A Review of New Developments in Finance with Deep Learning: Deep Hedging and Deep Calibration
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Hutchinson, James M & Lo, Andrew W & Poggio, Tomaso, 1994.
"A Nonparametric Approach to Pricing and Hedging Derivative Securities via Learning Networks,"
Journal of Finance, American Finance Association, vol. 49(3), pages 851-889, July.
- James M. Hutchinson & Andrew W. Lo & Tomaso Poggio, 1994. "A Nonparametric Approach to Pricing and Hedging Derivative Securities Via Learning Networks," NBER Working Papers 4718, National Bureau of Economic Research, Inc.
- Magnus Wiese & Lianjun Bai & Ben Wood & Hans Buehler, 2019. "Deep Hedging: Learning to Simulate Equity Option Markets," Papers 1911.01700, arXiv.org.
- Johannes Muhle-Karbe & Max Reppen & H. Mete Soner, 2016. "A Primer on Portfolio Choice with Small Transaction Costs," Papers 1612.01302, arXiv.org, revised May 2017.
- Heston, Steven L, 1993. "A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options," The Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 327-343.
- Igor Halperin, 2019. "The QLBS Q-Learner goes NuQLear: fitted Q iteration, inverse RL, and option portfolios," Quantitative Finance, Taylor & Francis Journals, vol. 19(9), pages 1543-1553, September.
- Lucio Fernandez-Arjona & Damir Filipovi'c, 2020. "A machine learning approach to portfolio pricing and risk management for high-dimensional problems," Papers 2004.14149, arXiv.org, revised May 2022.
- A. E. Whalley & P. Wilmott, 1997. "An Asymptotic Analysis of an Optimal Hedging Model for Option Pricing with Transaction Costs," Mathematical Finance, Wiley Blackwell, vol. 7(3), pages 307-324, July.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Lim, Terence & Lo, Andrew W. & Merton, Robert C. & Scholes, Myron S., 2006. "The Derivatives Sourcebook," Foundations and Trends(R) in Finance, now publishers, vol. 1(5–6), pages 365-572, April.
- Roberto Daluiso & Marco Pinciroli & Michele Trapletti & Edoardo Vittori, 2023. "CVA Hedging by Risk-Averse Stochastic-Horizon Reinforcement Learning," Papers 2312.14044, arXiv.org.
- E. Ramos-P'erez & P. J. Alonso-Gonz'alez & J. J. N'u~nez-Vel'azquez, 2020. "Forecasting volatility with a stacked model based on a hybridized Artificial Neural Network," Papers 2006.16383, arXiv.org, revised Aug 2020.
- Xinfu Chen & Min Dai & Wei Jiang & Cong Qin, 2022. "Asymptotic analysis of long‐term investment with two illiquid and correlated assets," Mathematical Finance, Wiley Blackwell, vol. 32(4), pages 1133-1169, October.
- Boris Ter-Avanesov & Homayoon Beigi, 2024. "MLP, XGBoost, KAN, TDNN, and LSTM-GRU Hybrid RNN with Attention for SPX and NDX European Call Option Pricing," Papers 2409.06724, arXiv.org, revised Oct 2024.
- Tseng, Chih-Hsiung & Cheng, Sheng-Tzong & Wang, Yi-Hsien & Peng, Jin-Tang, 2008. "Artificial neural network model of the hybrid EGARCH volatility of the Taiwan stock index option prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(13), pages 3192-3200.
- Ghysels, E. & Harvey, A. & Renault, E., 1995.
"Stochastic Volatility,"
Papers
95.400, Toulouse - GREMAQ.
- Ghysels, E. & Harvey, A. & Renault, E., 1996. "Stochastic Volatility," Cahiers de recherche 9613, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
- GHYSELS, Eric & HARVEY, Andrew & RENAULT, Eric, 1995. "Stochastic Volatility," LIDAM Discussion Papers CORE 1995069, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Ghysels, E. & Harvey, A. & Renault, E., 1996. "Stochastic Volatility," Cahiers de recherche 9613, Universite de Montreal, Departement de sciences economiques.
- Eric Ghysels & Andrew Harvey & Eric Renault, 1995. "Stochastic Volatility," CIRANO Working Papers 95s-49, CIRANO.
