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Market participants usually seek exposure to global beta which are best achieved usually through large capitalization equities where higher idiosyncratic risk represents a potential source of alpha. This study empirically explored the persistence and drivers of idiosyncratic risk across the S&P 500, CAC 40, FTSE 100, DAX, and Nikkei 225 for a period of 20 years (2004 – 2024). Utilizing a quantitative risk decomposition framework, the analysis revealed a stark dichotomy where the S&P 500 exhibits minimal idiosyncratic risk, functioning as a proxy for global systematic factors. The Nikkei 225 was dominated by idiosyncratic risk which can be attributed to the unique domestic monetary policy. The European counterparts occupied a middle ground, with idiosyncratic risk amplified by sectoral concentrations. The correlation analysis further suggested a deep regional integration within the European markets and a diversification potential with the Japanese equity market. The findings challenged the notion that globalization has harmonized global financial market returns. These findings also demonstrates that idiosyncratic risk remains a significant and potentially compensable component of the concept of international investing, necessitating a strategic shift towards factor aware asset allocation.

Traditional asset pricing models assume rational investors and informational efficiency. However, persistent anomalies, and recurrent financial crises challenge these assumptions. This study synthesizes findings from leading international research to evaluate how cognitive biases shape asset prices and provides a comprehensive review and synthesis of behavioral asset pricing in international financial markets over a period from 2004 to 2024. Evidence from the extensive stock market data, cross-market behavioral heterogeneity and survey-based risk premia consistently demonstrates that behavioral effects are time-varying and regime-dependent. The findings indicate that behavioral heterogeneity intensifies during boom and bubble periods, diminishes during crashes, and generates predictable patterns in returns across asset classes and countries. Overall, the study re-iterates support for a dynamic behavioral asset pricing framework that integrates psychological factors into international financial market analysis.

This research investigates how the overall mood of investors influences the profits of the major commercial banks traded on the JSE. Although behavioural factors are increasingly acknowledged in financial markets, there is very little empirical evidence that investor sentiment has any impact on the South African banking sector, despite this sector being the main driver of financial stability and economic growth. This study investigated whether investor sentiment has a significant impact on bank stock returns in both the short and long term. The research period ranged from September 2008 to March 2025 and used monthly return data. The paper implements the Autoregressive Distributed Lag (ARDL) approach to illustrate immediate and long-term relationships between sentiment, macroeconomic variables, and bank performance. The findings demonstrate that investor sentiment is one of the significant factors influencing bank stock returns, but the effect varies between different banks. Sentiment, on average, tends to have a negative effect on the majority of banks in the long run, which means that in times of extreme optimistimism  are followed by those of overvaluation and subsequent correction. However, one bank revealed a positive return-sentiment relationship which suggests that characteristics unique to a specific bank can have a moderating effect on behavioural factors. The short-run outcomes indicate that bank stock returns are very reactive to changes in sentiment and macroeconomic shocks and at the same time, diagnostic tests for model reliability support these results. The paper contributes to behavioural finance literature by delivering fresh data derived from an emerging market and providing an answer to the problem of bank-level disaggregated analysis that has been neglected. In addition to the theoretical contributions, the results can be turned into actionable insights by investors, policymakers, and portfolio managers who will be reminded of the importance of including sentiment indicators in their bank performance assessment and risk management activities in the South African financial sector.

The Johannesburg Stock Exchange (JSE) is considered a cornerstone of the South African economy, with its size-based indices serving as critical benchmarks for passive investment and portfolio construction. Although macroeconomic variables affect stock returns, the existing literature has primarily relied on linear models which yield heterogeneous results and do not allow for the dynamic and changing structure of financial markets. Consequently, this study investigates the nonlinear, regime-dependent effects of key macroeconomic variables such as inflation, money supply, short- and long-term interest rates, GDP, and the real effective exchange rate (REER) on the returns of the JSE Fledgling, Small-Cap, and Mid-Cap indices. Utilizing monthly data from 2002 to 2024, the study employs a two-state Markov Regime-Switching which allows the study to endogenously address the changes in bull and bear market regimes. The most pressing finding is that the Real Effective Exchange Rate (REER) is a consistently positive driver of returns across all market conditions, while the influences of other variables, such as interest rates and GDP growth, are highly dependent on the market regime (bull or bear) and the specific index size. Finally, these findings lead us to conclude that the relationship between macroeconomic fundamentals and stock returns is not a constant phenomenon but rather is fundamentally dependent on the regime, lending strong support for the Adaptive Market Hypothesis. This insight is significant for investors and portfolio managers, underscoring the necessity of adaptive, regime-sensitive strategies for effective risk management and portfolio allocation on the JSE.

