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The Importance of the Loss Function in Option Valuation

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Cited by:

  1. Hui Chen & Antoine Didisheim & Simon Scheidegger, 2021. "Deep Structural Estimation: With an Application to Option Pricing," Papers 2102.09209, arXiv.org.
  2. Cui, Yiran & del Baño Rollin, Sebastian & Germano, Guido, 2017. "Full and fast calibration of the Heston stochastic volatility model," European Journal of Operational Research, Elsevier, vol. 263(2), pages 625-638.
  3. Jarrow, Robert & Kwok, Simon Sai Man, 2015. "Specification tests of calibrated option pricing models," Journal of Econometrics, Elsevier, vol. 189(2), pages 397-414.
  4. Jiawang Nie & Suhan Zhong, 2023. "Loss functions for finite sets," Computational Optimization and Applications, Springer, vol. 84(2), pages 421-447, March.
  5. Horatio Cuesdeanu & Jens Carsten Jackwerth, 2018. "The pricing kernel puzzle in forward looking data," Review of Derivatives Research, Springer, vol. 21(3), pages 253-276, October.
  6. Shackleton, Mark B. & Taylor, Stephen J. & Yu, Peng, 2010. "A multi-horizon comparison of density forecasts for the S&P 500 using index returns and option prices," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2678-2693, November.
  7. Janis Bauer & Holger Fink & Eva Stoller, 2020. "Are Issuer Margins Fairly Stated? Evidence from the Issuer Estimated Value for Retail Structured Products," Forecasting, MDPI, vol. 2(4), pages 1-23, September.
  8. Andreou, Panayiotis C. & Charalambous, Chris & Martzoukos, Spiros H., 2010. "Generalized parameter functions for option pricing," Journal of Banking & Finance, Elsevier, vol. 34(3), pages 633-646, March.
  9. Bernales, Alejandro & Guidolin, Massimo, 2014. "Can we forecast the implied volatility surface dynamics of equity options? Predictability and economic value tests," Journal of Banking & Finance, Elsevier, vol. 46(C), pages 326-342.
  10. Yushan Yang & Nuoya Gong & Keying Xie & Qingfei Liu, 2022. "Predicting Gasoline Vehicle Fuel Consumption in Energy and Environmental Impact Based on Machine Learning and Multidimensional Big Data," Energies, MDPI, vol. 15(5), pages 1-17, February.
  11. Thibaut Moyaert & Mikael Petitjean, 2011. "The performance of popular stochastic volatility option pricing models during the subprime crisis," Applied Financial Economics, Taylor & Francis Journals, vol. 21(14), pages 1059-1068.
  12. Back, Janis & Prokopczuk, Marcel & Rudolf, Markus, 2013. "Seasonality and the valuation of commodity options," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 273-290.
  13. repec:qut:auncer:2012_11 is not listed on IDEAS
  14. Cristian Homescu, 2011. "Implied Volatility Surface: Construction Methodologies and Characteristics," Papers 1107.1834, arXiv.org.
  15. Christoffersen, Peter & Jacobs, Kris & Chang, Bo Young, 2013. "Forecasting with Option-Implied Information," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 581-656, Elsevier.
  16. Mehrdoust, Farshid & Noorani, Idin & Kanniainen, Juho, 2024. "Valuation of option price in commodity markets described by a Markov-switching model: A case study of WTI crude oil market," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 215(C), pages 228-269.
  17. Peter Christoffersen & Kris Jacobs, 2004. "Which GARCH Model for Option Valuation?," Management Science, INFORMS, vol. 50(9), pages 1204-1221, September.
  18. Patton, Andrew J. & Timmermann, Allan, 2007. "Properties of optimal forecasts under asymmetric loss and nonlinearity," Journal of Econometrics, Elsevier, vol. 140(2), pages 884-918, October.
  19. Konstantinos Skindilias & Chia Lo, 2015. "Local volatility calibration during turbulent periods," Review of Quantitative Finance and Accounting, Springer, vol. 44(3), pages 425-444, April.
  20. Corsi, Fulvio & Fusari, Nicola & La Vecchia, Davide, 2013. "Realizing smiles: Options pricing with realized volatility," Journal of Financial Economics, Elsevier, vol. 107(2), pages 284-304.
  21. Patton, Andrew J., 2011. "Volatility forecast comparison using imperfect volatility proxies," Journal of Econometrics, Elsevier, vol. 160(1), pages 246-256, January.
  22. Hui Chen & Antoine Didisheim & Simon Scheidegger, 2021. "Deep Structural Estimation:With an Application to Option Pricing," Cahiers de Recherches Economiques du Département d'économie 21.14, Université de Lausanne, Faculté des HEC, Département d’économie.
