Journal articles on the topic 'Stock market'
To see the other types of publications on this topic, follow the link: Stock market.
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'Stock market.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
Truong, Loc Dong, H. Swint Friday, and Tran My Ngo. "Market Reaction to Delisting Announcements in Frontier Markets: Evidence from the Vietnam Stock Market." Risks 11, no. 11 (November 16, 2023): 201. http://dx.doi.org/10.3390/risks11110201.
Full textAbstract:
This paper aims to measure the effects of delisting on stock returns for the Vietnam stock market. This study employs a sample of 118 stocks that were compulsorily delisted from the market between January 2011 and December 2021. Using an event study methodology, the empirical findings confirm that the delisting has negative effects on stock returns in the Vietnam stock market. Specifically, results derived from tests show that the average abnormal return of delisted stocks continuously declines during three trading days following the announcement of delisting. Moreover, it is found that the differences in cumulative abnormal returns between post-delisting and pre-delisting periods are significantly negative for all tracking periods. Apart from the negative effect of delisting on stock abnormal returns, we also find that the impact of delisting on stock returns for smaller companies is greater than for bigger companies. These results imply that investors can earn abnormal returns by using delisting information in the Vietnam stock market.
2
Yaya, OlaOluwa, Olayinka Adenikinju, and Hammed A. Olayinka. "African stock markets’ connectedness: Quantile VAR approach." Modern Finance 2, no. 1 (February 6, 2024): 51–68. http://dx.doi.org/10.61351/mf.v2i1.70.
Full textAbstract:
The present paper investigates African stock markets’ linkages by considering stocks in the continent’s largest economies, specifically Egypt, Kenya, Morocco, Nigeria, South Africa, and Tunisia. Using a dataset that spanned November 25, 2008, to September 18, 2023, the quantile connectedness approach of Chatziantoniou et al. (2021) is employed, and the results unfold these interesting dynamics of African market connectivity: (i) In the bearish market phase, South African stock dominated the entire network, transmitting shocks to the remaining stocks, while Moroccan and Kenyan stocks played similar role mildly. (ii) In the bullish market phase, Nigerian stock dominated the market as a major net transmitter of shock supported by South African and Kenyan stock markets. (iii), The Egyptian and Tunis stock markets are net shock receivers in both the bear and bull market phases. (iv), At the median quantile value, stocks become less riskier and the Kenyan stock market becomes the most vulnerable while Nigerian, Egyptian, and South African stock markets are influenced by other stock markets when markets are calm. (v), Though, African stocks are underperforming, interested portfolio managers will learn from the trading strategies to be adopted to maximize their returns. These findings will benefit portfolio managers, international stakeholders, and regulators.
3
Kirkulak Uludag, Berna, and Muzammil Khurshid. "Volatility spillover from the Chinese stock market to E7 and G7 stock markets." Journal of Economic Studies 46, no. 1 (January 7, 2019): 90–105. http://dx.doi.org/10.1108/jes-01-2017-0014.
Full textAbstract:
PurposeThe purpose of this paper is to examine volatility spillover from the Chinese stock market to E7 and G7 stock markets. Using the estimated results, the authors also analyze the optimal weights and optimal hedge ratios for the portfolios including stocks from E7 and G7 countries.Design/methodology/approachThe authors employed generalized vector autoregressive-generalized autoregressive conditional heteroskedasticity approach, developed by Ling and McAleer (2003), in order to analyze daily data on the national stock indices. Considering the late establishment of some E7 stock markets, the sampling covers the period from 1995 through 2015.FindingsThe findings indicate significant volatility spillover from the Chinese stock market to E7 and G7 stock markets. In particular, the Chinese stocks highly co-move with the stocks of countries within a same geographical region. While the highest volatility spillover occurs between China and India among E7 countries, the highest volatility spillover occurs between China and Japan among G7 countries. Furthermore, the examination of optimal weights and hedge ratios suggest that investors should hold more stocks from G7 countries than E7 countries for their portfolios.Originality/valueTo the best of the authors’ knowledge, this is the first study which investigates the volatility spillover in the stock markets of G7 and E7 countries. Moreover, the current study contributes particularly to the existing limited literature on the Chinese stock market. Since the Chinese stock market is not fully integrated to other markets and it is subject to intense government interventions, there is a widely accepted belief that the contagion effects from the Chinese stock market to other stock markets are not influential. This view discourages and limits the prospect studies. However, the findings of this paper refute this view and indicate significant interaction among the Chinese stock market and E7 and G7 stock markets.
4
Yousaf, Imran, Shoaib Ali, and Wing-Keung Wong. "An Empirical Analysis of the Volatility Spillover Effect between World-Leading and the Asian Stock Markets: Implications for Portfolio Management." Journal of Risk and Financial Management 13, no. 10 (September 25, 2020): 226. http://dx.doi.org/10.3390/jrfm13100226.
Full textAbstract:
This study employs the Vector Autoregressive-Generalized Autoregressive Conditional Heteroskedasticity (VAR-AGARCH) model to examine both return and volatility spillovers from the USA (developed) and China (Emerging) towards eight emerging Asian stock markets during the full sample period, the US financial crisis, and the Chinese Stock market crash. We also calculate the optimal weights and hedge ratios for the stock portfolios. Our results reveal that both return and volatility transmissions vary across the pairs of stock markets and the financial crises. More specifically, return spillover was observed from the US and China to the Asian stock markets during the US financial crisis and the Chinese stock market crash, and the volatility was transmitted from the USA to the majority of the Asian stock markets during the Chinese stock market crash. Additionally, volatility was transmitted from China to the majority of the Asian stock markets during the US financial crisis. The weights of American stocks in the Asia-US portfolios were found to be higher during the Chinese stock market crash than in the US financial crisis. For the majority of the Asia-China portfolios, the optimal weights of the Chinese stocks were almost equal during the Chinese stock market crash and the US financial crisis. Regarding hedge ratios, fewer US stocks were required to minimize the risk for Asian stock investors during the US financial crisis. In contrast, fewer Chinese stocks were needed to minimize the risk for Asian stock investors during the Chinese stock market crash. This study provides useful information to institutional investors, portfolio managers, and policymakers regarding optimal asset allocation and risk management.
5
Shkolnyk, Inna, Serhiy Frolov, Volodymyr Orlov, Viktoriia Dziuba, and Yevgen Balatskyi. "Influence of world stock markets on the development of the stock market in Ukraine." Investment Management and Financial Innovations 18, no. 4 (November 24, 2021): 223–40. http://dx.doi.org/10.21511/imfi.18(4).2021.20.
Full textAbstract:
Viewing the development of the stock market in Ukraine, the economy, which world financial organizations characterize as small and open, is largely determined by the trends formed by the global stock markets and leading stock exchanges. Therefore, the study aims to analyze Ukraine’s stock market, the world stock market, stock markets in the regions, and to assess their mutual influence. The study uses the data of the World Federation of Exchanges and National Securities and Stock Market Commission (Ukraine) from 2015 to 2020. Stock market performance forecasts are built using triple exponential smoothing. Based on pairwise correlation coefficients, the existence of a significant dependence in the development of the world stock market on the development of the American stock market was determined. Regarding the Ukrainian stock exchanges, only SE “PFTS” demonstrated its dependence on the US stock market. The results of the regression model based on an exponentially smoothed series of trading volumes in all markets showed that variations in the volume of trading on the world stock market are due to the situation on the US stock markets. Trading volume dynamics on Ukrainian stock exchanges such as SE “PFTS” and SE “Perspektiva” is almost 50% determined by the development of stock markets in the American region. Although Ukraine is geographically located in Europe, the results show a lack of significant links and the impacts of stock markets in this region on the major Ukrainian stock exchanges and the stock market as a whole.
6
Zhang, Yunqi, Zeqi Zhang, and Xiaoyu Zhang. "Stock Market Downturn and Stock Market Concentration." Journal of Economics, Finance and Accounting Studies 5, no. 2 (April 23, 2023): 152–63. http://dx.doi.org/10.32996/jefas.2023.5.2.12.
