scholarly journals The effect of the introduction of market makers on stock liquidity: evidence from the Brazilian stock market

2021 ◽  
Vol 13 (2) ◽  
Author(s):  
Gabriel Augusto de Carvalho ◽  
João Eduardo Ribeiro ◽  
Laíse Ferraz Correia
Keyword(s):  
Stock Market ◽  
Confidence Level ◽  
Trading Volume ◽  
Stock Exchange ◽  
Structural Break ◽  
Market Liquidity ◽  
Market Makers ◽  
Turnover Ratio ◽  
Before And After ◽  
Structural Break Test

Purpose: This study aimed to analyze whether the introduction of market makers as specialized intermediaries in the trading of stocks listed on the Brazilian stock exchange is a useful procedure for increasing the market liquidity of these assets. Methodology: The Chow structural break test was performed in the time series of the liquidity proxies, average spread, turnover ratio, and financial volume on a sample of 55 stocks. We chose to consider data in the window of 260 days before and after the start of the market maker's activity, because it represents the approximate number of trading sessions in a year, and to avoid erroneous conclusions due to the volatility of the Brazilian stock market. Results: The results showed with a 99% confidence level that after the introduction of market makers, (i) 67% of the stocks analyzed had abrupt and statistically significant changes in the average spread; (ii) 47% in the turnover ratio; and (iii) 60% had changes in the volume transactions. At the confidence level of 95%, (i) 76% of the stocks analyzed showed abrupt changes in the average spread; (ii) 65% had changes in turnover; (iii) and 69% had changes in the trading volume. Using a lower confidence level of 90%, the results revealed 85% of the stocks had abrupt and statistically significant changes in the average spread, 78% in the turnover ratio, and 73% in the trading volume. Contributions of the Study: This paper provides strong evidence on the performance of market makers and the influence they have on the market liquidity of stocks traded on the Brazilian stock exchange. We found that contracting market makers increase market liquidity and contribute significantly to the assets’ transactions.

Earnings Management and Stock Liquidity

2021 ◽  
pp. 66-84
Author(s):  
Hakan Özkaya
Keyword(s):  
Stock Market ◽  
Earnings Management ◽  
Trading Volume ◽  
Management Practices ◽  
Positive Association ◽  
Discretionary Accruals ◽  
Market Liquidity ◽  
Stock Liquidity ◽  
Turnover Ratio ◽  
Liquidity Measures

This chapter tests whether the earnings management practices in Turkey are considered informative or opportunistic by outside investors by examining its effect on stock liquidity. Earnings management is measured by discretionary accruals calculated by two different competing methods. Stock liquidity is also proxied by two different measures: the illiquidity measure of Amihud and the turnover ratio. Amihud's illiquidity measure indicates firms' daily price responses associated with the trading volume and the turnover ratio indicates how many times a stock changes its owner in a year. Relevant control variables are also included in the models. A positive association between earnings management and stock liquidity implies informative earnings management and vice versa. Earnings management is found to be positively associated with stock market liquidity. Results favor the informative earnings management view for Turkish firms and are robust to alternative specifications of earnings management and stock liquidity measures.

scholarly journals Multidimensional Liquidity: Evidences from Indian Stock Market

2016 ◽  
Vol 5 (2) ◽  
Author(s):  
Sharad Nath Bhattacharya ◽  
Pramit Sengupta ◽  
Mousumi Bhattacharya ◽  
Basav Roychoudhury
Keyword(s):  
Machine Learning ◽  
Stock Market ◽  
Stock Markets ◽  
Trading Volume ◽  
Stock Exchange ◽  
Market Liquidity ◽  
Percentage Error ◽  
Efficiency Coefficient ◽  
Learning Tools ◽  
Indian Stock Market

