• The Journal of Asian Finance, Economics and Business
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• v.8 no.9
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• pp.287-300
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• 2021

The study is conducted to find out the impact of the country- and corporate-level governance and firm internationalization on stock liquidity of 120 listed firms in Japan, Hong Kong, Pakistan, and India. Panel data is used in the current study. The annual time span covered in the current study is 10 years. The current study explores results based on secondary data. The findings of the 'robust panel corrected standard error' estimator shows that the internationalization strategy of firms positively influences the stock liquidity. The internationalization strategy of multinational corporations proves to be an effective methodology for improving stock liquidity in the home market as well as abroad. The study also shows that a stronger relationship exists between stock liquidity and internationalization in those countries where the regulatory settings are effective, the judiciary system is efficient and shareholders' rights are protected. Corporate governance and stock liquidity are negatively associated. The study also finds a negative relationship between country-level governance mechanisms and stock liquidity. Whereas the 'robust panel corrected error' estimator shows a positive association between corporate governance mechanisms and firm internationalization. The study depicts that effective corporate governance motivates multinational companies to expand their business abroad.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.9
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• pp.45-52
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• 2021

Stock price fluctuations affect investor returns, particularly, in this pandemic situation that has triggered stock market shocks. As a result of this situation, investors prefer to move their money into a safer portfolio. Therefore, in this study, we approach an efficient portfolio model using smart beta and combining others to obtain a fast method to predict investment stock returns. Smart beta is a method to selects stocks that will enter a portfolio quickly and concisely by considering the level of return and risk that has been set according to the ability of investors. A smart beta portfolio is efficient because it tracks with an underlying index and is optimized using the same techniques that active portfolio managers utilize. Using the logistic regression method and the data of 100 low volatility stocks listed on the Indonesia stock exchange from 2009-2019, an efficient portfolio model was made. It can be concluded that an efficient portfolio is formed by a group of stocks that are aggressive and actively traded to produce optimal returns at a certain level of risk in the long-term period. And also, the portfolio selection model generated using the smart beta, beta, alpha, and stock variants is a simple and fast model in predicting the rate of return with an adjusted risk level so that investors can anticipate risks and minimize errors in stock selection.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.1
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• pp.51-58
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• 2022

Various studies have been conducted from the past to the present because stock price forecasts provide stability in the national economy and huge profits to investors. Recently, there have been many studies that suggest stock price prediction models using various input data such as macroeconomic indicators and emotional analysis. However, since each study was conducted individually, it is difficult to objectively compare each method, and studies on their impact on stock price prediction are still insufficient. In this paper, the effect of input data currently mainly used on the stock price is evaluated through the predicted value of the deep learning model and the error rate of the actual stock price. In addition, unlike most papers in emotional analysis, emotional analysis using the news body was conducted, and a method of supplementing the results of each emotional analysis is proposed through three emotional analysis models. Through experiments predicting Microsoft's revised closing price, the results of emotional analysis were found to be the most important factor in stock price prediction. Especially, when all of input data is used, error rate of ensembled sentiment analysis model is reduced by 58% compared to the baseline.

• Journal of Distribution Science
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• v.21 no.5
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• pp.101-111
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• 2023

Purpose: The purpose of this paper is to examine the effect of the VKOSPI index on short-term stock returns after a large-scale stock price shock of individual stocks of firms in the distribution industry in Korea. Research design, data, and methodology: This study investigates the effect of the change of the VKOSPI index or investor mood on abnormal returns after the event date from January 2004 to July 2022. The significance of the abnormal return, which is obtained by subtracting the rate of return estimated by the market model from the rate of actual return on each trading day after the event date, is determined based on T-test and multifactor regression analysis. Results: In Korea's distribution industry, the simultaneous occurrence of a bad investor mood and a large stock price decline, leads to stock price reversals. Conversely, the simultaneous occurrence of a good investor mood and a large-scale stock price rise leads to stock price drifts. We found that the VKOSPI index has strong explanatory power for these reversals and drifts even after considering both company-specific and event-specific factors. Conclusions: In Korea's distribution industry-related stock market, investors show an asymmetrical behavioral characteristic of overreacting to negative moods and underreacting to positive moods.

• Asia pacific journal of information systems
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• v.30 no.2
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• pp.439-456
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• 2020

In online shopping, "out-of-stock" and "sold-out" are used to indicate product unavailability, and this unavailability and its effects on consumers' behaviors have been studied with great interest for practical purposes. However, few studies have specifically discussed out-of-stock and sold-out products in the same paper. We hypothesized that consumers might cognitively interpret items marked out-of-stock and sold-out differently, and in this paper, we studied these potential differences from the perspectives of consumers' emotions, behaviors, and loyalty based on the stimulus-organism-response framework. In order to explore the differences, we used a multi-method approach that consisted of experiments, surveys, and interviews. Specifically, we built an experimental website on which the same products were categorized as either out-of-stock or sold-out, and we measured the participants' emotions, attitudes, and intentions after the experiment. After two weeks, we conducted interviews to confirm our results and to learn more about consumers' everyday behavior. In the results, males and females demonstrated differences in emotion, behaviors, and loyalty with the interaction effects of an item's being marked out-of-stock versus sold-out. We found that the consumers demonstrated different levels of loyalty based on whether the item was marked out-of-stock or sold-out. We discuss the strategic implications of our findings.

