Do Share Repurchases Promote Efficient Stock Price?

2021 ◽  
Vol 12 (3) ◽  
pp. 2537-2546
Author(s):  
Chong-Meng Chee Et.al
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Fixed Effects ◽  
Practical Implication ◽  
Informed Trading ◽  
Share Repurchases ◽  
Share Repurchase ◽  
Price Support ◽  
Share Prices ◽  
Unbalanced Panel Data

Purpose: This paper examines whether a greater firm’s repurchase intensity translates into more efficient stock price. Design/ Methodology/ Approach: An unbalanced panel data, that consists of a sample of 337 US repurchasing firms between 2012 and 2016, was analyzed. Based on the result of the Hausman test, fixed effects estimator was employed to estimate the coefficients. To address heterogeneity across time and firms, time effect and standard error clustered by firms were applied. Findings:Agreater firms’ share buyback intensity stimulates faster incorporation of information in price and results more efficient stock prices. The main findings were further confirmed with robustness test and supports the notion that share repurchase serves as signalling tool and price support to promote more efficient stock price. Practical implication: The finding has implication on how share repurchase can be used in three ways: to ease panic selling and deep selling pressure during the downtime; enhance informed trading in which is a result of information signalled by managerial share repurchases; and attract investors’ attention on neglected and undervalued stock. Originality/value: This research provides new insight and empirical evidenceto reject public cynicism about share repurchases used by firms to manipulate their share prices.

scholarly journals Do Share Repurchases Distort Stock Prices? Evidence from the United States and Malaysia

2021 ◽  
pp. 232102222110243
Author(s):  
Chong-Meng Chee ◽  
Nazrul Hisyam bin Ab Razak ◽  
Bany Ariffin bin Amin Noordin
Keyword(s):  
Stock Prices ◽  
The United States ◽  
Jel Classification ◽  
Share Repurchases ◽  
Alternative Measure ◽  
Share Repurchase ◽  
Price Support ◽  
Global Finance ◽  
The Usa ◽  
Sample Support

Heavy share buyback years after the global finance crisis 2008–2009 drew criticism from scholars and financial press that share repurchases were being used by firms to manipulate their stock prices. This paper examines whether a greater firm’s repurchase intensity distorts stock prices reflecting to information. We analyse 2 sets of unbalanced panel data that contain a sample of 337 US and another sample of 167 Malaysian repurchasing firms between 2012 and 2016. Contrary to the criticism, we find that a greater firms’ share buyback intensity in the USA stimulates faster incorporation of information in price and results in more efficient stock prices. The main findings hold true and are robust when an alternative measure of share repurchase intensity was used. The findings of US sample support the notion that share repurchase serves as a signalling tool and price support to promote more efficient stock prices. We also find no strong evidence supporting the notion that shares repurchased by Malaysian firms distort stock prices. JEL Classification: G10, G14, G35

scholarly journals Stock Market Reaction to COVID-19: Evidence in Customer Goods Sector with the Implication for Open Innovation

2020 ◽  
Vol 6 (4) ◽  
pp. 99
Author(s):  
Zaky Machmuddah ◽  
St. Dwiarso Utomo ◽  
Entot Suhartono ◽  
Shujahat Ali ◽  
Wajahat Ali Ghulam
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Practical Implication ◽  
Efficient Market Hypothesis ◽  
Future Research ◽  
Observation Data ◽  
Economic Sectors ◽  
Significant Difference ◽  
Before And After ◽  
Long Term Impact

The coronavirus pandemic has spread all over the world, affecting both the health and economic sectors. The aim of this research was to observe stock prices of customer goods before and after the COVID-19 pandemic using event study and the comparison test. The sample included data of daily closing stock prices and volume of stock trade during the three months before (−90 days) and after (+90 days) the occurrence of the COVID-19 pandemic ongoing, totaling 2670 observation data both before and after the COVID-19 pandemic, for a total of 5340. The research findings indicate a significant difference between the daily closing stock price and volume of stock trade before and after the COVID-19 pandemic. The current research has both theoretical and practical implications: the findings strengthen the efficient market hypothesis, which states that the more complete the provided information, the more efficient the market. The practical implication is that investors should be careful when choosing to invest. Investors should choose customer goods sector companies that provide products that are much needed by customers, for example, pharmacy, food, beverages, etc. Future research is needed to investigate the long-term impact of the pandemic on the economy.

