用极值理论分析股票市场风险

Proceedings of the 3rd International Conference on Vision, Image and Signal Processing Pub Date : 2019-08-26 DOI:10.1145/3387168.3389113

Lijun Liu, Yongmei Ding, Yunfeng Peng

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引用次数: 0

摘要

风险是股票市场永恒的主题。随着中国经济全球化的进一步深入，中国金融市场风险变得更加复杂，这使得计量工具变得至关重要。股票价格评估通常采用极值分布，并建立了块极大值模型(BMM)和峰值超过阈值模型(POT)。本文以上海证券交易所指数2006年6月1日至2018年4月1日的日收益率为指标，通过上述两个模型计算风险值VaR和预期差额ES。我们比较了两种评估方法对提高风险度量精度的影响，结果表明，POT比BMM对风险度量更稳定。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Analysis on Risk of Stock Market Via Extreme Value Theory

Risk is the perpetual theme in the stock market. Chinese financial market risks have become complicated as Chinese economic globalization further deepens, which makes the measurement tools critical and significant. Extreme distribution usually has been chosen for assessing the stock prices, further the Block Maxima Model (BMM) and the Peak-Over-Threshold (POT) model have been established. In our paper, the Value at risk (VaR) and Expected Shortfall (ES) are calculated via the above two models through daily rate of return from Jun. 1 of 2006 to April 1 of 2018 for Shanghai Stock Exchange index. We compare the two assessing methods for improving the accuracy of risk measurement, which shown that the POT is more stable than the BMM to risk measurement.

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Proceedings of the 3rd International Conference on Vision, Image and Signal Processing

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