Various dimensions of liquidity including breadth, depth, resiliency, tightness, immediacy are examined using BSE 500 and NIFTY 500 indices from Indian Equity market. Liquidity dynamics of the stock markets were examined using trading volume, trading probability, spread, Market Efficiency coefficient, and turnover rate as they gauge different dimensions of market liquidity. We provide evidences on the order of importance of these liquidity measures in Indian stock market using machine learning tools like Artificial Neural Network (ANN) and Random Forest (RF). Findings reveal that liquidity variables collectively explains the movements of stock markets. Both these machine learning tools performs satisfactorily in terms of mean absolute percentage error. We also evidenced lower level of liquidity in Bombay Stock Exchange (BSE) than National Stock Exchange (NSE) and findings supports the liquidity enhancement program recently initiated by BSE.

scholarly journals The Impact of Foreign Investor Trading Activity on Vietnamese Stock Market

2017 ◽  
Vol 9 (1) ◽  
pp. 109 ◽  
Author(s):  
Tri Minh Nguyen
Keyword(s):  
Stock Market ◽  
Trading Volume ◽  
Stock Exchange ◽  
Market Performance ◽  
Market Liquidity ◽  
Arch Model ◽  
Trading Activity ◽  
Foreign Investors ◽  
Investor Trading ◽  
The Impact

The empirical research examines the impact of net purchase of foreign investors on performance of stock market and market liquidity. In this study, market performance is proxied by VN-index, which measures growth of equity market and market liquidity is estimated by the trading volume of whole market. The data is collected in Vietnamese Stock Exchange in the period of 1215 intraday from 2011 to 2014. By using ARCH model, main findings of this research are: first, there is positive relationship between market performance and net purchase; second, performance of stock market is influence by lag factor and third, liquidity of market is affected negatively by trading activity of foreign investors.

Uji Komparasi Abnormal Return, Trading Volume, Trading Frequency, Dan Bid-Ask Spread Sebelum Dan Sesudah Share Split

2016 ◽  
Vol 8 (2) ◽  
pp. 24-45
Author(s):  
Tania Hayu Safira ◽  
Febryanti Simon
Keyword(s):  
Abnormal Return ◽  
Trading Volume ◽  
Stock Exchange ◽  
Distributed Data ◽  
Trading Frequency ◽  
Bid Ask Spread ◽  
Analysis Technique ◽  
Before And After ◽  
Test Of Hypothesis ◽  
Kolmogorov Smirnov

This study is event study that was conduct to examine the differences of abnormal return, trading volume, trading frequency and bid-ask spread before and after the events of share split. The object of this research is the companies that did share split and listed in Indonesia Stock Exchange in 2008 - 2015. The samples are 30 companies chosen by purposive sampling method. The criteria are the company did not do corporate action right issue, pre-emptive rights, a share dividend and bonus shares in the same year with share split. Event window used in this study was 30 days consisting of 15 days before and 15 days after the share split. Data analysis technique begins with a test of normality using Kolmogorov – Smirnov and transform for unnormally distributed data. Then, test of hypothesis using Paired t – test to compare the differences before and after share split. The results of this study showed that volume trading activity and trading frequency had significant differences before and after the share split. While, variable abnormal return and bid-ask spread had not significant differences before and after the share split. Keywords: Abnormal return, bid-ask spread, share split, trading frequency, trading volume.

Absence of the weekend effect and industry-style portfolios

2019 ◽  
Vol 12 (4) ◽  
pp. 463-475
Author(s):  
Selma Izadi ◽  
Abdullah Noman
Keyword(s):  
New York ◽  
Stock Market ◽  
Structural Breaks ◽  
Stock Exchange ◽  
Structural Break ◽  
Weekend Effect ◽  
Content Type ◽  
Market Portfolio ◽  
The Us ◽  
Using Data

