Relevant bibliographies by topics / Stock market

Academic literature on the topic 'Stock market'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 August 2024

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Journal articles on the topic "Stock market"

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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.

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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.
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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.

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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.
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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.

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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.
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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.

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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.
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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.

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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.
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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.

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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.
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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.

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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.
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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.

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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.
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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.

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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
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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.

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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.
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Dissertations / Theses on the topic "Stock market"

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Wong, Michael C. S. "Technical analysis and market inefficiency a study of the Hong Kong stock market /." online access from ProQuest databases, 1997. http://libweb.cityu.edu.hk/cgi-bin/er/db/pqdiss.pl?9907800.

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Liu, Yuna. "Essays on Stock Market Integration - On Stock Market Efficiency, Price Jumps and Stock Market Correlations." Doctoral thesis, Umeå universitet, Nationalekonomi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-119873.

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This thesis consists of four self-contained papers related to the change of market structure and the quality of equity market. In Paper [I] we found, by using of a Flexible Dynamic Component Correlations (FDCC) model, that the creation of a common cross-border stock trading platform has increased the long-run trends in conditional correlations between foreign and domestic stock market returns. In Paper [II] we study whether the creation of a uniform Nordic and Baltic stock trading platform has affected weak-form information efficiency. The results indicate that the stock market consolidations have had a positive effect on the information efficiency and turnover for an average firm. The merger effects are, however, asymmetrically distributed in the sense that relatively large (small) firms located on relatively large (small) markets experience an improved (reduced) information efficiency and turnover. Although the results indicate that changes in the level of investor attention (measured by turnover) may explain part of the changes in information efficiency, they also lend support to the hypothesis that merger effects may partially be driven by changes in the composition of informed versus uninformed investors following a stock. Paper [III] analyzes whether the measured level of trust in different countries can explain bilateral stock market correlations. One finding is that generalized trust among nations is a robust predictor for stock market correlations. Another is that the trust effect is larger for countries which are close to each other. This indicates that distance mitigates the trust effect. Finally, we confirm the effect of trust upon stock market correlations, by using particular trust data (bilateral trust between country A and country B) as an alternative measurement of trust. In Paper [IV] we present the impact of the stock market mergers that took place in the Nordic countries during 2000 – 2007 on the probabilities for stock price jumps, i.e. for relatively extreme price movements. The main finding is that stock market mergers, on average, reduce the likelihood of observing stock price jumps. The effects are asymmetric in the sense that the probability of sudden price jumps is reduced for large and medium size firms whereas the effect is ambiguous for small size firms. The results also indicate that the market risk has been reduced after the stock market consolidations took place.
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Chen, Gang. "The Chinese stock market : an emperical analysis of market segmentation, inter-relationships and theoretical versus actual stock prices." Thesis, University of Aberdeen, 2011. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=165872.

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This thesis contributes to our knowledge of the behaviour of the Chinese stock market by offering an empirical investigation into issues such as market segmentation, inter‐relationships between Chinese stock markets and inter‐relationships with foreign stock markets. Basic questions which have been typically analysed for developed stock markets are considered in this thesis. These include an analysis of core concepts such as volatility; causal links with economic variables and the reasons why the theoretical stock price may be different from the actual stock price. Methodological methods include; cointegration, generalised autoregressive heteroscedastic modelling (GARCH), vector autoregressive framework modelling (VAR) and panel data analysis. Both daily and monthly observations are used over a time period from 1996 to 2006. The results indicate that there is a rich set of reasons why we may observe phenomena such as a discount on B shares and a relationship between A shares and B shares. The findings also suggest that China is not isolated from the rest of the world and that there is evidence of inter‐relationships with foreign stock markets and that Chinese stock market prices are close to their fundamental value. This is not generally the finding for developed stock markets. Overall, it appears that the methodological approaches usually associated with developed stock markets can serve us well as useful tools in creating a deeper understanding of the underlying fundamentals describing the Chinese stock market.
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Kwok, Kam Hong. "Two essays on Chinese stock market /." View abstract or full-text, 2003. http://library.ust.hk/cgi/db/thesis.pl?FINA%202003%20KWOK.

