Mark Joshi

Personal Details

First Name:	Mark
Middle Name:
Last Name:	Joshi
Suffix:
RePEc Short-ID:	pjo106
	[This author has chosen not to make the email address public]
	http://www.markjoshi.com

Affiliation

Department of Economics
Faculty of Business and Economics
University of Melbourne

Melbourne, Australia
http://www.economics.unimelb.edu.au/
RePEc:edi:demelau (more details at EDIRC)

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

1. Jiun Hong Chan and Mark Joshi, 2012. "Optimal Limit Methods for Computing Sensitivities of," Department of Economics - Working Papers Series 1142, The University of Melbourne.

   Cited by:

   1. Frazier, David T. & Oka, Tatsushi & Zhu, Dan, 2019. "Indirect inference with a non-smooth criterion function," Journal of Econometrics, Elsevier, vol. 212(2), pages 623-645.
      • David T. Frazier & Tatsushi Oka & Dan Zhu, 2017. "Indirect Inference with a Non-Smooth Criterion Function," Papers 1708.02365, arXiv.org, revised Jul 2019.
   2. Christian P. Fries, 2018. "Stochastic Algorithmic Differentiation of (Expectations of) Discontinuous Functions (Indicator Functions)," Papers 1811.05741, arXiv.org, revised Nov 2019.

Articles

1. Mark S. Joshi & Dan Zhu, 2016. "Optimal Partial Proxy Method for Computing Gammas of Financial Products with Discontinuous and Angular Payoffs," Applied Mathematical Finance, Taylor & Francis Journals, vol. 23(1), pages 22-56, March.

   Cited by:

   1. Roberto Daluiso, 2023. "Fast and Stable Credit Gamma of CVA," Papers 2311.11672, arXiv.org.
   2. Frazier, David T. & Oka, Tatsushi & Zhu, Dan, 2019. "Indirect inference with a non-smooth criterion function," Journal of Econometrics, Elsevier, vol. 212(2), pages 623-645.
      • David T. Frazier & Tatsushi Oka & Dan Zhu, 2017. "Indirect Inference with a Non-Smooth Criterion Function," Papers 1708.02365, arXiv.org, revised Jul 2019.

2. Joshi, Mark S. & Zhu, Dan, 2016. "The Efficient Computation And The Sensitivity Analysis Of Finite-Time Ruin Probabilities And The Estimation Of Risk-Based Regulatory Capital," ASTIN Bulletin, Cambridge University Press, vol. 46(2), pages 431-467, May.

   Cited by:

   1. Jingchao Li & Bihao Su & Zhenghong Wei & Ciyu Nie, 2022. "A Multinomial Approximation Approach for the Finite Time Survival Probability Under the Markov-modulated Risk Model," Methodology and Computing in Applied Probability, Springer, vol. 24(3), pages 2169-2194, September.

3. Denis Belomestny & Mark Joshi & John Schoenmakers, 2015. "Addendum to: Multilevel dual approach for pricing American style derivatives," Finance and Stochastics, Springer, vol. 19(3), pages 681-684, July.

   Cited by:

   1. Mark S. Joshi, 2016. "Analysing the bias in the primal-dual upper bound method for early exercisable derivatives: bounds, estimation and removal," Quantitative Finance, Taylor & Francis Journals, vol. 16(4), pages 519-533, April.

4. Joshi, Mark & Tang, Robert, 2014. "Effective sub-simulation-free upper bounds for the Monte Carlo pricing of callable derivatives and various improvements to existing methodologies," Journal of Economic Dynamics and Control, Elsevier, vol. 40(C), pages 25-45.

   Cited by:

   1. Ivan Guo & Gregoire Loeper, 2016. "Pricing Bounds for VIX Derivatives via Least Squares Monte Carlo," Papers 1611.00464, arXiv.org.
   2. Nicholas Andrew Yap Swee Guan, 2015. "Regression and Convex Switching System Methods for Stochastic Control Problems with Applications to Multiple-Exercise Options," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 5-2015, January-A.
   3. Ivan Guo & Gregoire Loeper, 2018. "Pricing Bounds for Volatility Derivatives via Duality and Least Squares Monte Carlo," Journal of Optimization Theory and Applications, Springer, vol. 179(2), pages 598-617, November.
   4. Mark S. Joshi, 2016. "Analysing the bias in the primal-dual upper bound method for early exercisable derivatives: bounds, estimation and removal," Quantitative Finance, Taylor & Francis Journals, vol. 16(4), pages 519-533, April.

