Prof. Dr. Gero Junike

Curriculum Vitae (short version):

• Since 09/2025: Associate Professor (deputy) for financial and insurance mathematics at Ludwig-Maximilians-Universität München, Germany.
• 2020-2025: (5y) Assistant Professor (Juniorprofessor) for insurance and financial mathematics at Carl von Ossietzky Universität Oldenburg, Germany.
• 2020: (3m) Postdoc at Finance and Insurance Group, Vrije Universiteit Brussel, Belgium, with Carole Bernard and Steven Vanduffel.
• 2019-2020: (1.5y) Specialist for algorithmic trading strategies, Finovesta GmbH, Düsseldorf, Germany.
• 2016-2019: (3y) PhD Student, Universitat Autònoma de Barcelona, Spain.
• 2017: (1y) Stay at KU Leuven, Belgium with Wim Schoutens.
• 2013-2015: (2y) Risk Manager at HSBC, Düsseldorf, Germany.
• 2011-2013: (2y) Master in Mathematics (with honors), TU Braunschweig, Germany.
• 2008-2011: (3y) Bachelor in Mathematics, TU Braunschweig, Germany.

Research Interests:

Preprints:

• Batch normalization does not improve initialization.
  Dannemann, J. and Junike, G. (2025). Preprint, [pdf]
  


• Enhancing Fourier pricing with machine learning.
  Junike, G. and Stier, H. (2025). Preprint, [pdf]
  


• Validation of machine learning based scenario generators.
  Flaig, S. and Junike, G. (2024). Preprint, [pdf]
  

Publications:

• From characteristic functions to multivariate distribution functions and European option prices by the damped COS method.
  Junike, G. and Stier, H. (2024). (accepted in SIAM Journal on Numerical Analysis), [pdf]
  


• Exact simulation of stochastic volatility models based on conditional Fourier cosine method.
  Brignone, R., Junike, G. (2025). European Journal of Operational Reseach, [pdf]
  


• Precise quantile function estimation from the characteristic function.
  Junike, G. (2025). Statistics and Probability Letters, [pdf]
  


• Profit and loss decomposition in continuous time and approximations.
  Junike, G., Stier, H., Christiansen, M. C. (2025). Finance and Stochastics, [pdf]
  


• On the number of terms in the COS method for European option pricing.
  Junike, G. (2024). Numerische Mathematik, [pdf], R-Code
  


• Failure of Fourier pricing techniques to approximate the Greeks.
  Behrens, T., Junike, G. and Schoutens, W. (2024). Frontiers of Mathematical Finance, [pdf]
  


• An empirical study of profit and loss allocations.
  Flaig, S. and Junike, G. (2024). European Actuarial Journal, [pdf]
  


• Cost-efficient payoffs under model ambiguity.
  Bernard, C., Junike, G., Lux, T. and Vanduffel, S. (2024). Finance and Stochastics, [pdf]
  


• Precise option pricing by the COS method–How to choose the truncation range.
  Junike, G. and Pankrashkin, K. (2022). Applied Mathematics and Computation, [pdf]
  


• Performance of advanced stock price models when it becomes exotic: an empirical study.
  Junike, G., Schoutens, W. and Stier, H. (2022). Annals of Finance, [pdf]
  


• Scenario generation for market risk models using generative neural networks.
  Flaig, S. and Junike, G. (2022). Risks, [pdf]
  


• Representation of distortion risk measures and applications.
  Junike, G. (2019). Scandinavian Actuarial Journal, [pdf]
  


• American and exotic options in a market with frictions.
  Junike, G., Arratia, A., Cabaña, A., and Schoutens, W. (2019). European Journal of Finance, [pdf]
  


• Implied liquidity risk premia in option markets.
  Guillaume, F., Junike, G., Leoni, P., and Schoutens, W. (2018). Annals of Finance, [pdf]
  


• Advanced stock price models, concave distortion functions and liquidity risk in finance.
Junike, G. (2019). PhD thesis, [pdf]

Talks and Presentations:

• Fourier Pricing techniques. (2025, July.)
  5th Barcelona summer school of Stochastic Analysis and Quantitative Finance, Barcelona, Spain.
  


• Cost-efficient payoffs under model ambiguity. (2025, July.)
  ISIPTA 2025: International Symposium on Imprecise Probabilities, Bielefeld, Germany.
  


• Validation of machine learning based scenario generators. (2025, June.)
  12th AMaMeF Conference, Verona, Italy.
  


• Detecting the memorizing effect in generative AI. (2025, Mar.)
  GPSD 2025 Conference (German probability and statistics days), Dresden, Germany.
  


• Failure of Fourier pricing techniques to approximate the Greeks. (2024, Nov.)
  Peter Carr Conference on Mathematical Finance, Washington, D.C., USA.
  


• Itô decompositions. (2024, Aug.)
  Bernoulli-ims 11th World Congress in Probability and Statistics, Bochum, Germany.
  


• The multidimensional COS method for option pricing. (2024, Apr.)
  International Conference on Computational Finance, Amsterdam, Netherlands.
  


• Empirical and theoretical analysis of profit and loss allocations. (2024, Feb.)
  Actuarial and Financial Mathematics Conference, Brussels, Belgium.
  


• Decomposition of profit and losses. (2023, Oct.)
  DGVFM-Workshop, Loccum, Germany.
  


• P&L attribution in dynamic time. (2023, Oct.)
  Munich Risk and Insurance Days 2023, Munich, Germany.
  


• How to handle the COS method for option pricing. (2023, Sept.)
  DMV annual meeting 2023, Ilmenau, Germany.
  


• How to handle the COS method for option pricing. (2023, June)
  11th AMaMeF Conference, Bielefeld, Germany.
  


• Sequential decompositions at their limit. (2023, May)
  Mathematical Finance and Stochastics: A Conference in Honor of David Nualart, San Sebastián, Spain.
  


• Sequential decompositions at their limit. (2023, Apr.)
  Belgian Financial Research Forum 2023, Brussels, Belgium.
  


• Profit and loss attribution by sequential decompositions. (2023, Mar.)
  GPSD 2023 Conference (German probability and statistics days), Essen, Germany.
  


• Precise option pricing by the COS method–How to choose the truncation range. (2022, Oct.)
  8th Workshop on Risk Management and Insurance Research, Barcelona, Spain.
  


• Representation of distortion risk measures and applications. (2022, Aug.)
  European Actuarial Journal Conference, Tartu, Estonia.
  


• American and exotic options in a market with frictions. (2022, May.)
  Dynamic Assessment Indices, workshop at IMSI, Chicago, USA.
  


• Some premium principles in actuarial science. (2021, Oct.)
  DGVFM-Workshop, online, Germany.
  


• Representation of distortion risk measures and applications. (2019, Feb.)
  Actuarial and Financial Mathematics Conference, Brussels, Belgium.
  


• Distortion functions and applications in insurance science and two price models. (2018, Nov.)
  Statistics Seminar, joint series Mathematics Department & ORSTAT, KU Leuven, Belgium.
  


• Conic finance and earning announcements. (2018, Apr.)
  Mathematical and Statistical Methods for Actuarial Sciences and Finance (Conference MAF), Madrid, Spain.
  

Teaching:

• Supervised learning
• Financial Mathematics
• Stochastic Analysis

Impressum & Contact: