数学学科2021系列学术报告之六

　　题目：Autoregressive models of the time series under volatility uncertainty and application to VaR model

　　报告人：杨淑振（山东大学-金融研究院）

　　时  间：2021年6月02日（周三），下午14：30-15：30

　　报告地点：1-301

　　报告摘要：Financial time series admits inherent uncertainty and randomness that changes over time. To clearly describe volatility uncertainty of the time series, we assume that the volatility of risky assets holds value between the minimum volatility and maximum volatility of the assets. This study establishes autoregressive models to determine the maximum and minimum volatilities, where the ratio of minimum volatility to maximum volatility can measure volatility uncertainty. By utilizing the value at risk （VaR） predictor model under volatility uncertainty, we introduce the risk and uncertainty, and show that the autoregressive model of volatility uncertainty is a powerful tool in predicting the VaR for a benchmark dataset. Joined work with Shige Peng.

　　报告人简介：杨淑振，山东大学金融研究院副教授、硕士生导师。研究方向为随机最优控制和金融数学，非线性期望理论在金融中应用。获得山东省2015年优秀博士论文，在 《International Journal of Robust and Nonlinear control》，《System control letter》，《经济研究》和《金融研究》等杂志上发表相关研究成果。