5. Beveridge, Christopher & Joshi, Mark & Tang, Robert, 2013. "Practical policy iteration: Generic methods for obtaining rapid and tight bounds for Bermudan exotic derivatives using Monte Carlo simulation," Journal of Economic Dynamics and Control, Elsevier, vol. 37(7), pages 1342-1361.

   Cited by:

   1. Christopher Beveridge & Mark Joshi, 2014. "The Efficient Computation Of Prices And Greeks For Callable Range Accruals Using The Displaced-Diffusion Lmm," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 17(01), pages 1-47.
   2. David A. Goldberg & Yilun Chen, 2018. "Polynomial time algorithm for optimal stopping with fixed accuracy," Papers 1807.02227, arXiv.org, revised May 2024.
   3. Christopher Beveridge & Mark Joshi, 2011. "Monte Carlo Bounds for Game Options Including Convertible Bonds," Management Science, INFORMS, vol. 57(5), pages 960-974, May.
   4. Maciej Klimek & Marcin Pitera, 2014. "The least squares method for option pricing revisited," Papers 1404.7438, arXiv.org, revised Nov 2015.
   5. Mark Joshi & Oh Kang Kwon, 2016. "Least Squares Monte Carlo Credit Value Adjustment With Small And Unidirectional Bias," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 19(08), pages 1-16, December.
   6. Wei, Wei & Zhu, Dan, 2022. "Generic improvements to least squares monte carlo methods with applications to optimal stopping problems," European Journal of Operational Research, Elsevier, vol. 298(3), pages 1132-1144.
   7. Nicholas Andrew Yap Swee Guan, 2015. "Regression and Convex Switching System Methods for Stochastic Control Problems with Applications to Multiple-Exercise Options," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 5-2015, January-A.
   8. Joshi, Mark & Tang, Robert, 2014. "Effective sub-simulation-free upper bounds for the Monte Carlo pricing of callable derivatives and various improvements to existing methodologies," Journal of Economic Dynamics and Control, Elsevier, vol. 40(C), pages 25-45.
   9. Jeechul Woo & Chenru Liu & Jaehyuk Choi, 2024. "Leave‐one‐out least squares Monte Carlo algorithm for pricing Bermudan options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(8), pages 1404-1428, August.
   10. Mark S. Joshi, 2016. "Analysing the bias in the primal-dual upper bound method for early exercisable derivatives: bounds, estimation and removal," Quantitative Finance, Taylor & Francis Journals, vol. 16(4), pages 519-533, April.

6. Ting Chen & Mark Joshi, 2012. "Truncation and acceleration of the Tian tree for the pricing of American put options," Quantitative Finance, Taylor & Francis Journals, vol. 12(11), pages 1695-1708, November.

   Cited by:

   1. Guillaume Leduc & Merima Nurkanovic Hot, 2020. "Joshi’s Split Tree for Option Pricing," Risks, MDPI, vol. 8(3), pages 1-26, August.
   2. Qianru Shang & Brian Byrne, 2021. "American option pricing: Optimal Lattice models and multidimensional efficiency tests," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(4), pages 514-535, April.

7. Mark Joshi & Mike Staunton, 2012. "On the analytical/numerical pricing of American put options against binomial tree prices," Quantitative Finance, Taylor & Francis Journals, vol. 12(1), pages 17-20, December.

   Cited by:

   1. Guillaume Leduc & Merima Nurkanovic Hot, 2020. "Joshi’s Split Tree for Option Pricing," Risks, MDPI, vol. 8(3), pages 1-26, August.

8. Ferdinando Ametrano & Mark Joshi, 2011. "Smooth simultaneous calibration of the LMM to caplets and co-terminal swaptions," Quantitative Finance, Taylor & Francis Journals, vol. 11(4), pages 547-558.