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Cheung, Ming-yan William. "Market microstructure of an order driven market." Click to view the E-thesis via HKUTO, 2005. http://sunzi.lib.hku.hk/hkuto/record/B3203782X.

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Lange, Joe. "An intraday analysis of stock market liquidity /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 1998. http://wwwlib.umi.com/cr/ucsd/fullcit?p9906485.

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Ignatius, Roger. "The Bombay Stock Exchange: tests of market efficiency." Thesis, University of North Texas, 1991. https://digital.library.unt.edu/ark:/67531/metadc332561/.

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This dissertation analyzes the efficiency of the Bombay Stock Exchange (BSE) and the relationship of stock return patterns on the BSE with those of the New York Stock Exchange (NYSE). The data includes daily closing values of the BSE and S&P 500 Indexes for the period 1979-1990 and bi-weekly closing prices on 27 of the most active stocks on the BSE for the period 1980-1990.
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Kim, Jaemin. "The impact of open market share repurchases on volatility and liquidity : are open market share repurchase firms making the market for their own shares? /." Thesis, Connect to this title online; UW restricted, 2001. http://hdl.handle.net/1773/8795.

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Cheung, Oi Lin. "Market reactions to stock splits in the Hong Kong stock market." Thesis, University of Macau, 1997. http://umaclib3.umac.mo/record=b1636218.

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Khalid, Al-abdulqader. "Share valuation and stock market efficiency in the Saudi stock market." Thesis, University of Dundee, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.561297.

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Books on the topic "Stock market"

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Elkouby, Jean-Maurice. Stock market behaviour. Carnforth, Lancs: Mace Computer Services, 1992.

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Fuller, Donna Jo. The stock market. Minneapolis: Lerner Publications Company, 2006.

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Dunnan, Nancy. The stock market. Englewood Cliffs, NJ: Silver Burdett Press, 1990.

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Ahmed, Ayaz. Stock market interlinkages in emerging markets. Islamabad: Pakistan Institute of Development Economics, 1998.

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Dorodnykh, Ekaterina. Stock Market Integration. London: Palgrave Macmillan UK, 2014. http://dx.doi.org/10.1057/9781137381705.

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Hiremath, Gourishankar S. Indian Stock Market. New Delhi: Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1590-5.

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Pictures, Zefa. The stock market. London: Zefa Pictures, 1997.

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Holloway, Clark. Stock market 101. Fremont, Calif: Jain Pub., 1996.

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Schwager, Jack D. Stock Market Wizards. New York: HarperCollins, 2007.

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1947-, Dimson Elroy, ed. Stock market anomalies. Cambridge [Cambridgeshire]: Cambridge University Press, 1988.

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Book chapters on the topic "Stock market"

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Busu, Mihail. "Stock Market." In Essentials of Investment and Risk Analysis, 51–82. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-15056-2_4.

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Goufeng, Sun. "Stock Market." In Financial Reforms in Modern China, 177–228. New York: Palgrave Macmillan US, 2015. http://dx.doi.org/10.1057/9781137504449_5.

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Khanchandani, Khushi, Neha Patil, and Vineeta Bhujle. "Virtual Stocks: Stock Market Simulator." In Information and Communication Technology for Competitive Strategies (ICTCS 2021), 253–65. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-0098-3_26.

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Andraszewicz, Sandra. "Stock Markets, Market Crashes, and Market Bubbles." In Psychological Perspectives on Financial Decision Making, 205–31. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-45500-2_10.

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Mobarek, Asma, and Sabur Mollah. "Market Integration in Developed and Emerging Markets." In Global Stock Market Integration, 73–97. New York: Palgrave Macmillan US, 2016. http://dx.doi.org/10.1057/9781137367549_3.

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Dorodnykh, Ekaterina. "Introduction." In Stock Market Integration, 1–5. London: Palgrave Macmillan UK, 2014. http://dx.doi.org/10.1057/9781137381705_1.

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Dorodnykh, Ekaterina. "A Literature Review of the Stock Market Integration." In Stock Market Integration, 6–28. London: Palgrave Macmillan UK, 2014. http://dx.doi.org/10.1057/9781137381705_2.

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Dorodnykh, Ekaterina. "Evidences from the Recent History." In Stock Market Integration, 29–49. London: Palgrave Macmillan UK, 2014. http://dx.doi.org/10.1057/9781137381705_3.