Full textAbstract:
As an important component of corporate inequality, stock market concentration has become a focus of attention in academia in recent years. However, existing literature focuses on its negative consequences, and research on the determinants of stock market concentration is scarce. This paper investigates for the first time how stock market downturns affect stock market concentration. Using data on stock markets in both the United States and China, we find a negative correlation between market-wide returns and stock market concentration. To address endogeneity and establish causal inference, we exploit two natural experiments: the COVID-19 pandemic and the subprime crisis. We find that stock market concentration increases during these crises, and we also find some heterogeneity between the United States and China. Our findings have important policy implications regarding inequality during market downturns.
7
Sharma, Gunjan. "A STUDY ON PERFORMANCE OF STOCKS OF BLUE CHIP COMPANIES IN INDIA." BSSS Journal of Management 14, no. 1 (June 30, 2023): 110–64. http://dx.doi.org/10.51767/jm1410.
Full textAbstract:
The main aims of this paper are to explain the discriminatory variables between the top 10 blue chip companies stocks in stock markets of the India. . Since there is relatively less empirical research on the stock selection in markets, with even less studies on the markets in the transition economies of India, this paper is designed to shed some light on the identification of blue chip stocks from Indian stock market. Results presented in this paper provide confirmatory evidence that the blue chip stocks from the selected stock markets of the Indian stock market can be identified by examining their dividend payout , Market price of share , EPS and relevant ratios were analyzed and research tools like Mean etc. The variables were tested with the help of hypothesis testing on the basis of ANNOVA to determine the performance of the selected stocks.
8
Lamichhane, Pitamber. "Individual Investors' Consciousness and Investment on Common Stocks." Journal of Academic Development 8, no. 1 (December 31, 2023): 45–60. http://dx.doi.org/10.3126/tjad.v8i1.64826.
Full textAbstract:
This paper analyzes Nepalese individual investors' consciousness and their investment on stocks. Investors’ consciousness creates positive environment for the investment which helps in capital formulation. This study has employed explorative research design to explain investors’ consciousness and investment on common stock in Nepalese stock market. Data were collected through survey from individual stock investors using structural questionnaire in Kathmandu valley in 2021. The estimated result of this study shows the level of investors’ consciousness (investors’ education and training, access to information, understanding of subjects and learning expectations etc.) is more than desirable level of 50 percent. Similarly, result indicates that conscious investors have chance of holding more common stock which indicates positive association between investors’ consciousness and level of investment in common stocks. Moreover, survey result reveals that investors assert problems on accessing of market information while making investment on stock in Nepalese stock market. This paper concludes that stock market should disseminate sufficient information of stocks, stock markets, stock returns, rules and regulation of security markets, security trading mechanism etc. to the investors through various training programs to make alert them for their sound investment decisions in Nepalese stock markets.
9
Lamichhane, Baburam. "Market Turnover of Nepalese Stock Market." Journal of Nepalese Business Studies 10, no. 1 (February 5, 2018): 96–100. http://dx.doi.org/10.3126/jnbs.v10i1.19137.
Full textAbstract:
Securities market turnover is one of the major behavioral phenomena of stock market. It always depends on the demand and supply of the securities, so the market turnover assumes a number of trading share units, values of share turnover and percentage share value of stocks. This paper is concerned to analyze the different areas of stock units’ turnover and value coverage of stock market .descriptive research design is applied for analyzing the stock market condition. The coverage of share units and share of value weight is analyzed of Nepal stock exchange market economy.The Journal of Nepalese Business Studies Vol. X No. 1 December 2017, Page: 96-100
10
Chi, Wei, Robert Brooks, Emawtee Bissoondoyal-Bheenick, and Xueli Tang. "Classifying Chinese bull and bear markets: indices and individual stocks." Studies in Economics and Finance 33, no. 4 (October 3, 2016): 509–31. http://dx.doi.org/10.1108/sef-01-2015-0036.
Full textAbstract:
Purpose This paper aims to investigate Chinese bull and bear markets. The Chinese stock market has experienced a long period of bear cycle from early 2000 until 2006, and then it fluctuated greatly until 2010. However, the cyclical behaviour of stock markets during this period is less well established. This paper aims to answer the question why the Chinese stock market experienced a long duration of bear market and what factors would have impacted this cyclical behaviour. Design/methodology/approach By comparing the intervals of bull and bear markets between stocks and indices based on a Markov switching model, this paper examines whether different industries or A- and B-share markets could lead to different stock market cyclical behaviour and whether firm size can determine the relationship between the firm stock cycles on the market cycles. Findings This paper finds a high degree of overlapping of bear cycles between stocks and indices and a high level of overlapping between the bear market and a fraction of stock with increasing stock prices. This leads to the conclusion that the stock performance and trading behaviour are widely diversified. Furthermore, the paper finds that the same industry may have different overlapping intervals of bull or bear cycles in the Shanghai and Shenzhen stock markets. Firms with different sizes could have different overlapping intervals with bull or bear cycles. Originality/value This paper fills the literature gap by establishing the cyclical behaviour of stock markets.
11
Gu, Anthony Yanxiang, and Chauchen Yang. "Short Sales Constraints and Return Volatility: Evidence from the Chinese A and H Share Markets." Review of Pacific Basin Financial Markets and Policies 10, no. 04 (December 2007): 469–78. http://dx.doi.org/10.1142/s021909150700115x.
Full textAbstract:
Returns of the same companies' common stocks, both non-market-adjusted and market-adjusted, exhibit greater volatility, on the Stock Exchange of Hong Kong where short selling is allowed than on the Shanghai Stock Exchange and Shenzhen Stock Exchange where short selling is restrained. This unique evidence indicates that short selling increases stock price volatility for the Chinese stocks in the Chinese stock markets.
12
Rahma Tri Benita, Siti Damayanti, and Irwan Adi Ekaputra. "Information Distribution and Informed Trading in Mixed and Islamic Capital Markets." International Journal of Business and Society 21, no. 3 (April 27, 2021): 1333–51. http://dx.doi.org/10.33736/ijbs.3353.2020.
Full textAbstract:
The correlation between volume and frequency with return volatility can explicate the information distribution process and informed traders' transaction behavior in a stock market. In this study, the Indonesian stock market represents the mixed market, while the Saudi Arabian stock market represents the Islamic market. We find that 94% and 96% of sharia-compliant stocks in Indonesia and Saudi Arabia follow the Mixture of Distribution Hypothesis (MDH). Consequently, we may conclude that sharia-compliant stocks in both markets are informationally efficient. However, we find that informed traders tend to behave differently in both markets. In the Indonesian market, informed traders exhibit competitive behavior in 95% of shariacompliant stocks and strategic transaction behavior in only 5% of the stocks. In contrast, in the Saudi Arabian market, we find that informed traders exhibit competitive behavior in only 38% of the stocks and strategic behavior in 62% of the stocks. The findings suggest that social and religious contexts may affect market participants' behavior.
13
Nyasha, Sheilla, and N. M. Odhiambo. "The Dynamics Of Stock Market Development In Kenya." Journal of Applied Business Research (JABR) 30, no. 1 (December 30, 2013): 73. http://dx.doi.org/10.19030/jabr.v30i1.8284.
Full textAbstract:
This paper highlights the origin of the stock market in Kenya, and traces the reforms that have been undertaken to develop the stock market. It also highlights the growth of the Kenyan stock market, as well as the challenges currently facing the market. The country has one stock market, known as the Nairobi Securities Exchange (formerly the Nairobi Stock Exchange). It is one of Africas largest stock markets. Since the early 1980s, a number of stock market reforms have been implemented in Kenya. These include the formation of a regulatory body (Capital Markets Authority CMA) in 1989, the replacement of the "Call-Over" trading system by the floor-based "Open-Outcry System" in 1991, the reduction of listing costs, the relaxation of the exchange control for locally controlled companies, and the repeal of the Exchange Control Act. Following these reforms, Kenyas stock market has developed significantly in terms of market capitalisation, the total value of stocks traded, and the turnover ratio. Although the stock market in Kenya has developed over the years, like many other developing countries' markets, it still faces a number of wide-ranging challenges.
