scholarly journals FENOMENA ANOMALI MUSIMAN INDEKS HARGA SAHAM DI INDONESIA

2021 ◽  
Vol 10 (2) ◽  
pp. 97-108
Author(s):  
G. A. Sri Oktaryani ◽  
Iwan Kusuma Negara ◽  
Weni Retnowati ◽  
Iwan Kusmayadi
Keyword(s):  
Stock Returns ◽  
Stock Price ◽  
Seasonal Effects ◽  
Seasonal Effect ◽  
Investment Strategies ◽  
Monthly Basis ◽  
Year Effect ◽  
Monthly Pattern ◽  
Day Of The Week ◽  
Daily Stock Returns

This Research aims to obtain empirical evidence about the existence of anomaly seasonal effects on market returns on a daily and monthly basis on the IHSG and the LQ-45 Index in Indonesia throughout January 2015 untill September 2020. The diversity of arguments and research results regarding the phenomenon of seasonal anomalies in stock returns derived from previous studies make this phenomenon interesting to study. We analyze daily stock returns by using the Kruskal Wallis test, while the average monthly return is analyzed using the one-way Anova. The findings show that the phenomenon of stock anomaly returns according to the daily pattern of the week (day of the week effect) and the monthly pattern (month of the year effect) on IHSG and the LQ-45 Index are not proven within the range research from January 2015 to September 2020. The results of stock price forecasting provide benefits in supporting investors to develop their investment strategies. Futhermore, this information is also important to choose and determine which stocks should be bought and sold. In addition to investors, this information is also useful for management to monitor the pattern of stock price movements, so that they can plan, formulate strategies and take anticipatory steps based on possible threats that could arise.Keywords :Anomaly Seasonal Effect, day of the week effect, month of the year effect, market Return  

scholarly journals Seasonal effects: Evidence from emerging African stock markets

2006 ◽  
Vol 37 (3) ◽  
pp. 41-52 ◽  
Author(s):  
C. Mlambo ◽  
N. Biekpe
Keyword(s):  
Stock Markets ◽  
Stock Exchange ◽  
West African ◽  
The Other ◽  
Seasonal Effects ◽  
Seasonal Effect ◽  
The West ◽  
Chi Square ◽  
Year Effect ◽  
Day Of The Week

The paper investigates seasonal effects in seventeen indices on nine African stock markets using regression analysis and the Kruskal-Wallis and Chi-square Median tests. Significant seasonal effects are found on some, but not all indices. The strongest effect observed is the month-of-the-year effect followed by the day-of-the-week effect. The West African Regional stock Exchange (BRVM) exhibited a reversed ‘December decline - January rise’ pattern, while the turn-of-the-month effect observed for Egypt disappeared after the turn-of-the-year effect was removed. Using the Kruskal-Wallis test, no seasonal effects for Namibia were found. For the other markets, at least one seasonal effect was observed, suggesting some exploitable trading opportunities.

scholarly journals Margin requirements and Stock Market Volatility in Bangladesh

2012 ◽  
Vol 3 (2) ◽  
pp. 29
Author(s):  
A. F. M. Mainul Ahsan ◽  
Mohammad Osman Gani ◽  
Md. Bokhtiar Hasan
Keyword(s):  
Stock Returns ◽  
Stock Price ◽  
Stock Exchange ◽  
Price Volatility ◽  
Market Volatility ◽  
Stock Market Volatility ◽  
Margin Requirements ◽  
Margin Requirement ◽  
Daily Stock Returns ◽  
The Impact

Officially margin requirements in bourses in Bangladesh were initiated on April 28, 1999, to limit the amount of credit available for the purpose of buying stocks. The goal of this paper is to measure the impact of changing margin requirement on stock returns' volatility in Dhaka Stock Exchange (DSE). The impact of margin requirement on stock price volatility has been extensively studied with mixed and ambiguous results. Using daily stock returns, we found mixed evidence that SEC's margin requirements have significant impact on market volatility in DSE.

