IDEAS home Printed from https://ideas.repec.org/r/eee/apmaco/v269y2015icp412-431.html
   My bibliography  Save this item

The Stochastic Grid Bundling Method: Efficient pricing of Bermudan options and their Greeks

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Kathrin Glau & Mirco Mahlstedt & Christian Potz, 2018. "A new approach for American option pricing: The Dynamic Chebyshev method," Papers 1806.05579, arXiv.org.
  2. Kirkby, J. Lars & Nguyen, Dang H. & Nguyen, Duy, 2020. "A general continuous time Markov chain approximation for multi-asset option pricing with systems of correlated diffusions," Applied Mathematics and Computation, Elsevier, vol. 386(C).
  3. Andersson, Kristoffer & Oosterlee, Cornelis W., 2021. "A deep learning approach for computations of exposure profiles for high-dimensional Bermudan options," Applied Mathematics and Computation, Elsevier, vol. 408(C).
  4. Purba Banerjee & Vasudeva Murthy & Shashi Jain, 2024. "Method of Lines for Valuation and Sensitivities of Bermudan Options," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 245-270, January.
  5. Calypso Herrera & Florian Krach & Pierre Ruyssen & Josef Teichmann, 2021. "Optimal Stopping via Randomized Neural Networks," Papers 2104.13669, arXiv.org, revised Dec 2023.
  6. Zhu, Yichen & Escobar-Anel, Marcos, 2022. "Polynomial affine approach to HARA utility maximization with applications to OrnsteinUhlenbeck 4/2 models," Applied Mathematics and Computation, Elsevier, vol. 418(C).
  7. Kathrin Glau & Ricardo Pachon & Christian Potz, 2019. "Speed-up credit exposure calculations for pricing and risk management," Papers 1912.01280, arXiv.org.
  8. Patrik Karlsson & Shashi Jain & Cornelis W. Oosterlee, 2016. "Fast and accurate exercise policies for Bermudan swaptions in the LIBOR market model," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 3(01), pages 1-22, March.
  9. Christian Bender & Nikolaus Schweizer, 2019. "`Regression Anytime' with Brute-Force SVD Truncation," Papers 1908.08264, arXiv.org, revised Oct 2020.
  10. Carlos Esparcia & Elena Ibañez & Francisco Jareño, 2020. "Volatility Timing: Pricing Barrier Options on DAX XETRA Index," Mathematics, MDPI, vol. 8(5), pages 1-25, May.
  11. Rongju Zhang & Nicolas Langrené & Yu Tian & Zili Zhu & Fima Klebaner & Kais Hamza, 2019. "Skewed target range strategy for multiperiod portfolio optimization using a two-stage least squares Monte Carlo method," Post-Print hal-02909342, HAL.
  12. Anastasia Borovykh & Andrea Pascucci & Cornelis W. Oosterlee, 2019. "Efficient Computation of Various Valuation Adjustments Under Local L\'evy Models," Papers 1905.01706, arXiv.org.
  13. Lokeshwar, Vikranth & Bharadwaj, Vikram & Jain, Shashi, 2022. "Explainable neural network for pricing and universal static hedging of contingent claims," Applied Mathematics and Computation, Elsevier, vol. 417(C).
  14. Tang, Kin-Boon & Zheng, Wen-Jie & Lin, Chao-Yang & Lin, Shih-Kuei, 2021. "Valuation of callable accreting interest rate swaps: Least squares Monte-Carlo method under Hull-White interest rate model," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
  15. Qian Feng & Cornelis W. Oosterlee, 2017. "Computing Credit Valuation Adjustment For Bermudan Options With Wrong Way Risk," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(08), pages 1-31, December.
  16. Yichen Zhu & Marcos Escobar-Anel, 2021. "A Neural Network Monte Carlo Approximation for Expected Utility Theory," JRFM, MDPI, vol. 14(7), pages 1-18, July.
