Applied and Computational Mathematics (ACM)

Finance

The famous Black-Scholes equation is an effective model for option pricing. It was named after the pioneers Black, Scholes and Merton who suggested it 1973.

In this research field our aim is the development of effective numerical schemes for solving linear and nonlinear problems arising in the mathematical theory of derivative pricing models.

An option is the right (not the duty) to buy (call option') or to sell (put option') an asset (typically a stock or a parcel of shares of a company) for a price E by the expiry date T. European options can only be exercised at the expiration date T. For American options exercise is permitted at any time until the expiry date. The standard approach for the scalar Black-Scholes equation for European (American) options results after a standard transformation in a diffusion equation posed on an bounded (unbounded) domain.

Another problem arises when considering American options (most of the options on stocks are American style). Then one has to compute numerically the solution on a semi-unbounded domain with a free boundary. Usually finite differences or finite elements are used to discretize the equation and artificial boundary conditions are introduced in order to confine the computational domain.

In this research field we want to design and analyze new efficient and robust numerical methods for the solution of highly nonlinear option pricing problems. Doing so, we have to solve adequately the problem of unbounded spatial domains by introducing artificial boundary conditions and show how to incorporate them in a high-order time splitting method.

Nonlinear Black-Scholes equations have been increasingly attracting interest over the last two decades, since they provide more accurate values than the classical linear model by taking into account more realistic assumptions, such as transaction costs, risks from an unprotected portfolio, large investor's preferences or illiquid markets, which may have an impact on the stock price, the volatility, the drift and the option price itself.

Special Interests

7026.

Maten, E Jan W; Ehrhardt, Matthias
MS40: Computational methods for finance and energy markets
19th European Conference on Mathematics for Industry, Seite 377

7025.

Teng, L.; Ehrhardt, M.; Günther, M.
Stochastic Correlation: Modelling, Analysis and Numerical Simulation with Applications in Finance
Herausgeber: World Scientific
2024

7024.

Günther, M.; Jacob, Birgit; Totzeck, Claudia
Data-driven adjoint-based calibration of port-Hamiltonian systems in time domain
Math. Control Signals Syst.
2024

7023.

Hastir, Anthony; Jacob, Birgit; Zwart, Hans
Linear-Quadratic optimal control for boundary controlled networks of waves
2024

7022.

Jamil, Hamza
Intrusive and non-intrusive uncertainty quantification methodologies for pyrolysis modeling
Fire Safety Journal, 143 :104060
2024
ISSN: 0379-7112

7021.

Hosfeld, René; Jacob, Birgit; Schwenninger, Felix; Tucsnak, Marius
Input-to-state stability for bilinear feedback systems
SIAM Journal on Control and Optimization, 62 (3) :1369-1389
2024

7020.

Erbay, Mehmet; Jacob, Birgit; Morris, Kirsten; Reis, Timo; Tischendorf, Caren
Index concepts for linear differential-algebraic equations in finite and infinite dimensions
2024

7019.

Schäfers, Kevin; Finkenrath, Jacob; Günther, Michael; Knechtli, Francesco
2024

7018.

Bartel, Andreas; Schaller, Manuel
Goal-oriented time adaptivity for port-{H}amiltonian systems
2024

7017.

Song, Yongcun; Wang, Ziqi; Zuazua, Enrique
2024

7016.

[german] Zeller, Diana; Bohrmann-Linde, Claudia
Falschinformationen in Videos? Mit dem Konzept KriViNat die Kompetenz der Informationsbewertung stärken
In Bohrmann-Linde, C.; Gökkus, Y.; Meuter, N.; Zeller, D., Editor, Band Netzwerk Digitalisierter Chemieunterricht. Sammelband NeDiChe-Treff 2022
Seite 9-15
Herausgeber: Chemiedidaktik. Bergische Universität Wuppertal
2024
9-15

7015.

Santos, Daniela Scherer; Klamroth, Kathrin; Martins, Pedro; Paquete, Luís
Ensuring connectedness for the Maximum Quasi-clique and Densest $k$-subgraph problems
2024

7014.

Ehrhardt, M.; Kruse, T.; Tordeux, A.
Dynamics of a Stochastic port-{H}amiltonian Self-Driven Agent Model in One Dimension
ESAIM: Math. Model. Numer. Anal.
2024

7013.

Stiglmayr, Michael; Uhlemeyer, Svenja; Uhlemeyer, Björn; Zdrallek, Markus
Determining Cost-Efficient Controls of Electrical Energy Storages Using Dynamic Programming
Journal of Mathematics in Industry
2024

7012.

Kossaczká, Tatiana; Jagtap, Ameya D; Ehrhardt, Matthias
Deep smoothness weighted essentially non-oscillatory method for two-dimensional hyperbolic conservation laws: A deep learning approach for learning smoothness indicators
Physics of Fluids, 36 (3)
2024
Herausgeber: AIP Publishing

7011.

Ackermann, Julia; Jentzen, Arnulf; Kuckuck, Benno; Padgett, Joshua Lee
Deep neural networks with ReLU, leaky ReLU, and softplus activation provably overcome the curse of dimensionality for space-time solutions of semilinear partial differential equations
arXiv:2406.10876 :64 pages
2024

7010.

Clément, François; Doerr, Carola; Klamroth, Kathrin; Paquete, Luís
Constructing Optimal ${L}_{\infty}$ Star Discrepancy Sets
2024

7009.

Bolten, Matthias; Doganay, Onur Tanil; Gottschalk, Hanno; Klamroth, Kathrin
Non-convex shape optimization by dissipative {H}amiltonian flows
Engineering Optimization
2024

7008.

Klamroth, Kathrin; Stiglmayr, Michael; Totzeck, Claudia
Consensus-Based Optimization for Multi-Objective Problems: A Multi-Swarm Approach
Journal of Global Optimization
2024

7007.

Vorberg, Lukas; Jacob, Birgit; Wyss, Christian
Computing the Quadratic Numerical Range
Journal of Computational and Applied Mathematics :116049
2024

7006.

Klass, Friedemann; Gabbana, Alessandro; Bartel, Andreas
Characteristic boundary condition for thermal lattice Boltzmann methods
Computers & Mathematics with Applications, 157 :195-208
2024
ISSN: 0898-1221

7005.

Fasi, Massimiliano; Gaudreault, Stéphane; Lund, Kathryn; Schweitzer, Marcel
Challenges in computing matrix functions
2024

7004.

Bailo, Rafael; Barbaro, Alethea; Gomes, Susana N.; Riedl, Konstantin; Roith, Tim; Totzeck, Claudia; Vaes, Urbain
CBX: Python and Julia packages for consensus-based interacting particle methods
2024

7003.

Kiesling, Elisabeth; Venzlaff, Julian; Bohrmann-Linde, Claudia
BNE-Fortbildungsreihe für Lehrkräfte und Studierende in der Didaktik der Chemie
Herausgeber: Gemeinsamer Studienausschuss (GSA) in der School of Education an der Bergischen Universität Wuppertal
Newsletter Lehrer*innenbildung an der Bergischen Universität Wuppertal
2024

7002.

Bauß, Julius; Stiglmayr, Michael
Augmenting Biobjective Branch & Bound with Scalarization-Based Information
Mathematical Methods of Operations Research
2024

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