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A Data-driven Market Simulator for Small Data Environments

Citations

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Cited by:

  1. Emiel Lemahieu & Kris Boudt & Maarten Wyns, 2023. "Generating drawdown-realistic financial price paths using path signatures," Papers 2309.04507, arXiv.org.
  2. Samuel N. Cohen & Derek Snow & Lukasz Szpruch, 2021. "Black-box model risk in finance," Papers 2102.04757, arXiv.org.
  3. Achintya Gopal, 2024. "NeuralFactors: A Novel Factor Learning Approach to Generative Modeling of Equities," Papers 2408.01499, arXiv.org.
  4. Samuel N. Cohen & Christoph Reisinger & Sheng Wang, 2022. "Estimating risks of option books using neural-SDE market models," Papers 2202.07148, arXiv.org.
  5. Giulia Di Nunno & Kk{e}stutis Kubilius & Yuliya Mishura & Anton Yurchenko-Tytarenko, 2023. "From constant to rough: A survey of continuous volatility modeling," Papers 2309.01033, arXiv.org, revised Sep 2023.
  6. Christa Cuchiero & Francesca Primavera & Sara Svaluto-Ferro, 2022. "Universal approximation theorems for continuous functions of c\`adl\`ag paths and L\'evy-type signature models," Papers 2208.02293, arXiv.org, revised Aug 2023.
  7. Christa Cuchiero & Wahid Khosrawi & Josef Teichmann, 2020. "A Generative Adversarial Network Approach to Calibration of Local Stochastic Volatility Models," Risks, MDPI, vol. 8(4), pages 1-31, September.
  8. Christa Cuchiero & Philipp Schmocker & Josef Teichmann, 2023. "Global universal approximation of functional input maps on weighted spaces," Papers 2306.03303, arXiv.org, revised Feb 2024.
  9. Beatrice Acciaio & Anastasis Kratsios & Gudmund Pammer, 2022. "Designing Universal Causal Deep Learning Models: The Geometric (Hyper)Transformer," Papers 2201.13094, arXiv.org, revised Mar 2023.
  10. Magnus Wiese & Phillip Murray & Ralf Korn, 2023. "Sig-Splines: universal approximation and convex calibration of time series generative models," Papers 2307.09767, arXiv.org.
  11. Andrea Coletta & Joseph Jerome & Rahul Savani & Svitlana Vyetrenko, 2023. "Conditional Generators for Limit Order Book Environments: Explainability, Challenges, and Robustness," Papers 2306.12806, arXiv.org.
  12. Christa Cuchiero & Wahid Khosrawi & Josef Teichmann, 2020. "A generative adversarial network approach to calibration of local stochastic volatility models," Papers 2005.02505, arXiv.org, revised Sep 2020.
  13. Mohamed Hamdouche & Pierre Henry-Labordere & Huyên Pham, 2023. "Generative modeling for time series via Schrödinger bridge," Working Papers hal-04063041, HAL.
  14. Magnus Wiese & Phillip Murray, 2022. "Risk-Neutral Market Simulation," Papers 2202.13996, arXiv.org.
  15. Ruslan Tepelyan & Achintya Gopal, 2023. "Generative Machine Learning for Multivariate Equity Returns," Papers 2311.14735, arXiv.org.
  16. Chung I Lu, 2023. "Evaluation of Deep Reinforcement Learning Algorithms for Portfolio Optimisation," Papers 2307.07694, arXiv.org, revised Jul 2023.
  17. Chung I Lu & Julian Sester, 2024. "Generative model for financial time series trained with MMD using a signature kernel," Papers 2407.19848, arXiv.org, revised Dec 2024.
  18. Francesca Biagini & Lukas Gonon & Niklas Walter, 2024. "Universal randomised signatures for generative time series modelling," Papers 2406.10214, arXiv.org, revised Sep 2024.
  19. Mohamed Hamdouche & Pierre Henry-Labordere & Huy^en Pham, 2023. "Generative modeling for time series via Schr{\"o}dinger bridge," Papers 2304.05093, arXiv.org.
  20. Rama Cont & Mihai Cucuringu & Renyuan Xu & Chao Zhang, 2022. "Tail-GAN: Learning to Simulate Tail Risk Scenarios," Papers 2203.01664, arXiv.org, revised Mar 2023.
  21. Blanka Horvath & Zacharia Issa & Aitor Muguruza, 2021. "Clustering Market Regimes using the Wasserstein Distance," Papers 2110.11848, arXiv.org.
  22. Christa Cuchiero & Guido Gazzani & Sara Svaluto-Ferro, 2022. "Signature-based models: theory and calibration," Papers 2207.13136, arXiv.org.
  23. Yannick Limmer & Blanka Horvath, 2023. "Robust Hedging GANs," Papers 2307.02310, arXiv.org.
  24. Christa Cuchiero & Guido Gazzani & Janka Moller & Sara Svaluto-Ferro, 2023. "Joint calibration to SPX and VIX options with signature-based models," Papers 2301.13235, arXiv.org, revised Jul 2024.
  25. Christa Cuchiero & Janka Moller, 2023. "Signature Methods in Stochastic Portfolio Theory," Papers 2310.02322, arXiv.org, revised Oct 2024.
  26. Sebastian Jaimungal, 2022. "Reinforcement learning and stochastic optimisation," Finance and Stochastics, Springer, vol. 26(1), pages 103-129, January.
  27. Alexandre Miot, 2020. "Adversarial trading," Papers 2101.03128, arXiv.org.
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