The Adaptive Market Hypothesis (AMH) allows for a re-evaluation of the relationship between macroeconomic variables and stock market returns, acknowledging that this relationship is time-varying and asymmetrical. This study investigates the impact of macroeconomic factors on the Johannesburg Stock Exchange (JSE) sector returns under varying market conditions from January 2008 to December 2024. Using a Markov regime-switching model, the findings show that macroeconomic effects on sectoral returns are regime-dependent and time-sensitive. In bullish markets, inflation growth has a significant negative impact on Industrial sector returns, but no significant effect during bearish regimes. For the Financial sector, inflation and money supply growth negatively affect returns, while the real effective exchange rate growth has a positive impact. In the Resource sector, all macroeconomic variables significantly influence returns during bearish conditions, with inflation growth showing a notable negative effect. Overall, JSE sector returns exhibit bull and bear market dynamics, and the influence of macroeconomic variables is neither uniform nor static aligning with the AMH framework.

Using a methodology from experimental finance based on qualitative analysis tools, this article aims at analyzing the potential existence of the ‘all that glitters attracts’ bias in order to explain the behavior of individual investors. For this purpose, we observed the investment strategies and behaviors of eight students in a continuous trading situation over three days. Using a fictional portfolio of 100,000 euros, the participants were given the opportunity to trade shares in companies from the CAC40 index (the 40 largest market capitalizations on the French market). Regarding the size of the companies in the index, we observe a high volume of information disclosed to the markets which could, to a certain extent, complicate the interpretation of the information signals sent. Based on trading journals - and more specifically the number of transactions carried out on specific stocks - we find that participants are strongly focused on companies that are closely followed by financial analysts and receive the most media coverage. To support our findings, we have also used a process of participative observation to collect first-hand experiences from participants during the experiment. The different elements collected suggest that the participants’ decision-making processes were largely influenced by the intensity of the companies’ communication and their presence in the information flows provided by the stock market websites. This conclusion leads us to believe that, in the mind of individual investors, marketing linked to the stock market life of companies seems to prevail over any informational content. In any case, in their decision-making process, the participants clearly selected shares that were in the spotlight, and so, depending on the context of analysis and the investigative tools used, we confirm the presence of an ‘anything that glitters attracts’ bias, a strong focus on available information and some herd effects. The contribution of this article is threefold: the analysis of a bias largely neglected by scientific studies in the financial field, the use of an innovative experimental protocol, and the use of methodological tools that provide an assessment of individuals' personal perceptions.

This study investigates the factors influencing investment decision-making within South Africa's financial markets, focusing on psychological, demographic, and external market elements. Drawing from Prospect Theory, the research reveals a deviation from traditional behavioral assumptions, highlighting that external market dynamics, rather than individual risk perceptions or demographic traits, predominantly guide investor behavior. Using a quantitative cross-sectional design, data were collected through structured questionnaires from 120 randomly selected South African investors aged 18 and older with market experience. Structural equation modelling assessed factors influencing risk perception and subsequently, investment behavior. The findings demonstrate that market-related variables significantly influence risk perception (? = 0.653, p < 0.001) and decision-making, aligning with the Efficient Market Hypothesis. In contrast to Prospect Theory's expectations, risk perception had no significant direct effect on investment choices (? = -0.009, p = 0.933). Cognitive biases and emotional influences exerted a moderate impact, while demographic characteristics, including gender, education, and experience, showed minimal influence on investment decisions, suggesting that practical market experience outweighs formal training. With robust construct validation (CR = 0.711 to 0.951), the study enhances the reliability and credibility of the findings. It highlights global regulatory frameworks as crucial for investor confidence. These results contribute to behavioral finance literature and support practical implications for policy, market transparency, and investor education. Future research should consider diverse populations and qualitative investors' perspectives.

