Gotowe bibliografie tematyczne / Stock Returns

Gotowa bibliografia na temat „Stock Returns”

Autor: Grafiati
Data publikacji: 4 czerwca 2021
Data aktualizacji: 7 lipca 2024

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Artykuły w czasopismach na temat "Stock Returns"

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Miasary, Seftina Diyah. "PENERAPAN VECTOR AUTOREGRESSIVE (VAR) DALAM MEMPREDIKSI RETURN SAHAM DI INDONESIA". Jurnal Edukasi dan Sains Matematika (JES-MAT) 8, nr 2 (30.09.2022): 171–80. http://dx.doi.org/10.25134/jes-mat.v8i2.6225.

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The rate of return (return) and risk are inseparable in investing activities. One equilibrium model that describes the relationship between return and risk assumes that the expected return is influenced by more than one macroeconomic factor. Furthermore, the causal relationship between stock returns and macroeconomic factor returns was analyzed using VAR. The application of VAR in this study is to predict stock returns through the stages of checking data stationarity, determining the optimal lag length, testing Granger causality between variables, estimating VAR model parameters and Portmanteau diagnostic tests, and predicting stock returns. The results show that the VAR (1) model is the most appropriate model to describe the relationship between stock returns and macroeconomic factor returns with a significant model owned by BBCA, ICBP, INTP, KLBF, and SMGR stocks. Furthermore, the VAR (1) model is used to predict the five stock returns. The prediction results show that INTP's stock returns are negative while the returns of the other four stocks are positive. This shows that INTP shares experienced a capital loss, while the stock returns of BBCA, ICBP, KLBF, and SMGR experienced capital gains
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Zevallos, Mauricio, i Carlos del Carpio. "Metal Returns, Stock Returns and Stock Market Volatility". Economia 38, nr 75 (1.08.2015): 101–22. http://dx.doi.org/10.18800/economia.201501.003.

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Given the extensive participation of mining stocks in the Peruvian stock market, the Lima Stock Exchange (BVL) provides an ideal setting for exploring both the impact of metal returns on mining stock returns and stock market volatility, and the comovements between mining stock returns and metal returns. This research is a first attempt to explore these issues using international metal prices and the prices of the most important mining stocks on the BVL and the IGBVL index. To achieve this, we use univariate GARCH models to model individual volatilities, and the Exponentially Weighted Moving Average (EWMA) method and multivariate GARCH models with time-varying correlations to model comovements in returns. We found that Peruvian mining stock volatilities mimic the behavior of metal volatilities and that there are important correlation levels between metals and mining stock returns. In addition, we found time-varying correlations with distinctive behavior in different periods, with rises potentially related to international and local historical events.
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Monita, Sonya Dwi. "Pengaruh Return On Equity dan Debt To Equity Ratio terhadap Return Saham dengan Price To Book Value sebagai Variabel Intervening". Journal of Business and Economics (JBE) UPI YPTK 7, nr 3 (26.09.2022): 402–8. http://dx.doi.org/10.35134/jbeupiyptk.v7i3.191.

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This study aims to determine the effect of Return On Equity (ROE) and Debt Equity Ratio (DER) on stock returns with Price To Book Value (PBV) as an intervening variable in Manufacturing companies listed on the Indonesia Stock Exchange 2017-2021. The sample in this study was taken by purposive sampling method on manufacturing stocks listed on the Indonesia Stock Exchange 2017-2021. The number of samples used as many as 118 companies. The analytical method of this research is using multiple linear regression analysis method. The results of this study indicate that Return On Equity (ROE) has a significant effect on Price To Book Value (PBV), Debt Equity Ratio (DER) has a significant effect on Price To Book Value (PBV), Return On Equity (ROE) has a significant effect on Return Stocks, Debt Equity Ratio (DER) is not significant on Stock Returns, Price To Book Value (PBV) has a significant effect on Stock Returns, Return On Equity (ROE) does not mediate on stock returns through Price To Book Value (PBV) as an intervening variable, Debt Equity Ratio (DER) does not mediate stock returns through Price To Book Value (PBV) as an intervening variable in Manufacturing companies listed on the Indonesia Stock Exchange 2017-2021
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Vidović, Jelena. "Risk-return-volume causality on the Croatian stock market". Ekonomski vjesnik 37, nr 1 (2024): 79–92. http://dx.doi.org/10.51680/ev.37.1.6.

