• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.195-220
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• 2018

In this study, we conducted an empirical analysis of the factors that affect the change of Bitcoin Closing Price. Previous studies have focused on the security of the block chain system, the economic ripple effects caused by the cryptocurrency, legal implications and the acceptance to consumer about cryptocurrency. In various area, cryptocurrency was studied and many researcher and people including government, regardless of country, try to utilize cryptocurrency and applicate to its technology. Despite of rapid and dramatic change of cryptocurrencies' price and growth of its effects, empirical study of the factors affecting the price change of cryptocurrency was lack. There were only a few limited studies, business reports and short working paper. Therefore, it is necessary to determine what factors effect on the change of closing Bitcoin price. For analysis, hypotheses were constructed from three dimensions of consumer, industry, and macroeconomics for analysis, and time series data were collected for variables of each dimension. Consumer variables consist of search traffic of Bitcoin, search traffic of bitcoin ban, search traffic of ransomware and search traffic of war. Industry variables were composed GPU vendors' stock price and memory vendors' stock price. Macro-economy variables were contemplated such as U.S. dollar index futures, FOMC policy interest rates, WTI crude oil price. Using above variables, we did times series regression analysis to find relationship between those variables and change of Bitcoin Closing Price. Before the regression analysis to confirm the relationship between change of Bitcoin Closing Price and the other variables, we performed the Unit-root test to verifying the stationary of time series data to avoid spurious regression. Then, using a stationary data, we did the regression analysis. As a result of the analysis, we found that the change of Bitcoin Closing Price has negative effects with search traffic of 'Bitcoin Ban' and US dollar index futures, while change of GPU vendors' stock price and change of WTI crude oil price showed positive effects. In case of 'Bitcoin Ban', it is directly determining the maintenance or abolition of Bitcoin trade, that's why consumer reacted sensitively and effected on change of Bitcoin Closing Price. GPU is raw material of Bitcoin mining. Generally, increasing of companies' stock price means the growth of the sales of those companies' products and services. GPU's demands increases are indirectly reflected to the GPU vendors' stock price. Making an interpretation, a rise in prices of GPU has put a crimp on the mining of Bitcoin. Consequently, GPU vendors' stock price effects on change of Bitcoin Closing Price. And we confirmed U.S. dollar index futures moved in the opposite direction with change of Bitcoin Closing Price. It moved like Gold. Gold was considered as a safe asset to consumers and it means consumer think that Bitcoin is a safe asset. On the other hand, WTI oil price went Bitcoin Closing Price's way. It implies that Bitcoin are regarded to investment asset like raw materials market's product. The variables that were not significant in the analysis were search traffic of bitcoin, search traffic of ransomware, search traffic of war, memory vendor's stock price, FOMC policy interest rates. In search traffic of bitcoin, we judged that interest in Bitcoin did not lead to purchase of Bitcoin. It means search traffic of Bitcoin didn't reflect all of Bitcoin's demand. So, it implies there are some factors that regulate and mediate the Bitcoin purchase. In search traffic of ransomware, it is hard to say concern of ransomware determined the whole Bitcoin demand. Because only a few people damaged by ransomware and the percentage of hackers requiring Bitcoins was low. Also, its information security problem is events not continuous issues. Search traffic of war was not significant. Like stock market, generally it has negative in relation to war, but exceptional case like Gulf war, it moves stakeholders' profits and environment. We think that this is the same case. In memory vendor stock price, this is because memory vendors' flagship products were not VRAM which is essential for Bitcoin supply. In FOMC policy interest rates, when the interest rate is low, the surplus capital is invested in securities such as stocks. But Bitcoin' price fluctuation was large so it is not recognized as an attractive commodity to the consumers. In addition, unlike the stock market, Bitcoin doesn't have any safety policy such as Circuit breakers and Sidecar. Through this study, we verified what factors effect on change of Bitcoin Closing Price, and interpreted why such change happened. In addition, establishing the characteristics of Bitcoin as a safe asset and investment asset, we provide a guide how consumer, financial institution and government organization approach to the cryptocurrency. Moreover, corroborating the factors affecting change of Bitcoin Closing Price, researcher will get some clue and qualification which factors have to be considered in hereafter cryptocurrency study.

