• Title/Summary/Keyword: Saudi Stock Market

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The Effect of COVID-19 Pandemic on Stock Market: An Empirical Study in Saudi Arabia

  • ALZYADAT, Jumah Ahmad;ASFOURA, Evan
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.5
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    • pp.913-921
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    • 2021
  • The objective of the study is to investigate the impact of the COVID-19 pandemic on Saudi Arabia stock market. The study relied on the data of the daily closing stock market price index Tadawul All Share Index (TASI), and the number of daily cases infected with COVID-19 during the period from March 15, 2020, to August 10, 2020. The study employs the Vector Auto-Regressive (VAR) model, the Impulse Response Function (IRF) and Autoregressive Conditional Heteroscedasticity (ARCH) models. The results of the correlation matrix and the Impulse Response Function (IRF) show that stock market returns responded negatively to the growth in COVID-19 infected cases during the pandemic. The results of ARCH model confirmed the negative impact of COVID-19 pandemic on KSA stock market returns. The results also showed that the negative market reaction was strong during the early days of the COVID-19 pandemic. The study concluded that stock market in KSA responded quickly to the COVID-19 pandemic; the response varies over time according to the stage of the pandemic. However, the Saudi government's response time and size of the stimulus package have played an important role in alleviating the impacts of the COVID-19 pandemic on Saudi Arabia Stock Market.

Momentum Strategies and Stock Returns: A Case of Saudi Stock Market

  • KHAN, Muhammad Asif;REHMAN, Ramiz Ur;AHMAD, Muhammad Ishfaq;HARTHI, Majed Al
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.7
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    • pp.365-373
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    • 2021
  • This paper investigates the presence of momentum profits in the Saudi stock market. The study applied a quantitative method by utilizing monthly closing prices of 194 listed firms on Tadawal (Saudi Stock Market). The data from January 2010 to February 2019 is taken from the Tadawal market database for analysis. The sample is further divided into two equal sub-samples based on the structural changes that occurred in the Saudi stock market. Moreover, the high- and low-value traded portfolios are also constructed to examine the presence of momentum profits. Sixteen investment strategies are formed for each sample. The results show a very strong presence of momentum profits in the Saudi stock market for the full sample as well as for the sub-samples. The momentum profits are observed for a longer investment horizon. The results confirm that the short or medium-term formation of portfolios produces negative momentum returns for high-value traded stocks. The low-value traded stocks portfolios give similar results to the full sample results in terms of momentum profits. The results suggest that an investor should keep an eye on the past performance of desired stocks for at least three-nine months in which they are willing to invest.

COVID-19 Pandemic and the Reaction of Asian Stock Markets: Empirical Evidence from Saudi Arabia

  • SHAIK, Abdul Rahman
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.12
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    • pp.1-7
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    • 2021
  • The study examines the influence of COVID-19 on the stock market returns of Saudi Arabia. The data was analyzed through event study methodology using daily price data of Tadawul All Share Index (TASI). The study examines the behavior pattern of the Saudi Arabian stock market in different phases during the event period by selecting six-event windows with a range of 10 days. The results report a negative Abnormal Return (AR) of -0.003 on the event date, while the abnormal returns reversed the next day to 0.005 positively. The result of Cumulative Abnormal Return (CAR) is negative and significant at the 1 percent level in all the six-event windows starting from the event date to day 59 after the event for the TASI index. Even though the influence of the COVID-19 pandemic decreased after 30 days of the event date, it increased during the last ten days of the event window. The stock market volatility of Saudi Arabia increased during the post-event period compared to the pre-event period with a negative mean return of -0.326 and a greater standard deviation. In a conclusion, the study found a significant influence of the COVID-19 pandemic on the stock market returns of TASI.