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Purpose: Causality between stock returns, volatility and traded volume for 10 most liquid stocks from Zagreb Stock Exchange (ZSE) is examined in this paper. Methodology: The paper relies on historical daily data regarding return, standard deviation and turnover for the period from 2015 to 2021. Vector Autoregressive Models (VARs) were estimated for each stock in-dividually. Based on estimated VAR models, Granger-causality tests were performed to estimate causality between trading volume, stock returns and volatility for most liquid stocks from the Croatian stock market. Results: Results strongly confirm that traded volume Granger causes volatility. Return remained irrelevant in terms of predicting traded volume and volatility of stock returns. Conclusion: Causality from return to volatility or causality from volatility to return can be confirmed only in shorter periods. Traded volume causes volatility for the majority of stocks regardless of how volatility was calculated. Causality from volatility to return and causality from volatility to volume are valid for half of the sample and need to be further investigated.
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WONG, HOCK TSEN. "REAL EXCHANGE RATE RETURNS AND REAL STOCK PRICE RETURNS IN THE STOCK MARKET OF MALAYSIA". Singapore Economic Review 64, nr 05 (12.12.2016): 1319–49. http://dx.doi.org/10.1142/s0217590816500387.

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This study examines the relationships between real exchange rate returns and real stock price returns in the stock market of Malaysia. The Kwiatkowski, Phillips, Schmidt and Shin (KPSS) and Dickey and Fuller (DF) unit root test statistics show that all the variables examined are found to be stationary in the first differences. The constant conditional correlation (CCC)-multivariate generalized autoregressive conditional heteroskedasticity (MGARCH) model shows that real exchange rate return of Malaysian ringgit against the United States dollar (RM/USD) and real stock price return of Kuala Lumpur Composite Index (KLCI) are found to be negative and significantly correlated. However, there is insignificant correlation between real exchange rate return of Malaysian ringgit against Japanese Yen (RM/¥) and real stock price return of KLCI. Moreover, the CCC-MGARCH models show that real exchange rate returns and real stock price returns of some stocks are found to be significantly correlated. The KPSS unit root test statistics show that the time invariant conditional variances of real exchange rate returns and real stock price returns are mostly found to be stationary in the levels. There is no evidence of Granger causality between the time invariant conditional variances of real exchange rate returns and real stock price return of KLCI but some evidence of Granger causality between the time invariant conditional variances of real exchange rate returns and real stock price returns. There is a link between the exchange rate market and the stock market in Malaysia but not every real stock price return is significantly linked with real exchange rate return.
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Kim, Dongnyoung, i Tih Koon Tan. "Ex-post stock return behaviour of corporate restructurings and corporate control". Review of Accounting and Finance 15, nr 4 (14.11.2016): 484–98. http://dx.doi.org/10.1108/raf-05-2015-0066.

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Purpose This paper aims to investigate the correlation between stock returns of the parent and newly created entity and the degree of return skewness in parents in the three different corporate restructurings. Design/methodology/approach Using a sample of spin-offs, equity carve-outs and tracking stocks, ordinary least squares regression is used to test the relationship between stock return correlation as well as stock return skewness and the type of corporate restructurings. Findings Tracking stock offering has the largest correlation in stock returns, whereas spin-off has the least correlation in stock returns. Also, the result from the skewness test is not consistent with the hypothesis that the stock returns skewness is positively related to the degree of ownership and control. Originality/value This is one of the few papers looking at the three corporate restructurings and their return skewness.
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Lumban Batu, Leon Franciscus, Rina Br Bukit i Narumondang Bulan Siregar. "Return on Equity, Cash Ratio & Debt Equity Ratio Affect Stock Returns in the Banking Industry Listed on the IDX With Non-Performing Loans as a Moderating Variable". International Journal of Research and Review 10, nr 7 (28.07.2023): 867–77. http://dx.doi.org/10.52403/ijrr.202307101.

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This study aims to determine the effect of return on equity, cash ratio and debt to equity ratio on stock returns in the banking industry listed on the IDX with non-performing loans as a moderating variable. The research design used is the simple design method. The population used in this study are banking companies listed on the Indonesia stock exchange for the 2016-2021 period, with a total sample of 26 companies using 156 data samples. The data analysis technique used is panel data analysis using the e-views program. The results of the study show that Return on equity has a positive and insignificant effect on stock returns, Cash ratio has a negative and significant effect on stock returns, Debt to equity ratio has a positive and insignificant effect on Return, Non-performing loans cannot moderate the effect of return on equity on returns stocks, non-performing loans cannot moderate the effect of cash ratio on stock returns and non-performing loans cannot moderate the effect of debt to equity ratio on stock returns. Keywords: Return on Equity, Cash Ratio and Debt to Equity Ratio, Stock Return, Non-Performing Loan
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Heny Sidanti i Annisa Istikhomah. "The Effect Of Stock Price, Share Return, Share Trading Volume, And Return Variant On Bid-Ask Spread On Textile And Garment Companies Listed On The Indonesia Stock Exchange, 2019-2020". International Journal of Science, Technology & Management 2, nr 4 (23.07.2021): 1357–66. http://dx.doi.org/10.46729/ijstm.v2i4.269.