Forecasting Stock Market Volatility: Evidence from Six Emerging Markets

2013 ◽  
Vol 14 (2) ◽  
pp. 68-93
Author(s):  
Naliniprava Tripathy ◽  
Ashish Garg
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Markets ◽  
Stock Price ◽  
Market Volatility ◽  
Future Market ◽  
Investment Strategies ◽  
Stock Market Volatility ◽  
Efficient Management ◽  
Asymmetric Garch

This paper forecasts the stock market volatility of six emerging countries by using daily observations of indices over the period of January 1999 to May 2010 by using ARCH, GARCH, GARCH-M, EGARCH and TGARCH models. The study reveals the positive relationship between stock return and risk only in Brazilian stock market. The analysis exhibits that the volatility shocks are quite persistent in all country’s stock market. Further the asymmetric GARCH models find a significant evidence of asymmetry in stock returns in all six country’s stock markets. This study confirms the presence of leverage effect in the returns series and indicates that bad news generate more impact on the volatility of the stock price in the market. The study concludes that volatility increases disproportionately with negative shocks in stock returns. Hence investors are advised to use investment strategies by analyzing recent and historical news and forecast the future market movement while selecting portfolio for efficient management of financial risks to reap benefits in the stock markets.

scholarly journals Testing Semi-strong Form Efficiency of Stock Market

2001 ◽  
Vol 40 (4II) ◽  
pp. 651-674 ◽  
Author(s):  
Salman Syed Ali ◽  
Khalid Mustafa
Keyword(s):  
Stock Returns ◽  
Stock Prices ◽  
Stock Markets ◽  
Efficient Market Hypothesis ◽  
Seasonal Effects ◽  
Efficient Market ◽  
New Information ◽  
Empirical Regularities ◽  
Day Of The Week ◽  
Stock Traders

The efficient market hypothesis suggests that stock markets are “informationally efficient”. That is, any new information relevant to the market is spontaneously reflected in the stock prices. A consequence of this hypothesis is that past prices cannot have any predictive power for future prices once the current prices have been used as an explanatory variable. In other words the change in future prices depends only on arrival of new information that was unpredictable today hence it is based on surprise information. Another consequence of this hypothesis is that arbitrage opportunities are wiped out instantaneously. Empirical tests of the efficient market hypothesis actually test for these consequences in various ways. Some of them have been summarised in earlier chapters. These tests generally could not conclusively accept the random-walk hypothesis of stock returns even when GARCH effects were accounted for. Many studies have found empirical regularities that are contrary to the efficient market hypothesis. For example, the monthly, weekly and daily returns on stocks tend to exhibit discernable patterns, such as seasonal affects, month of the year affect, day of the week affect, hourly affect etc. In case of Pakistan’s stock markets too such affects are identified. Such as the Ramadan affect [see Hussain and Uppal (1999)], seasonal effects and day of the week affect. Further, the wide spread use of “technical analysis” among stock traders and their ability to predict to some extent the direction of movements in the prices of individual stocks over medium term testifies to the existence of patterns and seasonal trends.

scholarly journals The impact of earnings management on market liquidity

2020 ◽  
Vol 17 (2) ◽  
pp. 389-396
Author(s):  
Do Thi Van Trang ◽  
Dinh Hong Linh
Keyword(s):  
Earnings Management ◽  
Stock Returns ◽  
Stock Price ◽  
Stock Exchange ◽  
Fixed Effect Model ◽  
Market Liquidity ◽  
Listed Firms ◽  
Daily Stock Returns ◽  
The Impact ◽  
Dollar Volume

This article investigates the impact of earnings management on market liquidity measured by the depth of the market. Managers have desired to provide amazing performance of companies, manage their earnings through non-discretionary accruals. Consequently, investors have trouble evaluating the stock value and misunderstanding of the market liquidity because of manipulated information.To this aim, the fixed-effect model (FEM) is implemented to analyze the financial information of 170 listed firms on the Vietnam Stock Exchange over the period 2013–2016. The empirical results emphasized that market liquidity is influenced by earnings management that means the higher level of earnings management, the better equity liquidity. The findings provide additional insight into the determinants of stock liquidity such as earnings management, firm size, daily trading dollar volume of stock, average daily trading dollar volume of the firm, daily returns of stock, daily stock returns, average closing stock price of the firm.

An examination of calendar anomalies: evidence from the Thai stock market

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rattaphon Wuthisatian
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Exchange ◽  
January Effect ◽  
Content Type ◽  
Current State ◽  
Managerial Implications ◽  
Monthly Pattern ◽  
Calendar Anomalies ◽  
Daily Stock Returns

PurposeThe study examines the existence of calendar anomalies, including the day-of-the-week (DOW) effect and the January effect, in the Stock Exchange of Thailand.Design/methodology/approachUsing daily stock returns from March 2014 to March 2019, the study performs regression analysis to examine predictable patterns in stock returns, the DOW effect and the January effect, respectively.FindingsThere is strong evidence of a persistent monthly pattern and weekday seasonality in the Thai stock market. Specifically, Monday returns are negative and significantly lower than the returns on other trading days of the week, and January returns are positive and significantly higher than the returns on other months of the year.Practical implicationsThe findings offer managerial implications for investors seeking trading strategies to maximize the possibility of reaching investment goals and inform policymakers regarding the current state of the Thai stock market.Originality/valueFirst, the study investigates calendar anomalies in the Thai stock market, specifically the DOW effect and the January effect, which have received relatively little attention in the literature. Second, this is the first study to examine calendar anomalies in the Thai stock market across different groups of companies and stock trading characteristics using a range of composite indexes. Furthermore, the study uses data during the period 2014–2019, which should provide up-to-date information on the patterns of stock returns in Thailand.

