Deep Learning Volatility
Horvath, B
Muguruza, A
Tomas, M
(28 Jan 2019)
doi:10.48550/arxiv.1901.09647
On deep calibration of (rough) stochastic volatility models
Bayer, C
Horvath, B
Muguruza, A
Stemper, B
Tomas, M
(22 Aug 2019)
doi:10.48550/arxiv.1908.08806
Sailing in rough waters: examining volatility of fMRI noise
Leppanen, J
Stone, H
Lythgoe, D
Williams, S
Horvath, B
doi:10.1101/2020.06.19.161570
Data Anonymisation, Outlier Detection and Fighting Overfitting with Restricted Boltzmann Machines
Kondratyev, A
Schwarz, C
Horvath, B
(01 Jan 2020)
doi:10.2139/ssrn.3526436
Deep Hedging under Rough Volatility
Horvath, B
Teichmann, J
Zuric, Z
(03 Feb 2021)
doi:10.48550/arxiv.2102.01962
Deep Hedging under Rough Volatility
Horvath, B
Teichmann, J
Zuric, Z
(01 Jan 2021)
doi:10.2139/ssrn.3778043
Hedging under rough volatility
Fukasawa, M
Horvath, B
Tankov, P
(09 May 2021)
doi:10.48550/arxiv.2105.04073
Mathematics of the Bond Market: A Lévy Processes Approach
Grbac, Z
Horvath, B
Quantitative Finance
volume 21
issue 8
1263-1265
(03 Aug 2021)
doi:10.1080/14697688.2021.1939118
Exotic Options and Hybrids: A Guide to Structuring, Pricing and Trading
Horvath, B
Quantitative Finance
volume 21
issue 9
1435-1436
(02 Sep 2021)
doi:10.1080/14697688.2021.1969032
Clustering Market Regimes using the Wasserstein Distance
Horvath, B
Issa, Z
Muguruza, A
(22 Oct 2021)
doi:10.48550/arxiv.2110.11848