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Dorodnykh, Ekaterina. "Determinants of Stock Market Integration." In Stock Market Integration, 50–83. London: Palgrave Macmillan UK, 2014. http://dx.doi.org/10.1057/9781137381705_4.

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Dorodnykh, Ekaterina. "Conclusions." In Stock Market Integration, 84–86. London: Palgrave Macmillan UK, 2014. http://dx.doi.org/10.1057/9781137381705_5.

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Conference papers on the topic "Stock market"

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Devi, M. Uma, P. Akilandeswari, and M. Eliazer. "Stock Market Ontology-Based Knowledge Management for Forecasting Stock Trading." In International Research Conference on IOT, Cloud and Data Science. Switzerland: Trans Tech Publications Ltd, 2023. http://dx.doi.org/10.4028/p-02laqd.

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Today’s markets are rather matured and arbitrage opportunities remain for a very short time. The main objective of the paper is to devise a stock market ontology-based novel trading strategy employing machine learning to obtain maximum stock return with the highest stock ratio. The paper aims to create a dynamic portfolio to obtain high returns. In this work, the impact of the applied machine learning techniques on the Chinese market was studied. The problem of investing a particular total amount in a large universe of stocks is considered. The Chinese stocks traded on Shanghai Stock Exchange and Shenzhen Stock Exchange are chosen to be the entire universe. The inputs that are considered are fundamental data and company-specific technical indicators unlike the macroscopic factors considered in the existing systems. In the stock market document repository, ontological constructs with Word Sense Disambiguation (WSD) algorithm improve the conceptual relationships and reduce the ambiguities in Ontological construction. The machine learning techniques Kernel Regression and Recurrent Neural Networks are used to start the analysis. The predicted values of stock prices from the Artificial Neural Network provided quite accurate results with an accuracy level of 97.55%. In this study, the number of nodes will be selected based on Variance-Bias plots by tracking the error on the in-sample data set and the validation data set.
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Bildirici, Melike, Bahri Sonüstün, and Seyit M. Gökmenoğlu. "CDS - Stock market chaotic relationship - Turkish stock market case." In TURKISH PHYSICAL SOCIETY 35TH INTERNATIONAL PHYSICS CONGRESS (TPS35). AIP Publishing, 2019. http://dx.doi.org/10.1063/1.5135466.

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Iacomin, Radu. "Stock market prediction." In 2015 19th International Conference on System Theory, Control and Computing (ICSTCC). IEEE, 2015. http://dx.doi.org/10.1109/icstcc.2015.7321293.

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Kumar, Gaurav, Kuldeep Mahto, Harsh Tandon, and Preeti Bajaj. "Stock Market Analysis." In 2021 3rd International Conference on Advances in Computing, Communication Control and Networking (ICAC3N). IEEE, 2021. http://dx.doi.org/10.1109/icac3n53548.2021.9725719.

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Balaji, Ch, B. Pavan Vara Prasad, and T. Harshitha. "A comparative analysis of Indian stock market with international stock markets." In CONTEMPORARY INNOVATIONS IN ENGINEERING AND MANAGEMENT. AIP Publishing, 2023. http://dx.doi.org/10.1063/5.0158538.

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Tasevska, Ivona. "EMPIRICAL RESEARCH ON THE INFORMATION EFFICIENCY OF THE MACEDONIAN STOCK EXCHANGE." In Economic and Business Trends Shaping the Future. Ss Cyril and Methodius University, Faculty of Economics-Skopje, 2022. http://dx.doi.org/10.47063/ebtsf.2022.0027.