• Journal of Distribution Science
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• v.13 no.9
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• pp.37-45
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• 2015

Purpose - This paper's aim is to investigate whether or not gross profitability explains the cross-sectional variation of the stock returns in the Korean stock market. Gross profitability is an alternative profitability measure proposed by Novy-Marx in 2013 to predict cross-sectional variation of stock returns in the US. He shows that the gross profitability adds explanatory power to the Fama-French 3 factor model. Interestingly, gross profitability is negatively correlated with the book-to-market ratio. By confirming the gross profitability premium in the Korean stock market, we may provide some implications regarding the well-known value premium. In addition, our empirical results may provide opportunities for the fund distribution industry to promote brand new styles of funds. Research design, data, and methodology - For our empirical analysis, we collect monthly market prices of all the companies listed on the Korea Composite Stock Price Index (KOSPI) of the Korea Exchanges (KRX). Our sample period covers July1994 to December2014. The data from the company financial statementsare provided by the financial information company WISEfn. First, using Fama-Macbeth cross-sectional regression, we investigate the relation between gross profitability and stock return performance. For robustness in analyzing the performance of the gross profitability strategy, we consider value weighted portfolio returns as well as equally weighted portfolio returns. Next, using Fama-French 3 factor models, we examine whether or not the gross profitability strategy generates excess returns when firmsize and the book-to-market ratio are controlled. Finally, we analyze the effect of firm size and the book-to-market ratio on the gross profitability strategy. Results - First, through the Fama-MacBeth cross-sectional regression, we show that gross profitability has almost the same explanatory power as the book-to-market ratio in explaining the cross-sectional variation of the Korean stock market. Second, we find evidence that gross profitability is a statistically significant variable for explaining cross-sectional stock returns when the size and the value effect are controlled. Third, we show that gross profitability, which is positively correlated with stock returns and firm size, is negatively correlated with the book-to-market ratio. From the perspective of portfolio management, our results imply that since the gross profitability strategy is a distinctive growth strategy, value strategies can be improved by hedging with the gross profitability strategy. Conclusions - Our empirical results confirm the existence of a gross profitability premium in the Korean stock market. From the perspective of the fund distribution industry, the gross profitability portfolio is worthy of attention. Since the value strategy portfolio returns are negatively correlated with the gross profitability strategy portfolio returns, by mixing both portfolios, investors could be better off without additional risk. However, the profitable firms are dissimilar from the value firms (high book-to-market ratio firms); therefore, an alternative factor model including gross profitability may help us understand the economic implications of the well-known anomalies such as value premium, momentum, and low volatility. We reserve these topics for future research.

• The Korean Journal of Financial Management
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• v.22 no.2
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• pp.189-212
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• 2005

This study examines the interactions between KTB spot and futures markets using the daily prices from March 4, 2002 to January 31, 2005. We use Granger causality test, impulse Response Analysis and Variance Decomposition through vector autoregressive analysis (VAR). However, considering the long-term relationships between the level variables of KTB spot and futures, we introduced Vector Error Correction Model. The main results are as follows. According to the results of Granger-causality test and impulse response analysis, we find that the yields of KTB forward have a great influence on the change of KTB spot but not vice versa. In terms of volatility analysis, there is no inter-dependence between KTB forward and spot markets. In the variance decomposition analysis we find that the short-term KTB forward has much more impact on the KTB spot market than the long-term KTB forward does. We think these results are meaningful for bond investors who are in charge of capital asset pricing valuation, risk management and international portfolio management.

• Journal of Distribution Science
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• v.13 no.5
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• pp.71-82
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• 2015

