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The purpose of this paper is to investigate the impact of the frequency of information acquisition on the frequency of stock trading. The authors also examined if the Big Five personality traits of investor influence the association between information acquisition and stock trading behavior.

The authors adopted NEO Five-Factor Inventory (Costa and McCrae, 1989) inventory to measure the Big Five personality traits of investors and examined the data collected from 541 individual investors of the Chinese stock market. To overcome the potential endogeneity bias, the authors followed two-stage least square method for estimating endogenous covariate by employing instrumental variable analysis. The authors performed probit regression to evaluate the moderating influence of investor personality traits on the association between information acquisition and stock trading behavior. The authors also performed several other tests to check the robustness of the key findings.

This research confirmed the previous findings that the more frequently investors acquire information, the more often they trade in stocks. Moreover, the authors added to the existing literature by providing empirical evidence that the Big Five personality traits moderate the relationship of information acquisition with stock trading behavior. Information acquisition tends to increase stock trading frequency in investors with conscientiousness, extraversion and agreeableness traits. On the other hand, it also has the tendency to decrease the intensity of stock trading in investors with openness and neuroticism traits.

The theoretical model in this study seeks to explain that the psychological factor, namely, investor personality, influences the way an investor interprets signals from information which in turn influences the investor decision to trade in securities. This research suggests that psychological characteristics of investors can be of relevance for policy makers in their attempts to improve their business in the financial services industry.

This study combines both information search literature and behavioral finance literature to investigate whether or not the information acquisition that relates to investors’ asset allocation decisions is influenced by investor personality. The study offers new theoretical insights into investors’ behavior due to the characteristics of the Chinese stock market which are uniquely different from other stock markets in the world. No previous study has been conducted so far in the Chinese stock market to explore variations in the impact of investors’ information acquisition on their stock trading by the Big Five personality and this paper strives to fill this research gap.

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.

The purpose of this paper is to investigate the role of financial advice on investor trading behavior by analyzing the influence of advisor personality.

The study utilized the Big Five personality framework from Costa and McCrae (1992) to measure personality traits of advisors and examined the data collected from 314 stock investor–advisor dyads. Personality traits of advisors were measured by the NEO-Five Factor Inventory (Costa and McCrae, 1989). Confirmatory factor analysis was conducted to assess the fitness of the Big Five model. We followed two-stage least square method for estimating endogenous covariate by employing instrumental variable analysis. Probit model was used to evaluate the moderating influence of advisor personality traits on the association between the usage of financial advice and trading behavior.

The authors found that financial advice positively impacts investors’ stock trading frequency. The authors also provide empirical evidence that financial advice is more likely to increase trading frequency when advisor personality tends to be openness, conscientiousness and agreeableness. On the other hand, information acquired from financial advisors causes fewer adjustments in investors’ portfolios when the personality of advisors is likely to be extraverted and neurotic.

The theoretical model in our study seeks to explain that a psychological factor, namely, advisor personality, influences the way an investor interprets information signals from financial advice, which, in turn, influences the investor’s decision to trade in securities.

This research suggests that characteristics of advisors other than those of investors can be of relevance for policy makers in their attempts to improve their business in the financial services industry.

Survey-based studies in finance are lacking. This study adds to the existing literature of behavioral finance that accounts for the observed variations in investors’ financial decision making explained by psychological factors. No previous study has been conducted so far exploring variations in the impact of financial advice on investors’ stock trading behavior by the Big Five advisor personality, and this paper strives to fill this research gap in Chinese stock market.

The purpose of this paper is to investigate the impact of the key sources of information, namely, financial advice, word-of-mouth communication and specialized press, on trading behavior of Chinese stock investors. The study also analyzed if the association between the key sources of information and trading behavior is influenced by investor personality.

The authors adopted the Big Five personality framework and examined the survey results of individual stock investors (n=541) in China. Personality traits of investors were measured by the NEO-Five Factor Inventory (Costa and McCrae, 1989). The authors performed probit regression analysis to evaluate the moderating influence of investor personality traits on the association between sources of information and stock trading behavior.

