用GARCH模型对标准普尔500指数的回报进行建模

Latin American Journal of Central Banking Pub Date : 2023-09-01 DOI:10.1016/j.latcb.2023.100096

Rodrigo Alfaro, Alejandra Inzunza

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引用次数: 0

摘要

本文给出了GARCH模型参数对S&；P500指数，基于收益率和CBOE波动率指数。使用2007年至2022年收集的每日样本，我们可以得出结论，添加波动率指数信息可以提高对长期波动率的估计。通过使用明尼阿波利斯联邦储备局报告的基于期权的指数对模型进行外部验证，我们能够提出一个校准模型来跟踪该股指的尾部风险。

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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Modeling S&P500 returns with GARCH models

This paper provides several estimates of the GARCH models’ parameters for the S&P500 index, based on returns and CBOE VIX. Using a daily sample collected from 2007 to 2022, we can conclude that adding the VIX information improves the estimates of the long-term volatility. By providing an external validation of the model using an option-based index reported by the Federal Reserve of Minneapolis, we are able to propose a calibrate model to track the tail-risk of this stock index.

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