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This study aims to obtain empirical evidence of the effect of Stock Price, Stock Return, Stock Trading Volume, and Return Variant on the Bid-Ask Spread of Stocks in Textile and Garment Companies Listed in Indonesia Stock Exchange in 2019-2020. The stock price used is the stock price recorded at the end of each closing period (closing price), stock returns are measured using the difference between returns on the research day and before the study divided by returns on the day before the study, stock trading volume is measured by the number of shares traded at the time of the study. t is divided by the number of shares outstanding at the time of the study, the variance of stock returns is measured using the standard deviation, and the bid-ask spread is measured by the difference between the selling price and the purchase price divided by the difference between the selling price and the purchase price divided by two. The population in this study is 17 textile and garment companies listed on the IDX. Based on the purposive sampling method, a sample of 16 companies was obtained with 309 data. This research data is obtained from the company's monthly data from 2019 to 2020. The results of the analysis show that stock prices and stock trading volumes affect the bid-ask spread, while stock returns and return variances do not affect the bid-ask spread. Meanwhile, simultaneously, stock prices, stock returns, stock trading volume, and return variance affect the bid-ask spread. This research data is obtained from the company's monthly data from 2019 to 2020. The results of the analysis show that stock prices and stock trading volume affect the bid-ask spread, while stock returns and return variances do not affect the bid-ask spread. Meanwhile, simultaneously, stock prices, stock returns, stock trading volume, and return variance affect the bid-ask spread. This research data is obtained from the company's monthly data from 2019 to 2020. The results of the analysis show that stock prices and stock trading volumes affect the bid-ask spread, while stock returns and return variances do not affect the bid-ask spread. Meanwhile, simultaneously, stock prices, stock returns, stock trading volume, and return variance affect the bid-ask spread.
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Huang, Fangzhou. "The impact of downside risk on UK stock returns". Review of Accounting and Finance 18, nr 1 (11.02.2019): 53–70. http://dx.doi.org/10.1108/raf-07-2017-0139.

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PurposeThis paper aims to investigate patterns in UK stock returns related to downside risk, with particular focus on stock returns during financial crises.Design/methodology/approachFirst, stocks are sorted into five quintile portfolios based on the relevant beta values (classic beta, downside beta and upside beta, calculated by the moving window approach). Second, patterns of portfolio returns are examined during various sub-periods. Finally, predictive powers of beta and downside beta are examined.FindingsThe downside risk is observed to have a significant positive impact on contemporaneous stock returns and a negative impact on future returns in general. In contrast, an inverse relationship between risk and return is observed when stocks are sorted by beta, contrary to the classic literature. UK stock returns exhibit clear time sensitivity, especially during financial crises.Originality/valueThis paper focuses on the impact of the downside risk on UK stock returns, assessed via a comprehensive sub-period analysis. This paper fills the gap in the existing literature, in which very few studies examine the time sensitivity in relation to the downside risk and the risk-return anomaly in the UK stock market using a long sample period.
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Truong, Loc Dong, H. Swint Friday i Tran My Ngo. "Market Reaction to Delisting Announcements in Frontier Markets: Evidence from the Vietnam Stock Market". Risks 11, nr 11 (16.11.2023): 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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Rozprawy doktorskie na temat "Stock Returns"

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Zevallos, Mauricio, i Carlos del Carpio. "Metal Returns, Stock Returns and Stock Market Volatility". Economía, 2015. http://repositorio.pucp.edu.pe/index/handle/123456789/118122.

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Given the extensive participation of mining stocks in the Peruvian stock market, the Lima Stock Exchange (BVL) provides an ideal setting for exploring both the impact of metal returns on mining stock returns and stock market volatility, and the comovements between mining stock returns and metal returns. This research is a first attempt to explore these issues using international metal prices and the prices of the most important mining stocks on the BVL and the IGBVL index. To achieve this, we use univariate GARCH models to model individual volatilities, and the Exponentially Weighted Moving Average (EWMA) method and multivariate GARCH models with time-varying correlations to model comovements in returns. We found that Peruvian mining stock volatilities mimic the behavior of metal volatilities and that there are important correlation levels between metals and mining stock returns. In addition, we found time-varying correlations with distinctive behavior in different periods, with rises potentially related to international and local historical events.
Dada la amplia participación de acciones mineras en el mercado de valores peruano, la Bolsa de Valores de Lima (BVL) resulta un escenario ideal para explorar tanto el impacto de los ren- dimientos de acciones de metales en los rendimientos de las acciones mineras y la volatilidad del Mercado de valores, así como los co-movimientos entre los rendimientos de las acciones mineras y los rendimientos de los metales. Este estudio es un primer intento en explorar estos temas usando precios internacionales de los metales y los precios de las acciones mineras más importantes de la BVL y del índice IGBVL. Para conseguir esto, hemos usado modelos GARCHunivariados para modelar las volatilidades individuales, y el método de Media Móvil Ponderada Exponencialmente (EWMA) y modelos GARCH multivariados con correlaciones de variantes en el tiempo a modelos de co-movimientos en rendimientos. Hemos encontrado que las volatilidades imitan el comportamiento de las volatilidades de los metales y que hay importantes niveles de correlación entre los metales y el retorno de las acciones mineras. Adicionalmente, encontramos correlaciones variantes en el tiempo con un comportamiento distintivo en periodos diferentes, el que aumenta potencialmente en relación con eventos históricos internacionales o nacionales.
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Kunze, Karl-Kuno, i Hans Gerhard Strohe. "Antipersistence in German stock returns". Universität Potsdam, 2010. http://opus.kobv.de/ubp/volltexte/2010/4558/.

