J. Teichmann

发表

A Semigroup Point Of View On Splitting Schemes For Stochastic (Partial) Differential Equations

Philipp Doersek, J. Teichmann, 2010, 1011.2651.

Weak and strong Taylor methods for numerical solutions of stochastic differential equations

J. Teichmann, Maria Siopacha, 2007, 0704.0745.

A constraint-based notion of illiquidity

J. Teichmann, T. Krabichler, 2020, 2004.12394.

Functional Analytic (Ir-)Regularity Properties of SABR-type Processes

J. Teichmann, L. Döring, B. Horvath, 2017, 1701.02015.

Functional Analytic (Ir-)Regularity Properties of SABR-type Processes

Josef Teichmann, Blanka Horvath, J. Teichmann, 2017 .

THE AFFINE LIBOR MODELS

J. Teichmann, A. Papapantoleon, M. Keller-Ressel, 2009, 0904.0555.

Path Properties and Regularity of Affine Processes on General State Spaces

W. Schachermayer, J. Teichmann, M. Keller-Ressel, 2011, 1105.0632.

Deep Replication of a Runoff Portfolio

J. Teichmann, T. Krabichler, 2020, 2009.05034.

A fundamental theorem of asset pricing for continuous time large financial markets in a two filtration setting

J. Teichmann, Christa Cuchiero, I. Klein, 2017, 1705.02087.

Deep hedging

J. Teichmann, H. Buehler, L. Gonon, 2018, Quantitative Finance.

Deep hedging

J. Teichmann, H. Buehler, L. Gonon, 2019, Quantitative Finance.

Optimal consumption and investment with power utility

F. Delbaen, J. Wissel, M. Schweizer, 2010 .

Characterization of optimal transport plans for the Monge-Kantorovich problem

Walter Schachermayer, Josef Teichmann, W. Schachermayer, 2007, 0711.1268.

A NEW VIEW ON THE FUNDAMENTAL THEOREM OF ASSET PRICING FOR LARGE FINANCIAL MARKETS

J. Teichmann, Christa Cuchiero, I. Klein, 2014 .

CONSISTENT YIELD CURVE PREDICTION

M. Wüthrich, J. Teichmann, 2016, ASTIN Bulletin.

Calculating the Greeks by cubature formulae

J. Teichmann, 2004, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

Cubature on Wiener space in infinite dimension

J. Teichmann, C. Bayer, 2007, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

Cubature methods for stochastic (partial) differential equations in weighted spaces

J. Teichmann, Dejan Velušček, Philipp Dörsek, 2012, 1201.4024.

Affine Processes on Symmetric Cones

E. Mayerhofer, J. Teichmann, Christa Cuchiero, 2011, 1112.1233.

Optimal Estimation of Generic Dynamics by Path-Dependent Neural Jump ODEs

J. Teichmann, F. Krach, Marc Nubel, 2022, 2206.14284.

How Infinitely Wide Neural Networks Benefit from Multi-task Learning -- an Exact Macroscopic Characterization

J. Teichmann, Jakob Heiss, Hanna Wutte, 2021, 2112.15577.

Infinite wide (finite depth) Neural Networks benefit from multi-task learning unlike shallow Gaussian Processes - an exact quantitative macroscopic characterization

J. Teichmann, Jakob Heiss, Hanna Wutte, 2021, ArXiv.

A heat kernel approach to interest rate models

J. Teichmann, J. Akahori, T. Tsuchiya, 2009, 0910.5033.

The Jarrow & Turnbull setting revisited

J. Teichmann, T. Krabichler, 2020, 2004.12392.

Consistent recalibration of yield curve models

M. Wüthrich, J. Teichmann, Philipp Harms, 2015, 1502.02926.

NOMU: Neural Optimization-based Model Uncertainty

Sven Seuken, J. Teichmann, Jakob Weissteiner, 2021, ICML.

