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Bayesian inference of biochemical kinetic parameters using the linear noise approximation. [PDF]

BMC Bioinformatics, 2009
Komorowski M, Finkenstädt B, Harper CV, Rand DA.   +3 more
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Volatility and variance swaps and options in the fractional SABR model

The European Journal of Finance, 2020
Appropriate capturing the nature of financial market volatility is a significant factor for the pricing of volatility derivatives. A recent study by Gatheral, Jaisson and Rosenbaum [2018.
Jeong-Hoon Kim, See-Woo Kim
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An artificial neural network representation of the SABR stochastic volatility model

The Journal of Computational Finance, 2018
In this article, the Universal Approximation Theorem of Artificial Neural Networks (ANNs) is applied to the SABR stochastic volatility model in order to construct highly efficient representations. Initially, the SABR approximation of Hagan et al. [2002] is considered, then a more accurate integration scheme of McGhee [2011] as well as a two factor ...
W. Mcghee
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Machine Learning SABR Model of Stochastic Volatility With Lookup Table

SSRN Electronic Journal, 2020
We present an embarrassingly simple method for supervised learning of SABR model’s European option price function based on lookup table or rote machine learning. Performance in time domain is comparable to generally used analytic approximations utilized in financial industry.
Mahir Lokvancic
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Asset Movement Forcasting with the Implied Volatility Surface Analysis Based on SABR Model

2022 IEEE 20th International Conference on Industrial Informatics (INDIN), 2022
In financial field, predicting the future price of an asset has always been a hot topic. There are mainly two existing methods: One is to model the trend of asset prices in price prediction.
Shaowei Xu, Hongxin Huan, Yuanyuan Qi, Guoxiang Guo, Jerome Yen   +4 more
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Candidate point selection using a self-attention mechanism for generating a smooth volatility surface under the SABR model

Expert Systems with Applications, 2021
Abstract In real markets, generating a smooth implied volatility surface requires an interpolation of the calibrated parameters by using smooth parametric functions. For this interpolation, practitioners do not use all the discrete parameter points but manually select candidate parameter points through time-consuming adjustments (e.g., removing ...
Junkee Jeon, Jungwoo Bae, Changhoon Song, Yongsik Kim, Hyeonuk Kim, Myungjoo Kang, Kyunghyun Park   +6 more
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Probability Distribution in the SABR Model of Stochastic Volatility [PDF]

, 2015
We study the SABR model of stochastic volatility (Wilmott Mag, 2003 [10]). This model is essentially an extension of the local volatility model (Risk 7(1):18–20 [4], Risk 7(2):32–39, 1994 [6]), in which a suitable volatility parameter is assumed to be stochastic.
Patrick S. Hagan, Andrew Lesniewski, Diana E. Woodward   +2 more
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Mass at Zero and Small-Strike Implied Volatility Expansion in the SABR Model

SSRN Electronic Journal, 2015
We study the probability mass at the origin in the SABR stochastic volatility model, and derive several tractable expressions for it, in particular when time becomes small or large. In the uncorrelated case, tedious saddlepoint expansions allow for (semi) closed-form asymptotic formulae.
Archil Gulisashvili, Blanka Horvath, Antoine Jacquier, Antoine Jacquier   +3 more
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