14
Nur Iqmal Ibrahim, Siti, Siti Aida Muhammad, and Mimi Hafizah Abdullah. "A Network Analysis of the Stock Market in Malaysia, Singapore and Indonesia." International Journal of Engineering & Technology 7, no. 4.1 (September 12, 2018): 99. http://dx.doi.org/10.14419/ijet.v7i4.1.28234.
Full textAbstract:
In this study, we investigate the stock market network among the stocks traded in Malaysia, Singapore and Indonesia using the minimal spanning tree approach. Based on the market capitalization, the monthly adjusted closing prices from 2016 until 2017 of 10 companies for each stock market are chosen to construct the network, and the most influential stocks between Malaysia, Singapore and Indonesia stock markets are identified. Findings of this study show that 3 out of 30 companies are identified as the most influential in the Malaysia, Singapore and Indonesia stock market.
15
Singh, Aditi, and Madhumita Chakraborty. "Examining Efficiencies of Indian ADRs and their Underlying Stocks." Global Business Review 18, no. 1 (January 25, 2017): 144–62. http://dx.doi.org/10.1177/0972150916666948.
Full textAbstract:
In this article, the efficient market hypothesis (EMH) is tested for US and Indian stock markets and Indian American depositary receipts (ADRs) and their underlying stocks. The approach used to observe changing market efficiency is time-varying Hurst exponent. The Hurst values have been calculated after filtering the financial asset return series for short-term dependence and volatility. Rolling window approach has been used to calculate Hurst exponent and observe time-varying long-range dependence. The data are filtered by autoregressive-generalized autoregressive conditional heteroscedasticity (AR-GARCH) method. The empirical results suggest that US stock market is more efficient than Indian stock market. All the ADRs, their underlying stocks and markets of both the countries have shown varying efficiency. The change in efficiency of Indian ADRs is more when compared to their underlying stocks, which suggests that stock of a company listed on stock indices of different countries may show different pace of evolution of efficiency depending on maturity of the market.
16
XIONG, DEWEN, and MICHAEL KOHLMANN. "THE COMPATIBLE BOND-STOCK MARKET WITH JUMPS." International Journal of Theoretical and Applied Finance 14, no. 05 (August 2011): 723–55. http://dx.doi.org/10.1142/s0219024911006449.
Full textAbstract:
We construct a bond-stock market composed of d stocks and many bonds with jumps driven by general marked point process as well as by an ℝn-valued Wiener process. By composing these tools we introduce the concept of a compatible bond-stock market and give a necessary and sufficient condition for this property. We study no-arbitrage properties of the composed market where a compatible bond-stock market is arbitrage-free both for the bonds market and for the stocks market. We then turn to an incomplete compatible bond-stock market and give a necessary and sufficient condition for a compatible bond-stock market to be incomplete. In this market we consider the mean-variance hedging in the special situation where both B(u, T) and eG(u, y, T)-1 are quadratic functions of T - u. So, we need to extend the notion of a variance-optimal martingale (VOM) as in Xiong and Kohlmann (2009) to the more general market. By introducing two virtual stocks [Formula: see text], we prove that the VOM for the bond-stock market is the same as the VOM for the new stock market [Formula: see text]. The mean-variance hedging problem in this incomplete bond-stock market for a contingent claim [Formula: see text] is solved by deriving an explicit solution of the optimal measure-valued strategy and the optimal cost induced by the optimal strategy of MHV for the stocks [Formula: see text] is computed.
17
Haq, Daffa Aqomal, Asep Nurhalim, and Ranti Wiliasih. "Sharia stock market integration of oic countries before and during the crisis of the russian-ukraine war." Halal Studies and Society 1, no. 1 (May 8, 2024): 25–32. http://dx.doi.org/10.29244/hass.1.1.25-32.
Full textAbstract:
An integrated stock market has negative impacts, such as accelerating co-movement, which is vulnerable to economic shocks and global market crises on the domestic market. One of the crises in 2022 was the Russia-Ukraine war which impacted the stock market, including Sharia stocks which were believed to be more resistant to the shocks of the global crisis. This study examines the development, integration, and response of OIC countries five Islamic stock markets in the Russia-Ukraine war. The method used is VAR/VECM on the DJIMMT25, SPSADS, SPSUUAEDS, JII, DJIMT, SPBMIR, and SPBMIU indices. The results show the same movement in the UAE and Saudi Arabia stock markets, while Turkey experienced a positive trend during the war. The Islamic stock market of the OIC countries during the Russia-Ukraine war was cointegrated. In contrast, the Malaysian stock market influenced the Islamic stock markets of the other four OIC countries. The IRF results show a permanent effect on the volatility of the Islamic stock market in OKI countries due to the shocks given. However, the volatility response is relatively small because the stock market itself dominates the contribution of shocks.
18
Khadke, Prof A., Samyak Ajmera, Anand Ghatol, Akshay Singh, and Himanshu Narwal. "Institutional Market Analysis in Stock Market." International Journal for Research in Applied Science and Engineering Technology 10, no. 11 (November 30, 2022): 1805–7. http://dx.doi.org/10.22214/ijraset.2022.47653.
Full textAbstract:
Abstract: A stock market, equity market, or share market is the aggregation of buyers and sellers of stocks (also called shares), which represent ownership claims on businesses. In stock market analysis we are trying to predict the price of given share or stock The result was achieved at the end of this project was quite impressive as model was able to predict the trend successfully, it was not 100% accurate but considering that model it predicted only on the basis of past data is quite impressive. All these things we are able to do with help of machine learning.
19
Phatangare, Sheetal, Abbas Taherbhai Madhvaswala, Kashish Rahate, Mohammed Nogamawala, and Mohamed Maged Mohamed Ahmed. "Stock Market Forecasting." International Journal for Research in Applied Science and Engineering Technology 11, no. 5 (May 31, 2023): 556–60. http://dx.doi.org/10.22214/ijraset.2023.51550.
Full textAbstract:
Abstract: Stock market forecasting seeks to determine the worth of a firm’s financial stocks in the future. Machine learning is being used in recent developments in stock market forecasting technology to produce forecasts based on the values of current stock market indices by training on their previous values. Future stock price projections can be difficult to make when trying to anticipate the stock market. It is incredibly challenging to forecast the stock market since shares fluctuate so frequently. Every day and frequently, stock. Foreseeing trends in the stock market is often correct using this method. This study forecasts the closing prices of numerous corporations using Long-Short Term Memory (LSTM) methodologies. These models are assessed using RMSE, which is one of the commonly used error measures. LSTM works better than SVR, as shown by the experiment's findings
20
Deshmukh, Tejas, Suraj Hume, Ritesh Rana, Yash Chahande, Harshal Kubde, and Charan Pote. "Stock Market Price Prediction." International Journal for Research in Applied Science and Engineering Technology 11, no. 4 (April 30, 2023): 4531–34. http://dx.doi.org/10.22214/ijraset.2023.51234.
Full textAbstract:
Abstract: In stock request valuation, the end is to prognosticate the unborn value of the fiscal stocks of a company. Machine learning itself employs different models to make vaccinating easier and more authentic. The paper focuses on the use of retrogression and LSTM-grounded machine literacy to prognosticate stock values. stock request valuation, the end is to prognosticate the unborn value of the fiscal stocks of a company. Machine learning itself employs different models to make vaticination easier and further authentic. The paper focuses on the use of retrogression and LSTM-grounded machine literacv accinatingsticate stock mores
21
Imhanzenobe, Japhet Osazefua. "Historical Development of Frontier Stock Markets in Sub-Saharan Africa." International Journal of Professional Business Review 8, no. 7 (July 10, 2023): e02659. http://dx.doi.org/10.26668/businessreview/2023.v8i7.2659.