Purpose - The purpose of this study is to investigate risk price implied from the pricing kernel of Korean stock distribution market. Recently, it is considered that the quantitative easing programs of major developed countries are contributing to a reduction in global uncertainty caused by the 2007~2009 financial crisis. If true, the risk premium as compensation for global systemic risk or economic uncertainty should show a decrease. We examine whether the risk price in the Korean stock distribution market has declined in recent years, and attempt to provide practical implications for investors to manage their portfolios more efficiently, as well as academic implications. Research design, data and methodology - To estimate the risk price, we adopt a non-parametric method; the minimum norm pricing kernel method under the LOP (Law of One Price) constraint. For the estimation, we use 17 industry sorted portfolios provided by the KRX (Korea Exchange). Additionally, the monthly returns of the 17 industry sorted portfolios, from July 2000 to June 2014, are utilized as data samples. We set 120 months (10 years) as the estimation window, and estimate the risk prices from July 2010 to June 2014 by month. Moreover, we analyze correlation between any of the two industry portfolios within the 17 industry portfolios to suggest further economic implications of the risk price we estimate. Results - According to our results, the risk price in the Korean stock distribution market shows a decline over the period of July 2010 to June 2014 with statistical significance. During the period of the declining risk price, the average correlation level between any of the two industry portfolios also shows a decrease, whereas the standard deviation of the average correlation shows an increase. The results imply that the amount of systematic risk in the Korea stock distribution market has decreased, whereas the amount of industry-specific risk has increased. It is one of the well known empirical results that correlation and uncertainty are positively correlated, therefore, the declining correlation may be the result of decreased global economic uncertainty. Meanwhile, less asset correlation enables investors to build portfolios with less systematic risk, therefore the investors require lower risk premiums for the efficient portfolio, resulting in the declining risk price. Conclusions - Our results may provide evidence of reduction in global systemic risk or economic uncertainty in the Korean stock distribution market. However, to defend the argument, further analysis should be done. For instance, the change of global uncertainty could be measured with funding costs in the global money market; subsequently, the relation between global uncertainty and the price of risk might be directly observable. In addition, as time goes by, observations of the risk price could be extended, enabling us to confirm the relation between the global uncertainty and the effect of quantitative easing. These topics are beyond our scope here, therefore we reserve them for future research.

• Journal of Korea Technology Innovation Society
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• v.15 no.2
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• pp.262-276
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• 2012

Transactions activation of intangible assets has become became a key factor for corporate survival and successful business in the knowledge economy. Thus, demand in correctly valuating technology has increased. The market approach is the reliable method because of the premise that the market value of an asset is directly related to the prices of comparable, competitive ones. However, it can be practically impossible in many cases because it is hard to find identical transactions, which are generally closely guarded business secrets. As a result, most of technology valuation is conducted by the income approach and this approach is used to derive estimates for such unobserved variables. In September 2011, the Ministry of Knowledge Economy enacted a law for operational guideline standards for technology valuation to encourage the domestic technology valuation market. The enforcement recommended that the market approach have precedence over other approaches. If this approach cannot be applied, then the valuator should writing that he used other approaches. In practice, it is hard to know whether or not information about comparable transactions exists. The proposed process provides valuators to assess suitability for practical use of market approach through the observation process of technology transactions information. At the same time, it offers them the opportunity to gain validity when using other approaches.

• Journal of Agricultural Extension & Community Development
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• v.20 no.1
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• pp.1-39
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• 2013

The Cooperatives Act was enacted. This enabled people to establish easily cooperatives at various fields. A cooperative is an important vehicle for rural community development. Therefore, the enactment of the Cooperatives Act can be a significant chance for rural policy. The Cooperatives Act have made three significant changes. First, cooperatives can start businesses at all the fields except for financial and insurance business. Second, requisites for people to establish cooperatives have been alleviated exceptionaly. Third, the Cooperatives Act introduced a new cooperative organization, social cooperative which aims to serve the socially excluded class. The self-help approach places rural community members at the core of a development process with two goals: to improve the quality of life within the community and to facilitate the community's capacity building. Community cooperatives contribute to accomplish those goals. One of the roles for cooperatives is to provide products and services at competitive prices. Providing a good or service at a competitive price bcomes increasingly important in some rural communities declines. Cooperative development processes have bic impacts on the ablility of community members to increase human asset and social capital. We conducted a survey targeting rural community businesses to grasp inclinations toward establishing cooperatives. The Cooperatives Act has gained low level of recognition. But so many community businesses wanted to establish cooperatives. This means there is a possibility for many community businesses to establish cooperatives without sufficient understanding. We suggested some policy issues for coping with this situation, as followings. First, the governments should provides rural community residents with opportunities to learn about cooperatives. Second, the current legal systems and regulations about business and social service should be reviewed to do away with the possible discrimination between the new cooperatives and the other forms of incoporation. Third, the cooperation of cooperatives should be encouraged and facilitated in rural communities.

