PENGARUH INTERNET FINANCIAL REPORTING, TINGKAT PENGUNGKAPAN INFORMASI BERBASIS WEBSITE, DAN JUMLAH SAHAM BEREDAR TERHADAP FREKUENSI PERDAGANGAN SAHAM

The objectives of this study are: (1) to prove, test, empirically and analyze the impact of Internet Financial Reporting on Stock Trading Frequency, (2) to prove, test, empirically and analyze the impact of the Website-Based Information Disclosure Level on Stock Trading Frequency, (3) Testing, proving, by empirical means and analyzing the impact of the Number of Outstanding Shares on the Trading Frequency of Shares. This study uses quantitative methods using secondary data taken from the company's website and the IDX through www.idx.co.id in 2016-2018. In this study, we will use data analysis techniques with multiple linear regression with the help of SmartPLS 3.29. The results of this study show that (1) "Internet Financial Reporting" has no effect on Stock Trading Frequency, (2) Website-Based Information Disclosure has no effect on Stock Trading Frequency, (3) Number of Outstanding Shares has no effect on Stock Trading Frequency. The implications of this research are paying attention to financial information in the company that is listed through the website then investors can predict future financial performance and prospects and can make decisions related to investment decision making, by uploading and updating information owned by the company can provide education to the public. users and prosper the company. The high and low level of disclosure of company website information will have a small impact on the impact of disclosure on investor decisions. In addition, taking into account factors other than the number of outstanding shares, such as fundamental factors and stock prices, can attract investors to invest in the company, because basically investors in buying shares must choose liquid shares.

Investor memory of past performance is positively biased and predicts overconfidence

We document a memory-based mechanism associated with investor overconfidence. In Studies 1 and 2, investors were asked to recall their most important trades in the recent past and then reported investing confidence and trading frequency. After the study, they looked up and reported the actual returns of these trades. In both studies, investors were biased to recall returns as higher than achieved, and larger memory biases were associated with greater overconfidence and trading frequency. The design of Study 2 allowed us to separately investigate the effects of two types of memory biases: distortion and selective forgetting. Both types of bias were present and were independently associated with overconfidence and trading frequency. Study 3 was an incentive-compatible experiment in which overconfidence and trading frequency were reduced when participants looked up previous consequential trades compared to when they reported them from memory.

IS BITCOIN IMMUNE TO THE COVID-19 PANDEMIC?

This study examines how Bitcoin’s trading characteristics react to the COVID-19 pandemic, using detailed futures trading data from the Chicago Mercantile Exchange. The results show that volume-weighted Bitcoin futures return responds positively to the spikes of public interest. Meanwhile, the surges of pandemic information do not harm market quality. Volume, bid-ask spread, and trading frequency remain stable, indicating that the positive price reaction is not a result of a few small uninformed trades. Bitcoin's conditional beta on the S&P 500 index drops to near zero, while the conditional beta on gold more than doubles. These results indicate that traders have been using Bitcoin as a safe-haven asset after the pandemic outbreak.

ROLE OF REGRET AVERSION AND LOSS AVERSION EMOTIONAL BIASES IN DETERMINING INDIVIDUAL INVESTORS’ TRADING FREQUENCY: MODERATING EFFECTS OF RISK PERCEPTION

Purpose: This study aims to investigate the moderating effect of risk perception on the relationship among emotional biases (i.e., regret aversion and loss aversion) and the trading frequency of individual investors in the context of the Pakistan Stock Exchange (PSX). Approach / Methodology: This study is conducted under the philosophical assumptions of the positivist paradigm and the approach is deductive. The convenience sampling technique is used for sample selection of registered individual investors on the database of PSX. This led the study towards designing a cross-sectional study. Furthermore, 384 questionnaires are used for the collection of primary data from a population of 0.22 million registered PSX individual investors. The direction and degree of relationship among variables of concern are analyzed by the multiple linear regression techniques. The structural Equation Modelling (SEM) technique is used for authentication of moderation results. Findings: The results depict that regret aversion and loss aversion have statistically significant and negative impacts on individual investors’ trading frequency. Whereas, risk perception has an insignificant & positive impact on individual investors’ trading frequency. Moreover, risk perception is found to moderate the relationship between these two emotional behavioral biases. Originality/Value: This current study is a pioneer in developing links between individual investors’ trading frequency, loss aversion, regret aversion, and risk perception. The article also contributes to the literature of behavioral finance, specifically while understanding the role of emotional biases in investment strategies. So, this article engenders the reader's thoughtfulness to find plausible explanations in minimizing the impact of emotional biases in trading frequency and decision-making of individual investors. Implications: This study implies that emotional biases and risk perception cause and moderate the magnitude of the trading frequency of individual investors. The regulatory bodies such as the Securities and Exchange Commission of Pakistan (SECP) and PSX can launch training programs for individual investors to train them in coping up with such emotional biases and risk perception. This might result in the enhancement of the market capitalization of the stock market.

What Drives Excess Trading during the COVID-19 Pandemic?

