Semi-strong Form Of Market Efficiency Research Articles

The Covid-19 Pandemic and the Consumer Staples Sector: A Test of Market Efficiency

On Wednesday March 11, 2020, the World Health Organization (WHO) declared the covid 19 outbreak a global pandemic (Cucinotta, 2020). How efficient is the consumer staples market reaction to the announcement of a global pandemic? The purpose of this study is to examine the risk adjusted returns on and around the pandemic announcement to test the semi-strong form market efficiency hypothesis using the standard event study methodology in the finance literature. Will returns in the consumer staples industry show larger than expected gains on and surrounding the WHO’s COVID-19 pandemic announcement? The finance literature offers little evidence supporting the link between pandemics and the stock market. The announcement of a pandemic by the WHO should significantly and quickly affect the market. According to Eugene Fama (1970), if the market is semi-strong form efficient, all public information is immediately factored into the market and no investor can use this information to achieve an above normal return when adjusted for risk. To study this relationship, data for the S&P 500 and 10 consumer staples sector firms were collected for the event period surrounding the announcement of the COVID-19 pandemic. This study tests the global pandemic announcement for semi-strong form market efficiency (Bacon &Howell 2021). Evidence here supports the expected positive signal associated with the sample of consumer staples sector firms in reaction to the announcement of the pandemic. Likewise, the study results support the semi-strong form efficient market hypothesis and suggest the possibility of trading on this information up to 15 days prior to the announcement consistent with the behavioral finance literature (Bacon & Howell 2021).

Comparative Analysis of Stock Prices, Abnormal Return, Cumulative Abnormal Return, and Trading Volume Activity in the Indonesia Stock Exchange: An Event Study of the Russia-Ukraine War

The Russia-Ukraine war has captured international attention and raised concerns about its potential implications on global financial markets. This study aimed to investigate the interplay between geopolitical events, market reactions within the Indonesia Stock Exchange (IDX), and the market efficiency of the IDX. The study employed event study methodology and analyzed changes in stock prices, abnormal returns, cumulative abnormal returns, and trading volume activity. The sample comprised 53 companies in the energy sector and 57 companies in the food and beverage sector listed on the IDX. The analysis focused on data from 10 days before and after three Russia-Ukraine conflict-related events, namely (1) the announcement of Russia’s invasion of Ukraine on the 24th of February 2022, (2) the announcement of an oil import embargo on Russia by the European Union on the 31st of May 2022, and (3) the announcement of the first wheat export ship’s departure from the port of Odesa on the 1st of August 2022. Both paired sample t-tests and paired sample Wilcoxon signed rank tests were conducted to assess the statistical significance of differences in the means of paired samples. The findings revealed significant differences in average stock prices before and after all three events in the energy sector. However, only events 2 and 3 displayed significant differences in average abnormal returns and cumulative abnormal returns. Moreover, events 1 and 3 exhibited significant differences in average trading volume activity. In the food and beverage sector, a significant difference in average stock prices was observed before and after event 2, while all three events presented significant differences in average abnormal returns and cumulative abnormal returns. Furthermore, event 3 showed a significant difference in average trading volume activity. These findings indicated that the IDX displayed varying reactions to different Russia-Ukraine conflict-related events. Notably, events involving multiple countries or entities exerted a greater impact on the energy and food and beverage sectors within the IDX, leading to more pronounced market reactions. Additionally, the findings suggested that the IDX exhibited a semi-strong form of market efficiency.

Market Reaction to the Implementation of Coal Royalty Tariff Policy in Indonesia

The impact of government regulation on the mining industry is captivating to explore, specifically the newly reformed Coal Royalty Tariff. This present research captures the market's response to two tariff policy reforms, namely the Indonesian Government Regulation Number 25 of 2021 and Government Regulation Number 15 of 2022 building upon the semi-strong form market efficiency. T-Test analysis is used to test the hypothesis in which the abnormal returns from sample companies in the mining sector on the Indonesia Stock Exchange surround the enactment of government regulations.  There is no abnormal return that occurred around the enactment of Government Regulation Number 25 of 2021, while the enactment of Government Regulation Number 15 of 2022 do generate abnormal return. Results imply a solid relationship between changes in risk and the investors’ expected future profitability as investors’ expectations are depicted in the stock price movements. This concludes that uncertainty following changes in government regulation constitutes an additional premium required by the investors. Our findings provide empirical evidence to the literature of semi-strong form market efficiency hypothesis (EMH) displaying that the market response to the implementation of changes in policies, especially the government should give proper attention to the issue of determining tariffs and investors should evaluate their required premium based on the impact of tariff changes.
 Keywords: Stock Price, Coal Mining, Government Policies, Royalty Rate

