Investigating Stock Market Volatility in Saudi Arabia Using the GARCH and EGARCH Models

被引:0
|
作者
Muneer, Saqib [1 ]
机构
[1] Univ Hail, Coll Business Adm, Dept Econ & Finance, Hail, Saudi Arabia
来源
PACIFIC BUSINESS REVIEW INTERNATIONAL | 2025年 / 17卷 / 07期
关键词
Stock market volatility; GARCH; EGARCH; Saudi stock exchange; SENTIMENT;
D O I
暂无
中图分类号
F [经济];
学科分类号
02 ;
摘要
Stock market acts as a key component of an economy by promoting capital creation, improves liquidity by bringing investments to the nation. It promotes economic growth, industrial development and employment. Saudi stock market known as Tadawul plays a significant role in shaping nations development and long term plans while it is also crucial for financial dynamics natively and worldwide. This paper aims to investigate the stock market volatility by applying GARCH and EGARCH models using Tadawul All Share daily price index data taken from 3 July2010 to 19 August2024.The ARCH parameter is significant in descriptive statistics which indicates the presence of heteroskedasticity in squared residuals demonstrating the need of applying GARCH model. Moreover, ARCH and GARCH terms are statistically significant in both models of study. While positive leverage value presence also suggests that, due to existence of asymmetric behavior the negative shocks in markets entail a higher impact than positive shocks in upcoming time period. Through findings of this study the major repercussions in stock market after the 2008 economic crisis can be seen. This study contributes towards the existing literature about stock market volatility research and it can also help investors to better gauge about the unpredictability of stock market shares due to existence of market instability. It also suggests that it is better to invest in diversified markets to lower the risk factor when markets are facing world crisis.
引用
收藏
页码:113 / 121
页数:9
相关论文
共 50 条
  • [21] GARCH-type forecasting models for volatility of stock market and MCS test
    Luo, Lingling
    Pairote, Sattayatham
    Chatpatanasiri, Ratthachat
    COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, 2017, 46 (07) : 5303 - 5312
  • [22] Volatility of pakistan stock market: A comparison of Garch type models with five distribution
    Naseem, Sobia
    Fu, Gao Lei
    Mohsin, Muhammad
    Zia-ur-Rehman, Muhammad
    Baig, Sajjad Ahmad
    AMAZONIA INVESTIGA, 2018, 7 (17): : 486 - 504
  • [23] Assessing nickel sector index volatility based on quantile regression for Garch and Egarch models: Evidence from the Chinese stock market 2018-2022
    Lu, Linna
    Lei, Yalin
    Yang, Yang
    Zheng, Haoqi
    Wang, Wen
    Meng, Yan
    Meng, Chunhong
    Zha, Liqiang
    RESOURCES POLICY, 2023, 82
  • [24] Oil prices, stock market returns, and volatility spillovers: evidence from Saudi Arabia
    Emrah Ismail Cevik
    Sel Dibooglu
    Atif Awad Abdallah
    Eisa Abdulrahman Al-Eisa
    International Economics and Economic Policy, 2021, 18 : 157 - 175
  • [25] Oil prices, stock market returns, and volatility spillovers: evidence from Saudi Arabia
    Cevik, Emrah Ismail
    Dibooglu, Sel
    Awad Abdallah, Atif
    Al-Eisa, Eisa Abdulrahman
    INTERNATIONAL ECONOMICS AND ECONOMIC POLICY, 2021, 18 (01) : 157 - 175
  • [26] Empirical Analysis of Chinese Stock Market Volatility Based on GARCH Models and Markov Switching Models
    Zou, Na
    Zhu, Jiahui
    Cai, Yanli
    PROCEEDINGS OF THE 2019 4TH INTERNATIONAL CONFERENCE ON SOCIAL SCIENCES AND ECONOMIC DEVELOPMENT (ICSSED 2019), 2019, 314 : 490 - 497
  • [27] GARCH model for volatility in stock return series of Vietnam stock market
    Le, Duc Thang
    Zhang, Qiang
    INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS & STATISTICS, 2014, 52 (01): : 94 - 110
  • [28] Comparing the performances of GARCH-type models in capturing the stock market volatility in Malaysia
    Lim, Ching Mun
    Sek, Siok Kun
    INTERNATIONAL CONFERENCE ON APPLIED ECONOMICS (ICOAE) 2013, 2013, 5 : 478 - 487
  • [29] Forecasting stock market volatility with non-linear GARCH models: a case for China
    Wei, WX
    APPLIED ECONOMICS LETTERS, 2002, 9 (03) : 163 - 166
  • [30] Application of Fuzzy Asymmetric GARCH-Models to Forecasting of Volatility of Russian Stock Market
    Lepskiy, Alexander
    Suevalov, Artem
    PROCEEDINGS OF THE SECOND INTERNATIONAL SCIENTIFIC CONFERENCE INTELLIGENT INFORMATION TECHNOLOGIES FOR INDUSTRY (IITI'17), VOL 1, 2018, 679 : 286 - 294