   Cited by:

   1. Beveridge, Christopher & Joshi, Mark & Tang, Robert, 2013. "Practical policy iteration: Generic methods for obtaining rapid and tight bounds for Bermudan exotic derivatives using Monte Carlo simulation," Journal of Economic Dynamics and Control, Elsevier, vol. 37(7), pages 1342-1361.

9. Joshi, Mark & Yang, Chao, 2011. "Fast delta computations in the swap-rate market model," Journal of Economic Dynamics and Control, Elsevier, vol. 35(5), pages 764-775, May.

   Cited by:

   1. Jos'e Da Fonseca & Alessandro Gnoatto & Martino Grasselli, 2012. "A flexible matrix Libor model with smiles," Papers 1203.4786, arXiv.org.
      • Da Fonseca, José & Gnoatto, Alessandro & Grasselli, Martino, 2013. "A flexible matrix Libor model with smiles," Journal of Economic Dynamics and Control, Elsevier, vol. 37(4), pages 774-793.
   2. Cristian Homescu, 2011. "Adjoints and Automatic (Algorithmic) Differentiation in Computational Finance," Papers 1107.1831, arXiv.org.
   3. Joshi, Mark & Tang, Robert, 2014. "Effective sub-simulation-free upper bounds for the Monte Carlo pricing of callable derivatives and various improvements to existing methodologies," Journal of Economic Dynamics and Control, Elsevier, vol. 40(C), pages 25-45.
   4. Jiun Hong Chan and Mark Joshi, 2012. "Optimal Limit Methods for Computing Sensitivities of," Department of Economics - Working Papers Series 1142, The University of Melbourne.

10. Christopher Beveridge & Mark Joshi, 2011. "Monte Carlo Bounds for Game Options Including Convertible Bonds," Management Science, INFORMS, vol. 57(5), pages 960-974, May.

    Cited by:

    1. Wong, Tat Wing & Fung, Ka Wai Terence & Leung, Kwai Sun, 2020. "Strategic bank closure and deposit insurance valuation," European Journal of Operational Research, Elsevier, vol. 285(1), pages 96-105.
    2. Christian Bender & Christian Gärtner & Nikolaus Schweizer, 2018. "Pathwise Dynamic Programming," Mathematics of Operations Research, INFORMS, vol. 43(3), pages 965-965, August.
    3. Yu Liu & Gongqiu Zhang, 2024. "Valuation Model of Chinese Convertible Bonds Based on Monte Carlo Simulation," Papers 2409.06496, arXiv.org, revised Nov 2024.

11. Joshi, Mark & Yang, Chao, 2011. "Efficient greek estimation in generic swap-rate market models," Algorithmic Finance, IOS Press, vol. 1(1), pages 17-33.

    Cited by:

    1. Joshi, Mark & Yang, Chao, 2011. "Fast delta computations in the swap-rate market model," Journal of Economic Dynamics and Control, Elsevier, vol. 35(5), pages 764-775, May.
    2. Cristian Homescu, 2011. "Adjoints and Automatic (Algorithmic) Differentiation in Computational Finance," Papers 1107.1831, arXiv.org.
    3. Mark Joshi & Chao Yang, 2010. "Fast And Accurate Pricing And Hedging Of Long-Dated Cms Spread Options," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 13(06), pages 839-865.

12. Joshi, Mark & Pitt, David, 2010. "Fast Sensitivity Computations for Monte Carlo Valuation of Pension Funds," ASTIN Bulletin, Cambridge University Press, vol. 40(2), pages 655-667, November.

    Cited by:

    1. Cristian Homescu, 2011. "Adjoints and Automatic (Algorithmic) Differentiation in Computational Finance," Papers 1107.1831, arXiv.org.

13. Jiun Hong Chan & Mark Joshi & Robert Tang & Chao Yang, 2009. "Trinomial or binomial: Accelerating American put option price on trees," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 29(9), pages 826-839, September.

