Explore the evidence.
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Etkin Piyasalar Hipotezi ve Davran??sal Finans, finansal literatürün kar??t argümanlar? savunan iki temel modelini olu?turmaktad?r. Bunlardan ilki yat?r?mc?lar? rasyonel olarak kabul ederken di?eri ise yat?r?mc?lar? normal olarak ifade etmektedir. Etkin Piyasa Hipotezi’ne göre piyasalar bilgisel olarak daima etkindir. Hisseler en nihayetinde denge fiyat?na ula?acakt?r. Ya?anan finansal krizler ise k?sa dönemli düzeltme hareketleridir. Davran??sal finans, alternatif bir model olarak geli?tirilmi?tir. Buna göre yat?r?mc?lar farkl? bilgilere farkl? zamanlarda ula?maktad?r ve onlar? farkl? de?erlendirmektedir. Yat?r?m kararlar? psikolojik ve duygusal faktörlerden etkilenmektedir. Yat?r?mc?lar?n makine olarak görülmesi kabul edilemez. Davran??sal finans çok daha yeni bir konumdad?r ve çok say?da yeni çal??maya ihtiyaç duymaktad?r. Bununla birlikte iki teori aras?ndaki çat??ma yeni finansal krizlerin önlenmesi aç?s?ndan çok önemlidir. Yak?n gelecekte teorilerin kar??t olmaktan ziyade tamamlay?c? olarak kullan?lmas? beklenmektedir.   

This study aims to determine the effect of six-factor (market return, firm size, value, profitability, investment, human capital) on excess return in companies with shares listed in LQ45 for the 2015-2019 period. The population of this study consists of 45 LQ45 companies listed on the Indonesia Stock Exchange (IDX). The purposive sampling method is the sample selection method that is used in this study. As a result, it shows that there are 26 companies that fit the criteria and taken as samples. Furthermore, the data analysis method that is used in this study is the panel data regression model. Based on the results of this study, it is showed that partially, market return (X1), firm size (X2), profitability (X4), and investment (X5) have a significant positive effect on the excess return of companies listed in LQ45 for the 2015-2019 period. Whereas, value (X3) and human capital (X6) do not have a significant effect on the excess return of companies listed in LQ45 for the 2015-2019 period partially. Another result also shows that simultaneously or as a whole, six-factors (market return, firm size, value, profitability, investment, human capital) have a significant effect on the excess return of companies listed in LQ45 for the 2015-2019 period.

The purpose of this article was to assess the impact of financial market liquidity on international capital flows in emerging markets. Specifically, the research investigates the effect of bond market liquidity and stock market liquidity on foreign portfolio investments using data for five emerging African countries, being Egypt, Kenya, Mauritius, Nigeria and South Africa, for the period 2000 to 2020. The data was sourced from the Bloomberg and World Bank (WDI) databases. Panel data analysis (fixed effects model) was undertaken using three different liquidity measures: the effective spread; Amihud’s (2002) illiquidity measure; and market impact as measured by trading volume. Our findings revealed mixed results. It was found that stock market liquidity attracted foreign portfolio investments. Although bond market liquidity, as measured by the volume of trade, promoted foreign portfolio investment, it was different for the effective spread, as the higher the effective spread, the higher the inward FPI flows, and vice versa. Results on the effects of the bond effective spread on FPI show that as long as the bonds are above the investable grade, investors are not discouraged by the cost of trading. Our findings thus confirm that FPI inflows are predisposed on liquid and efficient host country financial markets. Further, the entrance of foreign investors in the host country’s domestic financial markets, leads to the enhancing of liquidity in the local market, thus increasing risk sharing between local and foreign investors.

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

This study tests for the applicability of the Adaptive Market Hypothesis (AMH) and Bounded rationality theories on the Johannesburg Stock Exchange (JSE). This is in order to determine the influence of behavioural risk factors on the efficiency of the stock market. Behavioural theories show a gap in the theory of Efficient Market Hypothesis. Using quantile regression, our study established the applicability of the Adaptive Market Hypothesis on the JSE. Past market returns were shown to be significant in predicting future returns and thus did not follow a random walk. The lagged return increased at higher quantiles and differed with changes in market conditions (i.e. pre-financial crisis, financial crisis and post-financial crisis).  Thus, the predictability of returns varies with a change in market conditions. This paper is focused on only on the Johannesburg stock exchange in South Africa, more specifically the movement is the all share index. The findings should be able to be applied to emerging and developed economies. Business confidence is found to have a negative relationship with returns showing a lag in time for sentiment to be incorporated in prices. In contrast, consumer confidence is found to have a positive relationship with returns. In summary, investors are shown to be influenced by fundamental and behavioural factors.

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.

This paper investigates whether personality traits, affects, and anticipated emotions measured before a stock market simulation explain participants’ trading style. The study relies on a sample of 133 undergraduate students from the University of Mons, Belgium, who participated in a four-hour CAC 40 trading simulation with a virtual portfolio of EUR 100,000. Regressions were estimated on several dimensions of trading style: number of transactions, minutes per order, average transaction size, average cash holdings, and portfolio volatility. The results show that psychological variables explain little of trading frequency or pacing but are informative about the structure of market exposure. Negative affect is associated with higher cash retention, whereas positive anticipated emotions are associated with lower cash holdings. Gender and openness also predict position size, while gender, age, and openness are significant predictors of portfolio volatility. Overall, the findings suggest that psychology explains less how much individuals trade than how they structure their market exposure.

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.