• Title/Summary/Keyword: Business profits

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Analysis of Trading Performance on Intelligent Trading System for Directional Trading (방향성매매를 위한 지능형 매매시스템의 투자성과분석)

  • Choi, Heung-Sik;Kim, Sun-Woong;Park, Sung-Cheol
    • Journal of Intelligence and Information Systems
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    • v.17 no.3
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    • pp.187-201
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    • 2011
  • KOSPI200 index is the Korean stock price index consisting of actively traded 200 stocks in the Korean stock market. Its base value of 100 was set on January 3, 1990. The Korea Exchange (KRX) developed derivatives markets on the KOSPI200 index. KOSPI200 index futures market, introduced in 1996, has become one of the most actively traded indexes markets in the world. Traders can make profit by entering a long position on the KOSPI200 index futures contract if the KOSPI200 index will rise in the future. Likewise, they can make profit by entering a short position if the KOSPI200 index will decline in the future. Basically, KOSPI200 index futures trading is a short-term zero-sum game and therefore most futures traders are using technical indicators. Advanced traders make stable profits by using system trading technique, also known as algorithm trading. Algorithm trading uses computer programs for receiving real-time stock market data, analyzing stock price movements with various technical indicators and automatically entering trading orders such as timing, price or quantity of the order without any human intervention. Recent studies have shown the usefulness of artificial intelligent systems in forecasting stock prices or investment risk. KOSPI200 index data is numerical time-series data which is a sequence of data points measured at successive uniform time intervals such as minute, day, week or month. KOSPI200 index futures traders use technical analysis to find out some patterns on the time-series chart. Although there are many technical indicators, their results indicate the market states among bull, bear and flat. Most strategies based on technical analysis are divided into trend following strategy and non-trend following strategy. Both strategies decide the market states based on the patterns of the KOSPI200 index time-series data. This goes well with Markov model (MM). Everybody knows that the next price is upper or lower than the last price or similar to the last price, and knows that the next price is influenced by the last price. However, nobody knows the exact status of the next price whether it goes up or down or flat. So, hidden Markov model (HMM) is better fitted than MM. HMM is divided into discrete HMM (DHMM) and continuous HMM (CHMM). The only difference between DHMM and CHMM is in their representation of state probabilities. DHMM uses discrete probability density function and CHMM uses continuous probability density function such as Gaussian Mixture Model. KOSPI200 index values are real number and these follow a continuous probability density function, so CHMM is proper than DHMM for the KOSPI200 index. In this paper, we present an artificial intelligent trading system based on CHMM for the KOSPI200 index futures system traders. Traders have experienced on technical trading for the KOSPI200 index futures market ever since the introduction of the KOSPI200 index futures market. They have applied many strategies to make profit in trading the KOSPI200 index futures. Some strategies are based on technical indicators such as moving averages or stochastics, and others are based on candlestick patterns such as three outside up, three outside down, harami or doji star. We show a trading system of moving average cross strategy based on CHMM, and we compare it to a traditional algorithmic trading system. We set the parameter values of moving averages at common values used by market practitioners. Empirical results are presented to compare the simulation performance with the traditional algorithmic trading system using long-term daily KOSPI200 index data of more than 20 years. Our suggested trading system shows higher trading performance than naive system trading.

Selection Model of System Trading Strategies using SVM (SVM을 이용한 시스템트레이딩전략의 선택모형)

