory and the numéraire portfolio, Mathematical Finance, 29(3):773–803, 2019, arxiv.org/abs/1611.09631v1
  • C. Cuchiero, C. Fontana and A. Gnoatto, Affine multipleyield curve models, Mathematical Finance, 29(2):568-611, 2019, http://arxiv.org/pdf/1603.00527v1.pdf
  • C. Cuchiero, I. Klein and J. Teichmann, A new perspective on the fundamental theorem of asset pricing for large financial markets, Theory of Probability and its Applications, 60(4):561-579, 2016, http://arxiv.org/pdf/1412.7562v1.pdf
  • C. Cuchiero, C. Fontana and A. Gnoatto, A general HJM framework formultiple yield curve modeling, Finance and Stochastics, 20(2):267–320, 2016, http://arxiv.org/pdf/1406.4301.pdf
  • C. Cuchiero and J. Teichmann, A convergence result for the Emerytopology and a variant of the proof of the fundamental theorem of asset pricing, Finance and Stochastics, 19(4): 743-761, 2015,
  • C. Cuchiero and J. Teichmann, Fourier transform methods for pathwise co-variance estimation in the presence of jumps, Stochastic processes and theirapplications, 125(1):116-160, 2015, http://arxiv.org/pdf/1301.3602.pdf
  • C. Cuchiero, M. Keller-Ressel, E. Mayerhofer and J. Teichmann, Affine processes on symmetric cones, Journal of Theoretical Probability, 2014, http://arxiv.org/pdf/1112.1233v1.pdf
  • C. Cuchiero and J. Teichmann, Path properties and regularity of affineprocesses on general state spaces, Séminaire de Probabilités XLV, 2013, http://arxiv.org/pdf/1107.1607v2.pdf
  • C. Cuchiero, M. Keller-Ressel and J. Teichmann, Polynomial processes and their applications to mathematical finance, Finance and Stochastics,16(4):711-740, 2012, http://arxiv.org/pdf/0812.4740v2.pdf
  • C. Cuchiero, D. Filipović, E. Mayerhofer and J. Teichmann, Affine processes on positive semidefinite matrices, Annals of Applied Probability, 21(2):397-463, 2011, arxiv.org/pdf/0910.0137v3.pdf
  • C. Cuchiero, D. Filipović and J. Teichmann, Affine Models, Encyclopediaof Quantitative Finance, 2010,
  • C. Cuchiero, Universal structures in Mathematical Finance, Internationale Mathematische Nachrichten, 08/2020