• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.807-814
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• 2021

As economic activities decrease, and the stock market decline due to COVID-19, many people are jumping into stock investment as an alternative source of income. As people's interest increases, many stock price analysis studies are underway to earn more profits. Due to the variance observed in the stock markets, it is necessary to analyze each stock independently and consistently. To solve this problem, we designed and implemented models and services that analyze stock prices using a reinforcement learning technique called Asynchronous Advantage Actor-Critic(A3C). Stock market data reflected external factors such as government bonds and KOSPI (Korea Composite Stock Price Index) as well as stock prices. Our proposed work provides a web service with a visual representation of predictions of stocks and stock information through which directions are given to investors to make safe investments without analyzing domestic and foreign stock market trends.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.4
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• pp.29-38
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• 2022

The enormous sway of COVID-19 on the international financial market has been felt across the globe. The financial markets of Bangladesh have also been similarly affected by the global epidemic and experienced a significant increase in volatility. To scrutinise the connection between COVID-19 and the Dhaka Stock Exchange (DSE) indices' return and instability, this study uses data of the DSE from February 2014 to September 2021. A comparative examination of the return and instability of the stock indices of the DSE has also been done considering the outbreak of the current COVID-19 situation. After using the GJR-GARCH (1,1) model, this review uncovers that the outbreak of COVID-19 has a statistically positive noteworthy association with the DSE stock indices' instability, which increases the market's volatility. Traders' fear and the rising frequency of COVID-19 reported patients could cause this. Besides, according to this study, COVID-19 shows a substantial positive linkage with stock market returns that increases the market's return. An appealing valuation, lower interest rates in the banking channel, economic rebound following the closure to prevent coronavirus transmission, improved remittance inflows, and a return of export revenues could all have contributed to this outcome. In addition, the findings also reveal that all market indices are in a mean-reverting phase.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.3
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• pp.195-202
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• 2022

This study investigates whether institutional investors increase or decrease the volatility of stock returns in the Thai stock market. For the purpose we used the data from SETSMART, a database provided by the Stock Exchange of Thailand (SET). Our sample is a balanced panel data covering 3,160 firm-year observations from 316 nonfinancial firms listed on the SET from 2011 to 2020. We analyze the link between institutional holdings and the volatility of stock returns by the pooled Ordinary Least Squares (OLS) model, the fixed effects model, and the random-effects model. In particular, we regress the stock return volatility on institutional ownership while controlling for firm size, financial leverage, growth opportunities, and stock turnover and accounting for industry effects and year effects. Our results indicate institutional investors' positive and significant influence on the volatility of the stock returns. Additionally, we performed the dynamic Generalized Method of Moment (GMM) estimator to alleviate concerns of possible endogeneity. The result still shows a positive impact of institutional investors on the volatility in stock returns. Overall, the findings of this study suggest that an increase in the volatility of stock returns in the Thai stock market may stem from a higher proportion of equity held by the institutional investors.

• Asia pacific journal of information systems
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• v.30 no.1
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• pp.31-52
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• 2020

Stock markets are popular investment avenues to people who plan to receive premium returns compared to other financial instruments, but they are highly volatile and risky due to the complex financial dynamics and poor understanding of the market forces involved in the price determination. A system that can forecast, predict the stock prices and automatically create a portfolio of top performing stocks is of great value to individual investors who do not have sufficient knowledge to understand the complex dynamics involved in evaluating and predicting stock prices. In this paper the authors propose a Stock prediction, Portfolio Generation and Selection model based on Machine learning algorithms, Artificial neural networks (ANNs) are used for stock price prediction, Mathematical and Statistical techniques are used for Portfolio generation and Un-Supervised Machine learning based on K-Means Clustering algorithms are used for Portfolio Evaluation and Selection which take in to account the Portfolio Return and Risk in to consideration. The model presented here is limited to predicting stock prices on a long term basis as the inputs to the model are based on fundamental attributes and intrinsic value of the stock. The results of this study are quite encouraging as the stock prediction models are able predict stock prices at least a financial quarter in advance with an accuracy of around 90 percent and the portfolio selection classifiers are giving returns in excess of average market returns.

