Factors Affecting Stock Prices in the UAE Financial Markets

Al‐Tamimi, Hussein A. Hassan; Alwan, Ali Abdulla; Rahman, Arsil Ainun

doi:10.1080/15475778.2011.549441

Cited by 56 publications

(42 citation statements)

References 18 publications

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“…Chandrasekhar and Pal [7] in the post election scenario, the holding patterns of different sensex based companies were affected by withdrawal of foreign portfolio capital. Al Tamimi [8], in his study on UAE markets concluded that besides fundamental factors influencing the stocks some external factors' influence (GDP, OIL prices, CPI etc) can also be seen. Jaskiran and Ravinder [9] in their study revealed that the FIIs are contributing to major stock trading and there is a need for the retail investors to take an active participation in trading so as to avoid potential danger in case of withdrawal of funds by FIIs at any point of time in future.…”

Section: Literature Overviewmentioning

confidence: 99%

Impact of Non-financial Determinants on Indian Banking Stocks – An Empirical Analysis

Ram

Dave

Rajesh

2019

JEMT

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Aims: This study aims at analysing the influence of some of the most important external factors (macro economic variables) on the stock prices particularly the banking stocks of India listed in stock exchanges of the country. Sample Design: Multistage design. Place and Duration of Study: Public and private sector banks of India listed in stock exchanges of the country for a 12 year period i.e. 2006-07 to 2017-18. Methodology: On the basis of market capitalisation the top five banks from each sector i.e. public and private are selected. The data of stock prices of these banks is collected from the annual reports of the banks. The data of the explanatory variables is collected from the reports of Central Statistics Office, financial journals etc. Results: The impact of the explanatory macroeconomic variables on the market prices of these banking stocks for the period is analysed with the help of suitable statistical techniques viz., Mean, Standard Deviation, correlation, and Multiple Regression Analysis. Conclusion: Some of the macroeconomic variables are influencing the stock prices of the banks.

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Section: Literature Overviewmentioning

confidence: 99%

Impact of Non-financial Determinants on Indian Banking Stocks – An Empirical Analysis

Ram

Dave

Rajesh

2019

JEMT

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“…There are many factors that have the tendency of affecting stock prices and the stock market in general (Shrestha & Biggyan, 2014). Studies by (Atiq et al, 2010;Al-Tamimia et al, 2011) categorized the factors that affect stock market to include company fundamentals, technical or external factors and market sentiments (behavior).…”

Section: Stock Markets' Reaction Determinantsmentioning

confidence: 99%

“…A study by (Al-Tamimia et al, 2011) highlight some of the fundamental factors of a company that might influence stock prices to include performance of the company, a change in board of directors, appointment of new management, and the creation of new assets, dividends, earnings, etc. A book titled "Corporate Finance: A Focused Approach" by (Ehrhardt & Brigham, 2014) states that "shareholders care about all dividends, both current and those expected in future".…”

Section: Company Fundamentalsmentioning

confidence: 99%

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Review of Stock Markets’ Reaction to New Events: Evidence from Brexit

Quaye¹,

Mu²,

Abudu³

et al. 2016

JFRM

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Several studies have evolved to deal with the determinants of stock market volatility. However, there exists a gap in literature with regards to the interrelation among the broad categories of factors that trigger stock market reaction namely company fundaments, technical factors and market sentiments. This paper provides a holistic and comprehensive theoretical review of drivers of stock markets' reaction as well as designs an interrelated conceptual framework of the factors that influence investors' decision making to fill the gap in literature. Brexit is presented as a case study to illustrate how investors and stock markets are affected by new events or information. This study will reveal some of the global staggering effects of Brexit at the end of trading on June 24, 2016 in areas such as currencies, stock markets, banks, commodities, bonds, automakers and homebuilders as well as hedge fund. Barely 24 hours after the results of Brexit were declared; global stock markets lost about $2 trillion in value. The British pound plunged to almost $1.33, its lowest level in over 30 years against the US dollar and gold proved to be one of the few safe havens for investors on that day. In order for investors to insulate themselves against loses from Black Swans events, the conclusion of this study recommends some protective mechanisms for investors which include avoidance of overexposure and stockpiling of cash.

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“…Previous studies such as those by (Al-Tamimi et al, 2011;Sharif et al, 2015) consider regression analysis for the prediction of stock prices using other predictor variables even though it is understood that there is a dependent relationship within the data due to its time series nature. Despite failing to meet the underlying assumption of independence, regression can still be used to statistically show the relationships between stocks and other variables that are known from an economic standpoint.…”

Section: Introduction To the Studymentioning

confidence: 99%

Model Comparison for the Prediction of Stock Prices in the NYSE

Switlyk

Shang²

2019

Journal of Mathematics and Statistics

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The stock market is an integral part of investments as well as the economy. The prediction of stock prices is an exciting and challenging problem that has been considered by many due to the complexity and noise within the market and to the potential profit that can be yielded from accurate predictions. We aim to construct and compare models used for the prediction of weekly closing prices for some of the top stocks in the New York Stock Exchange (NYSE) and to discuss the relationship between stock prices and the predictor variables. Relationships explored in the study include that with macroeconomic variables such as the Federal Funds Rate and the M1 money supply and market indexes such as the CBOE Volatility Index, the Wilshire 5000 Total Market Full Cap Index, the CBOE interest rate for 10-year T-notes and bonds, and NYSE commodity indexes including XOI and HUI. Models are built using methods of regression analysis and time series analysis. Models are analyzed and compared with one another by considering their predictive ability, accuracy, fit to the underlying model assumptions, and usefulness in application. The final models considered are a pooled regression model involving the median weekly closing price across all stocks, a varying intercept model considering the weekly closing price for each individual stock, and an ARIMA time series model that predicts the median weekly closing stock price based on past prices.

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Factors Affecting Stock Prices in the UAE Financial Markets

Cited by 56 publications

References 18 publications

Impact of Non-financial Determinants on Indian Banking Stocks – An Empirical Analysis

Impact of Non-financial Determinants on Indian Banking Stocks – An Empirical Analysis

Review of Stock Markets’ Reaction to New Events: Evidence from Brexit

Model Comparison for the Prediction of Stock Prices in the NYSE

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