Efficient Market Research Articles

Stock price overreaction: evidence from bull and bear markets

PurposeIn this paper, we provide new evidence to strengthen the stock market overreaction hypothesis by examining a new context that has not been explored before. Our research is inspired by the widely held belief that investor sentiment experiences abrupt changes from optimism to pessimism as the market switches between bull and bear states.Design/methodology/approachIf the stock market overreaction hypothesis is correct, it implies that investors are inclined to become excessively optimistic during bull markets and overly pessimistic during bear markets, resulting in overreaction and subsequent market correction. Consequently, the study first develops two testable hypotheses that can be used to uncover the presence of stock market overreaction with subsequent correction. These hypotheses are then tested using long-term data from the US market.FindingsThe study's findings support the hypothesis while also revealing a significant asymmetry in investor overreaction between bull and bear markets. Specifically, our results indicate that investors tend to overreact towards the end of a bear market, and the subsequent bull market starts with a prompt and robust correction. Conversely, investors appear to overreact only towards the end of a prolonged bull market. The correction during a bear market is not confined to its initial phase but extends across its entire duration.Research limitations/implicationsOur study has some limitations related to its focus on investigating stock market overreaction in the US market and analyzing the pattern of mean returns during bull and bear market states. Expanding our study to different global markets would be necessary to understand whether the same stock market overreaction effect exists universally. Furthermore, exploring the relationship between volatility and overreaction during different market phases would be an exciting direction for future research, as it could provide a more complete picture of market dynamics.Practical implicationsOur study confirms the presence of the stock market overreaction effect, which contradicts the efficient market hypothesis. We have observed specific price patterns during bull and bear markets that investors can potentially exploit. However, successfully capitalizing on these patterns depends on accurately predicting the turning points between bull and bear market states.Social implicationsThe results of our study have significant implications for market regulators. Stock market overreactions resulting in market corrections can severely disrupt the market, leading to significant financial losses for investors and undermining investor confidence in the overall market. Further, the existence of overreactions suggests that the stock market may not always be efficient, raising regulatory concerns. Policymakers and regulators may need to implement policies and regulations to mitigate the effects of overreactions and subsequent market corrections.Originality/valueThis paper aims to provide additional support for the stock market overreaction hypothesis using a new setting in which this hypothesis has not been previously investigated.

Does Contrarian Investing Beat the Conventional Strategies and the Index?

Traditional momentum strategies on the stock market are implemented in accordance with the efficient market hypothesis and involve making investments in accordance with market trends. However, this hypothesis has been repeatedly criticized by supporters of behavioral finance, who allow the irrational nature of investment decisions, which led to the emergence of contrarian investment strategies, based on the overreaction hypothesis and the reversal effect (over a longer horizon, loser stocks outperform winners), according to which investments are made in opposite direction to the market, involves buying the losing stocks and selling the winners. According to contrarian investment strategies, when buying shares, investors prefer a lower level of P/E ratios (Price – earnings ratio), which indicates the valuation multiple placed to the company’s market price vis-à-vis its net profits. The article examines the hypothesis that P/E ratio and contrarian investment are related, based on data for 2010–2022 for 50 shares of India, whose stock market is developing rapidly, examines the differences between the top ten P/E stocks and the bottom ten P/E stocks using inflation adjusted return on investment (ROI) to determine, whether or not, an investment in such stocks would generate sufficient returns to outpace inflation over a period of ten years. The article tests 3 hypotheses that investing in stocks with low P/E ratios in the Nifty 50 index (a live benchmark that illustrates how each industry contributes to India’s GDP) will generate higher returns than investing in stocks with high P/E ratios, over a long-term horizon (H1), inflation (Н2), the Nifty 50 index (Н3). The sources of data were finalized to be BSE Official Website, NSE Official Website, Yahoo Finance, Screener, Annual Reports, etc. The article calculates the profits for top 10 P/E stocks (conventional strategy) and bottom 10 P/E stocks (contrarian investing), and determining the returns from top 10 P/E stocks and the bottom 10 P/E stocks (when calculating for 10 years, the same steps were repeated: synchronously, once a year, both types of shares were bought at Purchase Price and sold a year later at Market Price). The calculations confirmed all 3 proposed hypotheses. Contrarian investing delivered returns of around 3.64 times the initial investment, whereas conventional investing produced returns of about 77.5% when comparing the top 10 P/E stocks to the bottom 10 P/E stocks in the Nifty 50 index. An outstanding return of 84.11%, which is a strong return when adjusted for inflation, was achieved using the contrarian strategy. As a result of the conventional strategy’s loss of 10.45% when adjusted for inflation, the study also shows that contrarian investing can assist an investor in hedging against inflation. This emphasizes how crucial it is to take a contrarian attitude when making stock market investments. At the same time, contrarian investment returns of 3.64 times the initial investment over this period surpass the benchmark Nifty 50 Index returns, which is 3.24 times.

