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https://ah.lib.nccu.edu.tw/handle/140.119/129849
題名: | Time Series Simulation with Randomized Quasi-Monte Carlo Methods: An Application to Value at Risk and Expected Shortfall | 作者: | 曾毓英 Tzeng, Yu-Ying Beaumont, Paul M. Ökten , Giray |
貢獻者: | 風管系 | 關鍵詞: | Quasi-Monte Carlo ; Randomized Quasi-Monte Carlo ; Time series simulation ; Value-at-risk ; Expected shortfall | 日期: | 2018 | 上傳時間: | 26-May-2020 | 摘要: | Quasi-Monte Carlo methods are designed to produce efficient estimates of simulated values but the error statistics of these estimates are difficult to compute. Randomized quasi-Monte Carlo methods have been developed to address this shortcoming. In this paper we compare quasi-Monte Carlo and randomized quasi-Monte Carlo techniques for simulating time series. We use randomized quasi-Monte Carlo to compute value-at-risk and expected shortfall measures for a stock portfolio whose returns follow a highly nonlinear Markov switching stochastic volatility model which does not admit analytical solutions for the returns distribution. Quasi-Monte Carlo methods are more accurate but do not allow the computation of reliable confidence intervals about risk measures. We find that randomized quasi-Monte Carlo methods maintain many of the advantages of quasi-Monte Carlo while also providing the ability to produce reliable confidence intervals of the simulated risk measures. However, the advantages in speed of convergence of randomized quasi-Monte Carlo diminish as the forecast horizon increases. | 關聯: | Computational Economics, Vol.52, pp.55-77 | 資料類型: | article | DOI: | https://doi.org/10.1007/s10614-017-9661-0 |
Appears in Collections: | 期刊論文 |
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