scholarly journals The effects of dividend policy to stock prices of listed companies in Vietnam stock market

2020 ◽  
Author(s):  
Thị Lam Hồ ◽  
Thùy Phương Trâm Hồ
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Dividend Policy ◽  
Corporate Value ◽  
Business Managers ◽  
Dividend Payment ◽  
Share Prices ◽  
Finance Management ◽  
The Impact

Dividend policy is one of the most important policies in corporate finance management. Understanding the impact of dividend policy on the distribution of profits, corporate value and thus on the stock price is important for business managers to make policies and for investors to make investment decisions. This study is conducted to evaluate the impact of dividend policy on share prices for companies listed on Vietnam’s stock market in the period from 2010 to 2018, based on the availability of continuous dividend payment data. Using the FGLS method with panel data of 100 companies listed on the HoSE and HNX, we find evidence of the impact of dividend policy on stock prices, supporting supports the bird in the hand and the signal detection theories. The findings of this study help to suggest a few recommendations for business managers and investors.

scholarly journals On the Impact of Dividend Payments on Stock Prices - an Empirical Analysis of the German Stock Market

2021 ◽  
Vol 16 (1) ◽  
pp. 255-269
Author(s):  
Konstantin Melching ◽  
Tristan Nguyen
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Signaling Theory ◽  
Share Price ◽  
Dividend Payment ◽  
Share Prices ◽  
Dividend Payments ◽  
Time Period ◽  
German Stock ◽  
The Impact

Abstract This paper examines the relation between dividend payments and stock prices of all firms in the German prime standard DAX 30 in the time period from 2012 to 2019. The irrelevance theory introduced by Miller and Modigliani states that dividend payments must not have an impact on stock prices in a perfect market. In contrast, the signaling theory and the dividend puzzle indicate that dividend payments are likely to have a profound impact on the stock price. According to our findings the ex-dividend decrease of stock prices was significantly smaller than the dividend payment. Nevertheless, the results support the impact of the dividend payment on the share price. Firstly, the existence of the ex-dividend markdown is a proof that dividend payments cause share price losses. Secondly, the study explains in particular that high dividend payments result in high share prices over the examined period. Thirdly, our analysis demonstrates a positive correlation between the dividend and the stock price development according to the signaling theory. Considering the above- mentioned results, we can conclude that the share price of a company is highly affected by the decision making of the company regarding the dividend policy.

scholarly journals Building stock market resilience through digital transformation: using Google trends to analyze the impact of COVID-19 pandemic

2020 ◽  
Vol 14 (1) ◽  
Author(s):  
Ding Ding ◽  
Chong Guan ◽  
Calvin M. L. Chan ◽  
Wenting Liu
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Digital Transformation ◽  
Google Trends ◽  
Building Stock ◽  
Market Sentiment ◽  
Price Performance ◽  
Novel Coronavirus ◽  
The Impact

Abstract As the 2019 novel coronavirus disease (COVID-19) pandemic rages globally, its impact has been felt in the stock markets around the world. Amidst the gloomy economic outlook, certain sectors seem to have survived better than others. This paper aims to investigate the sectors that have performed better even as market sentiment is affected by the pandemic. The daily closing stock prices of a total usable sample of 1,567 firms from 37 sectors are first analyzed using a combination of hierarchical clustering and shape-based distance (SBD) measures. Market sentiment is modeled from Google Trends on the COVID-19 pandemic. This is then analyzed against the time series of daily closing stock prices using augmented vector autoregression (VAR). The empirical results indicate that market sentiment towards the pandemic has significant effects on the stock prices of the sectors. Particularly, the stock price performance across sectors is differentiated by the level of the digital transformation of sectors, with those that are most digitally transformed, showing resilience towards negative market sentiment on the pandemic. This study contributes to the existing literature by incorporating search trends to analyze market sentiment, and by showing that digital transformation moderated the stock market resilience of firms against concern over the COVID-19 outbreak.

