Option pricing under sub-mixed fractional Brownian motion based on time-varying implied volatility using intelligent algorithms
Author:
Publisher
Springer Science and Business Media LLC
Subject
Geometry and Topology,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s00500-023-08647-2.pdf
Reference51 articles.
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2. Apley DW, Zhu J (2020) Visualizing the effects of predictor variables in black box supervised learning models. J R Stat Soc Ser B (stat Methodol) 82(4):1059–1086. https://doi.org/10.1111/rssb.12377
3. Araneda AA, Bertschinger N (2021) The sub-fractional CEV model. Phys A Stat Mech Appl 573:125974. https://doi.org/10.1016/j.physa.2021.125974
4. Audrino F, Colangelo D (2010) Semi-parametric forecasts of the implied volatility surface using regression trees. Stat Comput 20(4):421–434. https://doi.org/10.1007/s11222-009-9134-y
5. Bandi FM, Russell JR, Yang C (2008) Realized volatility forecasting and option pricing. J Econom 147(1):34–46. https://doi.org/10.1016/j.jeconom.2008.09.002
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