With an observational research design, using only publicly available stock price data, this paper aims to demonstrate that momentum extends beyond the medium term (3 to 12 months) when generating momentum profiles using a preset term-structure. The optimal holding period is a function of the formation period – the longer the formation period, the shorter the holding period and vice versa. Convention has it that once a stock begins to gain momentum it usually maintains it for 15 months before faltering, reversing some gains after 18 months. A full momentum cycle (formation plus hold) should complete within 24 months, peaking at 18 months. A dataset of 370 stocks, listed on the Johannesburg Stock Exchange (JSE) between 2007 and 2024, was used to generate momentum profiles from daily historical prices. Profiling shifts the focus onto the holding period to classify momentum cycles on the eventual outcome. Cycles are classified as mini, regular, ultra, super and hyper, depending on duration. Clusters of momentum appear when generating profiles for individual stocks, allowing one to identify optimal entry and exit points into active momentum cycles. Results show that major cycles comprise many minor cycles. Medium-term momentum or regular cycles, therefore, may consist of several mini cycles. The main finding of this paper is that there is potential to remain in active cycles for several years, thereby holding momentum. A custom momentum index, updated weekly with variable members, may give some indication of the state of momentum in a market at a particular point in time as an increase in index levels tend to correspond with an increase in active momentum cycles or momentum activity.

The market resilience of a stock is an integral component of financial market because it supports smooth trading and absorb market shocks. However, the contention has always been to effectively determine the level of resilience in stocks with the application of proper methodology to make informed decisions. Therefore, aim of this study was to examine the level of market resilience in selected stocks in the Johannesburg stock exchange. Using a fixed effect model, the findings of this study indicates that most securities trading on the exchange lack market resilience. This was evident in the significant relationship between the specific independent and dependent variables. A risk coefficient should therefore be assigned to bid and ask to spread to enhance market resilience. These risk coefficients will induce the bid and ask prices to be close to the fundamental price.

The market tightness of equity securities is an integral component of financial market because it supports smooth trading and absorb market shocks. However, the contention has always been to effectively determine the level of tightness in equity securities with the application of proper methodology in order to make informed decisions. Therefore, aim of this study was to examine the level of market tightness in selected stocks in the Johannesburg stock exchange. Using a variance ratio model, the findings of this study indicates that most securities trading on the exchange lack market tightness. This was evident in the difference between the one, two and three months variances that were not equal to 1 . Therefore, a specialist system should be introduced in order to facilitate the execution of trades without significantly moving the prices of equity securities. This study improves the frontier of knowledge regarding liquidity management, by empirically investigating the market tightness of equity securities.

A recurring theme in the literature and discussion of stock market analysis is the concept of the January effect which essentially implies buy in December and sell in January. The January effect is based on the perceived seasonality trend where short term investors hope to take advantage of the arbitrage opportunity between December and January. However, this perceived anomaly continues is seen as a myth and has been strongly rejected by many market participants in the current dispensation. The purpose of this paper was to investigate the January effect in the Nikkei 225, JSE, CAC 40, DAX, and the NASDAQ Index from February 2019 to February 2024. A F-test statistics was used to explore the phenomenon. The findings indicated that there is no significant difference between the realised returns in January and those of the other month for the most recent five years. This led to the conclusion that, while the January effect may have been observed, it is no longer evident in financial markets, hence market participants should avoid using this type of arbitrage approach because it may result in massive losses

The efficient market hypothesis assumes that financial markets fully incorporate all available information, rendering past information irrelevant for predicting future prices. However, numerous studies challenge this notion and suggest the presence of long-term memory in market dynamics. Understanding long-term memory in financial markets has important implications for investors and policymakers. The aim of this study was to empirically investigate long term memory in financial markets. This study employed a Hurst model for a sample of 5 financial markets from June 1, 2018, to June 1, 2023. The findings revealed that four out of the five sampled financial market exhibits long term memory which challenges the efficient market hypothesis concept. Therefore, portfolio managers and active market participants can utilize long-term memory to optimize asset allocation decisions by considering the persistent effects of past returns and adjust portfolio weights to take advantage of potential return predictability and manage risk.

