Kernel Smoothing for Nested Estimation with Application to Portfolio Risk Measurement
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DOI: 10.1287/opre.2017.1591
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References listed on IDEAS
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Cited by:
- Kun Zhang & Ben Mingbin Feng & Guangwu Liu & Shiyu Wang, 2022. "Sample Recycling for Nested Simulation with Application in Portfolio Risk Measurement," Papers 2203.15929, arXiv.org.
- Guangxin Jiang & L. Jeff Hong & Barry L. Nelson, 2020. "Online Risk Monitoring Using Offline Simulation," INFORMS Journal on Computing, INFORMS, vol. 32(2), pages 356-375, April.
- Weihuan Huang & Nifei Lin & L. Jeff Hong, 2022. "Monte-Carlo Estimation of CoVaR," Papers 2210.06148, arXiv.org.
- Liu, Xiaoyu & Yan, Xing & Zhang, Kun, 2024. "Kernel quantile estimators for nested simulation with application to portfolio value-at-risk measurement," European Journal of Operational Research, Elsevier, vol. 312(3), pages 1168-1177.
- Youngjun Choe & Henry Lam & Eunshin Byon, 2018. "Uncertainty Quantification of Stochastic Simulation for Black-box Computer Experiments," Methodology and Computing in Applied Probability, Springer, vol. 20(4), pages 1155-1172, December.
- Wang, Tianxiang & Xu, Jie & Hu, Jian-Qiang & Chen, Chun-Hung, 2023. "Efficient estimation of a risk measure requiring two-stage simulation optimization," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1355-1365.
- Qiyun Pan & Eunshin Byon & Young Myoung Ko & Henry Lam, 2020. "Adaptive importance sampling for extreme quantile estimation with stochastic black box computer models," Naval Research Logistics (NRL), John Wiley & Sons, vol. 67(7), pages 524-547, October.
- David J. Eckman & Shane G. Henderson & Sara Shashaani, 2023. "Diagnostic Tools for Evaluating and Comparing Simulation-Optimization Algorithms," INFORMS Journal on Computing, INFORMS, vol. 35(2), pages 350-367, March.
- Lucio Fernandez‐Arjona & Damir Filipović, 2022. "A machine learning approach to portfolio pricing and risk management for high‐dimensional problems," Mathematical Finance, Wiley Blackwell, vol. 32(4), pages 982-1019, October.
- Qin, Chang-Xiong & Liu, Zhao, 2022. "Reference price effect of partially similar online products in the consideration stage," Journal of Business Research, Elsevier, vol. 152(C), pages 70-81.
- Mingbin Ben Feng & Eunhye Song, 2020. "Efficient Nested Simulation Experiment Design via the Likelihood Ratio Method," Papers 2008.13087, arXiv.org, revised May 2024.
- Dang, Ou & Feng, Mingbin & Hardy, Mary R., 2023. "Two-stage nested simulation of tail risk measurement: A likelihood ratio approach," Insurance: Mathematics and Economics, Elsevier, vol. 108(C), pages 1-24.
- Runhuan Feng & Peng Li, 2021. "Sample Recycling Method -- A New Approach to Efficient Nested Monte Carlo Simulations," Papers 2106.06028, arXiv.org.
- Hongjun Ha & Daniel Bauer, 2022. "A least-squares Monte Carlo approach to the estimation of enterprise risk," Finance and Stochastics, Springer, vol. 26(3), pages 417-459, July.
- Xin Yun & Yanyi Ye & Hao Liu & Yi Li & Kin-Keung Lai, 2023. "Stylized Model of Lévy Process in Risk Estimation," Mathematics, MDPI, vol. 11(6), pages 1-14, March.
- Devang Sinha & Siddhartha P. Chakrabarty, 2024. "Multilevel Monte Carlo in Sample Average Approximation: Convergence, Complexity and Application," Papers 2407.18504, arXiv.org.
- Feng, Ben Mingbin & Li, Johnny Siu-Hang & Zhou, Kenneth Q., 2022. "Green nested simulation via likelihood ratio: Applications to longevity risk management," Insurance: Mathematics and Economics, Elsevier, vol. 106(C), pages 285-301.
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Keywords
nested estimation; kernel estimation; portfolio risk measurement;All these keywords.
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