• Journal of Digital Convergence
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• v.14 no.10
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• pp.393-398
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• 2016

Stock information applications allow users to look up and find current stock information whenever and wherever. This study researched what kind of user experience the finance experts get when using these applications and what they suggest. The research was conducted through an in-depth interview of 8 finance experts, who worked minimum of three years, and used both Kakao Stock and JeungGwon Tong, the most used stock information applications, for a minimum duration of six months. The results show the user experience of Kakao Stock rated a bit higher than JeungGwon Tong. Since the objective of such applications are to show stock informations, the experts all rated the pleasurable and meaningful aspects rather low. They suggested, the developers should provide a more advanced and accurate information. They also suggested user interest recognized content be presented along with more convenient user interface to elevate usability. Hopefully, this study becomes a base to further study of user experience of various on and offline stock information services and they become a reference to develop a service with great user experience.

• The Journal of Industrial Distribution & Business
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• v.10 no.6
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• pp.51-58
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• 2019

Purpose - Prior studies reported that the opacity of information caused stock price crash. If managers fail to disclose unfavorable information about the firm over a long period of time, the stock price is overvalued compared to its original value. If the accumulated information reaches a critical point and spreads quickly to the market, the stock price plunges. Information management by management's disclosure policy can cause information uncertainty, which will lead to a plunge in stock prices in the future. Thus, this study aims at examining the impact of disclosure quality on crash risk by focusing on the unfaithful disclosure firms. Research design, data, and methodology - This study covers firms listed on KOSPI and KOSDAQ from 2004 to 2013. Firms excluded from the sample are non-December firms, capital-eroding firms, and financial firms. The financial data used in the research was extracted from the KIS-Value and TS2000 database. Unfaithful disclosure firm designation data was collected from the Korea Exchange's electronic disclosure system (kind.krx.co.kr). Stock crash is measured as a dummy variable that equals one if a firm experiences at least one crash week over the fiscal year, and zero otherwise. Results - Empirical results as to the relation between unfaithful disclosure corporation designation and stock price crashes are as follows: There was a significant positive association between unfaithful disclosure corporation designation and stock price crash. This result supports the hypothesis that firms that have previously exhibited unfaithful disclosure behavior are more likely to suffer stock price plunges due to information asymmetry. Second, stock price crashes due to unfaithful disclosures are more likely to occur in Chaebol firms. Conclusions - While previous studies used estimates as a proxy for information opacity, this study used an objective measure such as unfaithful disclosure corporation designation. The designation by Korea Exchange is an objective evidence that the firm attempted to conceal and distort information in the previous year. The results of this study suggest that capital market investors need to investigate firms' disclosure behaviors.

• The Korean Journal of Applied Statistics
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• v.31 no.3
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• pp.409-416
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• 2018

Significant research has been conducted in the financial sector on the behavior of investors in the stock market. In this paper, we directly measure the degree of interest using the ranking of the frequency mentioned in the stock message board operated by Daum Communications Corp. and test the fact that the higher ranking of the frequency results in the higher stock returns in order to investigate the attention effect on the stock returns in the Korean stock market. We also propose and apply the likelihood ratio test procedure for order restricted hypotheses in order to test the attention effect. The test results shows that the higher rank in the frequency mentioned in the message board is related to stock returns (p-value < $10^{-6}$). Therefore, we conclude that an investors' attention effects exist in the Korean stock market.

• Journal of Digital Convergence
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• v.18 no.11
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• pp.267-272
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• 2020

Macroeconomics are one of the indicators that are preceded and analyzed when analyzing stocks because it shows the movement of a country's economy as a whole. The overall economic situation at the national level, such as national income, inflation, unemployment, exchange rates, currency, interest rates, and balance of payments, has a great affect on the stock market, and economic indicators are actually correlated with stock prices. It is the main source of data for analysts to watch with interest and to determine buy and sell considering the impact on individual stock prices. Therefore, economic indicators that impact on the stock price are analyzed as leading indicators, and the stock price prediction is predicted through deep learning-based prediction, after that the actual stock price is compared. If you decide to buy or sell stocks by analysis of stock prediction, then stocks can be investments, not gambling. Therefore, this research was conducted to enable automated stock trading by using macro-indicators and deep learning algorithms in artificial intelligence.

• Journal of Forest and Environmental Science
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• v.36 no.1
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• pp.37-46
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• 2020

Vegetation carbon sequestration and regeneration are the two major parameters of forest research. In this study, we analyzed the vegetation carbon stock and regeneration of community-managed pine plantation of Kathmandu, central Nepal. Vegetation data were collected from 40 circular plots of 10 m radius (for the tree) and 1m radius (for seedling) applying a stratified random sampling and nested quadrat method. The carbon stock was estimated by Chave allometric model and estimated carbon stock was converted into CO₂ equivalents. Density-diameter (d-d) curve was also prepared to check the regeneration status and stability of the plantation. A d-d curve indicates the good regeneration status of the forest with a stable population in each size class. Diversity of trees was very low, only two tree species Pinus roxburghii and Eucalyptus citriodora occurred in the sample plots. Pine was the dominant tree in terms of density, basal area, biomass, carbon stock and CO₂ stock than the eucalyptus. The basal area, carbon stock and CO₂ stock of forest was 33±1.0 ㎡ ha^-1, 108±5.0 Mg ha^-1 and 394±18 Mg ha^-1, respectively. Seedling and tree density of the plantation was 4,965 ha^-1 and 339 ha^-1 respectively. The forest carbon stock showed a positive relationship with biomass, tree diameter, height and basal area but no relationship with tree density. Canopy cover and tree diameter have a negative effect on seedling density and regeneration. In conclusion, the community forest has a stable population in each size class, sequestering a significant amount of carbon and CO₂ emitted from densely populated Kathmandu metro city as the forest biomass hence have a potentiality to mitigate the global climate change.