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| 基于GARCH模型和VAR上证综指风险波动性度量研究 |
| Research on Risk Volatility Measurement of the Shanghai Composite Index Based on GARCH Model and VAR |
| 投稿时间：2025-03-06 修订日期：2025-03-31 |
| DOI： |
| 中文关键词: 金融风险 统计推断 风险度量 风险管理 |
| 英文关键词:Financial Risk Statistical Inference Risk Measurement Risk Management |
| 基金项目: |
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| 中文摘要: |
| 本文探讨了GARCH模型在金融风险度量中的应用，特别是针对上证指数。研究发现，GARCH模型能有效的捕捉市场波动性，有效刻画收益率的时变性、非对称性及波动聚集效应，而且在不同分布假设下，风险度量的结果存在差异。而VaR的风险度量结果显著依赖于分布假设。进一步的分析表明，EGARCH和PARCH模型的VaR时计算误差更小，且能更好适应厚尾特征，更能反映市场风险。 |
| 英文摘要: |
| This paper explores the application of GARCH models in financial risk measurement, specifically targeting the SSE Index. The study found that GARCH models effectively capture market volatility, accurately characterize the time-varying nature and asymmetry of returns, as well as volatility clustering effects. However, risk measurement results exhibit differences under varying distributional assumptions. Notably, the outcomes of Value-at-Risk (VaR) calculations show significant dependence on distributional assumptions. Further analysis reveals that the EGARCH and PARCH models demonstrate smaller computational errors in VaR estimation, better adapt to heavy-tailed characteristics, and more accurately reflect market risks. |
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