基于贝叶斯算法的证券市场风险研究

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最新推荐文章于 2024-03-03 23:42:39 发布

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本文链接：https://blog.youkuaiyun.com/yql_617540298/article/details/111568260

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本文研究了证券市场风险，特别是在VaR模型基础上，结合贝叶斯算法和GARCH-POT模型构建新模型。通过对金融时间序列的分析，采用贝叶斯参数估计方法，利用MCMC抽样进行仿真模拟，揭示了证券市场风险的特征。通过实证研究，提出了抵御风险的措施，强调了投资者教育、宏观调控和法律体系完善的重要性。

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【摘要】

证券市场风险是指由于受到各种不确定因素引起证券市场价格非理性剧烈变动及证券资产迅速贬值，从而使市场行为主体可能受到损失。风险事件是风险产生的必要条件，是直接导致损失发生的不确定性事件，也是导致证券市场风险结果的直接原因。本文基于贝叶斯算法对于证券市场风险进行研究，在原有VaR算法的基础上，综合运用贝叶斯算法和GARCH-POT 模型构建新的模型算法，使用一种特殊的蒙特卡罗方法MCMC算法进行抽样。考虑金融时序的特征，采用两阶段分布模型度量证券市场风险，分布的中间部分采用GARCH模型拟合，尾部采用POT模型拟合。最终形成对于证券市场风险的分析，提出相应的抵御措施。

【关键词】

贝叶斯算法、市场风险、GARCH-POT算法

Research on stock market risk based on Bayesian algo

【Abstract】

The securities market risk is the result of a variety of uncertainties caused by the irrational stock market prices and the rapid depreciation of the securities assets, so that the market may be subject to losses. The risk event is the necessary condition of the risk, which is the direct cause of the result of the risk of security market, which is the direct cause of the occurrence of the loss. In this paper based on Bayesian algorithm for the securities market risk research, in the original VaR algorithm based on, using Bayesian algorithm and GARCH-POT model to construct new model algorithm, the sampling was carried out using a special Monte Carlo method MCMC algorithm. Two stage distribution model to measure the risk of securities market by considering the characteristics of financial time series, the distribution of the middle part of the use of GARCH model fitting, the tail of the pot model fitting. Finally formed for the analysis of the risk of stock market, puts forward the corresponding measures to resist.

【Keywords】

Bayesian algorithm、market risk、GARCH-POT algorithm

2.3.2 VaR计算方法不足分析... 4