• Journal of Korea Entertainment Industry Association
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• v.14 no.2
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• pp.155-164
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• 2020

This study identifies the relationship between selection value, existence value, heritage value, pride, and show on satisfaction, and suggests cultural marketing and cultural policy suggestions for Jikji cultural assets to activate Jikji as tourism cultural assets. Was intended. Therefore, the implications of this study are as follows. First, Jikji cultural property officials should develop tourism products that can mix Jikji cultural properties with the image and attractiveness of Jikji cultural properties. In addition, it is necessary to pay attention to education and public relations by city and county in providing local information, prices, and services for tourists to increase the satisfaction of tourists. Second, Jikji cultural property officials should suggest ways to create differentiating elements from tourism of other cultural properties. By emphasizing the existence, the existence value of Jikji cultural property should be increased. Third, Jikji cultural property officials should emphasize that Jikji tourism is more valuable as cultural heritage than now, and develop unique killer contents that can be boasted to others in tourism and present it to tourists. Fourth, Jikji cultural property officials should prepare a plan for local residents to recognize how excellent cultural heritage is. It should also be recognized that Jikji cultural property has high added value as a tourist factor. Lastly, Jikji cultural property officials should promote various jikji projects to local residents and tourists to increase their pride and awareness that Jikji cultural property exists in a certain area.

• Journal of Popular Narrative
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• v.25 no.4
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• pp.321-359
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• 2019

In the 1970s, the full-scale development of the area now known as Gangnam began, ushering in the era of real estate investment on apartments which transformed housing styles in Korea. Apartments were pitched as the most ideal type of housing, creating a competitive market of high demand and skyrocketing prices. The apartments were also viewed as a means of quick asset investment among middle-class Koreans. Within this apartment frenzy stood the female real estate speculator, the bokbuin. This study seeks to locate the bokbuin in the real estate development market after the late 1970s. The apartment speculation boom cannot be attributed to the bokbuin alone, yet she became the target of public anger and criticism, singled-out as being responsible for fueling illegal and unethical investments. The apartment boom of the 1970s was in fact generated in large part by the government, developers, construction companies and realtors. While their pursuit of profit was deemed as legitimate, the bokbuin's conduct was mostly tainted by presumed illegitimate and greedy motivations. This study problematizes this gendering of real estate investment and treat the bokbuin as a byproduct of the family-centered culture in East Asia. Analyzing Im Kwon Taek's film "Mrs. Speculator", Park Ki Won's conte, "Bokbuin", Park Wan Seo's short story, "Children of Paradise", "The People of Seoul", this study shows that bokbuin's pursuit was not hers alone; it was the collective pursuit with her husband for the enhancement of family finances. This stud y argue that the bokbuin embodied the thickly misogynistic climate of the 1970s that projected the chaotic rise of greed onto the woman.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.129-148
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• 2023

Bitcoin is a blockchain technology-based digital currency that has been recognized as a representative cryptocurrency and a financial investment asset. Due to its highly volatile nature, Bitcoin has gained a lot of attention from investors and the public. Based on this popularity, numerous studies have been conducted on price and trend prediction using machine learning and deep learning. This study employed LSTM (Long Short Term Memory) and CNN (Convolutional Neural Networks), which have shown potential for predictive performance in the finance domain, to enhance the classification accuracy in Bitcoin price trend prediction. XAI(eXplainable Artificial Intelligence) techniques were applied to the predictive model to enhance its explainability and interpretability by providing a comprehensive explanation of the model. In the empirical experiment, CNN was applied to technical indicators and Google trend data to build a Bitcoin price trend prediction model, and the CNN model using both technical indicators and Google trend data clearly outperformed the other models using neural networks, SVM, and LSTM. Then SHAP(Shapley Additive exPlanations) was applied to the predictive model to obtain explanations about the output values. Important prediction drivers in input variables were extracted through global interpretation, and the interpretation of the predictive model's decision process for each instance was suggested through local interpretation. The results show that our proposed research framework demonstrates both improved classification accuracy and explainability by using CNN, Google trend data, and SHAP.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.107-122
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• 2017

Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.