    Cited by:

    1. Jin, Xing & Li, Xun & Tan, Hwee Huat & Wu, Zhenyu, 2013. "A computationally efficient state-space partitioning approach to pricing high-dimensional American options via dimension reduction," European Journal of Operational Research, Elsevier, vol. 231(2), pages 362-370.
    2. Guillaume Leduc & Merima Nurkanovic Hot, 2020. "Joshi’s Split Tree for Option Pricing," Risks, MDPI, vol. 8(3), pages 1-26, August.
    3. Ting Chen & Mark Joshi, 2012. "Truncation and acceleration of the Tian tree for the pricing of American put options," Quantitative Finance, Taylor & Francis Journals, vol. 12(11), pages 1695-1708, November.
    4. J. X. Jiang & R. H. Liu & D. Nguyen, 2016. "A Recombining Tree Method For Option Pricing With State-Dependent Switching Rates," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 19(02), pages 1-26, March.
    5. Dasheng Ji & B. Brorsen, 2011. "A recombining lattice option pricing model that relaxes the assumption of lognormality," Review of Derivatives Research, Springer, vol. 14(3), pages 349-367, October.
    6. Luca Vincenzo Ballestra, 2021. "Enhancing finite difference approximations for double barrier options: mesh optimization and repeated Richardson extrapolation," Computational Management Science, Springer, vol. 18(2), pages 239-263, June.

14. Mark Joshi, 2009. "Achieving smooth asymptotics for the prices of European options in binomial trees," Quantitative Finance, Taylor & Francis Journals, vol. 9(2), pages 171-176.

    Cited by:

    1. Yury Lebedev & Arunava Banerjee, 2024. "Gaussian Recombining Split Tree," Papers 2405.16333, arXiv.org.
    2. Guillaume Leduc & Merima Nurkanovic Hot, 2020. "Joshi’s Split Tree for Option Pricing," Risks, MDPI, vol. 8(3), pages 1-26, August.
    3. Dong Zou & Pu Gong, 2017. "A Lattice Framework with Smooth Convergence for Pricing Real Estate Derivatives with Stochastic Interest Rate," The Journal of Real Estate Finance and Economics, Springer, vol. 55(2), pages 242-263, August.
    4. Kyoung-Sook Moon & Hongjoong Kim, 2013. "A multi-dimensional local average lattice method for multi-asset models," Quantitative Finance, Taylor & Francis Journals, vol. 13(6), pages 873-884, May.

15. Mark Joshi & Alan Stacey, 2008. "New and robust drift approximations for the LIBOR market model," Quantitative Finance, Taylor & Francis Journals, vol. 8(4), pages 427-434.

    Cited by:

    1. Antonis Papapantoleon & John Schoenmakers & David Skovmand, 2011. "Efficient and accurate log-L\'evy approximations to L\'evy driven LIBOR models," Papers 1106.0866, arXiv.org, revised Jan 2012.
    2. Xu Chenglong & Guan Wei & Liang Yijuan, 2015. "A Comparison of Control Variate Methods for Pricing Interest Rate Derivatives in the LIBOR Market Model," Journal of Systems Science and Information, De Gruyter, vol. 3(1), pages 48-58, February.
    3. Nicola Bruti-Liberati & Eckhard Platen, 2006. "On Weak Predictor-Corrector Schemes for Jump-Diffusion Processes in Finance," Research Paper Series 179, Quantitative Finance Research Centre, University of Technology, Sydney.
    4. Antonis Papapantoleon, 2009. "Old and new approaches to LIBOR modeling," Papers 0910.4941, arXiv.org, revised Apr 2010.
    5. Antonis Papapantoleon & John Schoenmakers & David Skovmand, 2011. "Efficient and accurate log-Lévi approximations to Lévi driven LIBOR models," CREATES Research Papers 2011-22, Department of Economics and Business Economics, Aarhus University.
    6. Antonis Papapantoleon & David Skovmand, 2010. "Numerical methods for the L\'evy LIBOR model," Papers 1006.3340, arXiv.org.
    7. Antonis Papapantoleon & David Skovmand, 2010. "Picard Approximation of Stochastic Differential Equations and Application to Libor Models," CREATES Research Papers 2010-40, Department of Economics and Business Economics, Aarhus University.
    8. Jaka Gogala & Joanne E. Kennedy, 2017. "CLASSIFICATION OF TWO- AND THREE-FACTOR TIME-HOMOGENEOUS SEPARABLE LMMs," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(02), pages 1-44, March.
    9. Antonis Papapantoleon & Maria Siopacha, 2009. "Strong Taylor approximation of stochastic differential equations and application to the L\'evy LIBOR model," Papers 0906.5581, arXiv.org, revised Oct 2010.
    10. Antonis Papapantoleon & David Skovmand, 2010. "Picard approximation of stochastic differential equations and application to LIBOR models," Papers 1007.3362, arXiv.org, revised Jul 2011.
    11. Henrard, Marc, 2007. "Skewed Libor Market Model and Gaussian HJM explicit approaches to rolled deposit options," MPRA Paper 1534, University Library of Munich, Germany.
    12. Antonis Papapantoleon, 2010. "Old and new approaches to LIBOR modeling," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 64(3), pages 257-275, August.
    13. Nicola Bruti-Liberati, 2007. "Numerical Solution of Stochastic Differential Equations with Jumps in Finance," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2007, January-A.