Purpose The existence of the weekend effect has been reported from the 1950s to 1970s in the US stock markets. Recently, Robins and Smith (2016, Critical Finance Review, 5: 417-424) have argued that the weekend effect has disappeared after 1975. Using data on the market portfolio, they document existence of structural break before 1975 and absence of any weekend effects after that date. The purpose of this study is to contribute some new empirical evidences on the weekend effect for the industry-style portfolios in the US stock market using data over 90 years. Design/methodology/approach The authors re-examine persistence or reversal of the weekend effect in the industry portfolios consisting of The New York Stock Exchange (NYSE), The American Stock Exchange (AMEX) and The National Association of Securities Dealers Automated Quotations exchange (NASDAQ) stocks using daily returns from 1926 to 2017. Our results confirm varying dates for structural breaks across industrial portfolios. Findings As for the existence of weekend effects, the authors get mixed results for different portfolios. However, the overall findings provide broad support for the absence of weekend effects in most of the industrial portfolios as reported in Robins and Smith (2016). In addition, structural breaks for other weekdays and days of the week effects for other days have also been documented in the paper. Originality/value As far as the authors are aware, this paper is the first research that analyzes weekend effect for the industry-style portfolios in the US stock market using data over 90 years.

scholarly journals Analisis Reaksi Pasar Terhadap Pengumuman Merger dan Akuisisi Pada Perusahaan Akuisitor yang Terdaftar di BEI

2018 ◽  
pp. 1870
Author(s):  
Ika Putri Adnyani ◽  
Gayatri Gayatri
Keyword(s):  
Abnormal Return ◽  
Trading Volume ◽  
Sampling Method ◽  
Stock Exchange ◽  
Cumulative Abnormal Return ◽  
Test Results ◽  
Volume Activity ◽  
Paired Sample ◽  
Analysis Technique ◽  
Before And After

This research is conducted on all acquisition companies that conduct acquisitions listed on Indonesia Stock Exchange 2011-2016 period. Sampling method using purposive sampling. The number of samples of this research is 50 companies. The market reaction in this study used abnormal return and trading volume activity. The testing of information content will be done by looking at differences in cumulative abnormal return and the average trading volume of shares five days before and five days after the announcement of the acquisition. Data analysis technique used is paired sample t-test. Based on the test results, found there are significant differences in the abnormal return of the acquirer company before and after the announcement of the acquisition. However, there is no difference in trading volume activity of the acquirer's stock before and after the acquisition announcement   Keywords: acquisitions, stock market, abnormal return, trading volume activity

scholarly journals IFRS and Stock Returns: An Empirical Analysis in Brazil

2016 ◽  
Vol 7 (2) ◽  
pp. 179 ◽  
Author(s):  
Rodrigo F. Malaquias ◽  
Anderson Martins Cardoso ◽  
Gabriel Alves Martins
Keyword(s):  
New York ◽  
Stock Market ◽  
Stock Returns ◽  
Stock Exchange ◽  
Relevant Information ◽  
Graphic Analysis ◽  
Accounting Numbers ◽  
Before And After ◽  
Accounting Reports ◽  
Accounting Convergence

In recent years, the convergence of accounting standards has been an issue that motivated new studies in the accounting field. It is expected that the convergence provides users, especially external users of accounting information, with comparable reports among different economies. Considering this scenario, this article was developed in order to compare the effect of accounting numbers on the stock market before and after the accounting convergence in Brazil. The sample of the study involved Brazilian listed companies at BM&FBOVESPA that had American Depository Receipts (levels II and III) at the New York Stock Exchange (NYSE). For data analysis, descriptive statistics and graphic analysis were employed in order to analyze the behavior of stock returns around the publication dates. The main results indicate that the stock market reacts to the accounting reports. Therefore, the accounting numbers contain relevant information for the decision making of investors in the stock market. Moreover, it is observed that after the accounting convergence, the stock returns of the companies seem to present lower volatility.

scholarly journals The dynamic relationship between stock returns and trading volumes in Nepalese stock market

2020 ◽  
Vol 23 (2) ◽  
pp. 161-172
Author(s):  
Prem Lal Adhikari
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Trading Volume ◽  
Time Series Data ◽  
Stock Exchange ◽  
Causal Effect ◽  
Empirical Relationship ◽  
Insurance Companies ◽  
Series Data ◽  
Dynamic Relationship

