• The Korean Journal of Financial Management
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• v.20 no.2
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• pp.41-72
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• 2003

The purposes of this paper are to build theoretical and empirically testable model to identify determining factors of ownership structure, and to analyze this model empirically using th Korea Stock Exchange panel data, and to test the impact of opening the stock market on the determinants of ownership structure. The determining factors of ownership structure identified in this paper include debt ratio, dividend, asset characteristics, profitability, growth business risk, size, institutional investors and chaebol-non chaebol dummy variable. Empirical panel estimation test reveals that this model can explain about $9\sim11%$ of the cross sectional variance in the equity ratio of large shareholders. The reasons that this model has too explanatory power are that some variables were measured with errors, and that there were some omitted variables in tested model. The regression results on the model variables ar generally in line with predictions. But the coefficient estimates on size is never significant. And it appears that the exogenous variable which explains opening the stock market has positive effect on the determinants of ownership structure.

• The Korean Journal of Financial Management
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• v.26 no.4
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• pp.191-234
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• 2009

This study examined on the volatility feedback hypothesis through the use of threshold GARCH-in-Mean (GJR-GARCH-M) model developed by Glosten, Jaganathan, and Runkle (1993) in the stock markets of 14 emerging countries during the period of January, 1996 to May, 2009. On this study, I found successful evidences which can support the volatility feedback hypothesis through the following three estimation procedures. First, I found relatively strong positive relationship between the expected market risk premiums and their conditional standard deviations from the GARCH-M model in the basis of daily return on each representative stock market index, which is appropriate to investors' risk-averse preferences. Second, I can also identify the significant asymmetric time-varying volatility originated from the investors' differentiated reactions toward the unexpected market shocks by applying the GJR-GARCH-M model and further find the lasting positive risk aversion coefficient estimators. Third, I derived the negative signs of the regression coefficient of unpredicted volatility on the stock market return by re-applying the GJR-GARCH-M model after I controlled the positive effect of predicted volatility through including the conditional standard deviations from the previous GARCH-M model estimation as an independent explanatory variable in the re-applied new GJR-GARCH-M model. With these consecutive results, the volatility feedback effect was successfully tested to be effective also in the various emerging stock markets, although the leverage hypothesis turned out to be insufficient to be applied to another source of explaining the negative relationship between the unexpected volatility and the ex-post stock market return in the emerging countries in general.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.209-235
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• 2022

Starting from 2010, blockchain technology, along with the development of artificial intelligence, has been in the spotlight as the latest technology to lead the 4th industrial revolution. Furthermore, previous research regarding blockchain's technological applications has been ongoing ever since. However, few studies have been examined the standards for classifying the blockchain economic ecosystem from a capital market perspective. Our study is classified into a collection of interviews of software developers, entrepreneurs, market participants and experts who use blockchain technology to utilize the blockchain economic ecosystem from a capital market perspective for investing in stocks, and case study methodologies of blockchain economic ecosystem according to application fields of blockchain technology. Additionally, as a way that can be used in connection with equity investment in the capital market, the blockchain economic ecosystem classification methodology was established to form an investment universe consisting of global blue-chip stocks. It also helped construct an intelligent portfolio through quantitative and qualitative analysis that are based on quant and artificial intelligence strategies and evaluate its performances. Lastly, it presented a successful investment strategy according to the growth of blockchain economic ecosystem. This study not only classifies and analyzes blockchain standardization as a blockchain economic ecosystem from a capital market, rather than a technical, point of view, but also constructs a portfolio that targets global blue-chip stocks while also developing strategies to achieve superior performances. This study provides insights that are fused with global equity investment from the perspectives of investment theory and the economy. Therefore, it has practical implications that can contribute to the development of capital markets.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1435-1440
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• 2021

With the advent of the low interest rate era, many investors are flocking to the stock market. In the past stock market, people invested in stocks labor-intensively through company analysis and their own investment techniques. However, in recent years, stock investment using artificial intelligence and data has been widely used. The success rate of stock prediction through artificial intelligence is currently not high, so various artificial intelligence models are trying to increase the stock prediction rate. In this study, we will look at various artificial intelligence models and examine the pros and cons and prediction rates between each model. This study investigated as stock prediction programs using artificial intelligence artificial neural network (ANN), deep learning or hierarchical learning (DNN), k-nearest neighbor algorithm(k-NN), convolutional neural network (CNN), recurrent neural network (RNN), and LSTMs.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.3
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• pp.661-670
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• 2012

In order to construct a profitable stock trading model, three considerations must be resolved in the model in integrated manner: profit principle, trader's conditions and stock market trends. Generally, a model will be developed through long experiences of stock trading that requires quite amount of expenses and time. This paper analyzes the issues involved in those considerations and proposes a road map for a trading model.

