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This article aims to examine how investor moods and aggressiveness differ in their state and influence investor stock market performance associated with the moon phase. The mechanisms and impact of full moon gravity on investor stock trading performance are explored through an experimental approach and econometrics model.

A time-series quasi-experimental study, using the full moon and new moon time periods, was coupled with a psychometric test of investors' behaviours, administered through an online survey, similar to a pre-post experiment. Confirmation of the results was achieved by using an econometric model, adopted from Dichev and Janes.

This research found that investor psychology is influenced by the full moon, but no effect was recorded during the new moon phase. Confirmed by the paired t-difference test, the small correlation, in addition to the quantitative model, the results show the full moon impacts market behaviour during its orbital phase. Consequently, the authors surmise that the full moon does influence investor cognition and emotion disarray, mood disorders, and aggressiveness, resulting in poor stock trading performance.

The need for an active investment strategy is the major implication of this study. During the full moon phase, investors tend to be more aggressive and moody and seek hedonic utility instead of the traditional economics utility, meaning that they tend to follow the sentiment of the market.

This paper fulfils an identified need to study how the full moon affects investor stock trading performance.

The purpose of this paper is to examine whether, and to what extent, specific personality traits drive investors’ trading behaviour.

This study investigates these assumptions in an innovative way by employing an integrated model and using structural equation modelling analysis to examine them simultaneously as they would occur in the complex real world environment.

The results provide strong evidence that these personality traits influence investors’ trading behaviour and stock trading performance. The most powerful relationships are found to be those between over-confidence and stock trading volume, frequency and performance.

To the best of the authors’ knowledge there is no any similar study. This paper is the authors’ original unpublished work and it has not been submitted to any other journal for reviews.

Are firms able to time the market? The purpose of this paper is to focus on the study of own stock trading, emphasizing both repurchase and resell operations on the open market as well as over the counter.

The authors use data on 37,997 own stock transactions from 2005 to 2015 of Euronext Lisbon listed firms. Following Dittmar and Field (2015), this paper uses relative transaction prices to ascertain the relative performance of own stock transactions, in the open market and over the counter.

Results show that firms can time both repurchases as well as resales. Firms repurchase (resell) at lower (higher) prices than those prevailing in the market. Moreover, market-timing ability proves to be higher after the bailout period and to be influenced by the own stock trading frequency. Trading on the open market allows for increased timing ability for own stock repurchasing and reselling activity. Finally, results show seasonal effects both in repurchase and resale performance. Also, more efficient but less valuable firms are more likely to be successful in timing the market.

The authors study both the repurchasing and the reselling activity of the same set of firms, of already issued stock, using high-frequency (daily) data. In addition, the authors study own stock trading both in the open market and OTC, and also study the impact of a major economic shift on the firms’ ability to time the market.

The purpose of this paper is to examine the effect of investors’ emotional state (mood) on their trading behaviour and performance.

A sample from a representative survey of 328 Greek individual investors has been used to empirically test the validity of the proposed associations. An iterative data collection process was followed, where individual investors had to complete a questionnaire every time they were trading in the Athens Stock Exchange, for a period of ten months. Exploratory factor analysis was first used to analyse the data set, followed by cluster analysis (to identify investor profiles based on differences in their mood).

Two clusters have been identified. The first cluster profile includes investors with high score of positive mood (thus, high energetic arousal and hedonic tone, low tense arousal and anger frustration), while the second profile consists of investors with negative mood (low energetic arousal and hedonic tone, high tense arousal and anger frustration). The comparison between the two profiles has shown that investors with positive mood achieve higher stock returns than investors with negative mood.

To the best of the authors’ knowledge there is no other similar study.

The main purpose of this paper is to investigate autocorrelation structure of stock and portfolio returns in a unique market setting of Saudi Arabia, where nearly all active traders are the retail individuals and the market operates under severe limits to arbitrage. Specifically, the authors examine how return autocorrelation of Saudi Arabian stock market is related to factors such as the day of the week, stock trading, performance on the preceding day and volatility.

The sample consists of the daily stock price and index data of 159 firms listed in Tadawul (Saudi Arabian Stock Exchange) for the period from January 2004 through December 2015. The methodology of Safvenblad (2000) is primarily used to investigate the autocorrelation structure of individual stock and index returns. The authors also use the Sentana and Wadhwani (1992) methodology to test for the presence of feedback traders in the Saudi stock market.

Results show that there is significantly positive autocorrelation in individual stock, size portfolio and market returns and that the last two are almost always larger than the first. Return autocorrelation is negatively related to firm size. Interestingly, return autocorrelation is positively related to trading frequency. For portfolios, autocorrelation of returns following a high absolute return day is significantly higher than that following a low absolute return day. Similarly, return autocorrelation during volatile periods is generally larger than that during tranquil periods. Return correlation between weekdays is usually larger than that between the first and last days of the week. Overall, the results suggest that the possible reason for positive autocorrelation in stock returns could be the presence of negative feedback traders who are engaged in frequent profit-taking activities.

