尼泊尔股票收益波动:Covid-19期间的证据

S. B. Rana
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引用次数: 0

摘要

本研究详细分析了2020年3月3日至2022年2月27日COVID-19期间尼泊尔股票收益波动模式。通过检验具有广义误差分布规范的GARCH家族模型,对称GARCH模型的结果表明,在研究期间尼泊尔的每日股票收益存在持续波动。观察到的股票日收益的持续波动表明,当前股票日收益的冲击存在于未来较长时期的预测方差中。非对称TGARCH(1,1)模型的结果表明,在研究期间尼泊尔股票日收益波动率存在杠杆效应。观察到的杠杆效应表明,与相同强度的互补新闻相比,负面新闻对波动性的影响更大。最后,研究结果表明,GARCH(1,1)模型是解释波动持续性的最佳拟合对称模型,TGARCH(1,1)模型是预测尼泊尔日股票时变条件波动率的最佳拟合非对称模型。本研究结果的主要含义是,它提供了一个额外的见解,以形成良好的投资策略,以解决尼泊尔股市的风险结构。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stock Returns Volatility in Nepal: Evidence during Covid-19
This study scrutinizes the stock returns volatility pattern in Nepal during the COVID-19 period from March 3, 2020 to February 27, 2022. By examining GARCH family models with Generalized Error Distribution specification, the results of symmetric GARCH models show that there is persistent volatility in daily stock returns in Nepal over the study period. The observed persistent volatility in daily stock returns indicate that the current shocks in daily stock returns exist in forecasting variance for longer period in future. The results of asymmetric TGARCH (1, 1) model show that there is the leverage effects on the volatility of daily stock returns in Nepal during the study period. The observed leverage effects implies that uncomplimentary news have larger effects on the volatility than the complimentary news of the same intensity. Finally, results establish the GARCH (1, 1) model as the best fitted symmetric model to explain the volatility persistence and the TGARCH (1,1) model as the best fitted asymmetric models to predict the leverage effects on the time varying conditional volatility of daily stock in Nepal. The main implication of findings from this study is that it offers an additional insight to form sound investment strategy to address risk structure of Nepali stock market.
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