Effect of Interest Rate Changes on Stock Market Volatility in Congo

Purpose: The aim of the study was to assess the effect of interest rate changes on stock market volatility in Congo. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Changes in interest rates have a notable impact on stock market volatility. When central banks adjust interest rates, it influences investor sentiment and economic forecasts. Typically, an increase in interest rates makes borrowing more expensive, which can dampen corporate profits and economic growth, leading to higher market volatility as investors reassess the value of stocks. Conversely, a decrease in interest rates generally lowers borrowing costs, potentially boosting corporate earnings and economic expansion, which can initially reduce market volatility. However, the long-term effects might differ as lower rates can also lead to overvaluation concerns, eventually increasing volatility. Additionally, interest rate changes signal monetary policy shifts and broader economic conditions, further influencing investor behavior and stock market dynamics. Overall, interest rate fluctuations are a critical factor contributing to stock market volatility through their direct and indirect effects on economic activities and investor perceptions. Implications to Theory, Practice and Policy: Efficient market hypothesis, portfolio theory and behavioral finance theory may be used to anchor future studies on assessing the effect of interest rate changes on stock market volatility in Congo. For practical implications, investors and financial institutions should develop risk management strategies that account for the short-term volatility spikes following interest rate announcements. From a policy perspective, policymakers should consider the lagged effects of interest rate changes when formulating monetary policy to ensure smoother market transitions.

Selective and Market Timing Skills: An Empirical Evaluation of Equity Mutual Funds in an Emerging Market

This study evaluates the selective and market timing skills of mutual funds managers using monthly net asset values of all 30 actively managed equity-based funds that operated from January 2012 to December 2021 obtained from the Securities and Exchange Commission. Selectivity is the ability to search for and choose undervalued securities to exploit the sub-optimal market weights of securities, while market timing is the ability to forecast the direction of the market and adjust portfolio betas to generate alpha. Two regression models, namely the Treynor-Mazuy (1966) and Henriksson-Merton (1981) were deployed for the study. The findings indicate that mutual funds did not exhibit significant selective skills or market timing abilities. This outcome is consistent with the Efficient Market Hypothesis (EMH). Consequently, it becomes challenging for investors or fund managers to consistently outperform the market through stock selection or market timing. Based on the study's results, the recommendation for investors is to consider low-cost passive investment strategies, such as index funds or exchange-traded funds (ETFs), over actively managed funds.

The Strategic Decision Making Analysis for a Semiconductor Company Based on SWOT Model

The focus of this work is to use SWOT analysis to assess the current situation of a company and determine its strategic direction. By gaining insight into a company's internal and external environment, we can better understand its strengths and weaknesses and use this information to make effective strategies and decisions. In addition, our research also shows that while companies perform well in new product development, customer-oriented approaches, and efficient market decision-making, there are still some limitations in financial management, production control, and product diversification that need to be addressed. The innovation of this work is the application of SWOT analysis to the strategic planning of fabless semiconductor companies. While SWOT analysis has been used in various industries and fields, applying it to fabless semiconductor companies is a novel approach. The significance of our study is that it provides a practical method to evaluate a company's competitive position and guidance for its future development. The paper concludes by emphasizing the importance of leveraging strengths, addressing weaknesses, and capitalizing on opportunities to ensure competitiveness and sustainable growth.