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Persistence of stock returns is an extensively studied and discussed theme in the analysis of financial markets. Antipersistence is usually attributed to volatilities. However, not only volatilities but also stock returns can exhibit antipersistence. Antipersistent noise has a somewhat rougher appearance than Gaussian noise. Heuristically spoken, price movements are more likely followed by movements in the opposite direction than in the same direction. The pertaining integrated process exhibits a smaller range – prices seem to stay in the vicinity of the initial value. We apply a widely used test based upon the modified R/S-Method by Lo [1991] to daily returns of 21 German stocks from 1960 to 2008. Combining this test with the concept of moving windows by Carbone et al. [2004], we are able to determine periods of antipersistence for some of the series under examination. Our results suggest that antipersistence can be found for stocks and periods where extraordinary corporate actions such as mergers & acquisitions or financial distress are present. These effects should be properly accounted for when choosing and designing models for inference.
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Brookins, Benjamin David Lee. "Investor sentiment and stock returns". Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/88379.

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Thesis: S.M. in Management Research, Massachusetts Institute of Technology, Sloan School of Management, 2014.
Title as it appears in MIT degrees awarded booklet, February 2014: Sentiment shocks and stock returns. Cataloged from PDF version of thesis.
Includes bibliographical references (page 45).
Since Keynes coined the term animal spirits economists have been debating what the real impact human psychology is on economic variables. The major challenge in identifying these effects is the close ties between negative (positive) emotions and poor (good) future real outlook. I exploit a historical weighting anomaly in a widely cited US stock index to examine the impact of psychology on stock returns. I first argue this is a plausibly exogenous shock, and compare this measure to other measures found in the literature. I find that the measure doesn't seem to relate to previous proxies for investor sentiment, however, when I examine survey measures of interest rates and consumer confidence we find a relationship. I then examine how sentiment affects the cross section of stock returns, consistent with predictions I find that small stocks earn low subsequent returns when sentiment is low, and high returns when sentiment is high.
by Benjamin David Lee Brookins.
S.M. in Management Research
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BARADARANNIA, Mohammadreza. "Liquidity And Expected Stock Returns". Thesis, The University of Sydney, 2013. http://hdl.handle.net/2123/9367.

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Liquidity is among the primary attributes of many investment plans and financial instruments. In the Financial Services industry, portfolio managers tailor portfolios to fit their clients’ investment horizons and liquidity objectives and consider illiquidity costs in managing their portfolios. The impact of illiquidity on expected stock returns has been the centre of many studies over the past decade. This thesis employs a low-frequency proxy for the effective spreads, recently developed by Holden (2009) and examines three research problems in liquidity-equity pricing. In research problem 1, I re-examine the liquidity effect on expected stock returns in the NYSE over the period 1926–2008, the pre-1963 period, for which there is a lack of research, and the post-1963 period. The results from the entire sample of 1926–2008 show that expected returns increase with the stock level illiquidity. However, illiquidity level has explanatory power in the cross-sectional variation of expected stock returns only over the post-1963 period, and is, both economically and statistically, insignificant for the whole sample and the pre-1963 period. These findings are robust after taking into account various characteristics and risk controls. On the other hand, evidence from the pre-1963 sample suggests that the systematic market liquidity risk is significant in association with cross-sectional expected stock returns. Nevertheless, the most accurate evidence is provided over the entire sample. The analysis over the whole period of 1926–2008 shows that the systematic liquidity risk plays a significant role in the cross-sectional variation of expected stock returns. In research problem 2, I investigate whether the effect of liquidity on equity returns can be attributed to the liquidity level, as a stock characteristic, or a market-wide systematic liquidity risk. I develop a CAPM liquidity-augmented risk model and test the characteristic hypothesis against the systematic risk hypothesis for the liquidity effect. I find that the two-factor systematic risk model explains the liquidity premium. The hypothesis that the liquidity characteristic is compensated irrespective of liquidity risk loadings is not supported in the data. This result is robust over 1930–2008 data and subsamples of pre-1963 and post-1963 data both in the time-series and the cross-sectional analysis. The results demonstrate that the liquidity augmented CAPM approach is the correct way to incorporate the liquidity risk. In research problem 3, I explore liquidity costs as the explanation for the idiosyncratic volatility premium documented in the literature. Liquidity costs may affect the estimation of idiosyncratic volatility through the microstructure-induced noise in closing equity returns. I eliminate the microstructure influences from the returns and re-estimate the idiosyncratic volatility. I show that liquidity can explain the pricing ability of idiosyncratic volatility reported in the literature for value-weighted portfolios after controlling for the three Fama–French factors and also the Carhart momentum factor. The findings are robust in both the regression and double sorting portfolio analyses. The results from the equally-weighted portfolios indicate that idiosyncratic volatility cannot predict returns ahead either before or after correcting for the microstructure-induced bias. This research provides new empirical evidence which can assist academics, portfolio managers and practitioners to develop a broader understanding of the impact of liquidity costs on stock returns, and to incorporate liquidity in their pricing models.
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Abhakorn, Pongrapeeporn. "The cross-section of stock returns". Thesis, University of York, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.428059.