  23. Le, Van & Zurbruegg, Ralf, 2014. "Forecasting option smile dynamics," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 32-45.
  24. Isabella Yunfei Zeng & Shiqi Tan & Jianliang Xiong & Xuesong Ding & Yawen Li & Tian Wu, 2021. "Estimation of Real-World Fuel Consumption Rate of Light-Duty Vehicles Based on the Records Reported by Vehicle Owners," Energies, MDPI, vol. 14(23), pages 1-19, November.
  25. Jitka Hilliard & Wei Li, 2014. "Volatilities implied by price changes in the S&P 500 options and futures contracts," Review of Quantitative Finance and Accounting, Springer, vol. 42(4), pages 599-626, May.
  26. Sang Byung Seo & Jessica A. Wachter, 2019. "Option Prices in a Model with Stochastic Disaster Risk," Management Science, INFORMS, vol. 65(8), pages 3449-3469, August.
  27. Cosma, Antonio & Galluccio, Stefano & Pederzoli, Paola & Scaillet, Olivier, 2020. "Early Exercise Decision in American Options with Dividends, Stochastic Volatility, and Jumps," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 55(1), pages 331-356, February.
  28. Torben G. Andersen & Nicola Fusari & Viktor Todorov, 2015. "Parametric Inference and Dynamic State Recovery From Option Panels," Econometrica, Econometric Society, vol. 83(3), pages 1081-1145, May.
  29. Sadayuki Ono, 2007. "Option Pricing under Stochastic Volatility and Trading Volume," Discussion Papers 07/05, Department of Economics, University of York.
  30. Cherif Guermat & Richard D. F. Harris, 2006. "Bias in the estimation of non-linear transformations of the integrated variance of returns," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(7), pages 481-494.
  31. Mencía, Javier & Sentana, Enrique, 2013. "Valuation of VIX derivatives," Journal of Financial Economics, Elsevier, vol. 108(2), pages 367-391.
  32. Thorsten Lehnert & Gildas Blanchard & Dennis Bams, 2014. "Evaluating Option Pricing Model Performance Using Model Uncertainty," LSF Research Working Paper Series 14-06, Luxembourg School of Finance, University of Luxembourg.
  33. Peter Christoffersen & Kris Jacobs & Karim Mimouni, 2007. "Models for S&P500 Dynamics: Evidence from Realized Volatility, Daily Returns, and Option Prices," CREATES Research Papers 2007-37, Department of Economics and Business Economics, Aarhus University.
  34. Carol Alexander & Andreas Kaeck, 2012. "Does model fit matter for hedging? Evidence from FTSE 100 options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 32(7), pages 609-638, July.
  35. Hansen, Peter Reinhard & Dumitrescu, Elena-Ivona, 2022. "How should parameter estimation be tailored to the objective?," Journal of Econometrics, Elsevier, vol. 230(2), pages 535-558.
  36. Claudia Yeap & Simon S Kwok & S T Boris Choy, 2018. "A Flexible Generalized Hyperbolic Option Pricing Model and Its Special Cases," Journal of Financial Econometrics, Oxford University Press, vol. 16(3), pages 425-460.
  37. Sang Byung Seo & Jessica A. Wachter, 2013. "Option Prices in a Model with Stochastic Disaster Risk," NBER Working Papers 19611, National Bureau of Economic Research, Inc.
  38. Mahringer, Steffen & Prokopczuk, Marcel, 2015. "An empirical model comparison for valuing crack spread options," Energy Economics, Elsevier, vol. 51(C), pages 177-187.
  39. Pascal François & Lars Stentoft, 2021. "Smile‐implied hedging with volatility risk," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(8), pages 1220-1240, August.
  40. Wolff, Christian & Bams, Dennis & Lehnert, Thorsten, 2005. "Loss Functions in Option Valuation: A Framework for Model Selection," CEPR Discussion Papers 4960, C.E.P.R. Discussion Papers.
  41. Carol Alexander & Alexander Rubinov & Markus Kalepky & Stamatis Leontsinis, 2012. "Regime‐dependent smile‐adjusted delta hedging," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 32(3), pages 203-229, March.
  42. Antonio Cosma & Stefano Galluccio & Paola Pederzoli & O. Scaillet, 2012. "Valuing American Options Using Fast Recursive Projections," Swiss Finance Institute Research Paper Series 12-26, Swiss Finance Institute.
  43. Hilliard, Jitka, 2013. "Testing Greeks and price changes in the S&P 500 options and futures contract: A regression analysis," International Review of Financial Analysis, Elsevier, vol. 26(C), pages 51-58.
  44. Peter Christoffersen & Steven Heston & Kris Jacobs, 2009. "The Shape and Term Structure of the Index Option Smirk: Why Multifactor Stochastic Volatility Models Work So Well," Management Science, INFORMS, vol. 55(12), pages 1914-1932, December.