Finite dimensional Realizations of Stochastic Equations

D. Filipović, J. Teichmann, 2001, math/0106155.

Optimal Estimation of Generic Dynamics by Path-Dependent Neural Jump ODEs

J. Teichmann, F. Krach, Marc Nübel, 2022, ArXiv.

Exotic one-parameter semigroups of endomorphisms of a symmetric cone

J. Teichmann, B. Kuzma, Klemen vSivic, 2014, 1408.2967.

Denise: Deep Robust Principal Component Analysis for Positive Semidefinite Matrices

J. Teichmann, Anastasis Kratsios, F. Krach, 2020, 2004.13612.

Absolutely Continuous Laws of Jump-Diffusions in Finite and Infinite Dimensions with Applications to Mathematical Finance

E. Lütkebohmert, J. Teichmann, Barbara Forster, 2005, SIAM J. Math. Anal..

ON FINITE-DIMENSIONAL TERM STRUCTURE MODELS

D. Filipović, J. Teichmann, 2002, math/0201204.

Optimal Estimation of Generic Dynamics by Path-Dependent Neural Jump ODEs

J. Teichmann, F. Krach, Marc Nübel, 2022, ArXiv.

How Infinitely Wide Neural Networks Can Benefit from Multi-task Learning -- an Exact Macroscopic Characterization

J. Teichmann, Jakob Heiss, Hanna Wutte, 2021, 2112.15577.

Regularity of finite dimensional realizations for evolution equations

D. Filipović, J. Teichmann, 2001, math/0112244.

A convergence result for the Emery topology and a variant of the proof of the fundamental theorem of asset pricing

J. Teichmann, Christa Cuchiero, 2015, Finance and Stochastics.

The proof of Tchakaloff’s Theorem

J. Teichmann, C. Bayer, 2005, math/0502473.

Affine Processes on Symmetric Cones

E. Mayerhofer, J. Teichmann, Christa Cuchiero, 2014, Journal of Theoretical Probability.

A Hyper-Geometric Approach to the BMV-Conjecture

W. Schachermayer, M. Drmota, J. Teichmann, 2004, math-ph/0408015.

Characterization of nonlinear Besov spaces

David J. Prömel, J. Teichmann, Chong Liu, 2018, Transactions of the American Mathematical Society.

Afﬁne processes are regular

W. Schachermayer, J. Teichmann, M. Keller-Ressel, 2011 .

Characterization of non-linear Besov spaces

David J. Promel, J. Teichmann, Chong Liu, 2018, 1806.04651.

Generalized Feller processes and Markovian lifts of stochastic Volterra processes: the affine case

J. Teichmann, Christa Cuchiero, 2020, Journal of Evolution Equations.

Neural Jump Ordinary Differential Equations: Consistent Continuous-Time Prediction and Filtering

Calypso Herrera, Florian Krach, Josef Teichmann, 2020, ICLR.

Theoretical Guarantees for Learning Conditional Expectation using Controlled ODE-RNN pdf

Calypso Herrera, Florian Krach, Josef Teichmann, 2020, ArXiv.

Neural Jump Ordinary Differential Equation

Calypso Herrera, Florian Krach, Josef Teichmann, 2020 .

Optimal Stopping via Randomized Neural Networks

J. Teichmann, Calypso Herrera, P. Ruyssen, 2021, Frontiers of Mathematical Finance.

Signature SDEs from an affine and polynomial perspective

J. Teichmann, Christa Cuchiero, Sara Svaluto-Ferro, 2023, 2302.01362.

Affine Processes on Positive Semidefinite Matrices

Damir Filipović, Josef Teichmann, Christa Cuchiero, 2009, 0910.0137.

Affine processes are regular

W. Schachermayer, J. Teichmann, M. Keller-Ressel, 2009, 0906.3392.

Aspects of Stochastic Integration beyond Standard Assumptions

P. Protter, J. Teichmann, 2021 .

A convergence result for the Emery topology and a variant of the proof of the fundamental theorem of asset pricing

Josef Teichmann, Christa Cuchiero, J. Teichmann, 2014, Finance Stochastics.

Stochastic analysis with modelled distributions

David J. Prömel, J. Teichmann, Chong Liu, 2020, Stochastics and Partial Differential Equations: Analysis and Computations.

Stochastic analysis with modelled distributions

David J. Prömel, J. Teichmann, Chong Liu, 2016, Stochastics and Partial Differential Equations: Analysis and Computations.

Discrete-Time Signatures and Randomness in Reservoir Computing pdf

Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega, 2020, IEEE Transactions on Neural Networks and Learning Systems.

Polynomial processes and their applications to mathematical finance

Josef Teichmann, Christa Cuchiero, Martin Keller-Ressel, 2008, Finance and Stochastics.