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 Pengaruh NPM, ROA, ROE terhadap Harga Saham pada Perusahaan LQ45

2020 ◽  
Vol 30 (5) ◽  
pp. 1258
Author(s):  
Kannia Aulia Sahari ◽  
I Wayan Suartana
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Linear Regression Analysis ◽  
Sampling Technique ◽  
Multiple Linear Regression Analysis ◽  
Fundamental Analysis ◽  
Share Prices ◽  
Research Population ◽  
Profitability Ratios

The purpose of this study is to determine the movement of stock prices, namely fundamental analysis where profitability ratios are often used in fundamental analysis, namely NPM, ROA and ROE This research was conducted on companies incorporated in the 2014-2018 LQ45 index on the Indonesia Stock Exchange. The research population is 68 companies. Samples were selected using a purposive sampling technique so that the number of samples obtained was 26 companies and the number of observations over 5 years was 130 observations. Data analysis techniques using multiple linear regression analysis. Based on the results of this analysis show that NPM and ROA have no effect on stock prices so that they are unable to increase share prices in companies incorporated in the LQ45 index, while ROE affects stock prices so the higher the ROE level the higher the stock prices at companies incorporated in the LQ45 index. Keywords: NPM; ROA; ROE; Stock Price.

scholarly journals Deterministic chaos and forecasting in Amazon’s share prices

Equilibrium ◽  
2020 ◽  
Vol 15 (2) ◽  
pp. 253-273
Author(s):  
Michael Hanias ◽  
Stefanos Tsakonas ◽  
Lykourgos Magafas ◽  
Eleftherios I. Thalassinos ◽  
Loukas Zachilas
Keyword(s):  
Time Series ◽  
Chaos Theory ◽  
Stock Prices ◽  
Stock Price ◽  
Chaotic Behavior ◽  
Financial Time Series ◽  
Deterministic Chaos ◽  
Value Added ◽  
Share Prices ◽  
Daily Data

Research background: The application of non-linear analysis and chaos theory modelling on financial time series in the discipline of Econophysics. Purpose of the article: The main aim of the article is to identify the deterministic chaotic behavior of stock prices with reference to Amazon using daily data from Nasdaq-100. Methods: The paper uses nonlinear methods, in particular chaos theory modelling, in a case study exploring and forecasting the daily Amazon stock price. Findings & Value added: The results suggest that the Amazon stock price time series is a deterministic chaotic series with a lot of noise. We calculated the invariant parameters such as the maxi-mum Lyapunov exponent as well as the correlation dimension, managed a two-days-ahead forecast through phase space reconstruction and a grouped data handling method.

scholarly journals Stock price reaction to cash dividend announcements in Vietnam

2017 ◽  
Vol 24 (02) ◽  
pp. 74-89
Author(s):  
Truong Nguyen Xuan ◽  
Huong Dao Mai ◽  
Anh Nguyen Thi Van
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Abnormal Returns ◽  
Cash Dividend ◽  
Share Prices ◽  
Price Reaction ◽  
Cumulative Abnormal Returns ◽  
Stock Price Reaction ◽  
The Uk

This study attempts to investigate the stock price reaction to divi-dend announcements using data of Vietnamese listed firms on Hochiminh Stock Exchange (HOSE). Standard event study meth-odology has been employed on a sample of 198 cash dividend an-nouncements made in 2011. The results show that stock prices react significantly and positively to the announcements of cash dividends, including both dividend increasing and dividend decreasing events. It is also plausible that cumulative abnormal returns exhibit an in-creasing trend before announcement yet a decreasing trend after announcement dates. More specifically, we find positively signifi-cant cumulative abnormal returns of around 1.03% on announce-ment dates; other larger windows also demonstrate positive abnor-mal returns of around 1.3%. In addition, cash dividends have differ-ent effects on share prices of firms from different industries. These results support the signaling hypothesis and are also consistent with prior findings of empirical research done on more developed mar-kets, i.e. the US and the UK.

scholarly journals ANALISIS PENGARUH RASIO KINERJA KEUANGAN TERHADAP HARGA SAHAM PT BANK MANDIRI PERSERO PERIODE 2014 – 2019

GANEC SWARA ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 963
Author(s):  
I KETUT KUSUMA WIJAYA
Keyword(s):  
Financial Performance ◽  
Stock Prices ◽  
Stock Price ◽  
Supply And Demand ◽  
Share Price ◽  
Financial Reports ◽  
Financial Ratio ◽  
Share Prices ◽  
Performance Variables ◽  
Simultaneous Test

     Share prices occur according to market supply and demand. Demand for shares is influenced by investors' expectations of the issuing company. The better the financial performance of a company, the higher investor expectations will be. This results in the shares becoming increasingly attractive and the share price will be higher. Conversely, if a company's financial performance is not good, investors' expectations will be low, so investors are not interested in investing in these shares. This causes the stock price to fall. The company's financial performance can be done by analyzing financial reports. This study aims to determine the effect of financial performance ratios on stock prices. The analytical tool used is multiple linear regression and hypothesis testing is done by partial test (T-test) and simultaneous test (F-test) and standardized coefficient test.     Based on the research results that simultaneously the financial ratio variable does not have a significant effect on stock prices. Meanwhile, only partially the NPM variable affects stock prices. Meanwhile, the financial performance variables (CAR, ROA, and LDR) do not affect stock prices. For the adjusted R2 value of 99.80%, it means that this value means that the variation of the independent variable which can explain the dependent variable is 99.80% and the remaining 2% is the variation of other variables that are not explained in the model.

