Main Stock Index Research Articles

Monetary Policy and Stock Market Return: The Case of Saudi Arabia Interest Rates hikes and Stocks Returns

The purpose of this research is to examine whether changes in macroeconomic variables have an effect on Saudi Arabia's main index, TASI and whether Monetary policy actions produce positive, negative or no effect at all for all listed companies. Accordingly, we examine the stock price adjustment around announcements of changes in interest rates, we examine the impact of a series of interest rate hikes on the stock returns under the main stock index in the Saudi Stock Market, TASI. The data covers four events between 16 March 2021 to 5 October 2022. We use an event study approach, with an estimation window length of [-250,-11] and an event window length of [-10,7], and we apply the OLS market model for daily data. The significance of the cumulative abnormal return CAAR is tested using the t statistics. The empirical results show that TASI responds negatively to three out of four announcements of interest rate hikes. The positive reaction occurs during the July 2022 monetary action. The positive reaction is attributed to the rising oil prices during that period. Finally, the results of this research open a window for future research to examine the impact of interest rates on the Saudi stock market over the long run.

Is a PhD an entrance ticket for an executive board?

This article deals with the question of whether many years of academic training can be the foundation for a successful management career. An analysis of all ATX, DAX and SMI-listed companies was carried out and the highest level of education of all executive board members was analysed. Statistical analyses were used to establish the connection between education and the position and function on an executive board. In addition, it was also analysed whether there is a statistical correlation between the composition of the board of directors and gender. There is a relationship between an academic education and the likelihood of being able to pursue a career on an executive board. However, a PhD is not necessarily a guarantee. Currently, gender also has a significant influence on management careers. This article provides an in-depth insight into the main stock indices in the German-speaking world. It should also serve as motivation that a proper academic education is a solid basis for one of the most sought-after jobs in a public limited company.

Uncertainty in Central and Eastern European markets. Evidence from Twitter-based uncertainty measures

ABSTRACT Purpose Increasing uncertainty has frequently been associated with alterations in investor behaviour in scientific discourse. Central and Eastern Europe (CEE) despite generating 10% of the EU’s GDP, has largely been overlooked in investigations into the relationship between socialmedia uncertainty and its impact on the stock markets. The purpose of this article is to examine the dependence between the largest stock indices of the CEE markets and Twitter uncertainty measures. Design/methodology/approach The Vector Autoregressive (VAR) methodology, specifically bivariate Granger causality is applied to investigate the relationship between social media messages and market behaviour reflected in returns of the main stock indices for Croatian CROBEX, Czech PX, Hungarian BUX, Polish WIG and Romanian BET indices. Findings The author discovers substantial evidence indicating that the CEE region exhibits heterogeneity concerning its relationship with uncertainty in stock markets, with measures related to recession, political events, and natural disasters being of utmost relevance. Originality/value­ While the VAR model and Granger causality have been studied in relation to many markets, there is a lack of studies on the effect of Twitter-based wider spectrum of uncertainty measures on the CEE region. Twitter-based uncertainty measures on the CEE region represent a significant knowledge gap, that when addressed, could offer valuable insight into the region’s financial dynamics, thus potentially affecting hedging strategies, enhancing investor’s awareness and informing policy-making decisions.

Impact of Automobile Companies Stock Returns on Indian Stock Market Indices with Special Reference to Nifty Fifty Index

The Nifty Fifty Index has a free-float market capitalization-weighted index.it represents the weighted average of the top 50 Indian companies listed on the National Stock Exchange ,and it is one of the main stock indices being used in India, besides the BSE Sensex of the Bombay Stock Exchange. The Nifty 50 index represents 62% of the free float market capitalization of the stocks listed in the NSE (NATIONAL STOCK EXCHANGE) as on September 30,2022.sectors ‘s stocks are performing more consistently and provide high return with high risk in (NSE)NATIONAL STOCK EXCHANGE ,these stocks are emerging as most reliable stock in capital market. Nifty Fifty Index also influenced by the variation in Automobile Industry which happened due to market fluctuation .The Automobile Sector has influenced by micro and macro indicators So in this, researcher found a relationship between Nifty Fifty Index and different selected Automobile companies by the application of some statistical tools like as regression to examine the impact of different companies stock return on Nifty fifty Index and correlation to check the relationship between Nifty Fifty and Automobile Sector Companies. And for this study data of 18 years from 1 January 2003 December 2022 has been taken. After the application of test this can be concluded that nifty fifty Index have impact of Automobile companies’ stock return variation on it and Nifty fifty index and Automobile companies are highly positively correlated with each other. At last it can be recommended that one variable can be used for forecasting another variable. So it can be concluded that development of economy and capital market has a relationship with performance of Automobile Industry in stock market and its return providing capacity. This study is going to be helpful for those investors who prefer to invest in Automobile Sector.