Regularity of affine processes on general state spaces

W. Schachermayer, J. Teichmann, M. Keller-Ressel, 2011 .

Markovian lifts of positive semidefinite affine Volterra-type processes

J. Teichmann, Christa Cuchiero, 2019, Decisions in Economics and Finance.

Applications of Signature Methods to Market Anomaly Detection

J. Teichmann, Erdinç Akyıldırım, Matteo Gambara, 2022, ArXiv.

FLEXIBLE COMPLETE MODELS WITH STOCHASTIC VOLATILITY GENERALISING HOBSON-ROGERS

J. Teichmann, R. Tompkins, 2004 .

Calculation of Greeks for Jump-Diffusions

J. Teichmann, Barbara Forster, Eva Luetkebohmert, 2005 .

Linearized filtering of affine processes using stochastic Riccati equations

J. Teichmann, L. Gonon, Lukas Gonon, 2018, Stochastic Processes and their Applications.

Estimating Full Lipschitz Constants of Deep Neural Networks pdf

Calypso Herrera, Florian Krach, Josef Teichmann, 2020, ArXiv.

Local Lipschitz Bounds of Deep Neural Networks

J. Teichmann, F. Krach, Calypso Herrera, 2020, 2004.13135.

Efficient Simulation and Calibration of General HJM Models by Splitting Schemes

Josef Teichmann, Philipp Dörsek, J. Teichmann, 2011, SIAM J. Financial Math..

Term Structure Models Driven by Wiener Processes and Poisson Measures: Existence and Positivity

Josef Teichmann, Damir Filipovic, Stefan Tappe, 2010, SIAM J. Financial Math..

Global universal approximation of functional input maps on weighted spaces

J. Teichmann, Christa Cuchiero, Philipp Schmocker, 2023, ArXiv.

Invariant manifolds with boundary for jump-diffusions

D. Filipović, J. Teichmann, Stefan Tappe, 2012, 1202.1076.

Denise: Deep Learning based Robust PCA for Positive Semidefinite Matrices

J. Teichmann, F. Krach, Calypso Herrera, 2020, ArXiv.

Denise: Deep Robust Principal Component Analysis for Positive Semidefinite Matrices

J. Teichmann, Anastasis Kratsios, F. Krach, 2020, 2004.13612.

Parabolic Free Boundary Price Formation Models Under Market Size Fluctuations

Marie-Therese Wolfram, Peter A. Markowich, Josef Teichmann, 2016, Multiscale Model. Simul..

A Generative Adversarial Network Approach to Calibration of Local Stochastic Volatility Models

Christa Cuchiero, Josef Teichmann, Wahid Khosrawi, 2020, Risks.

How implicit regularization of Neural Networks affects the learned function - Part I pdf

Josef Teichmann, Jakob Heiss, Hanna Wutte, 2019, ArXiv.

On the effectiveness of Randomized Signatures as Reservoir for Learning Rough Dynamics

Enea Monzio Compagnoni, T. Hofmann, Anna Scampicchio, 2022, 2023 International Joint Conference on Neural Networks (IJCNN).

Randomized Signature Layers for Signal Extraction in Time Series Data pdf

Antonio Orvieto, Thomas Hofmann, Josef Teichmann, 2022, ArXiv.

Deep Neural Networks, Generic Universal Interpolation, and Controlled ODEs

Christa Cuchiero, Josef Teichmann, Martin Larsson, 2019, SIAM J. Math. Data Sci..

Generalized Feller processes and Markovian lifts of stochastic Volterra processes: the affine case

J. Teichmann, Christa Cuchiero, 2018, 1804.10450.

A new perspective on the fundamental theorem of asset pricing for large financial markets

J. Teichmann, Christa Cuchiero, I. Klein, 2014, 1412.7562.

Smooth Perfectness through Decomposition of Diffeomorphisms into Fiber Preserving Ones

J. Teichmann, Stefan Haller, 2001, math/0110041.

Deep Hedging under Rough Volatility pdf

Josef Teichmann, Blanka Horvath, Zan Zuric, 2021, SSRN Electronic Journal.

A deep learning model for gas storage optimization

J. Teichmann, T. Krabichler, Hanna Wutte, 2021, Decisions in Economics and Finance.

Deep Hedging: Hedging Derivatives Under Generic Market Frictions Using Reinforcement Learning

Josef Teichmann, Lukas Gonon, Ben Wood, 2019, SSRN Electronic Journal.

A new extrapolation method for weak approximation schemes with applications

Josef Teichmann, J. Teichmann, Dejan Velušček, 2009, 0911.4380.

