Results 71 to 80 of about 1,033 (104)

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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Latent profiling of five-dimensional psychological resilience across generations: a deep clustering and behavioural divergence analysis in pre-conflict Iran. [PDF]

Front Psychiatry
Shakouri Youvalari T, Zaim Gökbay I.
europepmc   +1 more source

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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.
See-Woo Kim, Jeong-Hoon Kim
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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 ...
Hyeonuk Kim, Kyunghyun Park, Junkee Jeon, Changhoon Song, Jungwoo Bae, Yongsik Kim, Myungjoo Kang   +6 more
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A General Valuation Framework for SABR and Stochastic Local Volatility Models

SIAM Journal on Financial Mathematics, 2018
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Cui, Zhenyu, Kirkby, J. Lars, Nguyen, Duy   +2 more
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SABR: A Stochastic Volatility Model in Practice

2019
The Black and Scholes model (BS) assumes that the volatility of an asset is constant over the trading period. As a result, BS returns a flat volatility surface. This assumption fails to capture the asset’s volatility dynamics (smile), which is particularly important if we want to price complex derivatives.
Bogatyreva, Natalya S., Grandez, Rodrigo, Rodríguez Apolinar, Sergio, Soldevilla, Abraham   +3 more
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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.
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Efficient simulation of generalized SABR and stochastic local volatility models based on Markov chain approximations

European Journal of Operational Research, 2020
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhenyu Cui, J. Lars Kirkby, Duy Nguyen
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Probability Distribution in the SABR Model of Stochastic Volatility

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 Hagan, Andrew Lesniewski, Diana Woodward   +2 more
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