Энтропия основных фондовых индексов как показатель неопределенности состояния экономики

The article considers the problem of assignment the optimal numerical criterion for assessment the stability and securi-ty of the economics, which allows to analyze the state of the economics and make decisions on its regulation. It is pro-posed to use the value of economics uncertainty as such criterion. The uncertainty is calculated as the entropy of the main stock indexes. The authors had calculated the entropy of the main stock indices over a ten-year time interval, performed a comparative analysis of the obtained results with historical data of the known economic policy uncertain-ty index, explained the choice of the entropy value as an uncertainty indicator for the economics.

The effects of the macroeconomic factors on the Bucharest Stock Exchange during the Covid-19 pandemic

"The purpose of the paper is to observe and analyze how the dynamics of macroeconomic factors influence the evolution of the Bucharest Stock Exchange (BVB) through the lens of the main stock indices (BET, BET-Plus, BET-FI), but also of the stock market capitalization. The research carried out consists of four stages. First, the monthly values of the macroeconomic factors considered were collected (inflation rate, reference interest rate, unemployment rate, RON-EURO and RON-USD exchange rates, producer price index, gold price, average salary and the Covid-19 number of cases) during the period 2020-2021, as well as the monthly values of the Bucharest Stock Exchange market indices (BET-Plus, BET and BET-FI) and of the stock market capitalization. These data were collected from the websites: www.bvb.ro (Bucharest Stock Exchange), www.bnr.ro (National Bank of Romania), www.innse.ro (National Institute of Statistics) and www.ms.ro (Ministry of Health). Then, the descriptive statistics was used to describe the collected data (mean value, standard deviation, minimum/ maximum value). This step is followed by the use of the Pearson correlation to capture the correlation between each stock market index and the macroeconomic factor included in the analysis. And finally, multiple regression was used to see exactly how the Romanian stock market indices are influenced by any changes of macroeconomic factors. Keywords: macroeconomic factors, Bucharest Stock Exchange, stock market indices, Covid-19 pandemic JEL Classification: B22, C32, G10"

Application of Fractal Geometry in Studies of the Bulgarian Financial Market

The present study presents and summarizes in a condensed manner the basic postulates and concepts arising from the principles and ideas of fractal geometry, applied in the field of behavior and dynamics of financial markets. A comparative analysis has been made between the classic financial and statistical indicators for measuring and summarizing a certain state of the financial system, on one hand, and the main quantitative parameters resulting from the fractal analysis, on the other. In the last part, an analysis and test for fractality of the Bulgarian financial market has been made represented by the main stock index – SOFIX.

Does COVID-19 Affect the Growth of the Fourth Industrial Revolution?

ABSTRACT The COVID-19 pandemic might accelerate Fourth Industrial Revolution such as FinTech, AI and Robotics. This study explores impact of the COVID-19 on Fourth Industrial Revolution by quantifying such an impact on stock market. Stock indices and ETFs are handled to find log-return distributions via kernel estimation. Before, during and after outbreak of the COVID-19, distributions and related measures are investigated. Results reveal that E-commerce and Fourth Industrial Revolution have grown 1.5-1.7 times in increase rates of daily net returns, compared to main stock indices. A statistical test supports that AI & Robotics sector has grown under influence of the COVID-19.

STOCK MARKET REACTION TO WHO’S COVID-19 ANNOUNCEMENT IN ASEAN-5 REGION

The aims of this research is to analyze the stock market reaction in the ASEAN-5 region (Indonesia, Malaysia, Singapore, Philippines, and Thailand) to the announcement of the global COVID-19 pandemic by the World Health Organization (WHO). The method used is an event study with abnormal return as the independent variable. The sample in this study is the main stock index of ASEAN-5 countries. Empirical results showed that there was a significant and insignificant abnormal return on certain days around the announcement of the COVID-19 pandemic by WHO in ASEAN-5. Subsequent findings showed that there was no difference in abnormal returns before and after the global announcement of COVID-19 by WHO.

