Modelling Monthly Volatility of the Muscat Securities Market (MSM) Index Using Auto Regressive Integrated Moving Average (ARIMA)

Shaik Nafeez Umar Shaik, Labeeb Mohammed Zeeshan
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引用次数: 1

Abstract

The Stock market is eyewitness’s responsive activities and is gradually more gaining importance. The purpose of the study is to measure the volatility of selected emerging indices Muscat Securities Market (MSM). Time series analysis techniques were used including Auto Regressive Integrated Moving Average (ARIMA) models. The time series data considered of this study taken MSM 30. The study period has taken from January 2013 to December 2018 except Sharia-compliant index would be June 2013 to December 2018. Tools used for the study is Unit Toot Test (Augmented Dickey–Fuller and Phillips-Perron), ARIMA models and for performance model using Theil’s U-Statistic. The study made a few observations which may help the investors and model builders to understand better about the stock market.
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基于自回归综合移动平均线(ARIMA)的马斯喀特证券市场(MSM)指数月度波动模型
股票市场是目击证人的反应性活动,其重要性日益凸显。研究的目的是衡量马斯喀特证券市场(MSM)选定的新兴指数的波动率。采用时间序列分析技术,包括自回归综合移动平均(ARIMA)模型。本研究考虑的时间序列数据取msm30。研究期间为2013年1月至2018年12月,但符合伊斯兰教法的指数为2013年6月至2018年12月。该研究使用的工具是单元图测试(增强Dickey-Fuller和Phillips-Perron)、ARIMA模型和使用Theil 's U-Statistic的性能模型。本研究的一些观察结果可能有助于投资者和模型构建者更好地了解股票市场。
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