scholarly journals Trends of industry-leading biotechnology stocks during COVID-19

2021 ◽  
Vol 10 (3) ◽  
Author(s):  
Navia Zhang ◽  
Meredith Haskins
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Blood Clotting ◽  
New Technologies ◽  
Share Prices ◽  
The World ◽  
Biotechnology Companies ◽  
Pandemic Vaccine ◽  
Biotechnology Sector ◽  
Roll Out

The 2019-nCoV coronavirus has significantly impacted the macroeconomic outlook for countries across the world. The biotechnology sector experienced a relatively positive stock price outlook, which corroborates the trends exhibited by biotechnology stocks in previous pandemics such as SARS (2003) and AH1N1 (2009). During the COVID-19 pandemic, vaccine roll-out rates have been more efficient than in any other pandemic, as companies today are more experienced in combating the time constraint to create vaccines. Gilead Sciences Inc. saw its shares rise 18% after developing the first FDA-approved COVID-19 vaccine, 'remdesivir'. In contrast, AstraZeneca's shares fell 2.28% in 2021 after its vaccine underwent investigations into blood-clotting side effects and subsequent suspension from several countries. Companies developing mRNA vaccines like Moderna, BioNTech, and Pfizer witnessed surges in share prices ranging from 10% to 20%. Many newer biotech companies such as Genexie, Sanovi, OnoSec, and Vaxart have also developed vaccines for COVID-19. Share prices are more volatile for these less established companies. This paper observes how developing new technologies, staging clinical trials, obtaining FDA approvals, gaining publicity, and several other complex factors have profound impacts on the stock prices of these biotechnology companies.

scholarly journals DPR Sebagai Pemediasi Antara CAONS, DTAR, Dan GCG Pada Harga Saham

2021 ◽  
Vol 17 (1) ◽  
pp. 202-224
Author(s):  
Ainun Jariah
Keyword(s):  
Path Analysis ◽  
Stock Prices ◽  
Stock Price ◽  
Investment Decisions ◽  
Price Volatility ◽  
Share Price ◽  
Stock Price Volatility ◽  
Research Results ◽  
Share Prices ◽  
Dividend Policies

The company's performance projections are the focus of investors, especially investment decisions, funding decisions, and dividend policies, plus GCG which contribute to stock price volatility. The purpose of his research to detect the influence of CAONS, DTAR, and GCG individually and simultaneously on DPR and share prices, with DPR as a mediator. The number of samples 37 industry company registered on the BEI during 5 years since 2012. Analysis of data is path analysis and sobel tests for mediation variables. The research results explain that partially DTAR and GCG have a significant effect on DPR. but the share prices all three variables have no significant impact . Simultaneously CAONS, DTAR, and GCG have a significant impact on DPR and than no significant on share price. DPR has an effect and significant on share prices. Partially and simultaneously CAONS, DTAR, and GCG have no relationship to stock prices through DPR, and DPR is only able to mediate CAONS to stock prices. Keyword: CAONS, DTAR, GCG, DPR, and Stock Prices.

scholarly journals Neural Network Backpropagation Identification of Jakarta Islamic Index (JII) Stock Price Patterns

2020 ◽  
Vol 4 (1) ◽  
pp. 90-94
Author(s):  
Musli Yanto ◽  
Liga Mayola ◽  
M. Hafizh
Keyword(s):  
Interest Rates ◽  
Stock Prices ◽  
Stock Price ◽  
Share Prices ◽  
Inflation Rates ◽  
Price Patterns ◽  
Price Movements ◽  
Pattern Determination ◽  
Network Patterns ◽  
Stock Price Movements

Jakarta Islamic Index (JII) is an organization engaged in the economy with the aim to pay attention to stock movements every day. With the JII, people who do not understand about shares and their movements, will be easy to know and understand the movement of shares that occur at certain times. The problem in this research is that many investors are unable to predict the rise and fall of stock prices. The prediction process can be done with a backpropagation algorithm. The algorithm is a concept of computer science which is widely used in the case of analysis, prediction and pattern determination. The process starts from the analysis of the variables used namely interest rates, exchange rates, inflation rates and stock prices that occurred in the previous period. The variables used are continued in the formation of network patterns and continued in the process of training and testing in order to produce the best network patterns so that they are used as a process of identifying JII stock price movements. The results obtained in the form of the value of stock price movements with an error rate based on the MSE value of 11.85% so that this study provides information in the form of knowledge for making a decision. The purpose of the research is used as input for investors in identifying share prices. In the end, the benefits felt from the results of this study, investors can make an initial estimate before investing in JII.

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