- A. Max Reppen & H. Mete Soner & Valentin Tissot-Daguette, 2022. "Deep Stochastic Optimization in Finance," Papers 2205.04604, arXiv.org.
- Shuaiqiang Liu & Cornelis W. Oosterlee & Sander M. Bohte, 2019.
"Pricing Options and Computing Implied Volatilities using Neural Networks,"
Risks, MDPI, vol. 7(1), pages 1-22, February.
- Shuaiqiang Liu & Cornelis W. Oosterlee & Sander M. Bohte, 2019. "Pricing options and computing implied volatilities using neural networks," Papers 1901.08943, arXiv.org, revised Apr 2019.
- Baule, Rainer & Münchhalfen, Patrick & Shkel, David & Tallau, Christian, 2023. "Fair-washing in the market for structured retail products? Voluntary self-regulation versus government regulation," Journal of Banking & Finance, Elsevier, vol. 148(C).
- Eric Jacquier & Robert Jarrow, "undated".
"Model Error in Contingent Claim Models (Dynamic Evaluation),"
Rodney L. White Center for Financial Research Working Papers
07-96, Wharton School Rodney L. White Center for Financial Research.
- Eric Jacquier & Robert Jarrow, "undated". "Model Error in Contingent Claim Models (Dynamic Evaluation)," Rodney L. White Center for Financial Research Working Papers 7-96, Wharton School Rodney L. White Center for Financial Research.
- Eric Jacquier & Robert Jarrow, 1996. "Model Error in Contingent Claim Models Dynamic Evaluation," CIRANO Working Papers 96s-12, CIRANO.
- Weiping Li & Su Chen, 2018. "The Early Exercise Premium In American Options By Using Nonparametric Regressions," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 21(07), pages 1-29, November.
- Minting Zhu & Mancang Wang & Jingyu Wu, 2024. "An Option Pricing Formula for Active Hedging Under Logarithmic Investment Strategy," Mathematics, MDPI, vol. 12(23), pages 1-20, December.
- Ben Hambly & Renyuan Xu & Huining Yang, 2021. "Recent Advances in Reinforcement Learning in Finance," Papers 2112.04553, arXiv.org, revised Feb 2023.
- Jiří Witzany & Milan Fičura, 2023. "Machine Learning Applications to Valuation of Options on Non-liquid Markets," FFA Working Papers 5.001, Prague University of Economics and Business, revised 24 Jan 2023.
- Guo, Jingjun & Kang, Weiyi & Wang, Yubing, 2024. "Multi-perspective option price forecasting combining parametric and non-parametric pricing models with a new dynamic ensemble framework," Technological Forecasting and Social Change, Elsevier, vol. 204(C).
- Johannes Muhle-Karbe & Max Reppen & H. Mete Soner, 2016. "A Primer on Portfolio Choice with Small Transaction Costs," Papers 1612.01302, arXiv.org, revised May 2017.
- A. Max Reppen & H. Mete Soner & Valentin Tissot-Daguette, 2023. "Deep stochastic optimization in finance," Digital Finance, Springer, vol. 5(1), pages 91-111, March.
- Hsuan-Chu Lin & Ren-Raw Chen & Oded Palmon, 2016. "Explaining the volatility smile: non-parametric versus parametric option models," Review of Quantitative Finance and Accounting, Springer, vol. 46(4), pages 907-935, May.
- Daglish, Toby & Neely, Chris, 2008. "Optimal discrete hedging in the Heston Stochastic Volatility Model," Working Paper Series 4007, Victoria University of Wellington, The New Zealand Institute for the Study of Competition and Regulation.
More about this item
Keywords
Financial engineering; Mathematical finance; Derivatives; Hedging; Calibration; Numerical optimization;All these keywords.
JEL classification:
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
- G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
NEP fields
This paper has been announced in the following NEP Reports:- NEP-BIG-2024-08-19 (Big Data)
- NEP-CMP-2024-08-19 (Computational Economics)
- NEP-INV-2024-08-19 (Investment)
- NEP-RMG-2024-08-19 (Risk Management)
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ime:imedps:24-e-02. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Kinken (email available below). General contact details of provider: https://edirc.repec.org/data/imegvjp.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.