The volatility of the Dow Jones Pharmaceuticals and Biotechnology Index in the context of the Coronavirus crisis

F. Darie, Illena Tache
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Abstract

This paper’s analysis was triggered by the outbreak of the new virus COVID-19. In December 2019, the Chinese officials alerted the World Health Organization (WHO) of the existence of an unknown deadly virus. Coronavirus has rapidly spread across the world - to Europe, Middle East and the USA, forcing the World Health Organization to declare COVID-19 a global pandemic. Its spread has generated major concerns for the health and economic sectors. Meanwhile, all countries hope for the development of a vaccine. Using as a research method the EGARCH model, this paper investigates if it can be applied to model the trend of volatility of the pharmaceuticals and biotechnology markets, especially during the health crisis. More specifically, this paper tries to identify whether different specifications of univariate GARCH models can usefully anticipate volatility in the stock indices market. The study uses estimates from both a symmetric and an asymmetric GARCH models, namely GARCH (1, 1) and EGARCH models, for the Dow Jones Pharmaceuticals and Biotechnology index (DJUSPN). The dataset is extracted from “Investing.com” and covers the period September 2019 - August 2020, resulting in a total of approximately 252 daily closing prices. The data focuses on the response of the highest capitalized pharmaceutical and biotechnology companies from the US to combat the outbreak of the coronavirus. This study concludes that the EGARCH model is better than the unconditional volatility and the conditional GARCH (1, 1) volatility and it is best suited for modelling and forecasting the fluctuations of the stock indexes.
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在冠状病毒危机背景下,道琼斯制药和生物技术指数的波动
本文的分析是由新型病毒covid -19的爆发引发的。2019年12月,中国官员向世界卫生组织(WHO)通报了一种未知的致命病毒。冠状病毒已经迅速蔓延到世界各地-欧洲,中东和美国,迫使世界卫生组织宣布covid -19全球大流行。它的传播引起了卫生和经济部门的重大关切。与此同时,各国都希望研制出疫苗。本文采用EGARCH模型作为研究方法,探讨了它是否可以用于模拟制药和生物技术市场的波动趋势,特别是在健康危机期间。更具体地说,本文试图确定不同规格的单变量GARCH模型是否可以有效地预测股票指数市场。该研究使用了道琼斯制药和生物技术指数(DJUSPN)的非对称和非对称GARCH模型,即GARCH(1,1)和degarch模型的估计。该数据集摘自“Investing.com”,涵盖2019年9月至2020年8月,共得出约252个每日收盘价。这些数据侧重于美国资本最高的制药和生物技术公司应对冠状病毒爆发的反应。研究表明,EGARCH模型优于无条件波动率和有条件GARCH(1,1)波动率,最适合于股票指数波动的建模和预测。
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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