Volatility of Daily Nepal Stock Exchange (Nepse) Index Return: A Garch Family Models

D. Dangal, R. Gajurel
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Abstract

The major intend of this study is to investigate the volatility clustering in NEPSE index. To reach the conclusion, 3392 annually observed time series data from 1 June 2006 to 7 April 2021 were obtained from various volume of annual trading report of Nepal Stock Exchange (NEPSE) and website of NEPSE and symmetric Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models––GARCH (1,1), GARCH-M (1,1) and asymmetric GARCH family models––TGARCH (1,1), EGARCH (1,1), and PGARCH (1,1) were employed. The stylized facts confirm that the volatility clustering and leverage effect on the return of NEPSE index are existed. The empirical analysis reveals that the positive correlation between volatility and the expected return of NEPSE index in terms of risk premium and then conditional variance process is persistent. The empirical results also show that the symmetric model is better fitted to full sampled period and asymmetric GARCH family models to before-and after-earthquake sampled period. This study covers the larger dataset which is divided into different episodes with different economic condition of Nepal and thus, it is assumed to be a purely an initial work on Nepalese stock exchange.
每日尼泊尔证券交易所(Nepse)指数回报的波动性:Garch家族模型
本研究的主要目的是研究NEPSE指数的波动聚类。本文利用尼泊尔证券交易所(NEPSE)和NEPSE网站2006年6月1日至2021年4月7日的3392个年度观测时间序列数据,采用对称广义自回归条件异方差(GARCH)模型GARCH(1,1)、GARCH- m(1,1)和非对称GARCH家族模型TGARCH(1,1)、EGARCH(1,1)和PGARCH(1,1)。程式化的事实证实了波动聚类和杠杆效应对NEPSE指数收益的影响是存在的。实证分析表明,波动率与NEPSE指数的预期收益在风险溢价和条件方差过程中呈持续的正相关关系。实证结果还表明,对称模型对全采样周期拟合较好,非对称GARCH族模型对震前和震后采样周期拟合较好。本研究涵盖了更大的数据集,该数据集分为尼泊尔不同经济状况的不同剧集,因此,它被认为是纯粹的尼泊尔证券交易所的初步工作。
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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