A STUDY OF THE DAY OF THE MONTH EFFECT IN THE INDIAN STOCK MARKET

Seasonality and seasonal variations are common phenomena associated with the stock markets and the Indian stock market is no exception to them. An interesting anomaly in seasonality is the day-of-the-week effect, which this paper tries to unravel. Many researchers have investigated the effects of seasonal fluctuations such as month-of-the-year, day-of-the-month, and day-of-the-week. Historical evidence suggests that these anomalies are prevalent in the market and if properly studied investors can take advantage of the market and try to beat the Efficient Market Hypothesis (EMH). This paper attempts to understand the day-of-the-week effect in the Indian stock market.

The Effect of Budget Deficits on Stock Market Returns in Emerging Markets: A Panel VAR Analysis

This study examines the impact of fiscal deficits on stock returns. The sample covers emerging markets for the period 2016Q1-2021Q4. The analysis results using panel vector autoregression (PVAR) and Granger causality tests indicate that fiscal deficits cause stock returns. These results are confirmed for countries with low and medium levels of financial development and for European countries. However, in countries with high levels of financial development such as the BRICS and ASEAN countries, no effect is observed. It is also found that this effect disappears during the COVID-19 pandemic. The results of the study question the strong form of the efficient market hypothesis (EMH). According to the EMH, stock prices should fully reflect all available information. However, the impact of fiscal deficits on stock returns in low- and middle-income countries and European countries suggests that market participants may not fully reflect this information, addressing the existence possibility of markets that are not efficient in the strong form.

Determinants of stock return in 10 biggest market capitalization on the Indonesian stock exchange

Several research results on the capital market in Indonesia fall into the category of market efficiency in the weak form, so the results of previous research do not reflect the theory of capital market efficiency in the strong form. The purpose of this research is to analyze and answer the existence of inconsistencies in the results of previous research as well as the phenomenon of stock returns which are not as described in capital market theory in strong form. This is what prompted researchers to do it again using different time series and cross-sectional data. This type of research is quantitative descriptive with a panel data multiple regression analysis method using 10 sample companies that are members of 50 large capitalization companies for 7 years. This research formula is to maximize the Stock Return value through leverage as an intervening variable using research objects of companies on the Indonesia Stock Exchange. Two research models are integrated into one and each goes through a model selection test stage, namely the Chow Test, Hausman Test, and Lagrange Multiplier Test using the eviews12 application. The results of this research explain that increasing ROA can have an impact on reducing Leverage (DER) and through DER it can explain the impact on Stock Returns, but ROA cannot directly explain Stock Returns. It is hoped that these results can help as a guide for investors to get maximum Stock Returns.

The Inefficiency of Bitcoin and the COVID-19 Pandemic

From the perspectives of asset pricing, market outreach, regulatory framework, and investor ethos, crypto markets differ substantially from traditional financial markets. Given these fundamental differences, it is interesting to examine how the notions of market efficiency apply to crypto markets, especially because the arguments of the efficient market hypothesis (Fama, 1970) and the adaptive market hypothesis (Lo, 2004, and Lo, 2008) were originally developed in the context of traditional financial markets. Research on the informational efficiency of crypto markets has attracted increasing attention in recent years. This paper examines the evolving efficiency of Bitcoin, the leading cryptocurrency, especially during the period when economies around the world were devastated by the Covid-19 pandemic. For a newly-emerged cryptocurrency with a market that is essentially global, a global shock like the Covid-19 pandemic presents ideal conditions for assessing how efficiency evolves as the market faces a series of shocks. Employing a fixed-length rolling window approach, this paper carries out the following tests: the automatic portmanteau test of Escanciano and Lobato (2009), the wild bootstrap automatic variance ratio test proposed by Kim (2009), the generalized spectral test of Escaciano and Valesco (2006), and the test proposed by Dominguez and Lobato (2003). The results provide evidence of episodes of inefficiency in a market that is efficient over extended periods. The inefficiency index constructed in this study shows that the Bitcoin market went through proportionately longer and more frequent episodes of inefficiency during the Covid-19 period. This is in line with the adaptive market hypothesis and has practical significance for investors and regulators.

