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A Nonparametric Approach to Pricing and Hedging Derivative Securities Via Learning Networks

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Cited by:

  1. Burak Saltoglu, 2003. "Comparing forecasting ability of parametric and non-parametric methods: an application with Canadian monthly interest rates," Applied Financial Economics, Taylor & Francis Journals, vol. 13(3), pages 169-176.
  2. Ghysels, Eric & Babii, Andrii & Chen, Xi & Kumar, Rohit, 2020. "Binary Choice with Asymmetric Loss in a Data-Rich Environment: Theory and an Application to Racial Justice," CEPR Discussion Papers 15418, C.E.P.R. Discussion Papers.
  3. Omid M. Ardakani, 2022. "Option pricing with maximum entropy densities: The inclusion of higher‐order moments," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(10), pages 1821-1836, October.
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  5. Clement, E. & Gourieroux, C. & Monfort, A., 2000. "Econometric specification of the risk neutral valuation model," Journal of Econometrics, Elsevier, vol. 94(1-2), pages 117-143.
  6. Lin, Shao-Bin & Chen, Chun-Da, 2013. "Applying the Model Order Reduction method to a European option pricing model," Economic Modelling, Elsevier, vol. 33(C), pages 533-536.
  7. Carl Remlinger & Bri`ere Marie & Alasseur Cl'emence & Joseph Mikael, 2021. "Expert Aggregation for Financial Forecasting," Papers 2111.15365, arXiv.org, revised Jul 2023.
  8. Gradojevic Nikola, 2016. "Multi-criteria classification for pricing European options," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(2), pages 123-139, April.
  9. Amarda Cano, 2020. "Evolution of Public Debt in Albania during 1990-2017 and its impact on the Economic Growth," European Journal of Marketing and Economics Articles, Revistia Research and Publishing, vol. 4, January -.
  10. Jun Lu & Hiroshi Ohta, 2003. "A data and digital-contracts driven method for pricing complex derivatives," Quantitative Finance, Taylor & Francis Journals, vol. 3(3), pages 212-219.
  11. Ke Nian & Thomas F. Coleman & Yuying Li, 2018. "Learning minimum variance discrete hedging directly from the market," Quantitative Finance, Taylor & Francis Journals, vol. 18(7), pages 1115-1128, July.
  12. 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.
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  16. Vortelinos, Dimitrios I., 2017. "Forecasting realized volatility: HAR against Principal Components Combining, neural networks and GARCH," Research in International Business and Finance, Elsevier, vol. 39(PB), pages 824-839.
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  21. Hoogerheide, Lennart F. & Kaashoek, Johan F. & van Dijk, Herman K., 2007. "On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: An application of flexible sampling methods using neural networks," Journal of Econometrics, Elsevier, vol. 139(1), pages 154-180, July.
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  24. Montagna, Guido & Morelli, Marco & Nicrosini, Oreste & Amato, Paolo & Farina, Marco, 2003. "Pricing derivatives by path integral and neural networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 189-195.
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  26. Michaelides, Panayotis G. & Vouldis, Angelos T. & Tsionas, Efthymios G., 2010. "Globally flexible functional forms: The neural distance function," European Journal of Operational Research, Elsevier, vol. 206(2), pages 456-469, October.
  27. 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.
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  29. Gunter Meissner & Noriko Kawano, 2001. "Capturing the volatility smile of options on high-tech stocks—A combined GARCH-neural network approach," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 25(3), pages 276-292, September.
  30. Yang Qu & Ming-Xi Wang, 2019. "The option pricing model based on time values: an application of the universal approximation theory on unbounded domains," Papers 1910.01490, arXiv.org, revised Apr 2021.
  31. Dimitris Bertsimas & Leonid Kogan & Andrew W. Lo, 1997. "Pricing and Hedging Derivative Securities in Incomplete Markets: An E-Aritrage Model," NBER Working Papers 6250, National Bureau of Economic Research, Inc.
  32. Ali Babikir & Henry Mwambi, 2016. "Evaluating the combined forecasts of the dynamic factor model and the artificial neural network model using linear and nonlinear combining methods," Empirical Economics, Springer, vol. 51(4), pages 1541-1556, December.
  33. Dimitris Bertsimas & Leonid Kogan & Andrew W. Lo, 2001. "Hedging Derivative Securities and Incomplete Markets: An (epsilon)-Arbitrage Approach," Operations Research, INFORMS, vol. 49(3), pages 372-397, June.
  34. Khurshid M. KIANI & Terry L. KASTENS, 2006. "Using Macro-Financial Variables To Forecast Recessions. An Analysis Of Canada, 1957-2002," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 6(3).
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  38. Broadie, Mark & Detemple, Jerome & Ghysels, Eric & Torres, Olivier, 2000. "American options with stochastic dividends and volatility: A nonparametric investigation," Journal of Econometrics, Elsevier, vol. 94(1-2), pages 53-92.
  39. Dimitris Bertsimas & Leonid Kogan & Andrew W. Lo, 2001. "When Is Time Continuous?," World Scientific Book Chapters, in: Marco Avellaneda (ed.), Quantitative Analysis In Financial Markets Collected Papers of the New York University Mathematical Finance Seminar(Volume II), chapter 3, pages 71-102, World Scientific Publishing Co. Pte. Ltd..
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  41. Raquel M. Gaspar & Sara D. Lopes & Bernardo Sequeira, 2020. "Neural Network Pricing of American Put Options," Risks, MDPI, vol. 8(3), pages 1-24, July.
  42. Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2223-2273.
  43. 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.
  44. Shu‐Heng Chen & Wo‐Chiang Lee & Chia‐Hsuan Yeh, 1999. "Hedging derivative securities with genetic programming," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 8(4), pages 237-251, December.
  45. Chen, Rui & Ren, Jinjuan, 2022. "Do AI-powered mutual funds perform better?," Finance Research Letters, Elsevier, vol. 47(PA).
  46. M. Ryan Haley & Todd B. Walker, 2010. "Alternative tilts for nonparametric option pricing," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 30(10), pages 983-1006, October.
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  48. Panayiotis Andreou & Chris Charalambous & Spiros Martzoukos, 2006. "Robust Artificial Neural Networks for Pricing of European Options," Computational Economics, Springer;Society for Computational Economics, vol. 27(2), pages 329-351, May.
  49. Ming Yuan, 2009. "State price density estimation via nonparametric mixtures," Papers 0910.1430, arXiv.org.
  50. Weijia Peng & Chun Yao, 2023. "Sector-level equity returns predictability with machine learning and market contagion measure," Empirical Economics, Springer, vol. 65(4), pages 1761-1798, October.
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