  17. Michael Ludkovski & Aditya Maheshwari, 2018. "Simulation Methods for Stochastic Storage Problems: A Statistical Learning Perspective," Papers 1803.11309, arXiv.org.
  18. Rongju Zhang & Nicolas Langren'e & Yu Tian & Zili Zhu & Fima Klebaner & Kais Hamza, 2018. "Local Control Regression: Improving the Least Squares Monte Carlo Method for Portfolio Optimization," Papers 1803.11467, arXiv.org, revised Sep 2018.
  19. Yichen Zhu & Marcos Escobar-Anel & Matt Davison, 2023. "A Polynomial-Affine Approximation for Dynamic Portfolio Choice," Computational Economics, Springer;Society for Computational Economics, vol. 62(3), pages 1177-1213, October.
  20. Karel J. in’t Hout & Jacob Snoeijer, 2021. "Numerical Valuation of American Basket Options via Partial Differential Complementarity Problems," Mathematics, MDPI, vol. 9(13), pages 1-17, June.
  21. Lukas Gonon, 2022. "Deep neural network expressivity for optimal stopping problems," Papers 2210.10443, arXiv.org.
  22. Ludovic Gouden`ege & Andrea Molent & Antonino Zanette, 2018. "Computing Credit Valuation Adjustment solving coupled PIDEs in the Bates model," Papers 1809.05328, arXiv.org.
  23. Andersson, Kristoffer & Oosterlee, Cornelis W., 2021. "Deep learning for CVA computations of large portfolios of financial derivatives," Applied Mathematics and Computation, Elsevier, vol. 409(C).
  24. Fei Cong & Cornelis W. Oosterlee, 2017. "Accurate and Robust Numerical Methods for the Dynamic Portfolio Management Problem," Computational Economics, Springer;Society for Computational Economics, vol. 49(3), pages 433-458, March.
  25. Karel in 't Hout & Jacob Snoeijer, 2021. "Numerical valuation of American basket options via partial differential complementarity problems," Papers 2106.01200, arXiv.org.
  26. Ruimeng Hu, 2019. "Deep Learning for Ranking Response Surfaces with Applications to Optimal Stopping Problems," Papers 1901.03478, arXiv.org, revised Mar 2020.
  27. Sebastian Becker & Patrick Cheridito & Arnulf Jentzen, 2020. "Pricing and Hedging American-Style Options with Deep Learning," JRFM, MDPI, vol. 13(7), pages 1-12, July.
  28. Ivan Guo & Nicolas Langren'e & Jiahao Wu, 2023. "Simultaneous upper and lower bounds of American option prices with hedging via neural networks," Papers 2302.12439, arXiv.org.
  29. Vikranth Lokeshwar & Vikram Bhardawaj & Shashi Jain, 2019. "Neural network for pricing and universal static hedging of contingent claims," Papers 1911.11362, arXiv.org.
  30. Shi, Ruoshi & Zhao, Yanlong & Bao, Ying & Peng, Cheng, 2022. "Sensitivity-based Conditional Value at Risk (SCVaR): An efficient measurement of credit exposure for options," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
  31. Ludovic Goudenège & Andrea Molent & Antonino Zanette, 2020. "Computing credit valuation adjustment solving coupled PIDEs in the Bates model," Computational Management Science, Springer, vol. 17(2), pages 163-178, June.
  32. Purba Banerjee & Vasudeva Murthy & Shashi Jain, 2021. "Method of lines for valuation and sensitivities of Bermudan options," Papers 2112.01287, arXiv.org.
  33. Matt Davison & Marcos Escobar-Anel & Yichen Zhu, 2022. "Optimal market completion through financial derivatives with applications to volatility risk," Papers 2202.08148, arXiv.org.
  34. Pan, Zeyu & Gao, Yin & Yuan, Lin, 2021. "Bermudan options pricing formulas in uncertain financial markets," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.