Stock News Dataset Quality Assessment by Evaluating the Data Distribution and the Sentiment Prediction

  • Alasmari, Eman;Hamdy, Mohamed;Alyoubi, Khaled H.;Alotaibi, Fahd Saleh
    • International Journal of Computer Science & Network Security
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    • v.22 no.2
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    • pp.1-8
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    • 2022
  • This work provides a reliable and classified stocks dataset merged with Saudi stock news. This dataset allows researchers to analyze and better understand the realities, impacts, and relationships between stock news and stock fluctuations. The data were collected from the Saudi stock market via the Corporate News (CN) and Historical Data Stocks (HDS) datasets. As their names suggest, CN contains news, and HDS provides information concerning how stock values change over time. Both datasets cover the period from 2011 to 2019, have 30,098 rows, and have 16 variables-four of which they share and 12 of which differ. Therefore, the combined dataset presented here includes 30,098 published news pieces and information about stock fluctuations across nine years. Stock news polarity has been interpreted in various ways by native Arabic speakers associated with the stock domain. Therefore, this polarity was categorized manually based on Arabic semantics. As the Saudi stock market massively contributes to the international economy, this dataset is essential for stock investors and analyzers. The dataset has been prepared for educational and scientific purposes, motivated by the scarcity of data describing the impact of Saudi stock news on stock activities. It will, therefore, be useful across many sectors, including stock market analytics, data mining, statistics, machine learning, and deep learning. The data evaluation is applied by testing the data distribution of the categories and the sentiment prediction-the data distribution over classes and sentiment prediction accuracy. The results show that the data distribution of the polarity over sectors is considered a balanced distribution. The NB model is developed to evaluate the data quality based on sentiment classification, proving the data reliability by achieving 68% accuracy. So, the data evaluation results ensure dataset reliability, readiness, and high quality for any usage.

History of The Legal Developments of Corporations in Saudi Arabia

  • Alzhrani, Abdulrahman AA
    • International Journal of Computer Science & Network Security
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    • v.22 no.8
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    • pp.420-424
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    • 2022
  • The Arab Automotive Company was the first corporation in Saudi Arabia and was founded in 1928. Since then, the number of Saudi corporations had increased. In 1985, Tadawul (The Saudi Stock Exchange ) was instituted under the supervision of the Saudi Arabian Monetary Authority (SAMA) and the base value of the index was 1000. This decision came as a response to accelerated growth in the number of Saudi corporations which had increased during the 1970s as the Saudi's economy developed.

Factors Affecting Climate Change Accounting Disclosure Among Saudi Publicly List Firms on the Saudi Stock Exchange Market

  • Asaad Mubarak Hussien, MUSA;Abubkr Ahmed Elhadi, ABDELRAHEEM;Abbas Abdelrahman, ADAM
    • The Journal of Asian Finance, Economics and Business
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    • v.10 no.2
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    • pp.99-108
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    • 2023
  • This study's goal is to investigate the effects of board size, the number of annual board meetings, the profitability of the company, and the audit Committee on the disclosure of climate change in Saudi companies listed on the stock exchange. It was conducted to evaluate affecting some factors on carbon emissions by the regression model. The study uses the content analysis method. Data was collected from the annual and sustainability reports, and the platform database Refinitiv, an LSEG (London Stock Exchange Group Company) for the period 2018 to 2021. The study sample is 51 companies. The study findings showed Saudi Arabia saw its first significant overall drop in CO2 emissions with a 22.61 MtCO2 decline (3.93%) in 2018. The study revealed a positive connection between the size of the director's board, and the disclosure of carbon emissions in Saudi firms listed on the stock market. While other factors are not related to the number of director's board meetings, the audit committee, and the profitability of the company on the disclosure of carbon emissions in the Saudi companies listed on the stock exchange.

Does Ramzan Effect the Returns and Volatility? Evidence from GCC Share Market

  • ABRO, Asif Ali;UL MUSTAFA, Ahmed Raza;ALI, Mumtaz;NAYYAR, Youaab
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.7
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    • pp.11-19
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    • 2021
  • The study aims to investigate the impact of seasonality in Gulf Cooperation Council (GCC) countries' share market during the month of Ramadan. It helps in finding the opportunities for stock market investors to earn abnormal (returns) gain by investing during Ramadan in GCC stock markets. This study uses stock returns data of GCC countries (Saudi Arabia, Bahrain, Qatar, Kuwait, Dubai, and UAE) from January 2004 to November 2019. Stock prices indexes of GCC stock markets have been obtained from Datastream. The ARCH-GARCH model is used to study the impact of the Ramadan month on the return and volatility of the stock market in GCC countries. The results showed that the Ramadan month has a significant impact on share market prices in Saudi Arabia and the United Arab Emirates. However, Ramadan has an insignificant impact on share market prices in Bahrain and Oman. The study found no evidence of serial correlational between residuals in Kuwait; meaning that stock return was not dependent on the prior stock returns in Kuwait, therefore, we cannot go for forecasting. The ARCH-LM test statistic for Qatar does not fulfill the requirement of a good regression model; therefore, we cannot go for forecasting or testing the hypothesis of Qatar.