How Implicit Regularization of ReLU Neural Networks Characterizes the Learned Function -- Part I: the 1-D Case of Two Layers with Random First Layer

J. Teichmann, Jakob Heiss, Hanna Wutte, 2019, 1911.02903.

A Sobolev rough path extension theorem via regularity structures

David J. Promel, J. Teichmann, Chong Liu, 2021, ESAIM: Probability and Statistics.

On Sobolev rough paths

David J. Promel, J. Teichmann, Chong Liu, 2020, 2006.03322.

Optimal Extension to Sobolev Rough Paths

David J. Prömel, J. Teichmann, Chong Liu, 2018, Potential Analysis.

Ramifications of generalized Feller theory

J. Teichmann, Christa Cuchiero, Tonio Mollmann, 2023, 2308.03858.

Global universal approximation of functional input maps on weighted spaces

J. Teichmann, Christa Cuchiero, Philipp Schmocker, 2023, ArXiv.

HOPF ’ S DECOMPOSITION AND RECURRENT SEMIGROUPS

J. Teichmann, 2001 .

How (Implicit) Regularization of ReLU Neural Networks Characterizes the Learned Function - Part II: the Multi-D Case of Two Layers with Random First Layer

J. Teichmann, Jakob Heiss, Hanna Wutte, 2023, ArXiv.

Machine Learning-powered Pricing of the Multidimensional Passport Option

J. Teichmann, Hanna Wutte, 2023, 2307.14887.

Jump-diffusions in Hilbert spaces: existence, stability and numerics

D. Filipović, J. Teichmann, Stefan Tappe, 2008, 0810.5023.

NOMU: Neural Optimization-based Model Uncertainty

Sven Seuken, J. Teichmann, Jakob Weissteiner, 2021, ICML.

A new approach to LIBOR modeling

J. Teichmann, A. Papapantoleon, Martin Keller-Ressel, 2009 .

How Implicit Regularization of ReLU Neural Networks Characterizes the Learned Function -- Part I: the 1-D Case of Two Layers with Random First Layer

J. Teichmann, Jakob Heiss, Hanna Wutte, 2019, 1911.02903.

Deep Neural Networks, Generic Universal Interpolation, and Controlled ODEs

Martin Larsson, J. Teichmann, Christa Cuchiero, 2019, SIAM J. Math. Data Sci..

FOUNDATIONS OF MARTINGALE THEORY AND STOCHASTIC CALCULUS FROM A FINANCE PERSPECTIVE

J. Teichmann, 2015 .

HOW CLOSE ARE THE OPTION PRICING FORMULAS OF BACHELIER AND BLACK–MERTON–SCHOLES?

W. Schachermayer, J. Teichmann, 2007, 0711.1272.

Hypoellipticity in infinite dimensions and an application in interest rate theory

Fabrice Baudoin, J. Teichmann, 2005, math/0508452.

A deep learning model for gas storage optimization

J. Teichmann, T. Krabichler, Hanna Wutte, 2021, Decisions in Economics and Finance.

Optimal Estimation of Generic Dynamics by Path-Dependent Neural Jump ODEs

J. Teichmann, F. Krach, Marc Nübel, 2022, ArXiv.

The Gärtner-Ellis Theorem, Homogenization, and Affine Processes

J. Teichmann, Archil Gulisashvili, 2014, 1406.3716.

A new perspective on the fundamental theorem of asset pricing for large financial markets

J. Teichmann, Christa Cuchiero, I. Klein, 2014, 1412.7562.

Hille-yosida theory in convenient analysis

J. Teichmann, 2002 .

PR ] 6 D ec 2 01 1 AFFINE PROCESSES ON SYMMETRIC CONES by Christa Cuchiero

E. Mayerhofer, J. Teichmann, Martin Keller-Ressel, 2011 .

Term Structure Models Driven by Wiener Process and Poisson Measures: Existence and Positivity

D. Filipović, J. Teichmann, Stefan Tappe, 2009, 0905.1413.

Fourier transform methods for pathwise covariance estimation in the presence of jumps

J. Teichmann, Christa Cuchiero, 2013, 1301.3602.

Affine Models

D. Filipović, J. Teichmann, Christa Cuchiero, 2008, 0809.1985.

Stopper-Controller Games embedded in Single-Player Control Problems

Martin Larsson, J. Teichmann, Marvin S. Mueller, 2020, 2006.09493.

Characterization of nonlinear Besov spaces

David J. Promel, J. Teichmann, Chong Liu, 2018, Transactions of the American Mathematical Society.