Full textAbstract:
Purpose: The purpose of this research is to review and compare the development of the three major frontier stock markets in Sub-Saharan Africa over time. The study provides some narrative around the historical development of each market as well as a theoretical backdrop for stock market development studies. Theoretical framework: The adaptive market hypothesis was used as the theoretical backdrop for the study. The adaptive market suggests that stock markets develop in an evolutionary manner (similar to natural selection). This evolution of stock market development is influenced by changes in investors’ behavior and regulatory standards. Design/methodology/approach: Data was collected from 1993 to 2020 on the IMF market efficiency score, the value of stocks traded, aggregate market capitalization, and the number of listed companies for the sample markets. The study used descriptive statistics and trend analysis to discuss and compare the stock market development indicators across the different selected frontier markets. Findings: The study discovered an improvement in stock market performance across the sample period. The Johannesburg Stock Exchange was found to be the most developed of the three stock exchanges. The Nigerian Stock Exchange was second while the Nairobi Stock Exchange was third. Some factors that erode the performance of these stock markets were also discussed. The practical and social implications: The sample stock markets are the major frontier markets, and so are often the first stop for foreign investors that want to penetrate the Sub-Saharan African markets. The performance of these markets often determines the level of foreign direct investment (FDI) and foreign portfolio investment (FPI) that flow into Africa. Originality/ Value: Few studies have investigated the performance of stock markets in Sub-Saharan Africa. Also, the few studies that investigate the performance of these markets rarely proceed to discuss the market-wide factors that erode the performance of these markets compared to those of developed economies. Some factors like the size of the economy, low financial literacy, misplaced government policies, poor investment culture, buy-and-hold-tight attitude, and high transaction costs were identified and discussed.
22
Chen, Muzi, Yuhang Wang, Boyao Wu, and Difang Huang. "Dynamic Analyses of Contagion Risk and Module Evolution on the SSE A-Shares Market Based on Minimum Information Entropy." Entropy 23, no. 4 (April 7, 2021): 434. http://dx.doi.org/10.3390/e23040434.
Full textAbstract:
The interactive effect is significant in the Chinese stock market, exacerbating the abnormal market volatilities and risk contagion. Based on daily stock returns in the Shanghai Stock Exchange (SSE) A-shares, this paper divides the period between 2005 and 2018 into eight bull and bear market stages to investigate interactive patterns in the Chinese financial market. We employ the Least Absolute Shrinkage and Selection Operator (LASSO) method to construct the stock network, compare the heterogeneity of bull and bear markets, and further use the Map Equation method to analyse the evolution of modules in the SSE A-shares market. Empirical results show that (1) the connected effect is more significant in bear markets than bull markets and gives rise to abnormal volatilities in the stock market; (2) a system module can be found in the network during the first four stages, and the industry aggregation effect leads to module differentiation in the last four stages; (3) some stocks have leading effects on others throughout eight periods, and medium- and small-cap stocks with poor financial conditions are more likely to become risk sources, especially in bear markets. Our conclusions are beneficial to improving investment strategies and making regulatory policies.
23
Chellaswamy, Karthigai Prakasam, Natchimuthu N, and Muhammadriyaj Faniband. "Stock Market Reforms and Stock Market Performance." International Journal of Financial Research 12, no. 2 (January 14, 2021): 202. http://dx.doi.org/10.5430/ijfr.v12n2p202.
Full textAbstract:
This paper analyses the impact of stock market reforms on the stock market performance in India using regression based event-study method. We consider nine stock market reforms introduced from 1998 to 2018. We find that the impact of stock market reforms on Nifty trading volume and Nifty return is different. This paper documents that the impact of the additional volatility measures, T+3 and T+2 settlement cycles, and margin provisions for intra-day crystallized losses reforms show a positive impact on trading volume post-reform. In contrast, internet trading, prohibition of fraudulent and unfair trade practices, delisting of equity shares, substantial acquisition of shares and takeovers listing obligations and disclosure requirements reforms decrease the trading volume post-reform. Our results of Nifty return reveal that the additional volatility measures, the T+2 settlement cycle, the prohibition of fraudulent and unfair trade practices, substantial acquisition of shares and takeovers, listing obligations and disclosure requirements have a significant and positive impact on return post-reform. It is evident that the impact of all nine stock market reforms is insignificant on Nifty return.
24
Setiawan, Budi, and Muhammad Hidayat. "PENGARUH PASAR MODAL NEGARA G-3 TERHADAP PASAR MODAL ASEAN-5." Jurnal Ilmiah Ekonomi Global Masa Kini 8, no. 3 (January 8, 2018): 11–15. http://dx.doi.org/10.36982/jiegmk.v8i3.348.
Full textAbstract:
The stock market has captured the attention of many practitioners and scholars in the past decade. It has become one of the most vital aspects of a modern market economy. The stock market provides companies with access to capital and gives opportunity for investors to have a slice of company ownership. The present paper investigates the impact of G-3 stock markets (US, Japan and Europe) to ASEAN-5 stock markets (Indonesia, Malaysia, Philippines, Thailand and Singapore). The data coverage is composed of daily closing stock index at G-3 stock markets and ASEAN-5 stock markets over the period from January 4, 2000 to December 31, 2014. The historical stock market data were analyzed by using Structured Equation Model (SEM). The empirical results suggest that the G-3 stock markets have a positive and significant impact on ASEAN-5 stock markets. For further, the researcher could add other Asia stock markets such as Nikkei225 Index (Japan), Hang Seng Index (Hong Kong), Kospi Index (South Korea), and BSE Index (India).Keywords: G-3 Stock Markets, ASEAN-5 Stock Markets, Structured Equation Model, Stock Market Diversification; Contagious Effect.Â
25
Chowdhury, Mohammad Ashraful Ferdous, Md Mahmudul Haque, and Md Nazrul Islam. "Contagion Effects on Stock Market of Bangladesh." International Journal of Asian Business and Information Management 8, no. 2 (April 2017): 1–14. http://dx.doi.org/10.4018/ijabim.2017040101.
Full textAbstract:
Due to increased globalization and economic integration in the global economy, contagion effects have been considered an important matter for the investors and policymakers. In the wake of the global financial crisis of September 2008, Islamic financial products were thrust into the spotlight as alternatives to the shaken conventional equity markets. The objective of this study is to discover the Islamic stock market dynamics of Bangladesh with the global Islamic stock markets such as Saudi Arabia, UAE, Kuwait, Europe, UK and Japan. For understanding long run relationship or the theoretical relationships among the Islamic stock market and short run co-movements among Islamic stocks, Johansen co-integration test and Vector Error Correction model (VECM) have been applied respectively. Furthermore, the investigation on short run dynamics is also carried through Impulse Response Function (IRF) analyses. The study found that the Japanese Islamic Stock market is affected to changes in other Islamic stock markets while Kuwait stock market is the leader in the sense it affects other stock market greatly. Bangladeshi Islamic stock market is found to be marginally affecting other stock markets but not as strong as Kuwait. Global Islamic stock market seems to have very little impact to Bangladesh Islamic stock market. The evidence of co-integration and short run dynamics help a diversification benefit may be derived from the cross boarder investment. The empirical evidence of co-integration and short run dynamic relationship found in this study will help investors in making efficient investment decisions and also enhance their understanding of market behavior.
26
Bensoltane, Héla. "Is there a “Flight to liquidity” phenomenon in the Saudi stock market?" International Journal of ADVANCED AND APPLIED SCIENCES 11, no. 4 (April 2024): 45–51. http://dx.doi.org/10.21833/ijaas.2024.04.006.
Full textAbstract:
The study examines how market illiquidity shocks affect stock prices and explores the "flight to liquidity" phenomenon in the largest stock market in the Middle East, specifically the Saudi stock market. It analyzes the relationship between these shocks and stock prices to understand the impact on both small and large firms. Utilizing a comprehensive database that contains daily data of all stocks listed on the Saudi stock market for over 20 years, the research evaluates the illiquidity of each stock and the entire market on a weekly basis. Market illiquidity shocks are determined using an autoregressive model, and the effect of these shocks on Saudi stock prices is assessed through illiquidity betas in linear regressions for both large and small firms. Initial findings show that illiquidity shocks were significant during periods of oil price declines and global financial crises. The results confirm that stock prices fall in response to market illiquidity shocks, with the impact varying by firm size; larger firms' stocks are less affected, indicating a flight to liquidity towards larger firms during market downturns. This pattern aligns with observations in the US and some emerging markets.