This is the first paper that thoroughly investigates the autocorrelation structure of the returns of the Saudi stock market using both index and individual stock returns. As this US$583bn (as of August 21, 2014) market opened to foreign institutional investors in June 2015, the results of this paper should be of significant value for the potential uninformed foreign investors in this relatively lesser known and previously closed yet highly prospective market.

The purpose of this study is to investigate the influence of mobile applications on investment decisions by retail investors in stocks and mutual funds. This study focuses on how mobile technologies are applied on mobile apps by retail investors for e-trading in emerging financial markets.

The study explored predictive relevance for the adoption behavior of retail investors under the Unified Theory of Acceptance and Use of Technology (UTAUT) framework. Further, goal contagion theory was applied to investigate the adoption behavior of investors towards e-trading. An adapted questionnaire was used to collect the date from April to June 2021 and data analysis was performed on 507 usable responses. The methodology adopted in this study is variance based partial least square structural equational modelling (PLS-SEM). Additionally, the study explains important and performing constructs based on the response of retail investors towards mobile app usage for investment decisions.

The study shows that effort expectancy, performance expectancy followed by perceived return were the primary determinants of behavioral intentions to use mobile applications by retail investors for e-trading. Further, habit of investors determined the adoption behavior of investors towards mobile apps. Additionally, the study revealed that perceived risk is not an important aspect for retail investors in comparison to perceived return.

The study in future can address to the aspect of personality traits of retail investors for technology adoption for investment decisions. Further investigation is required on addressing unobserved heterogeneity of retail investors towards technology adoption process in emerging financial markets.

The study provides theoretical and practical implications for retail investors, financial advisors and technology companies to understand the behavioral pattern and mobile apps adoption behavior of retail investors in emerging financial market. The findings in the study will help broking firms to sensitize their clients for effective use of their respective mobile apps for e-trading purposes. The study will strengthen the knowledge of financial advisors to understand investment behavior of retail investors in emerging financial markets.

This study unfolds a novel framework of research to understand the technology adoption pattern of retail investors for e-trading by mobile applications in emerging financial markets. The present study provides significant understanding in the domain of technology adoption by retail investors under behavioral finance environment.

This study is a pioneer in the academic literature to investigate the relationship between Valentine’s Day and stock market returns of major economies around the world.

Specific control variables for Valentine's Day are introduced to eliminate the potential influence of other effects.

The findings indicate that stock returns are higher on the days when Valentine's Day is approaching than on other days for most cases, showing “the Valentine Effect” in the stock market.

Unlike other holiday effects in the previous literature, the Valentine's Day effect cannot be explained by many conventional theories, such as tax-loss selling and the inventory adjustment hypothesis.

This paper aims to investigate Chinese bull and bear markets. The Chinese stock market has experienced a long period of bear cycle from early 2000 until 2006, and then it fluctuated greatly until 2010. However, the cyclical behaviour of stock markets during this period is less well established. This paper aims to answer the question why the Chinese stock market experienced a long duration of bear market and what factors would have impacted this cyclical behaviour.

By comparing the intervals of bull and bear markets between stocks and indices based on a Markov switching model, this paper examines whether different industries or A- and B-share markets could lead to different stock market cyclical behaviour and whether firm size can determine the relationship between the firm stock cycles on the market cycles.

This paper finds a high degree of overlapping of bear cycles between stocks and indices and a high level of overlapping between the bear market and a fraction of stock with increasing stock prices. This leads to the conclusion that the stock performance and trading behaviour are widely diversified. Furthermore, the paper finds that the same industry may have different overlapping intervals of bull or bear cycles in the Shanghai and Shenzhen stock markets. Firms with different sizes could have different overlapping intervals with bull or bear cycles.

This paper fills the literature gap by establishing the cyclical behaviour of stock markets.

Several studies and research related to event study and terrorist bombing acts have different conclusions. Moreover, research on terrorist bombings worldwide has never been conducted. Hence, this research aims at examining the impact of terrorist bombing using the abnormal return variables by looking at all bombings around the world in the past 10 years. This research uses a paired t-test by looking at the abnormal return before, during, and after a bombing act. Results show no significant difference between the abnormal return before, during, and after bombing acts.

Investors' behavior in financial markets is often under the influence of various psychological and cognitive factors, as well as personality characteristics. This research explores which behavioral factors and personality traits affect investment decisions and, consequently, investment performance.

A survey analysis was conducted on a sample of 310 investors in Croatia. Partial least squares structural equation modeling was used to obtain the results.

Overconfidence heuristic, prospect theory elements, emotions and stability and plasticity (as big two personality dimensions) positively affect investment decisions, while herding has a negative effect. Investment decisions, observed through the preference for long-term investments, consequently have a positive effect on the investment performance satisfaction.

This research proposes a unique comprehensive model of the effect of numerous different cognitive and psychological behavioral factors on investment decisions. Furthermore, the influence of investment decisions on investment performance is observed simultaneously. Understanding human behavior based on their personal characteristics can help investors to make better investment decisions. Advisors can learn from human behavior and guide their clients in the right direction when it comes to stock investment. Scientists will be able to replicate the model with other data and make comparative analyses.