Old age care fund helps to manage their funds In easy way

Abstract: A Old Age Care Funds is a sort of investment vehicle in which the combined capital of several participants is used to purchase a diverse range of bonds, equities, and other securities. Funds, which are professionally managed, give people the chance to invest in a variety of assets without having to handle them themselves. The value of the Fund shares that investors purchase varies according to how well the underlying assets perform. Funds are well-liked by both rookie and seasoned investors because they offer diversity, liquidity, and expert management. Diverse mutual fund categories, such as stock, bond, money market, and hybrid funds, are available to suit varying investment goals and risk tolerances. Investors can select funds according to their risk tolerance, time horizon, and financial objectives. Securities regulators supervise mutual funds to maintain transparency and safeguard the interests of investors. They are now an essential instrument for people to develop a diversified investment portfolio and engage in the financial markets. Old Age Care Fund portfolio analysis is an important component of investment management that includes a variety of approaches for evaluating the performance, risk, and composition of investment portfolios. The efficient market hypothesis (EMH) states that markets are efficient and reflect all available information, making it difficult for fund managers to regularly outperform the market, according to Malkiel and Fame (1970). Jensen (1968) proposed the Capital Asset Pricing Model (CAPM), which emphasizes risk-adjusted returns and the identification of alpha, which indicates a fund manager’s capacity to create excess returns above the market. IndexTerms – Python, Powet-BI, Data Analysis.

Testing the Adaptive Market Hypothesis and Time-Varying Efficiency in the Indian Equity Market

The study examines the adaptive market hypothesis (AMH) as an evolutionary principle of the alternative efficient market hypothesis in the Indian stock market (Sensex and Nifty50) on the daily return from April 2014 to May 2020. Based on AMH, investors behave, learn, and adapt to market conditions. This distinction of dynamic market conditions is divided into bull and bear market classifications. We apply three variations of the variance ratio test and the returns have been whitened using the Autoregressive model with generalized autoregressive conditional heteroskedasticity (AR-GARCH) approach to examine the nonlinear predictability test. Further, we evaluate a fixed-length subsample window framework to detect the time-varying predictability and examine whether market conditions affect stock return predictability and market condition. The study confirms inefficient market behaviour during crises, fear, panic, macroeconomic events and each market adapts differently to certain market conditions. Furthermore, the return series exhibits significant periods of efficiency and inefficiency consistent with the adaptive market hypothesis. The evidence of our findings sheds light on efficient market behaviour in dynamic market conditions and market environments for researchers, investors in investment strategies and policy intervention in risk containment measures and control market manipulation.

Personal values and entrepreneurship: does the unemployment rate matter?

PurposeThe study responds to the calls for multilevel approaches in entrepreneurship research and seeks to answer whether the relationships between personal values and entrepreneurship remain stable across different economic conditions, using the unemployment rate as a moderator. It pays attention to the solo self-employed and women, as these groups are particularly vulnerable when crises occur.Design/methodology/approachWe use Schwartz's theory of human values, which has been understudied in entrepreneurship and follow a correlational research design with micro and macro variables. Multilevel logistic regression is applied to the data from the large sample of 151,032 individuals participating in six waves of the European Social Survey. Solo self-employed are distinguished from those employing others, and analyses are run separately for men and women to understand gender differences.FindingsThe findings show that self-direction and achievement are positively, and benevolence and security negatively related to entrepreneurship. The high unemployment rate lowers the positive relationships with self-direction and achievement and mitigates the negative relationship with security, but only for the solo self-employed and not for employers. Results mostly hold for both genders.Research limitations/implicationsThe study suggests that security-related values should not be omitted from entrepreneurship research focused on entrepreneurs' values. It also emphasizes the need to distinguish between various subgroups of entrepreneurs and their motivation, which is important for efficient active labor market policies.Originality/valueThe study utilizes multilevel analyses that account for individual- and country-level influences on entrepreneurial activity. It contributes to understanding how economic context influences value salience and supports the applicability of Schwartz's theory of human values in entrepreneurship.