27
O'Sullivan, Mary. "The Expansion of the U.S. Stock Market, 1885–1930: Historical Facts and Theoretical Fashions." Enterprise & Society 8, no. 3 (September 2007): 489–542. http://dx.doi.org/10.1017/s1467222700006182.
Full textAbstract:
Based on an analysis of the leading trading markets for stock in the United States, I document the dramatic expansion that took place in the scale and scope of the country's stock market from the mid-1880s to the early 1930s. My analysis suggests that a broadbased stock market was a long way from being established even by the early teens. It took the impetus provided by World War I, plus the enthusiasm of the 1920s, to bring such a market into existence. I consider the capacity of today's fashionable theories, which link the development of stock markets to improvements in minority shareholder protection, to explain the growth of the U.S. stock market, and find that they cannot account for the historical patterns that I identify. However, I suggest that there are other arguments that are worthy of further consideration. First, there were factors, besides minority shareholder rights, that led to changes in the demand for corporate stocks during this period, especially an increase in the demand for stocks by institutional investors, notably banks and insurance companies, as well as the emergence of a retail market for stocks after World War I. Second, there were also important developments in the supply of corporate stocks after the War, including the issuance of stock to fund the expansion of young firms, but especially to facilitate mergers and acquisitions by established firms, which seem to have played an important role in driving the expansion of the U.S. stock market.
28
Mamcarz, Katarzyna. "Gold market and selected Nordic stock markets: Granger causality." Ekonomia i Prawo 21, no. 2 (June 30, 2022): 463–87. http://dx.doi.org/10.12775/eip.2022.026.
Full textAbstract:
Motivation: The turbulence in financial markets, especially stocks, makes investors seek safer ways of capital allocation. Gold exhibiting a low or negative correlation with stocks can constitute an alternative form of investment for them. The price volatility of aforementioned assets has impact on investors’ decisions. That is why the assessment of interrelations between stock and gold returns is important. The direction of causality between the analysed variables is reflected by the fact that investors tend to transfer their funds from gold markets to more profitable markets, or return to gold markets. The research focuses on linkages between gold-stock markets of selected Nordic countries which in comparison with countries classified as key producers and consumers of gold were not under investigation so far. There is therefore a research gap in empirical research.
Aim: The aim of this paper is to investigate the causal relationship between the rates of return on stock markets in three Nordic countries, represented by their respective indices — OMXH25 (Finland: the Helsinki Stock Exchange Index), OMXS30 (Sweden: the Stockholm Stock Exchange Index) and OSEAX (Norway: the Oslo Børs All Share Index) — and the returns from investment in gold. The VAR model was applied in the analysis to perform a Granger non-causality linear test, along with decomposition of variance and the impulse response function. The study covered the period between September 2001 and October 2020.
Results: The study showed no causality between the analysed rates of return, except in Norway, where the gold market was found to have an impact on the stock market, assuming a statistical significance of 0.14. In the other two countries, changes in gold prices did not affect stock prices, and vice versa.
29
Kumar, Shivam. "INVESTOR PERCEPTION TOWARDS THE STOCK MARKET." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (May 1, 2024): 1–5. http://dx.doi.org/10.55041/ijsrem32943.
Full textAbstract:
A stock market is a market in which stocks are bought and sold. It is also called industrial securities market, because it is the market for the trading of company stocks i.e. corporate securities; both those securities listed on stock exchange as well as those only traded privately. The term ‘Stock Market’ is often used as synonymous to ‘Stock Exchange’. But there is a difference in the two terms. Stock exchange is a corporation in the business of bringing buyers and sellers of stocks together. It is a major part of stock market, but not whole of it. Because a stock market besides stock exchanges also includes the market for new issue of securities. Thus the stock market can be divided into two constituents as follows: - 1. Primary Market or New Issue Market 2. Secondary Market or Stock Exchange
30
Sari, Linda Karlina, Noer Azam Achsani, and Bagus Sartono. "THE VOLATILITY TRANSMISSION OF MAIN GLOBAL STOCK'S RETURN TO INDONESIA." Buletin Ekonomi Moneter dan Perbankan 20, no. 2 (October 31, 2017): 229–56. http://dx.doi.org/10.21098/bemp.v20i2.813.
Full textAbstract:
Stock return volatility is a very interesting phenomenon because of its impact on global financial markets. For instance, an adverse shocks in one country’s market can be transmitted to other countries’ market through a particular mechanism of transmission, causing the related markets to experience financial instability as well (Liu et al., 1998). This paper aims to determine the best model to describe the volatility of stock returns, to identify asymmetric effect of such volatility, as well as to explore the transmission of stocks return volatilities in seven countries to Indonesia’s stock market over the period 1990-2016, on a daily basis. Modeling of stock return volatility uses symmetric and asymmetric GARCH, while analysis of stock return volatility transmission utilizes Vector Autoregressive system. This study found that the asymmetric model of GARCH, resulted from fitting the right model for all seven stock markets, provides a better estimation in portraying stock return volatility than symmetric model. Moreover, the model can reveal the presence of asymmetric effects on those seven stock markets. Other finding shows that Hong Kong and Singapore markets play dominant roles in influencing volatility return of Indonesia’s stock market. In addition, the degree of interdependence between Indonesia’s and foreign stock market increased substantially after the 2007 global financial crisis, as indicated by a drastic increase of the impact of stock return volatilities in the US and UK market on the volatility of Indonesia’s stock return.
31
Jiang, Jing. "Cross-sectional variation of market efficiency." Review of Accounting and Finance 16, no. 1 (February 13, 2017): 67–85. http://dx.doi.org/10.1108/raf-02-2016-0018.
Full textAbstract:
Purpose This paper aims to provide evidence that market efficiency varies greatly across individual stock, and across market exchanges. Design/methodology/approach Three approaches, partial adjustment model, Dimson beta model and variance ratio test, are used on a large sample of US stocks. Findings This paper finds prices are closer to random walk benchmarks (i.e. more efficient) for stocks with better liquidity provision, frequent trading, greater return volatility, higher prices, larger market capitalizations and smaller trade sizes. These findings suggest that liquidity stimulates arbitrage activity, which, in turn, enhances market efficiency. Market efficiency also varies with information environment. The results show that stocks with greater information-based trading exhibit higher level of efficiency. Finally, market structure influences market efficiency. New York Stock Exchange stocks achieve higher level of efficiency than NASDAQ stocks do. The empirical results are robust and not driven by differences in stock attributes between the two markets. Research limitations/implications Overall, these results indicate that liquidity provision, stock attributes and market structure exert a significant impact on the realization of market efficiency. Practical implications In addition, this paper is also relevant to both stock exchanges facing increased competition and to market regulators. Originality/value Prior studies offer little evidence on the speed at which new information is impounded into the price. There is also limited evidence regarding how liquidity provision and market structure affect market efficiency. Using a transformation of the speed of price adjustment and other measurements as proxies for individual stock efficiency, this study may shed further lights on our understanding of market efficiency.
32
Nyasha, Sheilla, and Nicholas M. Odhiambo. "The Brazilian stock market development: A critical analysis of progress and prospects during the past 50 years." Risk Governance and Control: Financial Markets and Institutions 3, no. 3 (2013): 7–15. http://dx.doi.org/10.22495/rgcv3i3art1.
Full textAbstract:
This paper highlights the origin of the stock market in Brazil, and traces the reforms that have been undertaken to develop the stock market. It also highlights the growth of the Brazilian stock market, as well as the challenges currently facing the market. The country has one big stock market, known as the BM&FBOVESPA, which is one of the world’s largest stock markets. Over the years, a number of stock market reforms have been implemented in Brazil. Among these reforms have been the restructuring of the financial market, the replacement of the traditional trading systems by full electronic trading systems, the enactment of new laws governing the stock market, as well as the revision of the existing laws. In addition, the formation of a regulatory body known as Securities and Exchange Commission (CVM) in 1976 also assisted in the creation of an environment conducive for the growth and development of the stock market. Since the implementation of these reforms, the Brazilian stock market has developed significantly in terms of market capitalisation, the total value of stocks traded, and the turnover ratio.