Capital Market Reactions to The Covid 19 Pandemic

This study aims to determine and analyze the capital market's reaction to the Covid 19 Pandemic in biotechnology companies listed on the Nasdaq. The method used in this study uses a type of quantitative method. This study uses an event study. The sampling method in this study was carried out using a non-probability random sampling approach. The announcement of the COVID-19 pandemic by the WHO and the commitment to produce a COVID-19 vaccine have had a significant impact on abnormal stock returns and trading volume activities of biotech companies listed on the NASDAQ stock market. However, there is no significant effect on the liquidity of biotech company stocks. In addition, the announcement of the COVID-19 pandemic also affected the volatility of biotech company stocks. In contrast, the announcement of a commitment to producing a COVID-19 vaccine did not significantly impact the volatility of biotech company stocks. So, it shows that the NASDAQ stock market reacts sensitively to announcements about the COVID-19 pandemic and efforts to produce COVID-19 vaccines by biotech companies. This shows that the COVID-19 pandemic has significantly impacted the stock market, especially in the biotechnology sector. The event study approach is used to test the market with a semi-strong form of market efficiency by demonstrating that the stock price reflects all published information (all publicly available information).

Market efficiency of Asian stock markets during the financial crisis and non-financial crisis periods

We examine the semi-strong form market efficiency level for the 12 major Asian markets with the stochastic dominance (SD) method during the financial crisis and non-financial crisis periods. Five famous value premium (VP) indicators, including book-to-market, cash flow-to-price, earnings-to-price, dividend-to-price, and sales-to-price ratios, are employed to examine the market efficiency during the two examination periods, respectively. The results of the SD test for performance between value (V) and growth (G) portfolios can be categorized into three sets: V=G (efficiency), V≻G (inefficiency, VP), and V≺G (inefficiency, reversal VP). Our main results show that the market efficiency or inefficiency level is not significantly different between the financial crisis and non-financial crisis periods. However, the evidence of further exploration of market inefficiency level shows that the different anomaly returns pattern exists in the two examination periods.

Merger Announcements, Financial Performance and Stock Price: A Test of Market Efficiency

Can investors earn above-normal risk-adjusted returns by acting on public information defined by merger announcements? This study tests the effect of a sample of 14 merger announcements on stock price returns using the risk-adjusted event-study methodology. Results show that an investor is not able to make above￾normal risk-adjusted returns on the announcement of mergers in support of semi-strong form market efficiency. Merger announcements stimulate significant positive returns around the merger announcement. Results show market over- and under-reaction around the merger announcement well documented in the behavioral finance literature. The evidence shows a significant stock price return reaction up to 1 day prior to the announcement consistent with the existence of insider trading (Ross and others, 2016). Do mergers strengthen companies’ financial performance? Results show that mergers are not value-increasing based on the pre-post-merger financial performance in support of the agency problem where large firm use excess free cash flow to get “bigger” not “better” by going shopping for other firms. In such cases, the firm’s merger maximizes size, not stockholder wealth, the goal of the firm.

MARKET REACTION IN THE MANUFACTURING SECTOR SHARE TO THE EVENT OF THE APPROVAL OF THE JOB CREATION LAW IN 2020

This study aims to determine the Market Reaction in Manufacturing Sector Stocks to the Legalization of the Job Creation Law 2020. The purposive sampling technique was used from all manufacturing companies listed on the Indonesia Stock Exchange for the 2020 period. The event study analysis technique was used in this study with an observation period of approx. 21 trading days (10 days before and 10 days after).
 The results of statistical tests on abnormal returns show that there is no significant difference in the average abnormal return before and after the event and indicates a semi-strong form of market efficiency. The results of statistical tests on trading volume activity show that there is a significant difference in average trading volume activity before and after the event. This study implies that the ratification of the Job Creation Law has an impact on the investment climate so that when major political events occur, it is hoped that market participants will be more careful in making investment decisions, especially in buying and selling shares.

Quantitative study of candlestick pattern & identifying candlestick patterns using deep learning for the Indian stock market

The stock market is an integral aspect of any country’s economic infrastructure. Analyzing and attempting to play the markets to maximize profits is an endeavor a large fraction of the population aspires to. Candlestick patterns are the backbone of Technical Analysis, used for trading in the stock market. There are a number of candlestick patterns in the market, each with its own benefits and downsides. Due to this, the task that befalls the hands of analysts is deciding which patterns provide the most effective gauge of the current market situation. Due to the large level of noise and widely recognized semi-strong form of market efficiency, analyzing and forecasting the stock market is infamously difficult. For traders that use Technical Analysis to trade, it's critical to be able to recognize candlestick patterns quickly. We will be attempting to determine their respective effectiveness with respect to the Indian Stock Market via exploratory analysis conducted on real-world market data. Also, we'll use candlestick charts to train neural networks and subsequently find patterns. Deep Learning will be used to recognize candlestick patterns in large-cap Indian equities.