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Rytchkov, Oleg. "Essays on predictability of stock returns". Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/42333.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, 2007.
Includes bibliographical references.
This thesis consists of three chapters exploring predictability of stock returns. In the first chapter, I suggest a new approach to analysis of stock return predictability. Instead of relying on predictive regressions, I employ a state space framework. Acknowledging that expected returns and expected dividends are unobservable, I use the Kalman filter technique to extract them from the observed history of realized dividends and returns. The suggested approach explicitly accounts for the possibility that dividend growth can be predictable. Moreover, it appears to be more robust to structural breaks in the long-run relation between prices and dividends than the conventional OLS regression. I show that for aggregate stock returns the constructed forecasting variable provides statistically and economically significant predictions both in and out of sample. The likelihood ratio test based on a simulated finite sample distribution of the test statistic rejects the hypothesis of constant expected returns at the 1% level. In the second chapter, I analyze predictability of returns on value and growth portfolios and examine time variation of the value premium. As a major tool, I use the filtering technique developed in the first chapter. I construct novel predictors for returns and dividend growth on the value and growth portfolios and find that returns on growth stocks are much more predictable than returns on value stocks. Applying the appropriately modified state space approach to the HML portfolio, I build a novel forecaster for the value premium. Consistent with rational theories of the value premium, the expected value premium is time-varying and countercyclical. In the third chapter, based on the joint work with Igor Makarov, I develop a dynamic asset pricing model with heterogeneously informed agents.
(cont.) I focus on the general case in which differential information leads to the problem of "forecasting the forecasts of others" and to non-trivial dynamics of higher order expectations. I prove that the model does not admit a finite number of state variables. Using numerical analysis, I compare equilibria characterized by identical fundamentals but different information structures and show that the distribution of information has substantial impact on equilibrium prices and returns. In particular, asymmetric information might generate predictability in returns and high trading volume.
by Oleg Rytchkov.
Ph.D.
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Setiono, Bambang. "Financial statement information and stock returns". Thesis, University of Manchester, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.629949.

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This research investigates the relation between stock returns and financial statement information. There are two main objectives of this research. The first objective is to investigate the ability of financial statement information to predict stock returns. The second objective is to investigate the degree to which the UK stock market anticipates or reacts with a delay to earnings, book value, and other nonearnings information. There are two prediction analyses performed in this study: indirect prediction of stock returns via earnings and direct prediction of stock returns. Using the indirect prediction approach, this research obtains trading profits (abnormal returns) between 7.16 percent and 19.71 percent for a 24 months holding period, depending on the specific measure of abnormal return and weighting scheme involved. Using the direct prediction approach, this study obtains trading profits between 2.02 percent and 3.43 percent for 12 months holding periods and between 2.42 percent and 5.01 percent for 24 months holding periods. Even though the direct prediction approach earns smaller and less significant trading profits, size and book-to-market effects as well as a control for time varying risk cannot explain the abnormal returns from the trading strategy. In contrast, controlling for time varying risk and size might explain the abnormal returns obtained from the indirect prediction approach. This research finds evidence of market anticipation as well as delayed reaction to earnings, book value, and other nonearnings information. The degree of market anticipation and delayed reaction to accounting information are related to market capitalization. There is more evidence of market anticipation to earnings from large firms than to earnings from small firms. On the other hand, there is more evidence of market anticipation to book values from small firms than to book values from large firms. In general, this research finds the degree of delayed market reaction to nonearnings information is higher than the degree of market anticipation of nonearnings information. However, by and large, the delayed market reaction to this nonearnings information is observed more for small firms.
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Klähn, Judith. "The predictability of German stock returns /". Wiesbaden : Wiesbaden : Deutscher Universitäts-Verlag ; Gabler, 2000. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=008969264&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.