33
Nyasha, Sheilla, and N. M. Odhiambo. "Stock Market Development In The United Kingdom: Prospects And Challenges." International Business & Economics Research Journal (IBER) 12, no. 7 (July 16, 2013): 725. http://dx.doi.org/10.19030/iber.v12i7.7963.
Full textAbstract:
This paper highlights the origin and development of the U.K. stockmarket. The country consists of one major stock market, known as the London Stock Exchange, which is one of the worlds largest stock markets. Stock market reforms have been implemented since the Big Bang of 1986 and the Exchange responded positively to most of these reforms, but not so positively to others. As a result of the reforms, the U.K.s stock market has developed, in terms of market capitalisation, the total value of stocks traded and the turnover ratio.Although the U.K. stock market has developed over the years, it still faceswide-ranging challenges, such as the uncertainties that come with new regulation and regulatory changes dominating at both domestic and international levels and the sovereign debt crisis that has left the U.K. stock market volatile.
34
Akinlaso, Mustapha Ishaq, Aroua Robbana, and Nura Mohamed. "Volatility transmission within financial markets during the COVID-19 pandemic: are faith-based investors well off in Tunisia?" Journal of Islamic Accounting and Business Research 13, no. 1 (December 1, 2021): 98–113. http://dx.doi.org/10.1108/jiabr-12-2020-0388.
Full textAbstract:
Purpose This paper aims to investigate the risk-return and volatility spillover within the Tunisian stock market during the COVID-19 pandemic analyzing both the Islamic and conventional stocks’ performance. Design/methodology/approach Both symmetric (GARCH and GARCH-M) and asymmetric (Threshold GARCH and Exponential GARCH) models are used to analyze the market returns and volatility response. Standard and Poor’s (S&P) index has been used to test both the Islamic and conventional stocks within the Tunisian stock market. Findings The findings suggest that both Tunisia Islamic and conventional stock markets are highly persistent; however, the conventional stock index showed a negative return spillover on the Islamic stocks during the pandemic. The conventional stock index has also shown a higher exposure to risk for a lower amount of return, and evidence of potential diversification benefit between both indexes was found during the pandemic, whereas the Islamic market showed a positive leverage effect, indicating a positive correlation between past return and future return; the conventional index implied a negative leverage effect. Originality/value The value of this paper emerges in studying three main aspects that are specific to the Tunisian stock market. This includes COVID-19 effect of return spillovers, volatility transmission across both conventional and Islamic stock market within the local financial market.
35
ATMAZ, ADEM, and SULEYMAN BASAK. "Stock Market and No‐Dividend Stocks." Journal of Finance 77, no. 1 (December 21, 2021): 545–99. http://dx.doi.org/10.1111/jofi.13098.
Full text
36
Kumar, Rakesh, and Raj S. Dhankar. "Asymmetric Volatility and Cross Correlations in Stock Returns under Risk and Uncertainty." Vikalpa: The Journal for Decision Makers 34, no. 4 (October 2009): 25–36. http://dx.doi.org/10.1177/0256090920090403.
Full textAbstract:
Capital market efficiency is a matter of great interest for policy makers and investors in designing investment strategy. If efficient market hypothesis (EMH) holds true, it will prevent the investors to realize extra return by utilizing the inherent information of stocks. They will realize extra returns only by incorporating the extra risky stocks in their portfolios. While empirical tests of EMH and risk-return relationship are plentiful for developed stock markets, the focus on emerging stock markets like India, Pakistan, Sri Lanka, etc., began with the liberalization of financial systems in these markets. With globalization and deregulation, the enormous opportunities of investment in South Asian stock markets have attracted the domestic and foreign institutional investors in general, and to reduce their portfolio risk by diversifying their funds across the markets in particular. The efforts are made in this study to examine the cross-correlation in stock returns of South Asian stock markets, their regional integration, and interdependence on global stock market. The study also examines the important aspects of investment strategy when investment decisions are made under risk and uncertainty. The study uses Bombay stock exchange listed index BSE 100 for India, Colombo stock exchange listed Milanka Price Index for Sri Lanka, Karachi stock exchange listed KSE 100 for Pakistan, Dhaka stock exchange listed DSE-General Index for Bangladesh, and S & P Global 1200 to represent the global market. It carries out a comprehensive analysis, tracing the autocorrelation in stock returns, cross correlations in stock returns under risk and uncertainty, interdependency among the South Asian stock markets, and that with the global stock market. The research methodology applied in the study includes application of Ljung-Box to examine the cross-correlation in stock returns, ARCH and its generalized models for the estimation of conditional and asymmetric volatilities, and Ljung-Box as a diagnostic testing of fitted models, and finally correlation to examine the interdependency of these markets in terms of stock returns and expected volatility. The results bring out the following: L-B statistics suggests the presence of autocorrelation in stock returns in all Asian stock markets; however, for the global market, autocorrelations are significant at 15 lags, and thereafter they are insignificant. The significant autocorrelations in stock returns report volatility clustering in stock returns, reject the EMH, and hold that current stock returns are significantly affected by returns being offered in the past. ARCH and its generalized models significantly explain the conditional volatility in all stock markets in question. The study rejects the relationship between stock returns and expected volatility; however, the relationship is significant with unexpected volatility. It brings out that investors adjust their risk premium for expected variations in stock prices, but they expect extra risk premium for unexpected variations. With their entry into the liberalization phase, South Asian stock markets have reported regional interdependence, and also interdependence with the global stock market.
37
Stereńczak, Szymon. "Conditional stock liquidity premium: is Warsaw stock exchange different?" Studies in Economics and Finance 38, no. 1 (January 11, 2021): 67–85. http://dx.doi.org/10.1108/sef-03-2020-0075.
Full textAbstract:
Purpose This paper aims to empirically indicate the factors influencing stock liquidity premium (i.e. the relationship between liquidity and stock returns) in one of the leading European emerging markets, namely, the Polish one. Design/methodology/approach Various firms’ characteristics and market states are analysed as potentially affecting liquidity premiums in the Polish stock market. Stock returns are regressed on liquidity measures and panel models are used. Liquidity premium has been estimated in various subsamples. Findings The findings vividly contradict the common sense that liquidity premium raises during the periods of stress. Liquidity premium does not increase during bear markets, as investors lengthen the investment horizon when market liquidity decreases. Liquidity premium varies with the firm’s size, book-to-market value and stock risk, but these patterns seem to vanish during a bear market. Originality/value This is one of the first empirical papers considering conditional stock liquidity premium in an emerging market. Using a unique methodological design it is presented that liquidity premium in emerging markets behaves differently than in developed markets.
38
Kolte, Geeta, Varadraj Kini, Harikrishnan Nair, and Prof Suresh Babu K. S. "Stock Market Prediction using Deep Learning." International Journal for Research in Applied Science and Engineering Technology 10, no. 4 (April 30, 2022): 26–32. http://dx.doi.org/10.22214/ijraset.2022.41159.
Full textAbstract:
Abstract: Stock market is very uncertain and highly volatile as the prices of stocks keep fluctuating due to several factors that make prediction of stocks a very difficult and complicated task. In the finance and trading world stock analysis and trading is a method for investors and traders to make buying and selling decisions. Investors and traders try to gain an edge in the markets by taking informed decisions by studying and evaluating past and current data. Stock market prediction has always been an important research topic in the financial and trading field [2]. Prediction of stock market is the act of trying to determine the future value of a company stock (nifty & sensex) or other financial instrument traded on an exchange. Our project explains the prediction of a stock using Machine Learning, which itself employs different models to make prediction easier and authentic. The paper focuses on the use of Recurrent Neural Networks (RNN) called Long Short Term Memory (LSTM) to predict stock values. This will help us provide more accurate results when compared to existing stock price prediction algorithms. The eminent analysis of the stock will be an asset for the stock market investors and will provide real-life solutions to the problems and also yield significant profit. Keywords: Stock Price Prediction, Machine Learning, Long Short-Term Memory, Recurrent Neural Networks
39
Matek, Petar-Pierre, and Maša Galić. "The impact of designated market-makers on liquidity in frontier markets." Zbornik radova Ekonomskog fakulteta u Rijeci 42, no. 1 (June 28, 2024): 95–121. http://dx.doi.org/10.18045/zbefri.2024.1.95.