scholarly journals The Impact of COVID-19 on the Stock Price of Socially Responsible Enterprises: An Empirical Study in Taiwan Stock Market

2021 ◽  
Vol 18 (4) ◽  
pp. 1398
Author(s):  
Kuo-Jung Lee ◽  
Su-Lien Lu
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Abnormal Returns ◽  
Recovery Phase ◽  
Socially Responsible ◽  
Cumulative Impact ◽  
Study Approach ◽  
Price Performance ◽  
The Impact

This study examines the impact of the COVID-19 outbreak on the Taiwan stock market and investigates whether companies with a commitment to corporate social responsibility (CSR) were less affected. This study uses a selection of companies provided by CommonWealth magazine to classify the listed companies in Taiwan as CSR and non-CSR companies. The event study approach is applied to examine the change in the stock prices of CSR companies after the first COVID-19 outbreak in Taiwan. The empirical results indicate that the stock prices of all companies generated significantly negative abnormal returns and negative cumulative abnormal returns after the outbreak. Compared with all companies and with non-CSR companies, CSR companies were less affected by the outbreak; their stock prices were relatively resistant to the fall and they recovered faster. In addition, the cumulative impact of the COVID-19 on the stock prices of CSR companies is smaller than that of non-CSR companies on both short- and long-term bases. However, the stock price performance of non-CSR companies was not weaker than that of CSR companies during times when the impact of the pandemic was lower or during the price recovery phase.

scholarly journals The Impact of Dividend Policy on Stock Price Volatility in Pakistan

2019 ◽  
Vol IV (I) ◽  
pp. 506-515
Author(s):  
Ziaullah Shah ◽  
Shehzad Khan ◽  
Muhammad Faizan Malik
Keyword(s):  
Panel Data ◽  
Stock Price ◽  
Dividend Policy ◽  
Price Volatility ◽  
Fixed Effect Model ◽  
Share Prices ◽  
Dividend Payments ◽  
Effect Model ◽  
Dividend Irrelevance ◽  
The Impact

The objective of this study is to inspect dividend policy influence on volatility of share prices. For investigation seven Non-financial segment/sectors have been selected. A sample of 137 firms who paid four dividend payments listed at PSX is analysed for the period of 2007-2017.Proxy for policy of dividend are earning per share, Payout ratio, dividend yield, while assets growth and firm size are taken as control variables. OLS regression model has been initially applied on panel data. The outcomes of fixed effect model are focused. Overall outcomes of the study confirmed that prices of stock is significantly influenced by policy of dividend and reject dividend irrelevance theory.

Life-cycle asset allocation and the peso problem: does ambiguity aversion matter?

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nuno Silva
Keyword(s):  
Life Cycle ◽  
Stock Market ◽  
Asset Allocation ◽  
Stock Prices ◽  
Stock Price ◽  
Ambiguity Aversion ◽  
Content Type ◽  
Portfolio Decisions ◽  
State Of The Economy ◽  
The Impact

PurposeThe study aims to show that ambiguity aversion exerts a non-negligible effect on the investors' decisions, especially due to the possibility of sharp declines in stock prices.Design/methodology/approachThe vast majority of previous studies on life-cycle consumption and asset allocation assume that the equity premium is constant. This study evaluates the impact of rare disasters that shift the stock market to a low return state on investors' consumption and portfolio decisions. The author assumes that investors are averse to ambiguity relative to the current state of the economy and must incur a per period cost to participate in the stock market and solve their optimal consumption and asset allocation problem using dynamic programming.FindingsThe results show that most young investors choose not to invest in stocks because they have low accumulated wealth and the potential return from their stock market investments would not cover the participation costs. Furthermore, ambiguity-averse investors hold considerably fewer stocks throughout their lifetime than ambiguity-neutral ones. The fraction of wealth invested in stocks over the typical consumer's life is hump-shaped: it is low for a young individual, peaks at his early 30s and then decreases until his retirement age.Originality/valueTo the best of the author’s knowledge, this is the first study that assesses the impact of negative stock price jumps on the optimal portfolio of an ambiguity-averse investor.