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Lin, Gang. "Nesting regime-switching GARCH models and stock market volatility, returns and the business cycle /". 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?p9906497.

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Kruger, Theunis Lodewicus. "Dividend stability, dividend yield and stock returns on the Johannesburg Stock Exchange". Thesis, Stellenbosch : Stellenbosch University, 2001. http://hdl.handle.net/10019.1/52241.

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Thesis (MBA)--Stellenbosch University, 2001.
ENGLISH ABSTRACT: This study investigates the relationship between dividends and stock returns on the Johannesburg Stock Exchange (JSE). In this mini study project a regression model is used to investigate the relationship between dividend yield portfolios and stock returns. Each of these dividend yield portfolios are further subdivided into dividend stability portfolios which together with a regression model are used to investigate the relationship between dividend stability and stock returns on the JSE. It follows from this study that there is a non-linear relationship between the risk-adjusted returns and dividend yields. A significant finding of this study is the fact that there is an inverse linear relationship between the dividend yield and average stock returns for dividend paying portfolios on the JSE. Investors on the JSE appear to place a premium on capital gains as opposed to dividends. It follows from this study that there is an inverse correlation between dividend stability and the risk-adjusted return with the beta coefficient increasing as dividend stability decreases. Within a particular yield portfolio, it is evident that higher systematic risk is associated with shares with unstable dividend yielding histories. It is clear from the results that this dividend signalling is not limited to high yielding stocks alone. As dividends are not entirely controlled by managers, a low stable dividend yield could signal a low exposure to systematic risk to outsiders.
AFRIKAANSE OPSOMMING: In hierdie studie word die verband tussen dividende en aandeelopbrengste op die Johannesburgse Effektebeurs ondersoek. 'n Regressiemodel is in hierdie mini werkstuk gebruik om die verwantskap tussen dividend opbrengsportfolios en aandeelopbrengs te ondersoek. Elk van hierdie opbrengsportfolios is vervolgens verder verdeel in dividendstabiliteitsportfolios wat tesame met 'n regressiemodel gebruik is om die verband tussen dividendstabiliteit en aandeelopbrengs te bepaal. Dit volg uit hierdie studie dat daar 'n nie-lineêre verband tussen risiko aangepaste aandeelopbrengs en dividendopbrengs bestaan. 'n Noemenswaardige bevinding is die inverse lineêre verwantskap tussen dividend en gemiddelde aandeelopbrengs vir dividend betalende aandele op die Johannesburgse Effektebeurs. Dit blyk asof beleggers op die Johannesburgse Effektebeurs 'n premie plaas op kapitaalgroei ten koste van dividendopbrengs. Dit volg ook uit hierdie studie dat daar 'n inverse korrelasie is tussen dividendstabiliteit en risiko aangepaste aandeelopbrengs met die beta koëffissiënte wat toeneem soos dividendstabiliteit afneem. Binne 'n spesifieke dividendopbrengsportfolio is dit duidelik dat hoër sistematiese risiko geassosieer word met onstabiele historiese dividendopbrengste. Dit volg uit die resultate dat hierdie inligtingoordrag deur middel van dividende, nie beperk is tot hoë dividendopbrengs aandele nie. Aangesien dividende nie uitsluitlik deur bestuurders beheer word nie, kan 'n aandeel met lae maar stabiele dividendopbrengs, 'n boodskap van lae blootstelling aan sistematiese risiko aan die mark oordra.
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Książki na temat "Stock Returns"

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McMillan, David G. Predicting Stock Returns. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-69008-7.

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Livdan, Dmitry. Financially constrained stock returns. Cambridge, Mass: National Bureau of Economic Research, 2006.

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Hjalmarsson, Erik. Predicting global stock returns. Washington, D.C: Federal Reserve Board, 2008.

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Schwert, G. William. Heteroskedasticity in stock returns. Cambridge, MA: National Bureau of Economic Research, 1989.

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Lamont, Owen A. Investment plans and stock returns. Cambridge, MA: National Bureau of Economic Research, 1999.

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Calvet, Laurent E. Multifrequency news and stock returns. Cambridge, MA: National Bureau of Economic Research, 2005.

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Titman, Sheridan. Capital investments and stock returns. Cambridge, Mass: National Bureau of Economic Research, 2003.

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Calvet, Laurent E. Multifrequency news and stock returns. Cambridge, Mass: National Bureau of Economic Research, 2005.

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Lamont, Owen A. Financial constraints and stock returns. Cambridge, MA: National Bureau of Economic Research, 1997.

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Asquith, Paul. Short interest and stock returns. Cambridge, MA: National Bureau of Economic Research, 2004.

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Części książek na temat "Stock Returns"

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McMillan, David G. "Introduction". W Predicting Stock Returns, 1–7. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69008-7_1.