There has been a proliferation of numerous investment strategies over the years, but one strategy is perceived to have stood the test of time. Investing in the foreseeable future is favored by many successful long-term investors which focus on maintaining a long-term investment horizon. Investing in the long term involves purchasing assets and holding onto them for an extended period, regardless of short-term market fluctuations. Exploring the benefits of this method can help investors make informed selections and build a disciplined investment mindset to achieve their financial goals. The goal of this study was to empirically evaluate the merits of a purchase and hold strategy in financial markets because of its perceived considerable influence on active market players. A Sharpe ratio was utilized for six financial markets from June 13, 2018, to June 13, 2023. The findings revealed that market participants can achieve a sustainable return by simply maintaining a long-term view of their portfolios. This was evident in the Nasdaq, CAC 40 and Nikkei 225. Upon selecting a particular risk tolerance and investment horizon, market participants may earn significant returns on their portfolios.

Studies in behavioral finance have shown that human behavior often diverges from the rationality assumed by economists, as their decisions can occasionally be swayed by their emotional and psychological states. Given this concern, the study examines psychological factors influencing individual decision-making in the South African financial market. A structured questionnaire was used in collecting data from 414 participants who are individual investors actively involved in trading in the Johannesburg stock exchange market with the application of the random sampling method. The main objective of this study is to explore the psychological variables or biases that determine the investment decision-making of individual investors. Furthermore, this paper investigates psychological factors such as Anchoring, Herding, Overconfidence and Representative biases in investment decision-making. Findings revealed that all the variables, overconfidence, herding, anchoring and representative heuristics have a relationship with each other but the only variable that influences the individual investment decision is the representative heuristic while less consideration is given to another variable. The results of this study would help financial advisors understand the high importance of psychological factors and help them integrate behavioral insights into investment strategies. This will in turn help them provide better services to their clients. It will also help individual investors to acknowledge and understand the psychological factors influencing investment decisions and how to take note of them to make better decisions. Policymakers can consider the implications of psychological biases on market stability.

To date, there are many myths surrounding security selection and fundamental analysis due to the notion that all available information is perfectly priced in security. However, fundamental analysis is still very useful in determining the financial health of security, which is much needed for long-term investing. The aim of this study was to perform a valuation analysis of international stock markets so as to recommend buy or sell signals suitable for investment decisions. This study made use of the coefficients of a multiple regression analysis and value drivers for the S&P 500, Nasdaq, JSE, DAX, Nikkei 225, BIST 100, FTSE, and SSE as of January 23, 2023. The findings revealed that the JSE, DAX, Nikkei 225, and FTSE are undervalued, which translates to a buy signal, while the S&P 500, Nasdaq, BIST 100, and SSE are overvalued. These findings imply that investing in the JSE, DAX, Nikkei 225, and FTSE will produce decent capital gains on a risk-adjusted basis.

In the dynamic world of financial markets, the prices of assets can exhibit dramatic fluctuations, sometimes soaring to dizzying heights or plummeting to alarming lows. However, amidst the chaos, a fascinating phenomenon emerges: a tendency for prices to revert back to their long-term average or mean level. This concept known as mean reversion has intrigued traders, investors, and researchers for decades. Understanding mean reversion provides valuable insights into market dynamics, investor behavior, and the potential for profitable trading strategies. The aim of this study was to empirically investigate mean reversion in financial markets. This study employed a Hurst model for a sample of five financial markets from June 1, 2018 to June 1, 2023. The findings revealed that four out of the five sampled financial markets exhibit mean reversion, which challenges the efficient market hypothesis concept. Therefore, portfolio managers and active market participants can utilize long-term memory to optimize asset allocation decisions by considering the persistent effects of past returns and adjusting portfolio weights to take advantage of potential return predictability and manage risk.