16. Mark S. Joshi, 2007. "A Simple Derivation of and Improvements to Jamshidian's and Rogers' Upper Bound Methods for Bermudan Options," Applied Mathematical Finance, Taylor & Francis Journals, vol. 14(3), pages 197-205.

    Cited by:

    1. Christopher Beveridge & Mark Joshi, 2011. "Monte Carlo Bounds for Game Options Including Convertible Bonds," Management Science, INFORMS, vol. 57(5), pages 960-974, May.
    2. Mark Broadie & Menghui Cao, 2008. "Improved lower and upper bound algorithms for pricing American options by simulation," Quantitative Finance, Taylor & Francis Journals, vol. 8(8), pages 845-861.
    3. Kian Guan Lim, 2021. "Bermudan option in Singapore Savings Bonds," Review of Derivatives Research, Springer, vol. 24(1), pages 31-54, April.
    4. Nicholas Andrew Yap Swee Guan, 2015. "Regression and Convex Switching System Methods for Stochastic Control Problems with Applications to Multiple-Exercise Options," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 5-2015, January-A.
    5. Joshi, Mark & Tang, Robert, 2014. "Effective sub-simulation-free upper bounds for the Monte Carlo pricing of callable derivatives and various improvements to existing methodologies," Journal of Economic Dynamics and Control, Elsevier, vol. 40(C), pages 25-45.
    6. Ferdinando Ametrano & Mark Joshi, 2011. "Smooth simultaneous calibration of the LMM to caplets and co-terminal swaptions," Quantitative Finance, Taylor & Francis Journals, vol. 11(4), pages 547-558.
    7. Mark S. Joshi, 2016. "Analysing the bias in the primal-dual upper bound method for early exercisable derivatives: bounds, estimation and removal," Quantitative Finance, Taylor & Francis Journals, vol. 16(4), pages 519-533, April.
    8. Denis Belomestny & John Schoenmakers & Fabian Dickmann, 2013. "Multilevel dual approach for pricing American style derivatives," Finance and Stochastics, Springer, vol. 17(4), pages 717-742, October.

17. Joshi, Mark S. & Liesch, Lorenzo, 2007. "Effective Implementation of Generic Market Models," ASTIN Bulletin, Cambridge University Press, vol. 37(2), pages 453-473, November.

    Cited by:

    1. Joshi, Mark & Yang, Chao, 2011. "Fast delta computations in the swap-rate market model," Journal of Economic Dynamics and Control, Elsevier, vol. 35(5), pages 764-775, May.
    2. Ferdinando Ametrano & Mark Joshi, 2011. "Smooth simultaneous calibration of the LMM to caplets and co-terminal swaptions," Quantitative Finance, Taylor & Francis Journals, vol. 11(4), pages 547-558.

18. Mark Joshi & Dherminder Kainth, 2004. "Rapid and accurate development of prices and Greeks for nth to default credit swaps in the Li model," Quantitative Finance, Taylor & Francis Journals, vol. 4(3), pages 266-275.

