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Building on the functional-analytic framework of operator-valued kernels and un-truncated signature kernels, we propose a scalable, provably convergent signature-based algorithm for a broad class of high-dimensional, path-dependent hedging problems.
URL https://arxiv.org/abs/1905.00711
Lyons, T., Nejad, S., Arribas, I.P.: Nonparametric pricing and hedging of exotic derivatives (2019) · 1905
Earlier work this paper cites.
The journal of Finance 49
Hutchinson, J.M., Lo, A.W., Poggio, T.: A nonparametric approach to pricing and hedging derivative securities via learning networks · 1994
Earlier work this paper cites.
The Annals of Applied Probability 5
Soner, H.M., Shreve, S.E., Cvitanic, J.: There is no nontrivial hedging portfolio for option pricing with transaction costs · 1995
Earlier work this paper cites.
Revista Matemática Iberoamericana 14
Lyons, T.J.: Differential equations driven by rough signals · 1998
Earlier work this paper cites.
Oxford University Press (2002)
Lyons, T., Qian, Z.: System control and rough paths · 2002
Earlier work this paper cites.
Journal of Machine Learning Research 5
De Vito, E., Rosasco, L., Caponnetto, A., Piana, M., Verri, A.: Some properties of regularized kernel methods · 2004
Earlier work this paper cites.
Ecole d’été de Probabilités de Saint-Flour XXXIV pp. 1–93 (2004)
Lyons, T., Caruana, M., Lévy, T.: Differential equations driven by rough paths · 2004
Earlier work this paper cites.
Analysis and Applications 04
CARMELI, C., DE VITO, E., TOIGO, A.: Vector valued reproducing kernel hilbert spaces of integrable functions and mercer theorem · 2006
Earlier work this paper cites.
Hubalek, F., Kallsen, J., Krawczyk, L.: Variance-optimal hedging for processes with stationary independent increments (2006)
2006
Earlier work this paper cites.
Lecture Notes in Mathematics. Springer Berlin Heidelberg (2007)
Lyons, T., Caruana, M., Lévy, T.: Differential Equations Driven by Rough Paths: Ecole d’Eté de Probabilités de Saint-Flour XXXIV-2004 · 2007
Earlier work this paper cites.
Cambridge Studies in Advanced Mathematics. Cambridge University Press (2010)
Friz, P., Victoir, N.: Multidimensional Stochastic Processes as Rough Paths: Theory and Applications · 2010
Earlier work this paper cites.
Mathematical Finance: An International Journal of Mathematics, Statistics and Financial Economics 20
Rogers, L.C., Singh, S.: The cost of illiquidity and its effects on hedging · 2010
Earlier work this paper cites.
Jeanblanc, M., Mania, M., Santacroce, M., Schweizer, M.: Mean-variance hedging via stochastic control and bsdes for general semimartingales (2012)
2012
Earlier work this paper cites.
Stochastics An International Journal of Probability and Stochastic Processes 86
Goutte, S., Oudjane, N., Russo, F.: Variance optimal hedging for continuous time additive processes and applications · 2014
Earlier work this paper cites.
URL https://arxiv.org/abs/1406.7871
Boedihardjo, H., Geng, X., Lyons, T., Yang, D.: The signature of a rough path: Uniqueness (2015) · 2015
Cited alongside, same era.
Stochastic Processes and their Applications 126
Flint, G., Hambly, B., Lyons, T.: Discretely sampled signals and the rough hoff process · 2016
Cited alongside, same era.
Mathematics and financial economics 11
Bank, P., Soner, H.M., Voß, M.: Hedging with temporary price impact · 2017
Cited alongside, same era.
Quantitative Finance 19
Buehler, H., Gonon, L., Teichmann, J., Wood, B.: Deep hedging · 2019
Cited alongside, same era.
Advances in Neural Information Processing Systems 32
Kidger, P., Bonnier, P., Perez Arribas, I., Salvi, C., Lyons, T.: Deep signature transforms · 2019
Cited alongside, same era.
In: ACM International Conference on AI in Finance (2020)
Arribas, I.P., Salvi, C., Szpruch, L.: Sig-sdes model for quantitative finance · 2020
In: Proceedings of the 40th International Conference on Machine Learning, ICML’23. JMLR.org (2023)
Cirone, N.M., Lemercier, M., Salvi, C.: Neural signature kernels as infinite-width-depth-limits of controlled resnets · 2023
Later among the works it cites.