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One of the basic hypotheses in modern finance that defines financial markets is the Efficient Market Hypothesis. The existence of information efficient markets, where all information is incorporated in the price of financial instruments is the basis of rational economic theory. There may be an upward or downward trend in the financial markets, but after the inclusion of new information in the financial instruments, they would stabilize until the next new information. In addition to the definition of efficient markets, the hypothesis of random walk has a significant application, which explains that the market cannot be beaten and that prices and returns move in a random upward or downward direction. The paper includes two methodologies to confirm the efficiency of the financial markets. The first research was conducted in order to confirm the hypothesis of a random walk implementing a coefficient of variance test. The test was conducted using a large series of data of the returns’ movement of stock exchange indices on the Macedonian, Belgrade, Zagreb, Sofia and Ljubljana Stock Exchange, as well as the American S&P500 index. The second research which is including the model of market multipliers was conducted for the most liquid stocks on the Macedonian Stock Exchange and selected stocks from the US Stock Exchange Markets, in order to show the underestimation or overestimation in relation to the market value of stocks, thus to show the sentiment that investors have when trading a certain type of stock. The results of the research show that the regional financial markets, as well as the domestic ones, do not follow the random walk, giving an opportunity to the possibility of using alternative behavioral approaches to explain the reasons for the deviation. For the second survey, where significant differences in the fundamental and market value of the stocks appear, the reason for the deviation is the expectations of investors.
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Chang, Juifang, and Son Van Duong. "Stock Index Forecasting for Vietnam's Stock Market." In 2012 Sixth International Conference on Genetic and Evolutionary Computing (ICGEC). IEEE, 2012. http://dx.doi.org/10.1109/icgec.2012.135.

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Wattenberg, Martin. "Visualizing the stock market." In CHI '99 extended abstracts. New York, New York, USA: ACM Press, 1999. http://dx.doi.org/10.1145/632716.632834.

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Wu, Liang-Chuan, and Liang-Hong Wu. "Stock Market Index Tracking." In 2009 International Conference on Management and Service Science (MASS). IEEE, 2009. http://dx.doi.org/10.1109/icmss.2009.5304681.

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Nagy, László, and Mihály Ormos. "Stock Market Index Clusters." In 2nd International Scientific Conference - Economics and Management: How to Cope With Disrupted Times. Association of Economists and Managers of the Balkans, Belgrade, Serbia; Faculty of Management Koper, Slovenia; Doba Business School - Maribor, Slovenia; Integrated Business Faculty - Skopje, Macedonia; Faculty of Management - Zajecar, Serbia, 2018. http://dx.doi.org/10.31410/eman.2018.181.

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Reports on the topic "Stock market"

1

Greenwood, Robin, Toomas Laarits, and Jeffrey Wurgler. Stock Market Stimulus. Cambridge, MA: National Bureau of Economic Research, March 2022. http://dx.doi.org/10.3386/w29827.

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Griffin, John, Federico Nardari, and Rene Stulz. Stock Market Trading and Market Conditions. Cambridge, MA: National Bureau of Economic Research, September 2004. http://dx.doi.org/10.3386/w10719.

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Shleifer, Andrei, and Robert Vishny. Stock Market Driven Acquisitions. Cambridge, MA: National Bureau of Economic Research, August 2001. http://dx.doi.org/10.3386/w8439.

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Guiso, Luigi, Paola Sapienza, and Luigi Zingales. Trusting the Stock Market. Cambridge, MA: National Bureau of Economic Research, October 2005. http://dx.doi.org/10.3386/w11648.

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Guo, Hui, and Robert Savickas. Idiosyncratic Volatility, Stock Market Volatility, and Expected Stock Returns. Federal Reserve Bank of St. Louis, 2003. http://dx.doi.org/10.20955/wp.2003.028.

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Chang, Briana, and Harrison Hong. Assignment of Stock Market Coverage. Cambridge, MA: National Bureau of Economic Research, January 2017. http://dx.doi.org/10.3386/w23115.

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Maggio, Marco Di, Amir Kermani, and Kaveh Majlesi. Stock Market Returns and Consumption. Cambridge, MA: National Bureau of Economic Research, January 2018. http://dx.doi.org/10.3386/w24262.

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McGrattan, Ellen, and Edward Prescott. Is the Stock Market Overvalued? Cambridge, MA: National Bureau of Economic Research, January 2001. http://dx.doi.org/10.3386/w8077.

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Barro, Robert, and José Ursúa. Stock-Market Crashes and Depressions. Cambridge, MA: National Bureau of Economic Research, February 2009. http://dx.doi.org/10.3386/w14760.

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Greenwald, Daniel, Martin Lettau, and Sydney Ludvigson. Origins of Stock Market Fluctuations. Cambridge, MA: National Bureau of Economic Research, January 2014. http://dx.doi.org/10.3386/w19818.

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