Analysis of BSF Maggot Farming Income in the Context of Organic Waste Management in NTB Province, Indonesia

This study investigates the factors influencing the income of Black Soldier Fly (BSF) maggot farmers in the NTB province of Indonesia. Utilizing a descriptive quantitative analysis method, data were collected from 32 maggot farmers through purposive sampling. The primary data were obtained via questionnaires administered to the selected farmers. The analysis employed a multiple regression model to evaluate the impact of various factors on farmers' income. The results indicate that the average monthly income of BSF maggot farmers is Rp 5,938,750 (364.35 USD). The income is significantly influenced by the amount of production, production cost, and selling price. Specifically, an increase in production amount and selling price positively correlates with higher income, while an increase in production cost negatively affects income. These findings highlight the critical role of efficient production practices and market strategies in enhancing the economic viability of BSF maggot farming.

Insider Trading Analysis of the Indonesian Capital Market

Insider trading is one of the crucial issues in the capital market that can have a significant impact on market integrity and stability. In Indonesia, the practice of insider trading not only causes losses for investors who do not have access to insider information but can also reduce investor confidence in the capital market as a whole. Research This article will analyze and explain Insider Trading in the Indonesian Capital Market. This study uses notative juridical methods or normative law. The results of this study explain that Insider Trading in the Indonesian Capital Market is contained in Articles 95, 96, 97, 98, 99, and Article 104 which explain that insiders from an issuer of public companies that have inside information are prohibited from buying or selling affects, or companies that make transactions with issuers where they work. The prohibition on the use of insider information is more due to unfair actions against others who are completely unaware of the existence of the information. Investor protection is one very important way because if investors do not get enough protection, they are reluctant to make transactions on the exchange. Without a large number of investors, capital market activities will be weak, and the function of the capital market will not develop, the principle of openness as one of the efforts to protect investors. Such protection efforts will be realized if the implementation of information transparency or full disclosure obligations containing material facts in activities that take place in the capital market in accordance with the purpose of the principle of openness itself, namely to create a fair, efficient and orderly market that protects Investors and helps determine accurate market prices which are all intended for the benefit of Investors or potential Investors.

The Role of Secure Property Rights in Driving Economic Growth: A Review of Recent Evidence

This paper aims to briefly explain the factors contributing to economic growth, particularly emerging and developing economies, emphasizing the impacts of secure property rights. Tangible and intangible assets such as land and minerals, patents and copyrights offer the investors legal recognition that enhances investment, inventive activities and efficient market exchange. The review demonstrates how property rights reforms have positively impacted agricultural yields, credit facilities, and FDI in sub-Saharan Africa, Southeast Asia and Latin American countries. The paper also focuses on the impact of intellectual property rights on technological advancement, especially in knowledge-based societies. While the previous shows that there are gains in reforms in property rights, it has to be stated that there are still hurdles in the implementation of property rights reforms for the benefit of the more significant population due to the following: ? Finally, the paper reiterates the importance of efficient and precise laws and policies that will enhance the efficiency of the property rights to enhance the economic returns.

Do ESG practices mediate the relationship between board characteristics and tax avoidance in G20 countries?

Purpose This study aims to investigate the direct and indirect relationship between board characteristics and corporate tax avoidance using the environmental, social and governance (ESG) index as a mediating variable in G20 countries. Design/methodology/approach To test the direct and indirect effects between board characteristics and tax avoidance using structural equation model analysis, this study used a panel data set of 522 companies from G20 countries between 2015 and 2021. Findings The regression results show that ESG reporting mediates the relationship between the board of directors and tax avoidance in G20 countries. Practical implications The findings have some policy and practical implications that may help regulators improve the quality of transactions and achieve more efficient market supervision. They recommend that governments implement regulations and restrictions on corporate tax avoidance through board mechanisms in G20 countries. Social implications The paper enables information users to assess future growth opportunities by emphasizing the importance of ESG policies and board characteristics in evaluating companies. Originality/value Although previous literature has investigated the direct relationship between the board of directors and tax avoidance, the present work focused on considering the direct and indirect association between the board of directors and tax avoidance through the mediating effect of ESG reporting, which has not been widely used in ESG studies so far.