Full textAbstract:
Many exchanges around the globe have implemented market-making schemes inan attempt to mitigate liquidity risk and enhance trading volume. This researchexamines the impact of designated market makers on stock liquidity in frontiermarkets, specifically measured by bid-ask spreads and trading turnover. Using adifference-in-differences analysis, we studied 19 stocks that introduced designatedmarket makers at the Zagreb Stock Exchange and Ljubljana Stock Exchangebetween May 2010 and January 2022. To the best of our knowledge, this is the firststudy investigating the impact of market makers in these specific markets and onlythe second in frontier markets overall. As expected, we find a significant reductionin bid-ask spreads for most stocks following the introduction of market makers.However, unlike findings of studies conducted in more developed markets, ourresults for turnover are not conclusive, suggesting that market makers alone maynot be sufficient to overcome structural impediments to market liquidity in frontiermarkets, such as lack of free float and the dominance of large investors with long-term investment horizons.
40
Miralles-Quirós, María del Mar, José Luis Miralles-Quirós, and Celia Oliveira. "The role of liquidity in asset pricing: the special case of the Portuguese Stock Market." Journal of Economics, Finance and Administrative Science 22, no. 43 (November 6, 2017): 191–206. http://dx.doi.org/10.1108/jefas-12-2016-0001.
Full textAbstract:
Purpose The aim of this paper is to examine the role of liquidity in asset pricing in a tiny market, such as the Portuguese. The unique setting of the Lisbon Stock Exchange with regards to changes in classification from an emerging to a developed stock market, allows an original answer to whether changes in the development of the market affect the role of liquidity in asset pricing. Design/methodology/approach The authors propose and compare two alternative implications of liquidity in asset pricing: as a desirable characteristic of stocks and as a source of systematic risk. In contrast to prior research for major stock markets, they use the proportion of zero returns which is an appropriated measure of liquidity in tiny markets and propose the separated effects of illiquidity in a capital asset pricing model framework over the whole sample period as well as in two sub-samples, depending on the change in classification of the Portuguese market, from an emerging to a developed one. Findings The overall results of the study show that individual illiquidity affects Portuguese stock returns. However, in contrast to previous evidence from other markets, they show that the most traded stocks (hence the most liquid stocks) exhibit larger returns. In addition, they show that the illiquidity effects on stock returns were higher and more significant in the period from January 1988 to November 1997, during which the Portuguese stock market was still an emerging market. Research limitations/implications These findings are relevant for investors when they make their investment decisions and for market regulators because they reflect the need of improving the competitiveness of the Portuguese stock market. Additionally, these findings are a challenge for academics because they exhibit the need for providing alternative theories for tiny markets such as the Portuguese one. Practical implications The results have important implications for individual and institutional investors who can take into account the peculiar effect of liquidity in stock returns to make proper investment decision. Originality/value The Portuguese market provides a natural experimental area to analyse the role of liquidity in asset pricing, because it is a tiny market and during the period studied it changed from an emerging to a developed stock market. Moreover, the authors have to highlight that previous evidence almost exclusively focuses on the US and major European stock markets, whereas studies for the Portuguese one are scarce. In this context, the study provides an alternative methodological approach with results that differ from those theoretically expected. Thus, these findings are a challenge for academics and open a theoretical and a practical debate.
41
Khan, Safi Ullah, and Syed Tahir Hijzi. "Single Stock Futures Trading and Stock Price Volatility: Empirical Analysis." Pakistan Development Review 48, no. 4II (December 1, 2009): 553–63. http://dx.doi.org/10.30541/v48i4iipp.553-563.
Full textAbstract:
This study examines impact of the introduction of single stock futures contracts on the return volatility of the SSFs-listed underlying stocks. The study documents a significant decrease in return volatility for the SSFs-underlying stocks following the introduction of single stock futures contracts on the Karachi Stock Exchange. The multivariate analysis in which the spot trading volume, the futures trading volume and open interest were partitioned into news and informationless components, the estimated coefficient of expected futures volume component is statistically significant and negatively related to volatility, suggesting that equity volatility is mitigated when the expected level of futures activity is high. The findings of the decreased spot price volatility of the SSFs-underlying stocks associated with large expected futures activity is important to the debate of regarding the role of equity derivatives trading in stock market volatility. These empirical results for the Pakistan’s equity market support theories implying that equity derivates trading improves liquidity provision and depth in the equity markets, and appear to be in contrast to the theories implying that equity derivates markets provide a medium for destabilising speculation. Finally, the SSFs-listed stocks were grouped with a sample of non-SSFs stocks to examine cross-sectional data for comparing changes in return volatility. After controlling for the effects of a number of determinants of volatility, sufficient evidence is found to support that, this multivariate test, like the previous analysis, provides no evidence that the volatility of the SSFsunderlying stocks is positively related to the introduction of the single stock futures trading in the Pakistan’s stock market.
42
Patidar, Jaydeep. "Web Trade Analytics." International Scientific Journal of Engineering and Management 03, no. 04 (April 23, 2024): 1–9. http://dx.doi.org/10.55041/isjem01704.
Full textAbstract:
This research introduces an innovative web application developed using the MERN (MongoDB, Express.js, React, Node.js) stack, enhanced with fundamental machine learning algorithms, designed to address the complexities of stock market analysis. The central focus is on creating a user-customizable dashboard, allowing investors to select specific stocks for real-time analysis, sentiment tracking, and future price prediction. The methodology integrates historical stock data with sentiment analysis sourced from news and social media. The machine learning algorithms leverage this data to generate buy or sell recommendations and forecast future price trends. Our findings underscore the practicality of this approach, enhancing investors' abilities to navigate the unpredictable stock market landscape and make informed decisions with an eye on the future. Keywords— Stock Market, MERN Stack, Predictive Analysis, Future Forecasting
43
Sable, Rachna, Shivani Goel, and Pradeep Chatterjee. "Techniques for Stock Market Prediction: A Review." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 5s (June 5, 2023): 381–402. http://dx.doi.org/10.17762/ijritcc.v11i5s.7056.
Full textAbstract:
Stock market forecasting has long been viewed as a vital real-life topic in economics world. There are many challenges in stock market prediction systems such as the Efficient Market Hypothesis (EMH), Nonlinearity, complex, diverse datasets, and parameter optimization. A stock's value on the stock market fluctuates due to many factors like previous trends of the stock, the current news, twitter feeds, any online customer feedbacks etc. In this paper, the literature is critically analysed on approaches used for stock market prediction in terms of stock datasets, features used, evaluation metrics used, statistical, machine learning and deep learning techniques along with the directions for the future. The focus of this review is on trend and value prediction for stocks. Overall, 68 research papers have been considered for review from years 1998-2023. From the review, Indian stock market datasets are found to be most frequently used datasets. Evaluation metrics used commonly are accuracy and Mean Absolute Percentage Error. ARIMA is reported as the most used frequently statistical technique for stick market prediction. Long-Short Term Memory and Support Vector Machine are the commonly used algorithms in stock market prediction. The advantages and disadvantages of frequently used evaluation metrics, machine learning, deep learning and statistical approaches are also included in this survey.
44
Cai, Huan, Meining Wang, and Chaonan Bai. "An Empirical Study of Investors’ Disposition Effect in China Based on Open Data from the Chinese Stock Markets." International Journal of Economics and Finance 10, no. 5 (April 13, 2018): 165. http://dx.doi.org/10.5539/ijef.v10n5p165.
Full textAbstract:
This paper focuses on investors’ different behavioral biases in China’s segmented stock markets and investigates the correlation between average holding periods, stock returns and investors’ disposition effect between 2010 and 2014. The results show that the disposition effect is prevalent in A-share market but is very weak in Growth Enterprise market and there is a lack of evidence to support the existence of disposition effect in B-share market. The study supports the view that investors’ experience and sophistication can partly help reduce investors’ behavioral biases in stock markets. It also indicates that investors in A-shares market prefer to hold stocks with larger market capitalization for longer periods, while investors of B-shares markets and Growth Enterprise market do not reveal a specific preference for market capitalization.