Testing the Information Content of Sustainability Reports for Telecommunications Companies in the Kingdom of Saudi Arabia

  • DIFALLA, Samhi Abdelaty;BELOUADAH, Fateh
    • The Journal of Asian Finance, Economics and Business
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    • v.9 no.10
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    • pp.137-145
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    • 2022
  • This study aims to test the information content of sustainability reports issued by the most significant telecommunications companies operating in the Kingdom of Saudi Arabia (Stc, Zain, and Mobily), and their compatibility with the national sustainability standards issued by the Ministry of Commerce in the Kingdom of Saudi Arabia in light of the Kingdom's vision 2030, and its impact on the stock exchange indices of these companies. The event study methodology was used to study the impact of publishing sustainability reports on stock prices and the trading volume of these companies' shares in the Saudi stock market during the period from (October 2020 to March 2021). The results indicate a significant impact of the information contained in the sustainability reports on stock prices and trading volume in the stock market, and the importance of directing the company's management towards more disclosure of information about sustainability in its environmental, social, and economic aspects instead of focusing only on information related to the financial performance and economic activity of the company. This encourages the listed companies to disclose the sustainability of the financial reports and standardize the form in which these disclosures are prepared.

Guarantees of Applying Disclosure and Transparency on the Companies Listed in the Saudi Capital Market

  • Moanes, Hani Mohamed
    • International Journal of Computer Science & Network Security
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    • v.22 no.4
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    • pp.274-284
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    • 2022
  • By explaining the essence of corporate governance as well as disclosure and transparency, the study examined the guarantees of applying disclosure and transparency to firms listed on the Saudi stock exchange. The research also addressed the disclosure and transparency duties of firms listed on the Saudi stock exchange. Finance to prepare a prospectus, as the Capital Market Authority's regulations required that the prospectus includes information that enables the investor in securities to make his investment decision based on real foundations based on the issuing company's financial position and to ensure that companies fulfill that disclosure in the prospectus. Firms who fail to disclose are required by law to do so, and the Capital Market Authority's laws mandate companies listed on the financial market to regularly report fundamental events linked to the issuer or the securities issued by it. The Capital Market Authority must make it available to the public dealing with the business issuing the securities, and The Capital Market Authority's Law and Regulations have imposed fines on corporations that do not comply with disclosure and make the Board of Director's report available. The research focused on activities that the legislator deemed to be a breach of the obligation of openness, such as the danger of many measures aimed at ensuring the impartiality and transparency of trading in the Saudi financial market, as well as the absence of conflicts of interest. The research also addressed the sanctions imposed on The source for failing to meet the obligation of disclosure and openness, as well as the mechanisms of compensating persons harmed by the failure to meet that responsibility.

Modeling and Forecasting Saudi Stock Market Volatility Using Wavelet Methods

  • ALSHAMMARI, Tariq S.;ISMAIL, Mohd T.;AL-WADI, Sadam;SALEH, Mohammad H.;JABER, Jamil J.
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.11
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    • pp.83-93
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    • 2020
  • This empirical research aims to modeling and improving the forecasting accuracy of the volatility pattern by employing the Saudi Arabia stock market (Tadawul)by studying daily closed price index data from October 2011 to December 2019 with a number of observations being 2048. In order to achieve significant results, this study employs many mathematical functions which are non-linear spectral model Maximum overlapping Discrete Wavelet Transform (MODWT) based on the best localized function (Bl14), autoregressive integrated moving average (ARIMA) model and generalized autoregressive conditional heteroskedasticity (GARCH) models. Therefore, the major findings of this study show that all the previous events during the mentioned period of time will be explained and a new forecasting model will be suggested by combining the best MODWT function (Bl14 function) and the fitted GARCH model. Therefore, the results show that the ability of MODWT in decomposition the stock market data, highlighting the significant events which have the most highly volatile data and improving the forecasting accuracy will be showed based on some mathematical criteria such as Mean Absolute Percentage Error (MAPE), Mean Absolute Scaled Error (MASE), Root Means Squared Error (RMSE), Akaike information criterion. These results will be implemented using MATLAB software and R- software.