Sustainability as a strategy base in Spanish firms: Sustainability reports and performance on the sustainable development goals

AbstractThis article examines corporate sustainability reports, the standards they use, and their connection to performance on the sustainable development goals (SDGs) from firms in the main Spanish stock index. The investigation was performed through an exploratory, descriptive, analytic study as well as examination of the disclosure and performance on the SDGs after Law 11/2018 went into effect in Spain. The study methods used include parametric correlations that explain the associations between the global reporting initiative (GRI) and environmental, social, and governance (ESG) standards and the level of performance on SDGs/ESG in the sustainability reports. We found that all firms present their verified sustainability reports, that the level of ESG information is above 75%, and that the GRI is the sustainability standard used. Further, all firms contribute on average a 75% level of information on all goals and on each of the 17 goals for the 2030 Agenda. We obtain significant analogies in level of disclosure of GRI‐ESG information and level of performance on the SDGs/ESG. In addition, the higher the level of information on environmental GRI standards, the better the firm's position in the environmental SDG ranking.

Impact of the war in Ukraine on the global stock market

This article focuses on and analyzes how the full-scale invasion of Russia on the territory of Ukraine on February 24, 2022, affected and continues to affect the part of the global capital market where securities are issued, bought and sold, namely the stock market. It is determined what any price changes are based on here; how stock markets can reflect the expectations of a certain group of people, in this case investors around the world, during a period of war; sanctions and pressure on the stock market. Also, the average response of twenty companies included in the Top-500 best stocks in the Center for Research in Security Prices database to percentage changes in the weighted commodity price index was evaluated. That is, we estimated how much a 1% change in the commodity price index would change the share prices of each of the 20 companies. It is determined separately how the military conflict affected the securities of American companies operating in various industries; for whom the war helped to increase capitalization, and for whom it contributed to the deterioration of the general financial condition. How the ranking of the best-performing S&P 500 stocks has changed in 2022. Why on September 13, the share prices of many global companies decreased, and the three main stock indexes (Dow Jones Industrial Average, Nasdaq Composite and S&P 500) had their worst day since June 2020. Forecast of their further changes. Separately, in addition to the American one, the changes that took place in the stock markets of Eastern countries, using the example of China, Thailand, India and Indonesia, are highlighted. Expected changes in the Russian stock market and the possibility of its complete disappearance due to sanctions imposed by various countries of the world are described. The situation on the market of Ukraine itself and the options of what exactly to invest in for domestic investors during the period of active military operations were considered. In addition to all this, the solution to problems related to the volatility of the stock market is highlighted. Thus, the question of the influence of the war between Ukraine and Russia on the state of the world stock markets, in modern realities, is paid a lot of attention not only by Ukrainian scientists, but also by foreign ones. This is not surprising, since it is impossible to ignore that the recent events have caused a chain effect, affecting firstly the prices of goods, the volume of exports, and subsequently the capitalization and growth or decline of the prices of securities of companies around the world.

Stock volatility may trigger the onset of acute coronary syndrome: A nationwide case-crossover analysis

<p>Stock volatility, an adverse psychological stressor, has been linked to cardiovascular mortality or hospitalization. However, no studies had quantified the risk of acute coronary syndrome (ACS) onset from stock market fluctuation. Using the time-stratified case-crossover design, which could control for the potential confounding from time-invariant, we conducted the analysis based on a nationwide registry comprising of 2,113,728 ACS patients in China from January, 2015 to December, 2021. We obtained daily returns (%) of three main stock indexes in Chinese Mainland, and matched the case and control days of ACS onset on hourly level. The data were analyzed using conditional logistic regression models. The associations between daily stock returns and ACS onset were U-shaped with stock rise and fall both increasing the risk of ACS onset. The excess risks associated with each 1%-decrease of daily stock returns for Shanghai, Shenzhen and ChiNext index were 0.96% (95%CI: 0.40,1.51), 0.65% (95%CI: 0.27,1.03) and 0.87% (95%CI: 0.52,1.21) at the concurrent day, respectively; and a 1%-increase of daily stock returns was associated with 1.06% (95%CI: 0.61,1.52), 0.45% (95%CI: 0.11,0.80) and 0.17% (95%CI: -0.08,0.41) increases of ACS onset, respectively. Thereafter, most of the associations gradually attenuated, disappeared after 3 days. The associations were significant for unstable angina and ST-segment-elevation myocardial infarction, but not for non-ST-segment-elevation myocardial infarction. This nationwide study provides novel and robust evidence that both stock rise and fall could increase the risk of ACS onset, highlighting the importance of heart care and psychological support during fluctuations of stock market.</p>