• Journal of Navigation and Port Research
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• v.47 no.2
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• pp.100-105
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• 2023

This study investigated determinants of stock betas of shipping companies in Korea. Beta is a measurement of sensitivity of an individual stock to the movement of the whole stock market. It is widely accepted that stock betas are not constant, but time-varying, which implies that they are affected by other factors. In this regard, this study examined betas of six shipping companies listed on the Korea Exchange for the period of 2000-2021 and their relationship with financial leverage, operating leverage, and cyclicality in the shipping market. Empirical analysis showed that betas of Korean shipping companies were positively associated with financial and operating leverages but negatively with cyclicality.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.10
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• pp.219-228
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• 2021

The study examines the behavior of stock prices after large price changes. It further examines the effect of firm size on stock returns, and the presence of the disposition effect. The study employs the event study methodology using daily price data from Pakistan Stock Exchange (PSX) for the period January 2001 to July 2012. Furthermore, to examine the factors that explain stock price behavior after large price movements, the study employs a two-way fixed-effect model that allows for the analysis of unobservable company and time fixed effects that explain market reversals or continuation. The findings suggest that winners perform better than losers after experiencing large price shocks thus showing a momentum behavior. In addition, the winners remain the winner, while the losers continue to lose more. This suggests that most of the investors in PSX behave rationally. Further, the study finds no evidence of disposition effect in PSX. The investors underreact to new information and the prices continue to move in the direction of initial change. The pooled regression estimates show that firm size is positively related to post-event abnormal returns while the fixed-effect model reveals the presence of unobservable firm-specific and time-specific effects that account for price continuation.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.9
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• pp.49-59
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• 2022

Based on assessing the impact of factors on the business efficiency of construction enterprises, the research team proposes policy implications to improve the business performance of listed construction enterprises in Vietnam in the coming time. The study used secondary data collected from the audited financial statements of 25 enterprises listed on Vietnam's stock market in the period 2015-2021 to estimate the factors affecting the business performance of construction enterprises. After collecting, the data will be encrypted and checked. The article uses a quantitative research method by using a linear regression model on Eviews 10 to analyze the data and analyze the impact of factors on the business performance of construction enterprises listed on Vietnam's stock market. The research result shows that firm size and growth rate positively affect business performance while capital structure, receivable management, fixed asset investment, and economic growth have a positive impact on the business performance of construction companies listed on the Vietnamese stock market. Based on this result, the paper also makes recommendations to the Vietnamese construction companies to enhance their business performance.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.10
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• pp.441-450
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• 2014

The stock market is constantly changing and sometimes the stock prices unaccountably plummet or surge. So, the stock market is recognized as a complex system and the change on the stock prices is unpredictable. Recently, many researchers try to understand the stock market as the network among individual stocks and to find a clue about the change of the stock prices from big data being created in real time from Internet. We focus on the correlation between the stock prices and the human interactions in Internet especially in the stock message boards. To uncover this correlation, we collected and investigated the articles concerning with 57 target companies, members of KOSPI200. From the analysis result, we found that there is no significant correlation between the stock prices and the article volume, but the strength of correlation between the article volume and the stock prices is relevant to the stock return. We propose a new method for recommending stock portfolio base on the result of our analysis. According to the simulated investment test using the article data from the stock message boards in 'Daum' portal site, the returns of our portfolio is about 1.55% per month, which is about 0.72% and 1.21% higher than that of the Markowitz's efficient portfolio and that of the KOSPI average respectively. Also, the case using the data from 'Naver' portal site, the stock returns of our proposed portfolio is about 0.90%, which is 0.35%, 0.40%, and 0.58% higher than those of our previous portfolio, Markowitz's efficient portfolio, and KOSPI average respectively. This study presents that collective human behavior on Internet stock message board can be much helpful to understand the stock market and the correlation between the stock price and the collective human behavior can be used to invest in stocks.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.3
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• pp.154-161
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• 2018

This study conducted to predict the stock market prices based on the assumption that internet news articles might have an impact and effect on the rise and fall of stock market prices. The internet news articles were tested to evaluate the accuracy by comparing predicted values of the actual stock index and the forecasting models of the companies. This paper collected stock news from the internet, and analyzed and identified the relationship with the stock price index. Since the internet news contents consist mainly of unstructured texts, this study used text mining technique and multiple regression analysis technique to analyze news articles. A company H as a representative automobile manufacturing company was selected, and prediction models for the stock price index of company H was presented. Thus two prediction models for forecasting the upturn and decline of H stock index is derived and presented. Among the two prediction models, the error value of the prediction model (1) is low, and so the prediction performance of the model (1) is relatively better than that of the prediction model (2). As the further research, if the contents of this study are supplemented by real artificial intelligent investment decision system and applied to real investment, more practical research results will be able to be developed.

• Journal of the Korea Society of Computer and Information
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• v.3 no.4
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• pp.139-144
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• 1998

Introduced into korea to diversify risk coming from the fluctuation of stock price with opening of the domestic capital market to foreigners, Suppress the turbulence of the dentistic securities market caused by the short term funds from foreign countries and vitalize investment in stock, the hedging transaction of stock index futures will promote the introduction of financial futures and commodity futures transaction. and it will contribute to enhancing the introduction all over the country and accelerating the advancement of the korea banking market. In addition, it is expected to make a great contribution to economic stability and smooth comic activity through its function of risk diversification and price decrement with the launch of the stock index futures.