  45. Elena Andreou & Constantinos Kourouyiannis & Andros Kourtellos, 2012. "Volatility Forecast Combinations using Asymmetric Loss Functions," University of Cyprus Working Papers in Economics 07-2012, University of Cyprus Department of Economics.
  46. Yun Yin & Peter G. Moffatt, 2019. "Correcting the Bias in the Practitioner Black-Scholes Method," JRFM, MDPI, vol. 12(4), pages 1-12, September.
  47. Kaeck, Andreas, 2013. "Asymmetry in the jump-size distribution of the S&P 500: Evidence from equity and option markets," Journal of Economic Dynamics and Control, Elsevier, vol. 37(9), pages 1872-1888.
  48. Sílvia Gonçalves & Massimo Guidolin, 2006. "Predictable Dynamics in the S&P 500 Index Options Implied Volatility Surface," The Journal of Business, University of Chicago Press, vol. 79(3), pages 1591-1636, May.
  49. Kaeck, Andreas & Seeger, Norman J., 2020. "VIX derivatives, hedging and vol-of-vol risk," European Journal of Operational Research, Elsevier, vol. 283(2), pages 767-782.
  50. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2021. "Cross-validated covariance estimators for high-dimensional minimum-variance portfolios," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 35(3), pages 309-352, September.
  51. Liu, Xiaoquan & Cao, Yi & Ma, Chenghu & Shen, Liya, 2019. "Wavelet-based option pricing: An empirical study," European Journal of Operational Research, Elsevier, vol. 272(3), pages 1132-1142.
  52. Tristan Guillaume, 2008. "Making the best of best-of," Review of Derivatives Research, Springer, vol. 11(1), pages 1-39, March.
  53. Anatolyev, Stanislav, 2009. "Dynamic modeling under linear-exponential loss," Economic Modelling, Elsevier, vol. 26(1), pages 82-89, January.
  54. Tony S. Wirjanto & Anyi Zhu, 2018. "Implied volatility surfaces during the period of global financial crisis," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 5(01), pages 1-50, March.
  55. Eudald Romo & Luis Ortiz-Gracia, 2021. "SWIFT Calibration of the Heston Model," Mathematics, MDPI, vol. 9(5), pages 1-20, March.
  56. Dennis Bams & Thorsten Lehnert & Christian C. P. Wolff, 2009. "Loss Functions in Option Valuation: A Framework for Selection," Management Science, INFORMS, vol. 55(5), pages 853-862, May.
  57. Bruce Mizrach, 2007. "Recovering Probabilistic Information From Options Prices and the Underlying," Departmental Working Papers 200702, Rutgers University, Department of Economics.
  58. Barletta, Andrea & Santucci de Magistris, Paolo & Sloth, David, 2019. "It only takes a few moments to hedge options," Journal of Economic Dynamics and Control, Elsevier, vol. 100(C), pages 251-269.
  59. Xin‐Jiang He & Sha Lin, 2023. "Analytically pricing European options under a hybrid stochastic volatility and interest rate model with a general correlation structure," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(7), pages 951-967, July.
  60. Graham Elliott & Allan Timmermann, 2016. "Economic Forecasting," Economics Books, Princeton University Press, edition 1, number 10740.
  61. Andersen, Torben G. & Fusari, Nicola & Todorov, Viktor & Varneskov, Rasmus T., 2019. "Unified inference for nonlinear factor models from panels with fixed and large time span," Journal of Econometrics, Elsevier, vol. 212(1), pages 4-25.
  62. Julien Hok & Philip Ngare & Antonis Papapantoleon, 2018. "Expansion formulas for European quanto options in a local volatility FX-LIBOR model," Papers 1801.01205, arXiv.org, revised Apr 2018.
  63. De Col, Alvise & Gnoatto, Alessandro & Grasselli, Martino, 2013. "Smiles all around: FX joint calibration in a multi-Heston model," Journal of Banking & Finance, Elsevier, vol. 37(10), pages 3799-3818.
  64. Yunbi An & Wulin Suo, 2009. "An Empirical Comparison of Option‐Pricing Models in Hedging Exotic Options," Financial Management, Financial Management Association International, vol. 38(4), pages 889-914, December.
  65. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2019. "Cross-validated covariance estimators for high-dimensional minimum-variance portfolios," Papers 1910.13960, arXiv.org, revised Oct 2020.
  66. Chalamandaris, Georgios & Tsekrekos, Andrianos E., 2009. "Common Factors and Causality in the Dynamics of Implied Volatility Surfaces: Evidence from the FX OTC Market," The Journal of Economic Asymmetries, Elsevier, vol. 6(1), pages 49-74.
