| 基于贝叶斯修正的多阶段情景元素生成 |
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| 引用本文： | 赵大萍,房勇.基于贝叶斯修正的多阶段情景元素生成[J].系统工程理论与实践,2016,36(8):1928-1936. |
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| 作者姓名： | 赵大萍 房勇 |
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| 作者单位： | 1. 首都经济贸易大学 金融学院, 北京 100070;2. 中国科学院 数学与系统科学研究院, 北京 100190 |
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| 基金项目： | 国家自然科学基金（71271201，71431008）；首都经济贸易大学2015年社科研基金；北京市优秀人才资助项目（20140000204400001） |
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| 摘 要： | 针对证券市场中资产未来收益的不确定性问题,本文基于随机波动率模型刻画了资产未来收益的情景元素,得到了资产未来收益分布的情景树,并在此基础上进一步采用贝叶斯理论修正了情景概率,最后利用国际证券市场的股票指数数据对模型进行了验证.算例结果表明,基于随机波动率模型的情景元素生成模型得到的情景元素质量良好,贝叶斯方法修正后的情景概率也与真实市场情况更贴合.
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| 关 键 词： | 情景生成 情景树 随机波动率模型 贝叶斯理论 |
| 收稿时间： | 2014-12-19 |
Multi-stage scenarios generation based on Bayes theory |
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| ZHAO Daping,FANG Yong.Multi-stage scenarios generation based on Bayes theory[J].Systems Engineering —Theory & Practice,2016,36(8):1928-1936. |
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| Authors: | ZHAO Daping FANG Yong |
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| Institution: | 1. School of Finance, Capital University of Economics and Business, Beijing 100070, China;2. Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China |
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| Abstract: | To solve the problem of securities return uncertainty in securities market, in this paper, we choose the stochastic volatility model to simulate the stock returns with scenarios, and build a scenario tree after the scenario generation. In addition, the scenario probability is fixed with Bayesian theory. Empirical experiments show that the scenario elements generated with the stochastic volatility model are well performed, and the fixed scenario probabilities are more consistent with the real market. |
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| Keywords: | scenario generation scenario tree stochastic volatility model Baysian theory |
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