    Cited by:

    1. Guangwu Liu, 2015. "Simulating Risk Contributions of Credit Portfolios," Operations Research, INFORMS, vol. 63(1), pages 104-121, February.
    2. Fathi, Abid & Nader, Naifar, 2007. "Price Calibration of basket default swap: Evidence from Japanese market," MPRA Paper 6013, University Library of Munich, Germany.
    3. Grundke, Peter, 2009. "Importance sampling for integrated market and credit portfolio models," European Journal of Operational Research, Elsevier, vol. 194(1), pages 206-226, April.
    4. Choe, Geon Ho & Jang, Hyun Jin, 2011. "Efficient algorithms for basket default swap pricing with multivariate Archimedean copulas," Insurance: Mathematics and Economics, Elsevier, vol. 48(2), pages 205-213, March.
    5. Zhiyong Chen & Paul Glasserman, 2008. "Fast Pricing of Basket Default Swaps," Operations Research, INFORMS, vol. 56(2), pages 286-303, April.
    6. Huei-Wen Teng & Cheng-Der Fuh & Chun-Chieh Chen, 2016. "On an automatic and optimal importance sampling approach with applications in finance," Quantitative Finance, Taylor & Francis Journals, vol. 16(8), pages 1259-1271, August.
    7. Lei, Lei & Peng, Yijie & Fu, Michael C. & Hu, Jian-Qiang, 2023. "Copula sensitivity analysis for portfolio credit derivatives," European Journal of Operational Research, Elsevier, vol. 308(1), pages 455-466.
    8. Ping Li & Ze†Zheng Li, 2015. "Change Analysis for the Dependence Structure and Dynamic Pricing of Basket Default Swaps," European Financial Management, European Financial Management Association, vol. 21(4), pages 646-671, September.
    9. Po-Cheng Wu, 2011. "Multi-Factor Approach For Pricing Basket Credit Linked Notes Under Issuer Default Risk," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 5(4), pages 115-128.

19. Mark Joshi & Riccardo Rebonato, 2003. "A displaced-diffusion stochastic volatility LIBOR market model: motivation, definition and implementation," Quantitative Finance, Taylor & Francis Journals, vol. 3(6), pages 458-469.

    Cited by:

    1. L. Steinruecke & R. Zagst & A. Swishchuk, 2015. "The Markov-switching jump diffusion LIBOR market model," Quantitative Finance, Taylor & Francis Journals, vol. 15(3), pages 455-476, March.
    2. Pan Tang & Belal E. Baaquie & Xin Du & Ying Zhang, 2016. "Linearized Hamiltonian of the LIBOR market model: analytical and empirical results," Applied Economics, Taylor & Francis Journals, vol. 48(10), pages 878-891, February.
    3. Jaehyuk Choi & Minsuk Kwak & Chyng Wen Tee & Yumeng Wang, 2021. "A Black-Scholes user's guide to the Bachelier model," Papers 2104.08686, arXiv.org, revised Feb 2022.
    4. Jaehyuk Choi & Minsuk Kwak & Chyng Wen Tee & Yumeng Wang, 2022. "A Black–Scholes user's guide to the Bachelier model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(5), pages 959-980, May.
    5. Sascha Desmettre & Simon Hochgerner & Sanela Omerovic & Stefan Thonhauser, 2021. "A mean-field extension of the LIBOR market model," Papers 2109.10779, arXiv.org.
    6. Dariusz Gatarek & Juliusz Jabłecki, 2021. "Between Scylla and Charybdis: The Bermudan Swaptions Pricing Odyssey," Mathematics, MDPI, vol. 9(2), pages 1-32, January.
    7. Zhanyu Chen & Kai Zhang & Hongbiao Zhao, 2022. "A Skellam market model for loan prime rate options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(3), pages 525-551, March.
    8. Fabrice Borel-Mathurin & Nicole El Karoui & Stéphane Loisel & Julien Vedani, 2020. "Locality in time of the European insurance regulation "risk-neutral" valuation framework, a pre-and post-Covid analysis and further developments," Working Papers hal-02905181, HAL.
    9. Riccardo Rebonato, 2006. "Forward-Rate Volatilities And The Swaption Matrix: Why Neither Time-Homogeneity Nor Time-Dependence Are Enough," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 9(05), pages 705-746.
    10. Jeechul Woo & Chenru Liu & Jaehyuk Choi, 2024. "Leave‐one‐out least squares Monte Carlo algorithm for pricing Bermudan options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(8), pages 1404-1428, August.
    11. Roger Lee & Dan Wang, 2012. "Displaced lognormal volatility skews: analysis and applications to stochastic volatility simulations," Annals of Finance, Springer, vol. 8(2), pages 159-181, May.
    12. Fries, Christian P. & Nigbur, Tobias & Seeger, Norman, 2017. "Displaced relative changes in historical simulation: Application to risk measures of interest rates with phases of negative rates," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 175-198.
    13. A. M. Ferreiro & J. A. Garc'ia & J. G. L'opez-Salas & C. V'azquez, 2024. "SABR/LIBOR market models: pricing and calibration for some interest rate derivatives," Papers 2408.01470, arXiv.org.
    14. P. Karlsson & K. F. Pilz & E. Schlögl, 2017. "Calibrating a market model with stochastic volatility to commodity and interest rate risk," Quantitative Finance, Taylor & Francis Journals, vol. 17(6), pages 907-925, June.