The results of the study confirm the previous findings that the key sources of information used by investors as a foundation of their financial choices have a significant influence on their trading behavior. The study also provides empirical evidence that investor personality traits moderate the relationship between the key sources of information and trading behavior. Financial advisors tend to increase the frequency of trading in investors with openness, extraversion, neuroticism and agreeableness personality traits, and tend to decrease the intensity of trading in investors with conscientiousness trait. On the other hand, financial information acquired from word-of-mouth communication is more likely to enhance trading frequency in extraverted and agreeable investors, and is more likely to reduce trading frequency in investors with openness, conscientiousness and neuroticism traits. Finally, the use of specialized press leads to more adjustment in portfolios of the investors with openness and conscientiousness traits than those with other personality traits. An alternative mediated model was not supported.

This research contributes to information search literature and behavioral finance literature and provides empirical evidence that the psychological characteristics of investors are significant predictors of the variations in information-trading link. The study offers new theoretical insights of investors’ behavior due to the characteristics of Chinese stock market which are unique from other stock markets in the world. To the authors’ best knowledge, no previous study has been conducted so far in Chinese stock market to explore variations with regards to the impact of the key sources of information on trading behavior by the Big Five investor personality and this paper seeks to fill this gap.

The rapid change of technology has significantly affected the financial markets in Thailand. In order to enhance the market efficiency and liquidity, the Stock Exchange of Thailand (SET) has granted Thai stock brokers permission to develop and offer their customers algorithm and automatic stock trading. However, algorithm trading on SET was not widely adopted. This chapter intends to design and empirically estimate a model in explaining Thai investors’ acceptance of algorithm trading. The theoretical framework is based on the theory of reasoned action and technology acceptance model (TAM). A sample of 400 investors who have used online stock trading and 300 investors who have used algorithm stock trading were observed and analyzed using structural equations model (SEM) and generalized linear regression model (GLM) with a Logit specification. The results confirm that attitudes, subjective norm, perceived risks, and trust toward algorithm stock trading are factors determining investors’ behavior and acceptance of using algorithm stock trading. Investor’s perception and trust on algorithm stock trading as a trading strategy is a major factor in determining their perceived behavior and control, which affect their decision on whether to invest using algorithm trading. Accordingly, it can be concluded that Thai investors is willing to accept algorithm trading as a new financial technology, but still has concern about the reliability and profitable of this new stock trading strategy. Therefore, algorithm trading can be promoted by building investors’ trust on algorithm trading as a reliable and profitable trading strategy.

This paper aims to investigate the impact of sources of information on trading behavior by analyzing the influence of investor personality in Chinese futures market.

The authors adopted the Big Five personality framework and examined the survey results of individual investors (n = 333) in Chinese futures market. Personality traits of futures investors were measured by the NEO-Five Factor Inventory (Costa and McCrae, 1989) which is a shortened version of revised NEO personality inventory of the Big Five model (Costa and McCrae, 1992). Confirmatory factor analysis was conducted to assess the fitness of model. Structural equation modeling was used to evaluate the moderating influence of investor personality traits on the association between source of information and trading behavior.

The results confirm the previous findings that the sources of information used by investors as a foundation of their financial choices have a significant impact on trading frequency. The authors also provide an empirical evidence that investor personality traits moderate the relationship between sources of information and trading behavior. Financial advice from professionals is likely to increase trading frequency in investors with neuroticism and openness personality traits, and to reduce trading frequency in conscientious and extravert investors. Similarly, financial information acquired via word-of-mouth communication results in more trading in extravert and agreeable investors. Finally, information acquisition from specialized press causes more adjustment of conscientious investors’ portfolios. Theoretical explanations, implications and recommendations for future research are discussed.

This study combines information search and behavioral finance literature to demonstrate that the impact of various sources of market information on asset allocation decisions is influenced by investor personality. No previous study has been conducted yet to explain variations in the impact of sources of information on trading behavior by the Big Five personality traits and this paper seeks to fill this gap in Chinese futures market.