Characteristic period analysis of the Chinese stock market using successive one-sided HP filter

<abstract><p>Time series of stock indices usually exhibit nonstationary and chaotic behavior. Analysis of the characteristics of the business cycle can reveal pertinent insights into the evolution of the stock volatility. This paper studies the characteristic periods of three main Chinese stock indices, i.e., the Shanghai composite index (SHCI), the Shenzhen component index (SZCI), and the Hang Seng index (HSI). We propose an approach based on the successive one-sided Hodrick-Prescott (SOHP) filtering and wavelet analysis of the empirical data from the stock markets, to detect their characteristic periods. In particular, the SOHP filter, which preprocesses the time series with a moving-horizon optimization procedure, enables us to extract the volatility cycles in different time scales from a stock time series and reduce noise distortion. The characteristic period of the stock index is then determined by the maxima of the wavelet power spectrum of the filtered data. The evolution of the characteristic period in time demonstrates rich information concerning the period stability of the stock market, as well as the cause and effect of the stock crash. To facilitate solving the moving-horizon optimization issue of the SOHP filter, we also present an incremental HP filtering algorithm, which greatly simplifies the involved inverse matrix operation in the HP-type filters.</p></abstract>

Hedging and safe haven properties of Ethereum: evidence around crises

ABSTRACT Given the broad scope of Ethereum and the wide range of its decentralized applications, this paper investigates its hedging and safe haven capabilities against main fiat currencies, stock and bond indices in the US and Europe, and crude oil and gold markets. We use daily data from January 2016 until February 2021 and apply percentile regressions and crisis event interaction analysis by selecting four worldwide events including US presidential elections, the Brexit referendum, and COVID-19. We reveal that Ethereum does not act as a hedge or a safe haven against fiat currencies, stock and bond indices, and gold. However, it does act as a strong safe haven against crude oil in calm and turbulent periods and against European bonds during market turbulence. The study provides insights to regulators and investors into the potential role of Ethereum in investment decision-making and protecting financial market participants in the US and EU.

A Statistical Analysis of Chinese Stock Indices Returns From Approach of Parametric Distributions Fitting

The stock price process in China is full of uncertainty hence the stock indices were introduced to serve as indicators of the financial market. How to capture the statistical characteristics of Chinese stock indices returns by the method of parametric distributions fitting could be useful in the fields of econometrics and risk management. In this paper, we use a wider range of parametric distributions to model four main Chinese stock indices. We find a generalization of the Student’s t distribution is shown to provide the best fit.

СУЧАСНІ ФІНАНСОВІ ТА ТОВАРНІ РИНКИ: ХАРАКТЕРИСТИКИ ТА ВИМІРИ

Modern financial systems are global in nature. The article reveals the current state of world financial markets. The example of stock index trends shows the main trends in global financial markets as a result of global challenges (the Covid-19 pandemic and the war in Ukraine). The trends of stock market indicators in different regions of the world are analyzed. The article reveals the current factors that affect the trends of stock indices. The influence of economic and political consequences caused by the pandemic and war on the further development of the world economy is studied. The role of geopolitical events on the development of commodity markets, in particular gold and oil, is shown. The main stock indices and how they react to changes in the world economic environment are analyzed. Thus, the article shows that negative global signals are causing concerns about rising inflation around the world, and rising rates are affecting investor sentiment. It has been proven that financial markets can calm down from the global decisions of international leaders and organizations. However, very often geopolitical decisions show signs of indecision, which affects the continuation of hostilities in Ukraine and contributes to the subsequent fluctuations of financial indicators. t is shown that the volatility of financial markets will remain high in the last week of June, due to the planned expiration of contracts for derivative instruments in June and political decisions of the G7 countries, which may ban Russian gold imports on Tuesday, June 28. The article analyzes the characteristics of the trends of major world stock indices and reveals the possible prospects for their development, as well as identifies the main factors of stock market trends at the present stage of development. The current state of the financial market of Ukraine is studied.