COVID-19 and the Health Industry: A Test of Market Efficiency

The World Health Organization declared the COVID-19 coronavirus outbreak as a global pandemic on March 11, 2020. How does the market react to a global pandemic announcement? How efficient is the market? The purpose of this study is to test for semi-strong form market efficiency. Will the healthcare industry show excess gains? A link between the market and pandemics can be inferred but has not been heavily studied. In the efficient market hypothesis, Fama (1970) proposes that in semi-strong form market efficiency, all public information is factored into the market and no investor can achieve a risk-adjusted, above normal return. To study this relationship, S&P 500 data on 10 healthcare firms was collected for several days surrounding the announcement and standard event study methodology from finance literature was used. Evidence here supports the expected positive signal associated with the sample firms and pandemic announcement. Likewise, the results support the semi-strong form efficient market hypothesis and suggests the possibility of trading on this information up to 24 days before the announcement.

Pairs trading: is it applicable to exchange-traded funds?

Among the various statistical trading strategies, pairs trading has been widely employed as a market neutral strategy owing to its simple approach and ease of application. In this context, we develop a cointegration-based pairs trading framework with a set of pre-conditions for pair eligibility and apply it to different asset classes. The performance analysis of a portfolio of 45 pairs is considered for the period of January 2007 to January 2021, which covers the period of a full market cycle of adjacent bull and bear periods; it is studied and benchmarked against the S&P500 index, which is considered as a proxy for the general market. We find an average annual return of 15% with an average Sharpe ratio of 1.43 after considering the transaction costs; we observe that this performance does not vary significantly with a change in the transaction cost levels and does not pass below the risk-free return levels with changing market conditions. Further, the strategy is observed to perform better during bear market conditions. Considering the highly liquid trading environment of the strategy, our findings raise a call for a discussion on the semi-strong form market efficiency.

Do stock splits matter for returns, volatility, and liquidity?

The purpose of this study is to investigate the impact of stock splits on the return, riskiness, and liquidity of stocks. Utilizing a sample of 94 stock splits taken place between 2010 and 2019 at Borsa Istanbul, the study analyzes the daily abnormal returns, change in volatility, and changes in volume around the stock split announcement and execution dates. The results display significant positive abnormal returns around the announcement date but not significant abnormal returns around the execution. The volatility and liquidity of stocks increase significantly around both announcement and execution dates. The findings are in line with the positive signaling, and liquidity hypotheses of stock split and with most of the observations reported in the empirical literature. The new evidence provided points out the lack of semi-strong form of market efficiency at Borsa Istanbul as far as the stock splits are considered.

Ho Chi Minh Stock Exchange Market: Operations and Efficiency

This paper presents an up-to-date account of market operations of the Ho Chi Minh Stock Exchange and examines its informational efficiency in recent years. The daily closing prices and rates of return of VN Index – the major market index of Ho Chi Minh Stock Exchange and 10 stocks chosen from different sectors are employed, from 2 January 2018 to 31 December 2019, to investigate the random walk hypothesis of market efficiency using the Lo-MacKinlay variance ratio test and Chow-Denning multiple variance ratio test. Our results show that the market index and individual sample stocks conform to the null hypothesis of a random walk type 3 model of a weak form market efficiency. The paper also presents the results of an Event Study to examine the semi-strong form market efficiency of the HOSE. The empirical results on this type indicate that there are significant abnormal returns and significant cumulative abnormal returns by trading the stocks around the events. These results are inconsistent with the requirements of a semi-strong form market efficiency, and it thus appears that further improvements in transmission of information and its speed within this market are needed to further improve the efficiency of this emerging market.

Machine Learning in Futures Markets

In this paper, we demonstrate how a well-established machine learning-based statistical arbitrage strategy can be successfully transferred from equity to futures markets. First, we preprocess futures time series comprised of front months to render them suitable for our returns-based trading framework and compile a data set comprised of 60 futures covering nearly 10 trading years. Next, we train several machine learning models to predict whether the h-day-ahead return of each future out- or underperforms the corresponding cross-sectional median return. Finally, we enter long/short positions for the top/flop-k futures for a duration of h days and assess the financial performance of the resulting portfolio in an out-of-sample testing period. Thereby, we find the machine learning models to yield statistically significant out-of-sample break-even transaction costs of 6.3 bp—a clear challenge to the semi-strong form of market efficiency. Finally, we discuss sources of profitability and the robustness of our findings.