The dynamics of investing in stock markets have changed considerably over the past twenty years. The value and growth investing concept has drawn much attention and continues to dominate portfolio management. Factor investing is an approach that aims at quantifying particular characteristics through matrixes of quality, value, momentum, and growth to improve the returns of a portfolio. Although the three-factor style of investing has gained widespread acceptance, the five-factor continues to be a source of disagreement among academics and industry practitioners. This study aimed to review the merits of five-factor investing critically. A critical literature review was used to review prior literature. The narratives from the literature reveal that the five-factor investing style will result in multiple sources of expected return. Hence, using five factors in portfolio formation has merits and will significantly improve the returns and most likely outperform the market portfolio. Factor premiums have proven to be drivers of asset return. Therefore, market participants and investment managers can intentionally assume additional exposures to deliver superior risk-adjusted returns compared to the market with the five-factor investing style. According to the author's knowledge, this is the first study to objectively analyze the literature on five-factor investing and propose that active managers can earn positive alphas on a risk-adjusted basis through factor exposures.

The debate on whether stock prices follow a random walk continues, becoming the foundation of modern portfolio theory. Supporters of the random walk theory still believe that modeling stock prices is a wasteful exercise. However, evidence from momentum pricing strategy and price reversals suggests otherwise. This study aimed to empirically explore the random walk theory in five international stock markets before and during the Covid-19 pandemic from June 30, 2017, to June 30, 2019, and January 1, 2020, to December 31, 2021. A multivariate runs test and a generalised distribution function was applied to investigate the theory. The results revealed no significant difference between the observed S-statistics runs and the expected ones, concluding that it is not common to observe random walks in financial markets consistently. Hence price changes in financial markets are significantly affected not only based on new information and investors’ expectations but also by irrationalities that exist among market participants. These irrationalities can be modeled using a generalised distribution function to produce price patterns.

The study intended to examine the effects of the information gap in the Dare es salaam stock exchange stock market. To meet this goal, three objectives were involved; the gap between the information offered by DSE and those needed by investors, the effects of the information gap on the trading in securities in DSE, and measures to apply to tackle the information gap in DSE. The study adopted a mixed research design. This method provides different types of information, such as detailed views of participants qualitatively and scores on instruments quantitatively, and when combined, they should yield the same results. The research was carried out in Dar es Salaam, the city of big investors in Tanzania, the head office of the Capital markets and Security Authority (CMSA), and the Dar es salaam stock exchange authority (DSE). Eighteen brokers and dealers were interviewed, and a questionnaire was distributed to 169 market dealers, brokers, custodians, nominated advisors, DSE employees, registered trustees, financial analysts, and customers to collect quantitative data. The data collection tools used were a questionnaire for quantitative data and an interview guide for qualitative data. Descriptive statistics, content analysis, and coding approaches were used to analyse and interpret data.

The Indonesia Stock Exchange has experienced high growth in its 32 years. The Composite Stock Price Index rose 1.012% in that period, or an average of 31.63% per year. This study analyzes the risk premium on the Indonesia Stock Exchange (IDX) in the last 32 years. In this study, we found the following facts. First, the risk premium at IDX is 2.24% per year if using annual data and 5.54% when using annualized monthly data. It seems that the risk premium in IDX is sensitive to the return calculation horizon used. Second, in the 1997-1998 economic and 2008 financial crises, the risk premium experienced a sharp decline but was followed by a sharp increase in the following months. Third, the macroeconomic variables of inflation and currency exchange rates significantly affect the risk premium, but the interest rate does not. The effect of macroeconomic variables on the risk premium is also sensitive to the horizon of the return calculation used. The results above are when using annual data. The three macroeconomic variables do not affect the risk premium when using monthly data.