CURRENT STOCK MARKET INDICATOR TRENDS AGAINST THE BACKGROUND OF COVID-19 AND THE RUSSIAN-UKRAINIAN WAR

The scientific work analyzes stock indices and how they react to external changes. Characteristic features of the main world stock indices are highlighted and described, and possible prospects for their development are revealed. The article reveals the meaning of such concepts as stock indices, considers their essence, key indicators, as well as the impact of global problems on market fluctuations. The work is devoted to the study of some of the main problems of humanity during the last decade. The authors consider how Covid- 19 and the Russian-Ukrainian war affected the stock markets. The work provides an analysis of the features and development trends of the main stock indices against the background of global events. The impact, economic and political consequences, possible threats caused by the pandemic and war, as well as prospects for the further development of the world economy are revealed. The study identifies the main problems and trends in the development of stock markets at the current stage. Covid-19 has shown how sensitive markets can be to global societal issues, including how it can significantly affect the global economy and stock indices. Also, an equally important problem considered in the article is the impact of the Russian-Ukrainian war on the economy and its further consequences are predicted. In general, the beginning of the full-scale armed aggression of the Russian Federation on the territory of Ukraine became a significant shock and challenge after the almost complete overcoming of the global Covid-19 pandemic. This discovery study examines the impact of the Covid-19 pandemic and war on USA, European, and East Asian stock indices. Our results show that changes in the background of Covid-19 and war had a significant impact on the Dow Jones, Nikkei 225, FTSE 100 and NASDAQ 100.

An Optimal Weighted Combined Model Coupled with Feature Reconstruction and Deep Learning for Multivariate Stock Index Forecasting

Stock index prediction plays an important role in the creation of better investment strategies. However, prediction can be difficult due to the random fluctuation of financial time series. In pursuit of improved stock index prediction, a hybrid prediction model is proposed in this paper, which contains two-step data pretreatment, double prediction models, and smart optimization. In the data pretreatment stage, in order to carry more information about the prediction target, multidimensional explanatory variables are selected by the Granger causality test, and to eliminate data redundancy, feature extraction is inserted with the help of principal component analysis; both of these can provide a higher-quality dataset. Bi-directional long short-term memory and bi-directional gated recurrent unit network, as the concurrent prediction models, can improve not only the precision, but also the robustness of results. In the last stage, the proposed model integrates the weight optimization of the cuckoo search of the two prediction results to take advantage of both. For the model performance test, four main global stock indices are used. The experimental results show that our model performs better than other benchmark models, which indicates the potential of the proposed model for wide application.

The impact of environmental performance on stock prices in the green and innovative context

This study examines the impact of environmental performance on firms' stock prices, considering the moderating effect of the green and innovative environmental context by country. Renewable energy policies, green technologies, and foreign trade form this environmental context of interest for the reduction of carbon emissions. Using a sample of 2638 firm-year observations for the firms listed in the main stock index of 16 European countries over the period of 2005–2017, we find that environmental performance is value-relevant, except during the worst years of a crisis, when it is not significant. Two elements of the green technological framework, namely, renewable energy policies and the potential transmission effect of technology through foreign trade, are valued by investors as offsetting factors of the positive effect exerted by carbon performance on the firm's value. This is consistent with the slow and costly adoption of greener technologies. However, registered green patents appear to be a turning point, showing a significant positive effect on the relationship between firms' environmental performances and their market values. Again, the crisis period interferes with deepening the negative effect of renewable energy policies and cancelling out the effect of green patents and foreign trade. On one hand, our results highlight the market's role in making inefficiencies visible and showing the potential future losses of green and innovative policies; on the other hand, the hampering interference of crisis periods must be considered by policymakers.

Fractional differentiation and its use in machine learning

This article covers the implementation of fractional (non-integer order) differentiation on real data of four datasets based on stock prices of main international stock indexes: WIG 20, S&P 500, DAX and Nikkei 225. This concept has been proposed by Lopez de Prado [5] to find the most appropriate balance between zero differentiation and fully differentiated time series. The aim is making time series stationary while keeping its memory and predictive power. In addition, this paper compares fractional and classical differentiation in terms of the effectiveness of artificial neural networks. Root mean square error (RMSE) and mean absolute error (MAE) are employed in this comparison. Our investigations have determined the conclusion that fractional differentiation plays an important role and leads to more accurate predictions in case of ANN.