Corporate insider purchases and the options market: Competition among informed investors

Corporate insiders have superior access to information; their trades, particularly purchases, should be informative. However, the extent of their informational advantage may be limited by the presence of other informed market participants. We document less frequent insider purchases in stocks with relatively high options trading activity. These purchases are followed by negligible abnormal returns. In contrast, stocks with less active options trading experience more frequent insider purchases, which yield positive abnormal returns over the subsequent six months. Our novel approach highlights the options market's role in screening uninformed insider trades, which ultimately contributes to more efficient stock market price formation.

Developing ukrainian enterprises using neural networks

The article explores the features of using neural networks for the development of Ukrainian enterprises. It examines the theoretical foundations of neural networks, their history, types, and examples of application in various industries. Special attention is given to analyzing the factors influencing enterprise development, such as technological innovations, economic conditions, organizational changes, competition level, and market conditions. It is shown that technological progress is a key factor in the development of enterprises in the modern world. The current state of development of Ukrainian enterprises is investigated in the context of adapting to new economic conditions, particularly during the war. The war in Ukraine significantly affects the economy, including the business sector. Internal challenges include political instability, economic reforms, workforce shortages due to mobilization, power outages, and the need for modernization of production facilities. External factors include global competition, the influence of international markets, and economic sanctions. Despite the challenging conditions, Ukrainian enterprises have growth opportunities through the implementation of the latest technologies, such as neural networks. The main challenges and opportunities for Ukrainian business are analyzed, and the directions for using neural networks for enterprise development are proposed for each development factor, considering the specifics of business operations in Ukraine. Specific examples of successful implementation of neural networks in the banking sector (PrivatBank), IT companies (SoftServe), and the agro-industrial complex (MHP) are provided. The article analyzes the advantages and disadvantages of using neural networks, such as increased efficiency, forecasting accuracy, service personalization, risk reduction, and challenges related to high costs, integration complexity, lack of qualified personnel, and data quality dependency. The prospects for enterprise development using neural networks are considered: productivity improvement, product and service quality enhancement, efficient resource management, risk reduction, innovative development, market adaptation, and resilience support. It is proven that the use of neural networks has significant potential for transforming enterprises, making them more efficient, flexible, and innovative.

Application of Stochastic Processes in Financial Market Models

This paper explores the significant role of stochastic processes in financial modeling, tracing the evolution from basic Brownian motion to sophisticated stochastic differential equations used in modern financial markets. Beginning with the historical development of Brownian motion, identified by Robert Brown and later mathematically modeled by Louis Bachelier for stock price fluctuations, the paper outlines its foundational influence on the Efficient Market Hypothesis and the random walk theory. The extension of these concepts in the Black-Scholes model for option pricing highlights the practical applications of these theories in predicting financial outcomes. The discussion progresses to geometric Brownian motion (GBM) and its crucial role in stock price modeling, emphasizing its use in Monte Carlo simulations for option pricing. The limitations of the Black-Scholes model and GBM in dealing with real market conditions such as stochastic volatility and jump-diffusion processes are addressed, showcasing the evolution of more complex models like the Heston model and GARCH. Interest rate models like the Vasicek and Cox-Ingersoll-Ross models are evaluated for their real-world applicability, particularly in scenarios of low and negative interest rates. This comprehensive review not only underscores the theoretical advancements in financial modeling but also its practical implications in contemporary financial markets.

From turbulence to resilience: A bibliometric insight into the complex interactions between energy price volatility and green finance

Given the growing concerns over climate change and energy price dynamics, this study provides a comprehensive bibliometric analysis of energy price volatility (turbulence) and the resilience of green financial markets. Using data from Scopus from 1994 to October 2023, we employ performance analysis, science mapping, and thematic analysis through bibliometric study. Efficient Market Hypothesis (EMH), Game Theory, Dynamic Capabilities, and Resource-based view provide solid theoretical foundations for understanding these dynamics. Our findings reveal four critical themes: sustainable development in the green energy sector, technological innovations and renewable energy integration, economic foundations and investment dynamics in green financial markets, and environmental impact and policy influence. The analysis highlights the pivotal role of green finance in mitigating energy market fluctuations and promoting sustainable development. Policymakers and practitioners should leverage innovative green financing strategies to enhance economic resilience and drive long-term sustainable development. We propose thought-provoking questions to guide future research on these themes.