Impact on Stock Price by the Inclusion to and Exclusion from CNX Nifty Index

2012 ◽  
Vol 13 (1) ◽  
pp. 39-50 ◽  
Author(s):  
M. Selvam ◽  
G. Indhumathi ◽  
J. Lydia
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Research Study ◽  
Stock Exchange ◽  
Valuation Effect ◽  
Index Maintenance ◽  
Indian Stock Market ◽  
The Impact ◽  
Indian Perspective

Changes in an index are a regular phenomenon and they take place due to the inclusion and exclusion of stocks from the index. The inclusion or exclusion of stocks creates great impact on the value of the firm. However, these changes are simply a short-lived event with no permanent valuation effect. The present research study analyzed the impact of the inclusion into and exclusion of certain stocks from National Stock Exchange (NSE) S&P CNX Nifty index with Indian perspective. The study provides evidence on whether the announcements of Nifty index maintenance committee have any information content. This will also demonstrate the efficiency of Indian stock market with particular reference to NSE. The study revealed that on an average, no permanent effects were observed on stock prices. It is also found from the study that the NSE reacted unfavourably to the inclusion and exclusion of stocks and it is impossible to earn any excess returns where the particular stocks are included or excluded from the index.

scholarly journals Using a Genetic Algorithm to Build a Volume Weighted Average Price Model in a Stock Market

2021 ◽  
Vol 13 (3) ◽  
pp. 1011
Author(s):  
Seung Hwan Jeong ◽  
Hee Soo Lee ◽  
Hyun Nam ◽  
Kyong Joo Oh
Keyword(s):  
Genetic Algorithm ◽  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Trading Volume ◽  
Weighted Average ◽  
Market Liquidity ◽  
Average Price ◽  
Volume Data ◽  
The Impact

Research on stock market prediction has been actively conducted over time. Pertaining to investment, stock prices and trading volume are important indicators. While extensive research on stocks has focused on predicting stock prices, not much focus has been applied to predicting trading volume. The extensive trading volume by large institutions, such as pension funds, has a great impact on the market liquidity. To reduce the impact on the stock market, it is essential for large institutions to correctly predict the intraday trading volume using the volume weighted average price (VWAP) method. In this study, we predict the intraday trading volume using various methods to properly conduct VWAP trading. With the trading volume data of the Korean stock price index 200 (KOSPI 200) futures index from December 2006 to September 2020, we predicted the trading volume using dynamic time warping (DTW) and a genetic algorithm (GA). The empirical results show that the model using the simple average of the trading volume during the optimal period constructed by GA achieved the best performance. As a result of this study, we expect that large institutions will perform more appropriate VWAP trading in a sustainable manner, leading the stock market to be revitalized by enhanced liquidity. In this sense, the model proposed in this paper would contribute to creating efficient stock markets and help to achieve sustainable economic growth.

scholarly journals EFFECT OF DIVIDEND POLICY ON STOCK PRICES

2015 ◽  
Vol 3 (1) ◽  
Author(s):  
Adnan ALİ ◽  
Farzand Ali Jan ◽  
Ilyas Sharif
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Dividend Policy ◽  
Random Effect ◽  
Capital Gains ◽  
Upward Movement ◽  
Significant Relation ◽  
Market Prices ◽  
Return On Equity ◽  
Share Prices

This investigates the effect of dividend policy on stock prices. Objective of the study is to see if there exists any relationship between dividend policy and stock prices. We analyzed 45 non-financial companies listed on KSE-100 index that have earned profits and paid dividend for a period of twelve year w.e.f. 2001. Technique adopted for sampling adopted is convenience sampling. As the nature of data is panel therefore, pooled regression, fixed and random effect tests are run. Random effect results are focused after applying Hausman’s test.Regression Results witness that Dividend per Share andRetention Ratio havean insignificant relationship with Share Market Prices.Dividend Payout Ratio has a significant positive relationship with Share Prices as supported by the Bird in hand theory suggested that owners give preference to a dollar of estimated dividends over a likely dollar of capital gains. Profit after tax, Earning per share and Return on Equity are the three control variables. Profit after Tax has insignificant relation to Stock Prices. Earnings per Share have positive significant relation to Stock Prices. There is negative significant relation between Return on Equity and Share Prices. It is recommended that firms in the sample should regularly pay dividend as it will cause an upward movement in the stock market prices. Whereas profit retention by firms will result in a decrease in the value of the stock market prices.