  • Park, Sungcheol;Kim, Sun Woong;Choi, Heung Sik
    • Journal of Intelligence and Information Systems
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    • v.20 no.2
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    • pp.59-71
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    • 2014
  • System trading is becoming more popular among Korean traders recently. System traders use automatic order systems based on the system generated buy and sell signals. These signals are generated from the predetermined entry and exit rules that were coded by system traders. Most researches on system trading have focused on designing profitable entry and exit rules using technical indicators. However, market conditions, strategy characteristics, and money management also have influences on the profitability of the system trading. Unexpected price deviations from the predetermined trading rules can incur large losses to system traders. Therefore, most professional traders use strategy portfolios rather than only one strategy. Building a good strategy portfolio is important because trading performance depends on strategy portfolios. Despite of the importance of designing strategy portfolio, rule of thumb methods have been used to select trading strategies. In this study, we propose a SVM-based strategy portfolio management system. SVM were introduced by Vapnik and is known to be effective for data mining area. It can build good portfolios within a very short period of time. Since SVM minimizes structural risks, it is best suitable for the futures trading market in which prices do not move exactly the same as the past. Our system trading strategies include moving-average cross system, MACD cross system, trend-following system, buy dips and sell rallies system, DMI system, Keltner channel system, Bollinger Bands system, and Fibonacci system. These strategies are well known and frequently being used by many professional traders. We program these strategies for generating automated system signals for entry and exit. We propose SVM-based strategies selection system and portfolio construction and order routing system. Strategies selection system is a portfolio training system. It generates training data and makes SVM model using optimal portfolio. We make $m{\times}n$ data matrix by dividing KOSPI 200 index futures data with a same period. Optimal strategy portfolio is derived from analyzing each strategy performance. SVM model is generated based on this data and optimal strategy portfolio. We use 80% of the data for training and the remaining 20% is used for testing the strategy. For training, we select two strategies which show the highest profit in the next day. Selection method 1 selects two strategies and method 2 selects maximum two strategies which show profit more than 0.1 point. We use one-against-all method which has fast processing time. We analyse the daily data of KOSPI 200 index futures contracts from January 1990 to November 2011. Price change rates for 50 days are used as SVM input data. The training period is from January 1990 to March 2007 and the test period is from March 2007 to November 2011. We suggest three benchmark strategies portfolio. BM1 holds two contracts of KOSPI 200 index futures for testing period. BM2 is constructed as two strategies which show the largest cumulative profit during 30 days before testing starts. BM3 has two strategies which show best profits during testing period. Trading cost include brokerage commission cost and slippage cost. The proposed strategy portfolio management system shows profit more than double of the benchmark portfolios. BM1 shows 103.44 point profit, BM2 shows 488.61 point profit, and BM3 shows 502.41 point profit after deducting trading cost. The best benchmark is the portfolio of the two best profit strategies during the test period. The proposed system 1 shows 706.22 point profit and proposed system 2 shows 768.95 point profit after deducting trading cost. The equity curves for the entire period show stable pattern. With higher profit, this suggests a good trading direction for system traders. We can make more stable and more profitable portfolios if we add money management module to the system.

A Comparative Review on Civil Money Penalties in Aviation Law (항공 과징금 제도의 비교법적 검토)

  • Lee, Chang-Jae
    • The Korean Journal of Air & Space Law and Policy
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    • v.34 no.1
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    • pp.3-38
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    • 2019
  • In 1984, Congress enacted a new measure of administrative sanctions which is a civil money penalty program for violations of Aviation Act and its implementing regulations. This civil money penalty system has been in operations in lieu of suspending or revoking certificates issued by Korean government, Ministry of Land, Infrastructure, and Transport. According to the rules of Aviation Business Act or Aviation Safety Act, where the Minister of Land, Infrastructure and Transport should order an air carrier to suspend operation because of her violation under certain rules, in which case the suspension of operation is likely to cause serious inconvenience to consumers of air transport services or to harm public interest, the Minister of the department may impose an administrative monetary penalty in lieu of the suspension of operation. In this regard, airline related civil money penalties are somewhat different from those of fair trade, which is the origin of the money penalties system in Korea. Civil money penalties in the field of fair trade are imposed on executive duty violations that undermine the value of the market economy order, and focus on reimbursement of profits due to violations and compensation for unfair spending by consumers. However, in the aviation sector, breach of duty by a business operator does not simply cause the property loss of the public, but it has a direct impact on life or property of the public. In this respect, aviation penalties are more likely to be administrative sanctions or punitive measures than refunds of unfair benefits, compared to penalties in the field of fair trade. In general, civil money penalties have been highly preferred as administrative sanctions because they are subject to investigations by administrative experts and thus, efficiency can be ensured and execution is quicker than judicial procedures. Moreover, in Korea, because punitive civil damages cannot awarded by the courts, the imposition of civil money penalties is recognized as a means of realizing social justice by recognizing the legal feelings of the people. However, civil money penalties are administrative sanctions, and in terms of effectiveness, they are similar to criminal fines, which are a form of punishment. Inadequate legislation and operation of penalties imposition may cause damage to the value of Constitution. Under the above recognition, this paper has been described for the purpose of identifying the present status of the civil money penalties imposition system and operating status in the area of air transport under the laws and regulations in Korea. Especially, this paper was focused on exploring the problem and improvement direction of Korean system through the comparative study with foreign laws and regulations.