  67. A. S. Hurn & K. A. Lindsay & A. J. McClelland, 2015. "Estimating the Parameters of Stochastic Volatility Models Using Option Price Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(4), pages 579-594, October.
  68. Hilliard, Jimmy E. & Hilliard, Jitka, 2019. "A jump-diffusion model for pricing and hedging with margined options: An application to Brent crude oil contracts," Journal of Banking & Finance, Elsevier, vol. 98(C), pages 137-155.
  69. Steffen Hitzemann & Marliese Uhrig-Homburg, 2019. "Empirical performance of reduced-form models for emission permit prices," Review of Derivatives Research, Springer, vol. 22(3), pages 389-418, October.
  70. Aurélie Lemmens & Sunil Gupta, 2020. "Managing Churn to Maximize Profits," Marketing Science, INFORMS, vol. 39(5), pages 956-973, September.
  71. Wing Hong Chan & Ranjini Jha & Madhu Kalimipalli, 2009. "The Economic Value Of Using Realized Volatility In Forecasting Future Implied Volatility," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 32(3), pages 231-259, September.
  72. Ryszard Kokoszczyński & Natalia Nehrebecka & Paweł Sakowski & Paweł Strawiński & Robert Ślepaczuk, 2010. "Option Pricing Models with HF Data – a Comparative Study. The Properties of Black Model with Different Volatility Measures," Working Papers 2010-03, Faculty of Economic Sciences, University of Warsaw.
  73. Gonzalez-Rivera, Gloria & Lee, Tae-Hwy & Mishra, Santosh, 2004. "Forecasting volatility: A reality check based on option pricing, utility function, value-at-risk, and predictive likelihood," International Journal of Forecasting, Elsevier, vol. 20(4), pages 629-645.
  74. Darko B. Vukovic & Lubov Spitsina & Ekaterina Gribanova & Vladislav Spitsin & Ivan Lyzin, 2023. "Predicting the Performance of Retail Market Firms: Regression and Machine Learning Methods," Mathematics, MDPI, vol. 11(8), pages 1-23, April.
  75. YongChern Su & MingDa Chen & HanChing Huang, 2010. "An application of closed-form GARCH option-pricing model on FTSE 100 option and volatility," Applied Financial Economics, Taylor & Francis Journals, vol. 20(11), pages 899-910.
  76. Du Du & Dan Luo, 2019. "The Pricing of Jump Propagation: Evidence from Spot and Options Markets," Management Science, INFORMS, vol. 67(5), pages 2360-2387, May.
  77. Timmermann, Allan & Patton, Andrew, 2003. "Properties of Optimal Forecasts," CEPR Discussion Papers 4037, C.E.P.R. Discussion Papers.
  78. Gurupdesh S. Pandher, 2007. "Regression-based modeling of market option prices: with application to S&P500 options," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(7), pages 475-496.
  79. Yongxin Yang & Yu Zheng & Timothy M. Hospedales, 2016. "Gated Neural Networks for Option Pricing: Rationality by Design," Papers 1609.07472, arXiv.org, revised Mar 2020.
  80. Arismendi, Juan C. & Back, Janis & Prokopczuk, Marcel & Paschke, Raphael & Rudolf, Markus, 2016. "Seasonal Stochastic Volatility: Implications for the pricing of commodity options," Journal of Banking & Finance, Elsevier, vol. 66(C), pages 53-65.
  81. Julien Hok & Philip Ngare & Antonis Papapantoleon, 2018. "Expansion Formulas For European Quanto Options In A Local Volatility Fx-Libor Model," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 21(02), pages 1-43, March.
  82. Panayiotis Andreou & Chris Charalambous & Spiros Martzoukos, 2014. "Assessing the performance of symmetric and asymmetric implied volatility functions," Review of Quantitative Finance and Accounting, Springer, vol. 42(3), pages 373-397, April.
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  84. Rui Fan & Stephen J. Taylor & Matteo Sandri, 2018. "Density forecast comparisons for stock prices, obtained from high‐frequency returns and daily option prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(1), pages 83-103, January.
  85. Cummins, Mark & Kiely, Greg & Murphy, Bernard, 2018. "Gas storage valuation under multifactor Lévy processes," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 167-184.
  86. Georgios Chalamandaris & Andrianos Tsekrekos, 2013. "Explanatory Factors and Causality in the Dynamics of Volatility Surfaces Implied from OTC Asian–Pacific Currency Options," Computational Economics, Springer;Society for Computational Economics, vol. 41(3), pages 327-358, March.
  87. Lorenzo Mercuri & Edit Rroji, 2018. "Option pricing in an exponential MixedTS Lévy process," Annals of Operations Research, Springer, vol. 260(1), pages 353-374, January.
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