Manuscript type: Research paperResearch aims: This study aims to examine the underlying psychological and sociological factors that drive excess trading in the Malaysian stock market during a global health crisis such as the COVID-19 pandemic. Design/Methodology/Approach: A self-administered online questionnaire was collected from 271 individual investors to examine the association between big-five personality traits and trading frequency. Demographic information and investment behaviours of investors were also included in the study. The multinomial logit regression model was used to test the research hypotheses. Research findings: Findings show that personality traits such as openness to experience and agreeableness have a significant influence on trading frequency. Demographic factors and investment behaviours such as gender, household income level, years of investment experience and type of investor all have a significant positive relationship with trading frequency. Theoretical contribution/Originality: This study contributes to the current investor behaviour literature in Malaysia, which remains to be very limited, especially during a global health crisis. The study indicates that personality traits, demographic, socio-economic factors, and investment behaviours affect the trading frequency of Malaysian. Practitioner/Policy implication: This study offers insights for financial institutions and individual investors on the type of personality traits, demographic, socio-economic factors, and investment behaviours that drive excess trading during a global health crisis. The findings provide important contributions to avoid serious mistakes in investment analysis and trading profitable investment strategies, thus improving individual and team performance. Research limitation/Implications: Some results are not significant and may be limited due to the small sample size used in this study. Future research could recruit more retail investors to confirm the significance level of those variables. Besides, the study can be conducted after the COVID-19 pandemic to explore whether there is any significant difference in the variables during and after the global health crisis.

Liquidity and asset pricing: evidence from a new free-float-adjusted price impact ratio

PurposeThis paper aims to empirically examine the relationship between stock liquidity and asset pricing, using a new price impact ratio adjusted for free float as the approximation of liquidity. The free-float-adjusted ratio is free from size bias and encapsulates the impact of trading frequency. It is more comprehensive than alternative price impact ratios because it incorporates the shares available to the public for trading.Design/methodology/approachThe authors are using univariate and multivariate econometric methods to test the significance of a newly created price impact ratio. The authors are using secondary data and asset pricing models in their analysis. The authors use a data sample of all US listed companies over the period of 1997–2017.FindingsThe authors provide evidence that the free-float-adjusted price impact ratio is superior to all price impact ratios used in the previous academic literature. The authors also discover that their findings are robust to the financial crises between 2007 and 2009.Originality/valueThis is the first comprehensive study on a newly established price impact ratio. The authors show the significance of this ratio and explain why it is superior to all previous price impact ratios, established in prior research.

Five Facts about Beliefs and Portfolios

We study a newly designed survey administered to a large panel of wealthy retail investors. The survey elicits beliefs that are important for macroeconomics and finance, and matches respondents with administrative data on their portfolio composition, their trading activity, and their login behavior. We establish five facts inthese data. (i) Beliefs are reflected in portfolio allocations. The sensitivity of portfolios to beliefs is small on average, but varies significantly with investor wealth, attention, trading frequency, and confidence. (ii) Belief changes do not predict when investors trade, but conditional on trading, they affect both the direction and the magnitude of trades. (iii) Beliefs are mostly characterized by large and persistent individual heterogeneity. Demographic characteristics explain only asmall part of why some individuals are optimistic and some are pessimistic. (iv) Expected cash flow growth and expected returns are positively related, both within and across investors. (v) Expected returns and the subjective probability of rare disasters are negatively related, both within and across investors. These five facts provide useful guidance for the design of macro-finance models. (JEL D83, E23, G11, G12, G41, G51)

Trading practice and Behavioral Biases of Individual Investors in Nepalese Stock Market

The paper was based on survey research design. There is significant association between experience group with herding bias and optimism bias and there is no significant association between experience group with investment decision bias, disposition effect bias, and overconfidence bias. Similarly there is significant association between trading frequency with herding bias, optimism bias, investment decision bias, disposition effect bias, and overconfidence bias. Heuristics may make investors overconfident as they overlook risks causing security price to move away from fundamentals. Investors tend to be overconfident and hence overestimate the accuracy of their forecast due to illusion of knowledge and illusion of control.

PENGARUH FREKUENSI PERDAGANGAN, VOLUME PERDAGANGAN, DAN KAPITALISASI PASAR TERHADAP RETURN SAHAM PERUSAHAAN MANUFAKTUR YANG TERDAFTAR DI BEI PERIODE 2016-2019

This study aims to determine the impact of Trading Frequency, Trading Volume, and Market Capitalization on the stock returns of Manufacturing Companies listed on the Indonesia Stock Exchange (BEI) for the 2016-2019 Period. The nature of this research is quantitative explanatory. The population is manufacturing companies listed on the Indonesia Stock Exchange from 2016 to 2019. The research sample of 18 manufacturing companies that are still listed on the Indonesia Stock Exchange with the sampling technique is purposive sampling. Data is taken in the form of secondary data obtained through annual reports and financial reports for 2016-2019. The analytical method used consists of multiple regression analysis, classical assumptions, hypothesis testing (t test) and the coefficient of determination test. From the research results it is concluded that based on the regression analysis, the following equation is obtained: Y = -0.060 + 0.044FRE + 0.011VOL + 0.033KAP + e. Based on hypothesis testing, the t test (partial testing) of the variable Trading Frequency has a significant negative effect on Stock Returns, Trading Volume has a significant positive effect on Stock Returns and Market Capitalization has a significant positive effect on Stock Returns. The R Square value of 0.068 indicates that the Trading Frequency, Trading Volume, and Market Capitalization have an effect of 6.8% while the remaining 93.2% is influenced by other variables outside the regression model.

Calculation Method and Application of Inter-Regional and Inter-Provincial Market Trading Space for Promoting the Consumption of Clean Energy

Inter-provincial market trading is putting up with to implement the national energy strategy, increasing clean energy consuming and optimization energy allocation in large-scale. To promote energy consumption, the inter-province power transmission channel’ potential needs to be full excavate to deal with clean energy fluctuation, improving trading frequency and reduce transaction period. This article puts up with an inter-province power market trading space calculation method to calculate the available power transmission ability of inter-provincial transmission channel, discovering transmission channel and releasing transaction space. Besides, for certain transmission channel or supply-demand province’s electricity requirements, the calculation method can explore the trading market space, organizing clean energy evacuation to improve transmission channel utilization and safety checking pass rates, reducing blocking.