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The purpose of this paper is to identify factors that influence the intention to use internet stock trading among investors in Malaysia.

A structured questionnaire was used to collect data from investors who are aware of internet stock trading in Malayisa. Out of 300 questionnaire only 144 were usable.

Findings show that attitude, subjective norm and perceived behavioral control has a direct positive relationship towards behavioral intention to use internet stock trading. The theory of planned behavior can be used to explain variation in behavioral intention and actual usage.

More variations of results could be gained through a wider coverage of respondents. Other factors such as descriptive norm and perceived usefulness should be used to increase the explanatory power of the dependent variable. A comparison of the same study of explanatory power between other intention‐based model could give another valuable contribution.

This study will provide information on factors that influence and affect investor's intention to use online stock trading. In addition, the result of the study could serve as a guideline by online stock broking organizations in understanding the factors and program that need to be instilled to increase online stock trading among current retail investors and future investors.

Not much has been written on understanding intention to use internet stock trading in a developing country.

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.

Aim of the present monograph is the economic analysis of the role of MNEs regarding globalisation and digital economy and in parallel there is a reference and examination of some legal aspects concerning MNEs, cyberspace and e‐commerce as the means of expression of the digital economy. The whole effort of the author is focused on the examination of various aspects of MNEs and their impact upon globalisation and vice versa and how and if we are moving towards a global digital economy.

On 6th September, 2000 the SEC issued a press release accusing 33 companies and individuals of fraudulently using the Internet to make more than $10m in illegal profits by driving up the prices of more than 70 small stocks. The companies and individuals, including a bus mechanic, a car service driver and a self‐chilling can company, boosted the total market value of these stocks by $1.7bn, claimed the SEC, in announcing 11 civil fraud lawsuits filed in federal courts. ‘What used to require a network of professional promoters and brokers, banks of telephones and months to accomplish can now be done in minutes by a single person using the Internet and a home computer,’ SEC enforcement director Richard H. Walker said. Two weeks later, the SEC announced that it had settled an enforcement proceeding brought against a 15‐year‐old stock trader who, operating from a computer in a bedroom in his parents' home, had earned more than $270,000 in profits over a six‐month period by engaging in classic ‘pump and dump’ market manipulation of small over‐the‐counter stocks.

This paper investigates the effects of different uncertainties on Internet stock trading (IST) adoption intentions of individual investors in China and aims to determine the interaction effects of trust and perceived benefits in the relationship between uncertainty dimensions and IST adoption intentions.

Using a structured questionnaire, a survey of 353 experienced stock traders was conducted in China. The proposed uncertainty-trust-perceived benefits framework was examined through structural equation modelling using Smart PLS 3.0.

The study found significant negative effects of perceived technology uncertainty, perceived regulatory uncertainty and perceived information asymmetry on the IST adoption intentions of individual investors. Perceived service intangibility was found to have only insignificant effects on IST adoption intentions. In terms of interaction results, trust significantly moderates the relationship between IST adoption intentions and, respectively, perceived technology uncertainty and perceived information asymmetry. Similarly, perceived benefits significantly moderate the relationship between intentions to adopt IST and both perceived technology uncertainty and perceived regulatory uncertainty.

The regulators for IST development in China could utilise the results of this study as guidelines for strategies to increase the use of IST among existing and potential investors.

Using social cognitive theory, this research investigates the effects of various uncertainties on IST adoption intentions of individual investors in China; these effects have not been explored by previous literature. Furthermore, few studies other than this one have investigated the interaction effects of factors which counteract the negative effect of other factors.

The authors investigate the extent to which online talk can influence contemporaneous and future stock trading, especially when market news is unpresented.

The authors propose an improved sentiment formula incorporating online hype, neutral sentiment and poster reputation. In addition, they conduct event study, OLS regression analyses and probit models.

First, investors tend to be more talkative in relation to firms that are (1) smaller size, (2) more growth-like, (3) with lower prices and higher short interests and (4) of higher beta. Second, the bullish tone of investors positively affects the abnormal returns of small-capitalization stocks. However, online talk has little impact on large-capitalization stocks, except that more postings boost trading liquidity. Third, online talk predicts the presence of future news regardless of firm size, with stronger predictive power found for small-capitalization stocks.

It is of interest to practitioners and researchers to study online talk so as to better understand the trading psychology of retail investors and the effects on the stock market. Furthermore, policymakers are interested in tracking activities on stock message boards in order to prevent security fraud and protect investors' interests.

The results are robust and suggest that online talk has significant impacts on stock trading exploiting an information asymmetry. This study of stock message board posting activities helps researchers to understand whether message contents contain valuable and unique content compared with information available via more traditional media channels.

This article empirically examines whether the ratio of research and development (R&D)spending to sales and marketing spending has an impact on the valuation of Dot Com companies. These companies are currently trading in today’s stock market. Previous research has not been able to link the lofty market value of Dot Com companies to a distinguishable trait. Many theories have been proposed without empirical findings to support them. We find those Dot Com companies with higher ratios of R&D spending are more likely to have higher stock market values in the subsequent year than those with lower ratios. A sensitivity test shows that the results are qualitatively the same even after market correction of high‐tech stock.

The purpose of this paper is to evaluate the profitability of technical trading relative to buy-and-hold (BH) strategy at firm level, controlling for firm size and trading volume.

This paper applies variable-length moving averages (VMAs) thoroughly to each and every stock listed on Taiwan Stock Exchange (TWSE) and computes the excess returns of technical trading relative to BH strategy. The samples are further grouped by firm size and trading volume. Furthermore, possible data snooping bias is investigated by employing Hansen’s (2005) Superior Predictive Ability tests.

The result shows that VMAs outperform the BH strategy. The profitability of VMAs, remarkably, is positively associated with size and trading volume. After correcting for data snooping bias, VMAs with longer moving averages outperform VMAs with shorter moving averages. The evidence suggests that size and volume information is accountable for trend projection.

Unlike past studies simply applying technical trading rules to market indices, portfolios, or selected stocks, this paper evaluates the profitability of technical trading by applying VMAs comprehensively to each and every individual stock listed on TWSE controlling for the effect of firm size and trading volume, providing more practical insights for trading individual stocks.

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.