IEEE BITS the Information Theory Magazine (2023)
Fermanian, A., Lyons, T., Morrill, J., Salvi, C.: New directions in the applications of rough path theory · 2023
Later among the works it cites.
arXiv preprint arXiv:2306.14258 (2023)
Hoglund, M., Ferrucci, E., Hernández, C., Gonzalez, A.M., Salvi, C., Sanchez-Betancourt, L., Zhang, Y.: A neural rde approach for continuous-time non-markovian stochastic control problems · 2023
Later among the works it cites.
arXiv preprint arXiv:2304.01479 (2023)
Horvath, B., Lemercier, M., Liu, C., Lyons, T., Salvi, C.: Optimal stopping via distribution regression: a higher rank signature approach · 2023
Later among the works it cites.
Journal of Algebra 634
Salvi, C., Diehl, J., Lyons, T., Preiss, R., Reizenstein, J.: A structure theorem for streamed information · 2023
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Cited alongside, same era.
Universitext. Springer International Publishing (2020)
Friz, P., Hairer, M.: A Course on Rough Paths: With an Introduction to Regularity Structures · 2020
Cited alongside, same era.
Applied Mathematical Finance 27
Lyons, T., Nejad, S., Perez Arribas, I.: Non-parametric pricing and hedging of exotic derivatives · 2020
Cited alongside, same era.
In: 2021 IEEE International Conference on Cyber Security and Resilience (CSR), pp. 35–40. IEEE (2021)
Cochrane, T., Foster, P., Chhabra, V., Lemercier, M., Lyons, T., Salvi, C.: Sk-tree: a systematic malware detection algorithm on streaming trees via the signature kernel · 2021
Cited alongside, same era.
In: International Conference on Machine Learning. PMLR (2021)
Lemercier, M., Salvi, C., Cass, T., Bonilla, E.V., Damoulas, T., Lyons, T.: Siggpde: Scaling sparse gaussian processes on sequential data · 2021
Cited alongside, same era.
In: International Conference on Artificial Intelligence and Statistics, pp. 3754–3762. PMLR (2021)
Lemercier, M., Salvi, C., Damoulas, T., Bonilla, E., Lyons, T.: Distribution regression for sequential data · 2021
Cited alongside, same era.
In: International Conference on Machine Learning, pp. 7829–7838. PMLR (2021)
Morrill, J., Salvi, C., Kidger, P., Foster, J.: Neural rough differential equations for long time series · 2021
Cited alongside, same era.
Later among the works it cites.
Thomas R. Cass, J.P.: A fubini type theorem for rough integration · 2023
Later among the works it cites.
arXiv preprint arXiv:2406.10354 (2024)
Barancikova, B., Huang, Z., Salvi, C.: Sigdiffusions: Score-based diffusion models for long time series via log-signature embeddings · 2024
Later among the works it cites.
arXiv preprint arXiv:2404.06583 (2024)
Cass, T., Salvi, C.: Lecture notes on rough paths and applications to machine learning · 2024
Later among the works it cites.
Chevyrev, I.: Rough path theory (2024) · 2024
Later among the works it cites.
arXiv preprint arXiv:2402.19047 (2024)
Cirone, N.M., Orvieto, A., Walker, B., Salvi, C., Lyons, T.: Theoretical foundations of deep selective state-space models · 2024
Later among the works it cites.
arXiv preprint arXiv:2405.13587 (2024)
Holberg, C., Salvi, C.: Exact gradients for stochastic spiking neural networks driven by rough signals · 2024
Later among the works it cites.
Advances in Neural Information Processing Systems 36
Issa, Z., Horvath, B., Lemercier, M., Salvi, C.: Non-adversarial training of neural sdes with signature kernel scores · 2024
Later among the works it cites.
arXiv preprint arXiv:2402.18477 (2024)
Manten, G., Casolo, C., Ferrucci, E., Mogensen, S.W., Salvi, C., Kilbertus, N.: Signature kernel conditional independence tests in causal discovery for stochastic processes · 2024
Later among the works it cites.
arXiv preprint arXiv:2403.11738 (2024)
Pannier, A., Salvi, C.: A path-dependent pde solver based on signature kernels · 2024
Later among the works it cites.