Blanka N. Horvath

• It was a pleasure to contribute to Nature magazine on the occasion of the 50th anniversary of the Black & Scholes Formula. A free access link to the short article can be found here:  50 Years of Black&Scholes: Golden Jubilee for an Iconic Formula, Nature, May-June 2023

• Book review: Mathematical Modeling and Computation in Finance by Cornelis W. Oosterlee and Lech A. Grzelak.
  with A. Gnoatto, Quantitative Finance ,Volume 22, 2022 - Issue 11 2022. 

• Rough volatility's steampunk vision of future finance 2021

• Contribution to the FaIR Advances Report 2021, August, 2020

• Risk.net Podcast: Blanka Horvath and Gordon Lee on market generator models, March 2020

• Honoured to receive the Quant Rising Star Award of Risk magazine at the Risk Awards, November 2019.

• Shortlisted for the Research Paper of the Year at the RiskMinds Awards Decemper 2019.

• K-Net Article: ``Building a Deep Neural Network", May 2019. 

• An interview for Fintech Capital Markets: Interview: using deep neural networks for derivatives pricing problems written by Anna Reitmann, April 2019.

• Deep Kalman Filters Can Filter with A. Kratsios, Y. Limmer, and X. Yang, October 2023. 

• Signature Trading: A Path-Dependent Extension of the Mean-Variance Framework with Exogenous Signals with O.  Futter, and M.  Wiese, August 2023.

• A Hybrid Quantum Wasserstein GAN with Applications to Option Pricing with F. D. Fuchs, July 2023.

• Non-parametric Online Market Regime Detection and Regime Clustering for Multidimensional and Path-Dependent Data Structures with Z. Issa, June 2023.

• Robust Hedging GANs with Y. Limmer, June 2023.

• Harnessing Quantitative Finance by Data-Centric Methods  with A. Muguruza Gonzalez, and M. S. Pakkanen,  in  Machine Learning and Data Sciences for Financial Markets: A Guide to Contemporary Practices,  Edited: A. Capponi, C.-A. Lehalle, Cambridge University Press, May 2023.
  
  

• Non-adversarial training of Neural SDEs with signature kernel scores with Z. Issa, M. Lemercier, C. Salvi, May 2023.

• Optimal Stopping via Distribution Regression: a Higher Rank Signature Approach, with M. Lemercier, C. Liu, T. Lyons, C. Salvi, April 2023.

• Model-Agnostic Pricing of Exotic Derivatives Using Signatures
  with A. Alden, C. Ventre, G. Lee: Proceedings of the Third ACM International Conference on AI in Finance, 96-104,  Nov 2022.

• Higher order kernel mean embeddings to capture filtrations of stochastic processes,
  with C. Salvi, M. Lemercier, C. Liu, T. Damoulas, and T. Lyons, Advances in Neural Information Processing Systems 34, 16635-16647, Dec 2021.

• Clustering Market Regimes Using the Wasserstein Distance, with Z. Issa and A. Muguruza, October 2021.

• Hedging under Rough Volatility, with M. Fukasawa and P. Tankov, May 2021: Book chapter in "Rough Volatility", 2023. 

• Sailing in rough waters: examining volatility of fMRI noise, with J.Leppanen, H. Stone, D. J. Lythgoe and S. Williams.
  Journal of Magnetic Resonance Imaging, Volume 78, Pages 69-79, May 2021.

• Deep Hedging under Rough Volatility, with J. Teichmann and Zan Zuric, February 2021.

• A data-driven market simulator for small data environments, with H. Buehler, T. Lyons, I Perez Arribas and B. Wood, June 2020. 

For earlier publications, please visit: Publications