20. Mark Joshi & Jochen Theis, 2002. "Bounding Bermudan swaptions in a swap-rate market model," Quantitative Finance, Taylor & Francis Journals, vol. 2(5), pages 370-377.

    Cited by:

    1. Raoul Pietersz & Antoon Pelsser, 2005. "Risk Managing Bermudan Swaptions in the Libor BGM Model," Finance 0502004, University Library of Munich, Germany.
       • Pietersz, R. & Pelsser, A.A.J., 2003. "Risk managing bermudan swaptions in the libor BGM model," Econometric Institute Research Papers EI 2003-33, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Pietersz, R. & van Regenmortel, M., 2005. "Generic Market Models," ERIM Report Series Research in Management ERS-2005-010-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
       • Raoul Pietersz & Marcel Regenmortel, 2006. "Generic market models," Finance and Stochastics, Springer, vol. 10(4), pages 507-528, December.
       • Raoul Pietersz & Marcel van Regenmortel, 2005. "Generic Market Models," Finance 0502009, University Library of Munich, Germany.
    3. Jensen, Malene Shin & Svenstrup, Mikkel, 2002. "Efficient Control Variates and Strategies for Bermudan Swaptions in a Libor Market Model," Finance Working Papers 02-23, University of Aarhus, Aarhus School of Business, Department of Business Studies.
    4. John Schoenmakers & Junbo Huang & Jianing Zhang, 2011. "Optimal dual martingales, their analysis and application to new algorithms for Bermudan products," Papers 1111.6038, arXiv.org, revised Feb 2012.
    5. Farshid Jamshidian, 2004. "Numeraire-invariant option pricing and american, bermudan, trigger stream rollover (v1.6)," Finance 0407015, University Library of Munich, Germany.
    6. Riccardo Rebonato, 2006. "Forward-Rate Volatilities And The Swaption Matrix: Why Neither Time-Homogeneity Nor Time-Dependence Are Enough," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 9(05), pages 705-746.
    7. Joshi, Mark & Tang, Robert, 2014. "Effective sub-simulation-free upper bounds for the Monte Carlo pricing of callable derivatives and various improvements to existing methodologies," Journal of Economic Dynamics and Control, Elsevier, vol. 40(C), pages 25-45.
    8. Ferdinando Ametrano & Mark Joshi, 2011. "Smooth simultaneous calibration of the LMM to caplets and co-terminal swaptions," Quantitative Finance, Taylor & Francis Journals, vol. 11(4), pages 547-558.
    9. Phelim P. Boyle & Adam W. Kolkiewicz & Ken Seng Tan, 2013. "Pricing Bermudan options using low-discrepancy mesh methods," Quantitative Finance, Taylor & Francis Journals, vol. 13(6), pages 841-860, May.

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1. NEP-CMP: Computational Economics (1) 2012-07-23

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