scholarly journals The Impact of Disclosure Sentiment on the Share Prices of Russian Companies

2021 ◽  
Vol 15 (2) ◽  
pp. 5-15
Author(s):  
Maksim Kopyrin ◽  
Iuliia Naidenova
Keyword(s):  
Stock Prices ◽  
Information Disclosure ◽  
Stock Price ◽  
Positive Impact ◽  
News Item ◽  
Marginal Effect ◽  
Share Prices ◽  
Stock Price Reaction ◽  
Tone Level ◽  
The Impact

Information about companies published in a news feed is invariably tinted by emotional tonality. As such, resultingperceptions may influence the opinion of market players, and consequently affect the dynamics of a company’s shareprice. This study aims to evaluate various hypotheses about the impact of the tone of news items regarding dividends,capital expenditures, and development on the stock prices of Russian companies. Information disclosure is extensivelystudied, and there have been limited studies on the effect of disclosures on Russian companies. However, until now, therehave been no research studies which verify hypotheses on the influence of news sentiment on corporate share prices inthe Russian market. This analysis was conducted using data from 49 Russian public companies included in the Moscow exchange indexover the period from the end of 2017 to the beginning of 2019. To account for the proximate impact of news items onconsequential market phenomena, an event study methodology was applied in order to estimate and construct themodels of dependency of cumulative abnormal return (CAR) on news tone level, and control for financial and nonfinancialfactors. Our results provide evidence for the positive impact of the tone of news texts on the share prices of Russian companies.The increase in news tone by one standard deviation leads to a cumulative abnormal stock return increase of 0.26percentage points. This result is consistent with previous research conducted on data from developed stock markets.Moreover, the relationship between the tone or sentiment level of a news item and the stock price reaction is linear,without the diminishing marginal effect. Our conclusions should prompt companies to invest effort in delivering information in a tonally positive way,highlighting the most positive news. Investors, in turn, should rationally approach the interpretation of publishedinformation.

scholarly journals A Stock Prices Prediction Approach Via Neural Network by Several Investor Indicators

2019 ◽  
pp. 477-484
Author(s):  
Yahui Chen ◽  
Zhan Wen ◽  
Qi Li ◽  
Yuwen Pan ◽  
Xia Zu ◽  
...  
Keyword(s):  
Neural Network ◽  
Stock Market ◽  
Bp Neural Network ◽  
Stock Prices ◽  
Stock Price ◽  
Quantitative Data ◽  
Prediction Models ◽  
Investor Behavior ◽  
Prediction Approach ◽  
The Impact

The prediction of stock indicators such as prices, trends and market indices is the focus of researchers. However, stock market has the characteristics of high noise and non-linearity. Generally, linear algorithms are not good for predicting stock market indicators. Therefore, BP neural network, a model suitable for nonlinear task, is widely used in stock market forecasting. However, many BP neural network prediction models are only based on historical stock quantitative data, and do not consider the impact of investor behavior on the stock market. Therefore, based on historical stock data and quantitative data of investor behavior of ten selected Chinese stocks, this paper trains a three-layer BP neural network to predict the stock prices such as the highest price ,the opening price ,the closing price, the lowest price in a short term. And then, the model that incorporates the investor behavior indicator is compared with the model that is not added. The results show that investor behavior indicators can improve the accuracy and generalization of the stock price forecasting model effectively, especially when the model based on stock quantitative data has a poor prediction accuracy on the test set.

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