Non-adversarial training of Neural SDEs with signature kernel scores
Horvath, B
Issa, Z
Lemercier, M
Salvi, C
11102-11126
(01 Jan 2023)
doi:10.52202/075280-0490
Asymptotic behaviour of randomised fractional volatility models
Horvath, B
Jacquier, A
Lacombe, C
Journal of Applied Probability
volume 56
issue 2
496-523
(30 Jun 2019)
doi:10.1017/jpr.2019.27
FILTERED NOT MIXED: FILTERING-BASED ONLINE GATING FOR MIXTURE OF LARGE LANGUAGE MODELS
Saqur, R
Kratsios, A
Krach, F
Limmer, Y
Tian, J
Willes, J
Horvath, B
Rudzicz, F
13th International Conference on Learning Representations Iclr 2025
31568-31601
(01 Jan 2025)
On the probability of hitting the boundary for Brownian motions on the SABR plane
Gulisashvili, A
Horvath, B
Jacquier, A
Electronic Communications in Probability
volume 21
issue none
(01 Jan 2016)
doi:10.1214/16-ecp26
Dirichlet Forms and Finite Element Methods for the SABR Model
Horvath, B
Reichmann, O
SIAM Journal on Financial Mathematics
volume 9
issue 2
716-754
(31 Jan 2018)
doi:10.1137/16m1066117
Volatility Options in Rough Volatility Models
Horvath, B
Jacquier, A
Tankov, P
SIAM Journal on Financial Mathematics
volume 11
issue 2
437-469
(27 Jan 2020)
doi:10.1137/18m1169242
Mass at zero in the uncorrelated SABR model and implied volatility asymptotics
Gulisashvili, A
Horvath, B
Jacquier, A
Quantitative Finance
volume 18
issue 10
1753-1765
(03 Oct 2018)
doi:10.1080/14697688.2018.1432883
Deep learning volatility: a deep neural network perspective on pricing and calibration in (rough) volatility models
Horvath, B
Muguruza, A
Tomas, M
Quantitative Finance
volume 21
issue 1
11-27
(02 Jan 2021)
doi:10.1080/14697688.2020.1817974
FUNCTIONAL ANALYTIC (IR-)REGULARITY PROPERTIES OF SABR-TYPE PROCESSES
DÖRING, L
HORVATH, B
TEICHMANN, J
International Journal of Theoretical and Applied Finance
volume 20
issue 03
1750013
(24 May 2017)
doi:10.1142/s0219024917500133
Clustering market regimes using the Wasserstein distance
Horvath, B
Issa, Z
Muguruza, A
The Journal of Computational Finance
(2024)
doi:10.21314/jcf.2024.005