45
Marisetty, Nagendra, and M. Suresh Babu. "Dividend Announcements and Market Trends." International Journal of Economics and Finance 13, no. 10 (September 15, 2021): 139. http://dx.doi.org/10.5539/ijef.v13n10p139.
Full textAbstract:
This research primarily aims to study the impact of dividend announcements on the stock price of companies listed in the Indian stock market. Incidental to the study, it is necessary to understand whether the market trends have any role in affecting the changes in share prices due to dividend announcements. The companies listed on the stock market are diverse in terms of the industry, market capitalization, and performance. We analyze the S&P BSE 500 index stocks, which declare cash dividend every year without fail for ten years from 2008 – 17. Total 1755 sample was tested for dividend announcement and sample divided into large, medium, and small sample sizes based on the market capitalization of the stocks to test the market trend effect. Event methodology market model used to calculate the abnormal returns on the dividend announcement day.
The present research study examined the impact of dividend announcements on stocks in the Indian stock market. The results observe in twenty-four times based on market capitalization wise and market trend-wise dividend announcements. The results of the study are not the same for all dividend announcement observations. The study found positive abnormal returns on event day in most of the dividend announcement observations and it is similar to Litzenberger and Ramaswamy (1982), Asquith and Mullins Jr (1983), Grinblatt, Masulis, and Titman (1984), Chen, Nieh, Da Chen, and Tang (2009) and many previous research results studied in major developed stock markets and emerging stock markets. Full sample, large-cap, and small-cap final dividend average abnormal returns are positively significant only in bull market trend (period 2) similar to Below and Johnson (1996) and other market trends final dividend announcement abnormal returns are positive in most of the observations, but returns are not significant. Average abnormal returns are sensitive to market trends, especially abnormal small-cap returns more vulnerable to market trends.
46
Fatima Farooq, Muhammad Saeed Meo, Sajid Ali, and Usman Rasheed. "Co-movement between Sukuk, Conventional Bond and Islamic Stock Markets under Bullish and Bearish Market Conditions: An Application of Quantile-on-Quantile Regression." Journal of Accounting and Finance in Emerging Economies 6, no. 3 (September 30, 2020): 839–56. http://dx.doi.org/10.26710/jafee.v6i3.1390.
Full textAbstract:
This study explores the asymmetric co-movement between conventional bonds market, sukuk market and Islamic stock markets of top ten Islamic economies. The study used daily data ranging from 1st January 2008 to 31st December 2019. However, for the dependency structure, we used Quantile-on-Quantile (QQ) method, which captures the dependence between the entire distributions of financial assets and uncovers some nuance features of the relationship. The empirical findings show that under the stress condition (bearish condition), both bonds and stocks markets negatively commove. However, in the bullish market condition, these markets show week positive correlation/ co-movement in all the sample economies. The findings also confirmed that under the bearish condition, a mild negative correlation exists between sukuk and Islamic stock markets except for Malaysia. However, in the bullish market condition, sukuk markets and stock markets show strong positive correlation in all sample economies. Furthermore, study also enriches quantiles estimation by using quantiles granger causality approach. The findings show that the conventional bond market, sukuk market and Islamic stock market granger cause to each other on all the quantiles (in bullish or bearish market conditions).
47
Nyasha, Sheilla, and Nicholas M. Odhiambo. "The Australian stock market development: Prospects and challenges." Risk Governance and Control: Financial Markets and Institutions 3, no. 2 (2013): 39–48. http://dx.doi.org/10.22495/rgcv3i2art3.
Full textAbstract:
This paper highlights the origin and development of the Australian stock market. The country has three major stock exchanges, namely: the Australian Securities Exchange Group, the National Stock Exchange of Australia, and the Asia-Pacific Stock Exchange. These stock exchanges were born out of a string of stock exchanges that merged over time. Stock-market reforms have been implemented since the period of deregulation, during the 1980s; and the Exchanges responded largely positively to these reforms. As a result of the reforms, the Australian stock market has developed in terms of the number of listed companies, the market capitalisation, the total value of stocks traded, and the turnover ratio. Although the stock market in Australia has developed remarkably over the years, and was spared by the global financial crisis of the late 2000s, it still faces some challenges. These include the increased economic uncertainty overseas, the downtrend in global financial markets, and the restrained consumer confidence in Australia.
48
Rijal, Syamsu, and Ashwani Kumar Aggarwal. "Fostering The Changing Economic Market Demand from The View of Various Behavioral Social Personal and Economic Transformation: Empirical Evidence from A Developed Country." Jurnal Multidisiplin West Science 3, no. 05 (May 31, 2024): 670–87. http://dx.doi.org/10.58812/jmws.v3i05.1202.
Full textAbstract:
The key objective of the study is to foster the changing market demand from the view of various social, behavioral, personal, and economic transformations on individual investment decisions at Shanghai and Shenzhen stock markets in China. The study used a questionnaire to survey a total of 345 investors holding stocks of listed companies at both Shanghai and Shenzhen stock exchanges. The results of the study indicate that behavioral factors, personal factors, and market factors have a significant positive impact on individual investor investment decisions in both shanghai and Shenzhen stock markets while social factors have an insignificant negative impact on individual investor investment decisions in both shanghai and Shenzhen stock markets. Chinese stakeholders will understand better the role of various social, behavioral, personal, and markets factors and their impacts on stock market performance at both Shanghai and Shenzhen stock markets. The findings have important insights for various stakeholders i.e. government, regulatory bodies, practitioners, academia, industry, and researchers.
49
Reddy, Yajanth Rami. "A Tensorized Hierarchical Graph Attention Network for Stock Market Forecasting." International Journal for Research in Applied Science and Engineering Technology 11, no. 10 (October 31, 2023): 590–94. http://dx.doi.org/10.22214/ijraset.2023.56043.
Full textAbstract:
Abstract: Stock market forecasting is a tough mission because of its complex and dynamic nature. Deep learning models have recently been proven to be successful at stock market predictions. Traditional deep learning models, however, frequently disregard the hierarchical structure and temporal relationships of the stock market. Here, we introduce the StockTensor, a brand-new tensorized hierarchical graph attention network for stock market forecasting. StockTensor models the hierarchical structure of the stock market data by constructing a hierarchical graph of stocks. At each level of the hierarchy, StockTensor uses a graph attention network to learn the relationships between stocks and aggregate the information from neighboring stocks. StockTensor also models the temporal dependencies of the stock market data by using a recurrent neural network. The recurrent neural network learns to predict future stock prices based on the current stock prices and the historical stock prices. We evaluate StockTensor on two real-world stock market datasets. The results show that StockTensor outperforms several stateof-the-art stock market forecasting models.
50
Indrayono, Yohanes. "What Factors Affect Stocks’ Abnormal Return during the COVID-19 Pandemic: Data from the Indonesia Stock Exchange." European Journal of Business and Management Research 6, no. 6 (November 4, 2021): 1–11. http://dx.doi.org/10.24018/ejbmr.2021.6.6.1139.
Full textAbstract:
This study identifies Indonesian investors’ reactions to the drop in stock prices on the Indonesia Stock Exchange market, during the early months of the COVID-19 crisis, before and after the World Health Organization (WHO) announced that its global spread constitutes a pandemic. It also explores variables that influence stock returns on this market during the financial crisis caused by the COVID-19 pandemic. This study uses a regression analysis of 70 firms, listed on the Indonesia Stock Exchange to examine the pandemic’s influence on trading volume, market capitalization, profitability, and book value for the period December 31, 2019, to April 30, 2020. The results show that stock returns were lower in the early period of the financial crisis caused by the pandemic. Firms’ trading volumes, profitability and book values positively affected stock returns and their market capitalization negatively affected stock returns during the study period. This study contributes useful insights to the finance literature and stock-market participants in terms of dealing with stock markets during financial crises. This study recommends that in any crisis investors should begin buying stocks or increasing their stock purchases to achieve abnormal returns by choosing stocks that perform well in terms of firm profitability and book value by looking a number of financial factors.