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McMillan, David G. "Where Does Returns and Cash-Flow Predictability Occur? Evidence from Stock Prices, Earnings, Dividends and Cointegration". W Predicting Stock Returns, 9–26. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69008-7_2.

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McMillan, David G. "Forecasting Stock Returns—Historical Mean Vs. Dividend Yield: Rolling Regressions and Time-Variation". W Predicting Stock Returns, 27–56. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69008-7_3.

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McMillan, David G. "Returns and Dividend Growth Switching Predictability". W Predicting Stock Returns, 57–75. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69008-7_4.

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McMillan, David G. "Which Variables Predict and Forecast Stock Market Returns?" W Predicting Stock Returns, 77–101. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69008-7_5.

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McMillan, David G. "Forecast and Market Timing Power of the Model and the Role of Inflation". W Predicting Stock Returns, 103–29. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69008-7_6.

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McMillan, David G. "Summary and Conclusion". W Predicting Stock Returns, 131–33. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69008-7_7.

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Politis, Dimitris N., Joseph P. Romano i Michael Wolf. "Subsampling Stock Returns". W Springer Series in Statistics, 291–314. New York, NY: Springer New York, 1999. http://dx.doi.org/10.1007/978-1-4612-1554-7_13.

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Wu, Kekun. "Nonstationarity of Stock Returns". W Difference Equations, Discrete Dynamical Systems and Applications, 153–65. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24747-2_12.

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Singh, Shveta, P. K. Jain i Surendra Singh Yadav. "Volatility in Stock Returns". W India Studies in Business and Economics, 145–60. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0868-9_7.

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Streszczenia konferencji na temat "Stock Returns"

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Horng, Wann-Jyi, i Jun-Yen Lee. "An Impact of U.S. and U.K. Stock Return Rates' Volatility on the Stock Market Returns: An Evidence Study of Germany's Stock Market Returns". W 2008 Third International Conference on Convergence and Hybrid Information Technology (ICCIT). IEEE, 2008. http://dx.doi.org/10.1109/iccit.2008.415.

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Kim, Youngsoo, i Jung Chul Park. "PRESIDENTIAL POWER AND STOCK RETURNS". W 48th International Academic Conference, Copenhagen. International Institute of Social and Economic Sciences, 2019. http://dx.doi.org/10.20472/iac.2019.048.026.

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Assagaf, Aminullah, Meithiana Indrasari i Eddy Yunus. "Determinants of Stock Returns on the Indonesian Stock Exchange". W Proceedings of the 1st Asian Conference on Humanities, Industry, and Technology for Society, ACHITS 2019, 30-31 July 2019, Surabaya, Indonesia. EAI, 2019. http://dx.doi.org/10.4108/eai.30-7-2019.2287602.

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"ARE SECURITIZED REAL ESTATE RETURNS MORE PREDICTABLE THAN STOCK RETURNS?" W 15th Annual European Real Estate Society Conference: ERES Conference 2008. ERES, 2008. http://dx.doi.org/10.15396/eres2008_252.

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Chang, Ya-chi, Sheng-yun Yu i Ruey-shii Chen. "Industry Concentration, Profitability and Stock Returns". W 2010 International Conference on Information Management, Innovation Management and Industrial Engineering (ICIII). IEEE, 2010. http://dx.doi.org/10.1109/iciii.2010.333.

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Zeng, Kailin, Ebenezer Fiifi Emire Atta Mills, Xiuzhi Zhang i Shaolong Zeng. "Co-momentum and Stock Market Returns". W Proceedings of the Third International Conference on Economic and Business Management (FEBM 2018). Paris, France: Atlantis Press, 2018. http://dx.doi.org/10.2991/febm-18.2018.27.

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Xie, Mengni. "Chinese Investor Sentiment and Stock Returns". W 2016 International Conference on Economics and Management Innovations. Paris, France: Atlantis Press, 2016. http://dx.doi.org/10.2991/icemi-16.2016.39.

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Malchev, Bojan. "Financial Performance Indicators and Stock Returns: A Decade-Long Analysis of MBI10 Firms in North Macedonia". W Economic and Business Trends Shaping the Future. Ss Cyril and Methodius University, Faculty of Economics-Skopje, 2023. http://dx.doi.org/10.47063/ebtsf.2023.0008.