 In finance, the relationship between stock returns and trading volume has been the subject of extensive research over the past years. The main motivation for these studies is the central role that trading volume plays in the pricing of financial assets when new information comes in. As being interrelated and interdependent subjects, a study regarding the trading volume and stock returns seem to be vital. It is a well-researched area in developed markets. However, very few pieces of literature are available regarding the Nepalese stock market that explores the association between trading volume and stock return. Realizing this fact, this paper aims to examine the empirical relationship between trading volume and stock returns in the Nepalese stock market using time series data. The study sample is comprised of 49 stocks traded on the Nepal Stock Exchange (NEPSE) from mid-July 2011 to mid-July 2018. This study examines the Granger Causality relationship between stock returns and trading volume using the bivariate VAR model used by de Medeiros and Van Doornik (2008). The study found that the overall Nepalese stock market does not have a causal relationship between trading volume and return on the stock. In the case of sector-wise study, there is a unidirectional causality running from trading volume to stock returns in commercial banks and stock returns to trading volume in finance companies, hydropower companies, and insurance companies. There is no indication of any causal effect in the development bank, hotel, and other sectors. This study also finds that there is no evidence of bidirectional causality relationships in any sector of the Nepalese stock market.

scholarly journals Trading Volume as a Predictor of Market Movement

2019 ◽  
Vol 8 (2) ◽  
pp. 57-69
Author(s):  
Edson Kambeu
Keyword(s):  
Logistic Regression ◽  
Stock Market ◽  
Regression Model ◽  
Trading Volume ◽  
Logistic Regression Model ◽  
Predictive Analytics ◽  
Stock Exchange ◽  
Stock Market Index ◽  
Trading Volumes ◽  
Popular Language

A logistic regression model is has also become a popular model because of its ability to predict, classify and draw relationships between a dichotomous dependent variable and dependent variables. On the other hand, the R programming language has become a popular language for building and implementing predictive analytics models. In this paper, we apply a logistic regression model in the R environment in order to examine whether daily trading volume at the Botswana Stock Exchange influence daily stock market movement. Specifically, we use a logistic regression model to find the relationship between daily stock movement and the trading volumes experienced in the recent five previous trading days. Our results show that only the trading volume for the third previous day influence current stock market index movement. Overall, trading volumes of the past five days were found not have an impact on today’s stock market movement. The results can be used as a basis for building a predictive model that utilizes trading as a predictor of stock market movement.

scholarly journals MARKET REACTION ON THE ANNOUNCEMENT OF SRI KEHATI INDEX IN INDONESIAN STOCK EXCHANGE

2019 ◽  
Author(s):  
Anggita Langgeng Wijaya ◽  
Mia Noviyanti ◽  
Probo Mahayu
Keyword(s):  
Trading Volume ◽  
Market Reaction ◽  
Stock Exchange ◽  
Abnormal Returns ◽  
Rank Test ◽  
Stock Trading ◽  
Population Sampling ◽  
Signed Rank ◽  
Before And After ◽  
Signed Rank Test

The purpose of this study was to test the market reaction to the announcement of the Sri Kehati Index on the Indonesia Stock Exchange. The population in this study is all companies included in the Sri Kehati Index from 2013 to 2016. The selection of samples was taken by the population sampling method. Hypothesis testing is done by paired t test and Wilcoxon Signed Rank Test. The findings of this research are: 1) there is no difference in abnormal returns before and after the announcement of the Sri Kehati Index on the Indonesia Stock Exchange. 2) There is a difference in the activity of stock trading volume before and after the announcement of the Sri Kehati index in the 5th and 6th periods, but there is no difference in the activity of stock trading volume in other periods. The Indonesia Stock Exchange did not react consistently to the announcement of the Sri Kehati Index.

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