scholarly journals STATISTICAL PROPERTIES OF STATISTICAL ENSEMBLES OF STOCK RETURNS

2000 ◽  
Vol 03 (03) ◽  
pp. 405-408 ◽  
Author(s):  
FABRIZIO LILLO ◽  
ROSARIO N. MANTEGNA
Keyword(s):  
New York ◽  
Stock Returns ◽  
Stock Price ◽  
Stock Exchange ◽  
Temporal Correlation ◽  
Statistical Properties ◽  
Central Moments ◽  
York Stock Exchange ◽  
Daily Stock Returns ◽  
Correlation Properties

We select n stocks traded in the New York Stock Exchange and form a statistical ensemble of daily stock returns for each of the k trading days of our database from the stock price time series. We analyze each ensemble of stock returns by extracting its first four central moments. We observe that these moments are fluctuating in time and are stochastic processes themselves. We characterize the statistical properties of central moments by investigating their probability density function and temporal correlation properties.

Stock return autocorrelation, day of the week and volatility

2017 ◽  
Vol 16 (2) ◽  
pp. 218-238 ◽  
Author(s):  
Shah Saeed Hassan Chowdhury ◽  
M. Arifur Rahman ◽  
M. Shibley Sadique
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Price ◽  
Stock Exchange ◽  
Saudi Arabian ◽  
Content Type ◽  
Limits To Arbitrage ◽  
Portfolio Returns ◽  
Autocorrelation Structure ◽  
Day Of The Week

Purpose The main purpose of this paper is to investigate autocorrelation structure of stock and portfolio returns in a unique market setting of Saudi Arabia, where nearly all active traders are the retail individuals and the market operates under severe limits to arbitrage. Specifically, the authors examine how return autocorrelation of Saudi Arabian stock market is related to factors such as the day of the week, stock trading, performance on the preceding day and volatility. Design/methodology/approach The sample consists of the daily stock price and index data of 159 firms listed in Tadawul (Saudi Arabian Stock Exchange) for the period from January 2004 through December 2015. The methodology of Safvenblad (2000) is primarily used to investigate the autocorrelation structure of individual stock and index returns. The authors also use the Sentana and Wadhwani (1992) methodology to test for the presence of feedback traders in the Saudi stock market. Findings Results show that there is significantly positive autocorrelation in individual stock, size portfolio and market returns and that the last two are almost always larger than the first. Return autocorrelation is negatively related to firm size. Interestingly, return autocorrelation is positively related to trading frequency. For portfolios, autocorrelation of returns following a high absolute return day is significantly higher than that following a low absolute return day. Similarly, return autocorrelation during volatile periods is generally larger than that during tranquil periods. Return correlation between weekdays is usually larger than that between the first and last days of the week. Overall, the results suggest that the possible reason for positive autocorrelation in stock returns could be the presence of negative feedback traders who are engaged in frequent profit-taking activities. Originality/value This is the first paper that thoroughly investigates the autocorrelation structure of the returns of the Saudi stock market using both index and individual stock returns. As this US$583bn (as of August 21, 2014) market opened to foreign institutional investors in June 2015, the results of this paper should be of significant value for the potential uninformed foreign investors in this relatively lesser known and previously closed yet highly prospective market.

scholarly journals Return Predictability of Stock Price Index in Tehran Stock Exchange

2013 ◽  
Vol 9 ◽  
pp. 59-64
Author(s):  
Mohsen Mehrara
Keyword(s):  
Stock Returns ◽  
Stock Price ◽  
Price Index ◽  
Stock Exchange ◽  
Asset Price ◽  
Estimation Method ◽  
Return Predictability ◽  
Recursive Estimation ◽  
Parameter Estimates ◽  
Daily Stock Returns

The question of whether asset price changes are predictable has long been the subject of many studies. Many studies, using historical returns based on random walk tests, have shown that stock return is not predictable. We study return predictability of the Tehran Exchange Price Index (TEPIX) based on monthly data from 2000 to 2011. For forecasting the return, we used a recursive estimation method in which the parameter estimates were updated recursively in light of new weekly observations, and also its regressors were changed recursively according to the Schwarz Bayesian Criterion. The results show that the daily stock returns are not predictable using publicly available information.

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