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This paper investigates the relationship between financial performance indicators and annual stock returns of the MBI10 companies in North Macedonia over a ten-year period from 2013 to 2022. A total of 100 observations from the Macedonian stock market index (MBI10) are analyzed, using audited financial statements as the primary data source. The financial performance indicators studied include Return on Assets (ROA), Return on Equity (ROE), Earnings per Share (EPS), and Dividend per Share (DPS). A multiple linear regression model is applied to examine the impact of these indicators on annual stock returns, with the model estimated through ordinary least squares (OLS) estimation. The research tests four hypotheses, aiming to establish significant positive relationships between ROA and Stock Return, as well as EPS and Stock Return. The results confirm the hypotheses related to ROA and EPS, with significant positive impacts on Stock Return. However, the relationships between ROE, DPS, and Stock Return lack statistical significance. The findings suggest that the financial performance indicators considered in this study only account for a limited proportion (4.9%) of the variations in Stock Return, indicating the influence of other essential factors not included in the model. To enhance the reliability of the findings, a robustness check was conducted by introducing two control variables: Macedonian GDP annual real growth rates, and DAX30 Index annual rate of return. The regression model, including these control variables, exhibited almost the same results as the model without them. Furthermore, the model with the control variables demonstrated a slightly higher Adjusted R Square value (0.058) compared to the model without them (0.049), implying a slightly improved explanatory power.This study highlights the complexities of the Macedonian stock market and emphasizes the importance of investigating additional factors that significantly contribute to stock price movements and returns in this specific market context.
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Devi, M. Uma, P. Akilandeswari i M. Eliazer. "Stock Market Ontology-Based Knowledge Management for Forecasting Stock Trading". W 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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Smerkolj, Nik, i Marko Jeran. "Testing Market Efficiency in Emerging Markets’ Stock Indices with Runs Tests". W Socratic Lectures 8. University of Lubljana Press, 2023. http://dx.doi.org/10.55295/psl.2023.ii17.

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According to the efficient market hypothesis (EMH), the prices of securities reflect all the available information on the market. Efficient markets have an important consequence – it is not possible for an investor to consistently outperform the market by using infor-mation that is not already reflected in the prices of securities. No matter how much re-sources one deploys into security analysis, no excess return can be made, which means that investors seeking higher returns must bear higher risk given the risk-return trade-off. Inefficient markets, on the other hand, offer investors opportunities for higher returns at the same risk profile. In this scientific contribution, we test seven emerging markets' stock indices for a weak form of market efficiency. Numerous previous research indicates that emerging markets are not fully efficient and that prices on their stock markets do not fol-low a random walk. We performed runs tests on weekly and monthly returns of stock in-dices and found statistically significant results in three indices for weekly and three in-dices for monthly returns, which indicates that these indices violate weak form of market efficiency. We found insignificant results, which indicate efficient markets, only for weekly and monthly returns on the Indian BSE Sensex 30 Index. Thus we come to similar conclusions as other authors that emerging markets persist to violate weak form of mar-ket efficiency and remain an attractive opportunity for investors seeking to exploit ineffi-ciencies. Keywords: Market efficiency; Efficient market hypothesis; Random walk; Emerging mar-kets; Stock Exchange Index; Runs test
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Raporty organizacyjne na temat "Stock Returns"

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Schwert, G. William, i Paul Seguin. Heteroskedasticity in Stock Returns. Cambridge, MA: National Bureau of Economic Research, maj 1989. http://dx.doi.org/10.3386/w2956.

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Livdan, Dmitry, Horacio Sapriza i Lu Zhang. Financially Constrained Stock Returns. Cambridge, MA: National Bureau of Economic Research, październik 2006. http://dx.doi.org/10.3386/w12555.

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Pastor, Lubos, i Pietro Veronesi. Political Cycles and Stock Returns. Cambridge, MA: National Bureau of Economic Research, luty 2017. http://dx.doi.org/10.3386/w23184.

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Bordalo, Pedro, Nicola Gennaioli, Rafael La Porta i Andrei Shleifer. Diagnostic Expectations and Stock Returns. Cambridge, MA: National Bureau of Economic Research, wrzesień 2017. http://dx.doi.org/10.3386/w23863.

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

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Asquith, Paul, Parag Pathak i Jay Ritter. Short Interest and Stock Returns. Cambridge, MA: National Bureau of Economic Research, kwiecień 2004. http://dx.doi.org/10.3386/w10434.

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Lamont, Owen, Christopher Polk i Jesus Saa-Requejo. Financial Constraints and Stock Returns. Cambridge, MA: National Bureau of Economic Research, październik 1997. http://dx.doi.org/10.3386/w6210.

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Lamont, Owen. Investment Plans and Stock Returns. Cambridge, MA: National Bureau of Economic Research, luty 1999. http://dx.doi.org/10.3386/w6973.

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Chan, Konan, Louis K. Chan, Narasimhan Jegadeesh i Josef Lakonishok. Earnings Quality and Stock Returns. Cambridge, MA: National Bureau of Economic Research, maj 2001. http://dx.doi.org/10.3386/w8308.

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Titman, Sheridan, K. C. John Wei i Feixue Xie. Capital Investments and Stock Returns. Cambridge, MA: National Bureau of Economic Research, wrzesień 2003. http://dx.doi.org/10.3386/w9951.

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