We investigate institutional investors’ trading behavior of acquiring firm stocks surrounding merger activities for the period 1992–2001. We label investment companies and independent investment advisors as active institutions and banks, nonbank trusts, and insurance companies as passive institutions. We analyze the trading behavior of active and passive institutions surrounding merger announcements and their eventual resolution. Our results indicate that active institutions significantly increase their holdings of acquiring firm stocks for mergers with higher announcement period abnormal return and this increase is more pronounced for stock mergers than cash mergers. Active institutions display preference for stock proposals at the merger announcement on the basis of their prior beliefs and this is explained by the “overreaction phenomenon.” However, they update their beliefs between announcement and final resolution as more information arrives into the market. Finally, active institutions appear to correct their overreaction behavior by displaying their greater preference for cash proposals as compared to stock proposals at the quarter of eventual outcome. The trading behavior of passive institutions suggests that these institutions disregard the market response of merger announcement in trading acquiring firm stocks at the announcement quarter. The passive institutions gradually update their beliefs and utilize the information released at the announcement in rebalancing their portfolios at the final resolution.

The purpose of this paper is to analyze the trading behaviors of retail investors and investigate their impacts on stock returns.

As retail investors are considered as the main noise traders in the capital market, using the trading records of Chinese retail investors from 2005 to 2009, the authors study their trading preferences and the correlation of their trades. Then, they use a multifactor model to test whether the co‐movement of stock returns could be explained by individual sentiment.

The authors' results show that the small‐cap stocks are obviously preferred by retail investors. Meanwhile, the net stock demands of retail investors are systematically correlated, even when the effect of market risk is excluded. In the perspective of the net stock demands, the authors use BSI to measure the individual sentiment, finding that individual sentiment plays an important role in the formation of the cross‐section of stock returns. However, the authors' results imply that BSI is a reverse indicator to predict the future returns, which implies that the trading behaviors of retail investors are irrational.

Consistent with behavioral theory, the authors' findings support the viewpoint that stock returns could be affected by the systematic correlated trading of retail investors. To some extent, their findings highlight the need to know more details of individual investors' trading behaviors through which the fluctuations of asset prices can be better understood.

The purpose of this paper is to examine whether the futures volatility could affect the investor behavior and what trading strategy different investors could adopt when they meet different information conditions.

This study introduces a two‐period overlapping generation model (OLG) model into the future market and set the investor behavior model based on the future contract price, which can also be extended to complete and incomplete information. It provides the equilibrium solution and uses cuprum tick data in SHFE to conduct the empirical analysis.

The two‐period OLG model based on the future market is consistent with the practical situation; second, the sufficient information investors such as institutional adopt reversal trading patterns generally; last, the insufficient information investors such as individual investors adopt momentum trading patterns in general.

Investor trading behavior is always an important issue in the behavioral finance and market supervision, but the related research is scarce.

The conclusion shows that the investors' behavior in Chinese future market is different from the Chinese stock market.

This study empirically analyzes and verifies the different types of trading strategies investors could; investors such as institutional ones adopt reversal trading patterns generally; while investors such as individual investors adopt momentum trading patterns in general.

The purpose of this paper is to investigate if earnings management affects the trades of different investors prior to earnings announcements.

Using a unique account-level trading data set from the Chinese stock market, the author investigates the different investor trading patterns prior to earnings announcements.

The author obtains direct evidence to show that: first, institutional investors, particularly active ones, tend to sell (buy) stocks before negative (positive) earnings surprises; second, institutional investors buy stocks intensively with the lowest earnings management and the highest earnings surprises, and the trading patterns are primarily driven by active institutions. No significant trading pattern is observed on the stocks with negative earnings surprises; and third, the author uses a natural experiment in accordance with the Chinese accounting standards reform to address endogeneity, and the causality of the results still holds.

The findings provide clear evidence by emphasizing the importance of earnings management in the formulation of investor decisions.