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Kernel Smoothing for Nested Estimation with Application to Portfolio Risk Measurement

Citations

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Cited by:

  1. 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.
  2. 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.
  3. Fabozzi, Frank J. & Recchioni, Maria Cristina & Renò, Roberto, 2025. "Fifty years at the interface between financial modeling and operations research," European Journal of Operational Research, Elsevier, vol. 327(1), pages 1-21.
  4. 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.
  5. Xiaoyu Liu & Yan Song & Hong-Fa Cheng & Kun Zhang, 2025. "A bootstrap-based bandwidth selection rule for kernel quantile estimators," Computational Statistics, Springer, vol. 40(7), pages 4037-4058, September.
  6. 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.
  7. 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.
  8. 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.
  9. Mingbin Ben Feng & Eunhye Song, 2020. "Efficient Nested Simulation Experiment Design via the Likelihood Ratio Method," Papers 2008.13087, arXiv.org, revised May 2024.
  10. 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.
  11. 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.
  12. Du-Yi Wang & Guo Liang & Kun Zhang & Qianwen Zhu, 2026. "Reliable Real-Time Value at Risk Estimation via Quantile Regression Forest with Conformal Calibration," Papers 2602.01912, arXiv.org.
  13. Nifei Lin & Yingda Song & L. Jeff Hong, 2024. "Efficient Nested Estimation of CoVaR: A Decoupled Approach," Papers 2411.01319, arXiv.org.
  14. Kun Zhang & Guangwu Liu & Shiyu Wang, 2022. "Technical Note—Bootstrap-based Budget Allocation for Nested Simulation," Operations Research, INFORMS, vol. 70(2), pages 1128-1142, March.
  15. Wenjia Wang & Yanyuan Wang & Xiaowei Zhang, 2024. "Smooth Nested Simulation: Bridging Cubic and Square Root Convergence Rates in High Dimensions," Management Science, INFORMS, vol. 70(12), pages 9031-9057, December.
  16. Weihuan Huang & Nifei Lin & L. Jeff Hong, 2022. "Monte-Carlo Estimation of CoVaR," Papers 2210.06148, arXiv.org.
  17. Guo Liang & Kun Zhang & Jun Luo, 2024. "A FAST Method for Nested Estimation," INFORMS Journal on Computing, INFORMS, vol. 36(6), pages 1481-1500, December.
  18. 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.
  19. 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.
  20. Weihuan Huang & Nifei Lin & L. Jeff Hong, 2024. "Monte Carlo Estimation of CoVaR," Operations Research, INFORMS, vol. 72(6), pages 2337-2357, November.
  21. Qidong Lai & Guangwu Liu & Bingfeng Zhang & Kun Zhang, 2025. "Simulating Confidence Intervals for Conditional Value-at-Risk via Least-Squares Metamodels," INFORMS Journal on Computing, INFORMS, vol. 37(4), pages 1087-1105, July.
  22. 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.
  23. Emanuele Borgonovo & Alessio Figalli & Elmar Plischke & Giuseppe Savaré, 2025. "Global Sensitivity Analysis via Optimal Transport," Management Science, INFORMS, vol. 71(5), pages 3809-3828, May.
  24. Runhuan Feng & Peng Li, 2021. "Sample Recycling Method -- A New Approach to Efficient Nested Monte Carlo Simulations," Papers 2106.06028, arXiv.org.
  25. 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.
  26. Devang Sinha & Siddhartha P. Chakrabarty, 2024. "Multilevel Monte Carlo in Sample Average Approximation: Convergence, Complexity and Application," Papers 2407.18504, arXiv.org.
  27. 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.
  28. Ben Mingbin Feng & Eunhye Song, 2025. "Efficient Nested Simulation Experiment Design via the Likelihood Ratio Method," INFORMS Journal on Computing, INFORMS, vol. 37(3), pages 723-742, May.
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