• Journal of Venture Innovation
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• v.1 no.2
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• pp.47-59
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• 2018

With the recent, rapid changes in the socio-economic environment, organizations of today are now required to present a framework of realistic consumer behaviors based on psychology, economy, and finance, in order to understand their investing customers. Stock investors show differences in terms of their decisions or evaluations in the process of investing. This is due to what is called the 'framing effect.' The decision frames of the investors are defined differently, and, as a result, this affects the decisions made by the investors. Preceding studies on stock investment rarely touched the topic of the effect of message framing on market participants in their stock investment, especially regarding the differences in terms of their risk management behaviors based on the message framing in stock investment. Therefore, the purpose of this study is to examine the influence of stock investment message framing on market participants in their investment decision making and empirically validate whether this message framing effect has a moderating effect on the factors of investment satisfaction. For this, 494 participants with stock investment experiences were interviewed from May 1 to 26, 2018, and the results were used as the data for the empirical analysis. The analysis of the data was conducted using SPSS 22.0 statistical analysis software. The results of this study were as follows; First, of the stock investment behavioral factors, the stock comprehension, recommendation by others for a stock, and the degree of risks of a stock affected stock investment satisfaction in a positive manner. And, of the behavioral factors of stock investment, stock comprehension, stock brand, recommendation on the stocks from others, past performances, and risk levels of stocks affected the intent of continued stock investment in a positive manner. Second, message framing turned out to affect stock investment satisfaction in a positive manner, and it also had a significant moderating effect to the relationship between the stock investment behavior and stock investment satisfaction. Third, message framing was found to affect continued stock investment intent significantly, with a significant moderating effect in the relationship between stock investment behavioral factor and continued stock investment intent.

• Management & Information Systems Review
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• v.33 no.2
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• pp.119-133
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• 2014

This Research focuses on the effect of the price limits change in KOSDAQ market change on the volatility. The sample period ranges from 22 May 2000 to 24 March 2010 for daily data. We construct two subsample periods for comparing with the effect of the change of the price limit. These limits were relaxed from 12% to 15% on March 25, 2005. The first subsample period is from 25 March 2000 to 24 March 2005. The second subsample period is from 25 March 2005. to 24 March 2010. We employee four different volatility, which are the range-based volatility of Parkinson(1980; PK), Garman and Klass(1980; GK) Rogers and Satchell(1991; RS), Yang and Zhang(2008; YZ). The empirical result as follows. The major findings are summarized as follows; First, the volatility of individual stocks in KOSDAQ market reduces significantly after the price limit change. Second, There is so high volatile especially when the volatility of stock prices is high. Third, There is no meaningful relationship between volatility and market capitalization. Fourth, the more volume stocks reduce the volatility. Our results show the volatility decreased the more large volume, the more trading amount and the high price stock.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.04a
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• pp.1017-1019
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• 2014

자본주의의 꽃이라 할 수 있는 주식시장은 기업의 정량화된 가치를 매매하는 곳이다. 또한 파생거래는 주식시장의 위험회피 목적으로 만들어졌다. 파생시장이 투기적인 목적으로 악용되기도 하지만 기관투자가에게는 헤지거래의 중요한 수단임은 명백한 사실이다. 파생거래에서 옵션 거래는 투기적인 성향의 개인 거래자와 시장을 선도하는 기관 거래자 간의 치열한 대결로 볼 수 있다. 옵션은 상품별로 시시각각 변하는 이론가와 실거래가가 존재한다. 이론가를 기준으로 한 이격도 매매는 레버리지가 큰 옵션 거래에서 효과적인 위험회피 방법이다. 하지만 이론가는 현실적인 시장가와 괴리가 있을 수밖에 없다. 보다 현실적인 평균값을 구하기 위해서는 실제 옵션가의 통계만이 확실한 방법이다. 이를 위해서 옵션 만기일에 상품별로 차트정보를 수집하여 데이터베이스화하면 효과적이다. 이는 매우 반복적인 작업으로 이를 효과적으로 수행할 수 있는 에 이전트를 개발하였다. 이를 이용하면 실거래가를 기본으로 하는 평균값을 추출할 수 있으며, 지수차이와 잔여일에 따른 옵션 평균값에 근거하여 이격도 매매에 활용할 수 있다.

• The Korean Journal of Applied Statistics
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• v.24 no.1
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• pp.1-10
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• 2011

This study investigates the dynamic structure of interdependence on the domestic and related major stock markets by employing a statistical framework. Finance theory predicts potential gains by international portfolio diversification if returns from investment in different national stock markets are not perfectly correlated or not cointegrated. The benefit of international diversification is limited when national stock markets are cointegrated because of the limited amount of independent variation by the presence of common factors. The statistical tests suggest that international diversification appears to be favorable after the period of the comovement of the stock prices caused by 1997 Asian financial crisis. The result reflects the increase in overseas investment and purchase of overseas funds after the early 2000's.

• Journal of Korea Port Economic Association
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• v.38 no.4
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• pp.107-118
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• 2022

In this study, daily data from January 2002 to June 2022 were used to investigate the relationship between risk-return relationship and market fear, uncertainty, stock market, and maritime freight index for the crude oil market. For this study, the time varying EGARCH-M model was applied to the risk-return relationship, and the wavelet consistency model was used to analyze the relationship between market fear, uncertainty, stock market, and maritime freight index. The analysis results of this study are as follows. First, according to the results of the time-varying risk-return relationship, the crude oil market was found to be related to high returns and high risks. Second, the results of correlation and Granger causality test, it was found that there was a weak correlation between the risk-return relationship and VIX, EPU, S&P500, and BDI. In addition, it was found that there was no two-way causal relationship in the risk-return relationship with EPU and S&P500, but VIX and BDI were found to affect the risk-return relationship. Third, looking at the results of wavelet coherence, it was found that the degree of the risk-return relationship and the relationship between VIX, EPU, S&P500, and BDI was time-varying. In particular, it was found that the relationship between each other was high before and after the crisis period (financial crisis, COVID-19). And it was found to be highly associated with organs. In addition, the risk-return relationship was found to have a positive relationship with VIX and EPU, and a negative relationship with S&P500 and BDI. Therefore, market participants should be well aware of economic environmental changes when making decisions.