Corporate Sponsorship of the 2008, 2012, and 2016 Summer Olympics: A Test of Market Efficiency

Corporate sponsorship is a form of advertising that companies pay to be associated with certain events. Firms with corporate sponsorships of an event such as the Olympic Games can maximize stockholder wealth by evaluating the returns on these investments. In order to evaluate the returns on these investment decisions, this study employs an event study methodology in the finance literature. Using the risk-adjusted event study methodology, this study tests the hypothesis that the risk-adjusted rates of return on the sponsor companies’ stock prices are significantly positively affected by this type of information. The event study tested the effect of the 2008 Beijing, 2012 London and 2016 Rio Summer Olympic games on the sponsor company’s stock prices. The opening ceremonies took place on August 8th, 2008, July 27th, 2012 and August 5th, 2016. Results for all 3 summer Olympic games and the combined global sample show positive gains to their risk-adjusted rates of return of stock prices leading to the opening ceremony, with small gains following the opening ceremony. The evidence also supports the semi-strong form of market efficiency. No investor was able to make an above normal return by acting on the event.

How do carbon prices react to regulatory announcements in China? A genetic algorithm with overlapping events

To investigate the impacts of regulatory announcements on China’s pilot carbon markets, as well as test the semi-strong form of market efficiency, a multivariate regression model with GARCH effects combined with multiple bilaterally modified dummy variables is established which allows us to investigate the potential overlapping influence from two timely adjacent events. The Shanghai, Guangdong and Hubei pilot carbon markets are taken as case studies. Based on the ADF test and the runs test, the results show that the China’s pilot carbon markets have achieved the weak form of efficiency but not the semi-strong form of efficiency. With the regression model the results show that the release of the allowance allocation plan will affect the carbon price trend, and the allowance auction can only play an auxiliary role as its impact on the carbon price is not decisive. In addition, ubiquitous ex-ante impact proves that the information leakage exists in each pilot carbon market. The model established in this paper is suitable for analyzing the impacts of overlapping events in different markets, which can effectively assist decision makers to distinguish the effects caused by overlapping events.

Causal Impact of Government Policy in Stock Market of Nepal

This study is directly related to the semi-strong form of market efficiency. 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.
 It examines the relationship between fiscal policy and stock index in Nepal with using data from 2003 to 2019. This research use market model to determine the statistical relationship. Overall the independent variable government policy poses significant relationship with stock index in Nepal.

Causal Impact of Government Policy in Stock Market of Nepal

This study is directly related to the semi-strong form of market efficiency. 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.
 It examines the relationship between fiscal policy and stock index in Nepal with using data from 2003 to 2019. This research use market model to determine the statistical relationship. Overall the independent variable government policy poses significant relationship with stock index in Nepal.

Forward and Reverse Stock Splits: A Test of Market Efficiency

The purpose of this study is to utilize the risk adjusted event study methodology to test the magnitude and timing of any effect that a stock split announcement has on a firm’s stock price. By analyzing market reactions of 50 NYSE or NASDAQ stock splits and comparing them to the corresponding dates’ S&P 500 performance, it is possible to determine if investors are able to earn above normal risk adjusted returns by acting on public announcements. The results suggest that investors would not be able to make atypical returns on the announcement of stock splits, supporting semi-strong form market efficiency.

STOCK MARKET REACTION TO BREXIT ANNOUNCEMENTS: EVIDENCE FROM A NATURAL EXPERIMENT

Using four Brexit-related announcements as a source of exogenous information shocks, we investigate the semi-strong form of efficiency in seven major European stock markets. Our results suggest that only the announcement of the Brexit referendum result produced statistically significant negative cumulative abnormal returns in the markets of the sample. However, with the exception of the Irish stock market, the effects ceased to be significant in a period of five trading sessions after the event. We also document an increase in trading activity, though statistically insignificant, in the day of the referendum and in the following days. Overall, our results are in line with the semi-strong form of market efficiency.

An Ex Post Assessment of Investor Response to Catastrophes

A large body of research has examined abnormal stock returns for insurance companies in the wake of major catastrophes. Most of these studies have investigated the ex ante factors that investors may consider when generating expectations of future profits, represented by postcatastrophe stock returns. We instead ask whether these expectations were ultimately correct by investigating the relationship between returns and the disaster’s effect on future earnings. We find that returns immediately following a disaster are not associated with future earnings. Approximately six days following a catastrophe, however, returns begin to show a significant positive relationship with future earnings. This relationship becomes stronger in subsequent days. We conclude that investors are unable to correctly predict a disaster’s net impact on profits immediately after a disaster because existing public information is insufficient or misunderstood. Only once insurers begin disclosing their estimated losses can investors make accurate predictions about a disaster’s effect on earnings. Our study shows that the investor expectations inferred in much of the existing literature are not predictive of future profits. Our findings are consistent with semistrong-form market efficiency in the wake of a major disaster.