The Effects of Game User's Social Capital and Information Privacy Concern on SNGReuse Intention and Recommendation Intention Through Flow (게임 이용자의 사회자본과 개인정보제공에 대한 우려가 플로우를 통해 SNG 재이용의도와 추천의도에 미치는 영향)

  • Lee, Ji-Hyeon;Kim, Han-Ku
    • Management & Information Systems Review
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    • v.37 no.4
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    • pp.21-39
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    • 2018
  • Today, Mobile Instant Message (MIM) has become a communication means which is commonly used by many people as the technology on smart phones has been enhanced. Among the services, KakaoGame creates much profits continuously by using its representative Kakao platform. However, even though the number of users of KakaoGame increases and the characteristics of the users are more diversified, there are few researches on the relationship between the characteristics of the SNG users and the continuous use of the game. Since the social capital that is formed by the SNG users with the acquaintances create the sense of belonging, its role is being emphasized under the environment of social network. In addition, game user's concerns about the information privacy may decrease the trust on a game APP, and it also caused to threaten about the game system. Therefore, this study was designed to examine the structural relationships among SNG users' social capital, concerns about the information privacy, flow, SNG reuse intention and recommendation intention. The results from this study are as follow. First of all, the participants' bridging social capital had a positive effect on the flow of an SNG, but the bonding social capital had a negative effect on the flow of an SNG. In addition, awareness of information privacy concern had a negative effects on the flow of an SNG, but control of information privacy concern had a positive effect on the flow of an SNG. Lastly, the flow of an SNG had a positive effect on the reuse intention and recommendation intention of an SNG. Also, reuse intention of an SNG had a positive effect on the recommendation intention. Based on the results from this study, academic and practical implications can be drawn. First, This study focused on KakaoTalk which has both of the closed and open characteristics of an SNS and it was found that the SNG user's social capital might be a factor influencing each user's behaviors through the user's flow experiences in SNG. Second, this study extends the scope of prior researches by empirically analysing the relationship between the concerns about the SNG user's information privacy and flow of an SNG. Finally, the results of this research can provide practical guidelines to develop effective marketing strategies considering them for SNG companies.

A Study on the Liability of Artificial Person(Natural Persons) with a Disregard of the Corporate Fiction in ESG (ESG측면에서의 법인격 부인과 법인관계인(자연인)의 책임에 관한 연구)

  • Kim, Dong-han;Kwon, Yong-man
    • Journal of Venture Innovation
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    • v.4 no.3
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    • pp.141-150
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    • 2021
  • Although management decisions centered on the board of directors and directors must be made in order to effectively promote ESG management, the company's management is not obligated to make decisions considering ESG factors. A Korean corporation(company) is an established organization for commercial or other profit, and the purpose of treating a legal organization as a corporation is to easily handle the legal relationship of a group (corporate's property) and individual property of a group member, but legal person such as rights to "harm public rights" or "defend fraud". Criminal liability for illegal acts of a corporation, but the liability of a corporation (natural person) for illegal acts of a corporation is recognized within a limited range, but the criminal liability of a corporation (natural person) is limited. As the social responsibility of a corporation is great, limiting the responsibility of a corporation-related person (natural person) to civil responsibility will halve its effectiveness if considering the impact on the corporation's national economy. Objective requirements such as the completeness of control, hybridization of property, infringement of creditors' rights, and small-capitalization, and the subjective intention of abusing the company system to avoid legal application to controlling shareholders should be denied. Despite the increasing influence on corporate society, such as large-scale projects and astronomical business profits, corporate officials (natural persons) are forced to be held liable for negligence and intentional liability within a limited range. In such cases, it is necessary to introduce criminal responsibility separately from civil responsibility to legal persons (natural persons) in consideration of the maturity of capitalism in Korean society and the economic status of the world. In Korea, the requirements for recognition of corporate denial are strict, but the United States says that it is sufficient to have control or fraud. Therefore, it is not about civil responsibility, but about criminal responsibility of a legal person (natural person), so if fraud is recognized, it can strengthen the corporate social responsibility.

A Study on the Impact of Venture Capital Investment Experience and Job Fit on Fund Formation and Investment Rate of Return (벤처캐피탈의 투자경험과 직무적합도가 펀드결성과 투자수익률에 미치는 영향력에 관한 연구)

  • Kim Dae-Hee;Ha Kyu-So
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.18 no.4
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    • pp.37-50
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    • 2023
  • Venture capital invests the necessary capital and supports management and technology in promising small and medium-sized venture companies in the early stages of start-up with promising technology and excellent manpower. It plays a role as a key player in the venture ecosystem that realizes profits by collecting the investment through various means after growth. Venture capital's job is to recruit various investors(LPs) to invest in small and medium-sized venture companies with growth potential through the formation of venture investment funds, and to collect investment as companies grow, distribute and reinvest. The main tasks of venture capitalists, which play the most important role in venture investment, are finding promising companies, corporate analysis and evaluation, investment screening, follow-up management, and investment recovery. Venture capital's success indicators are fund formation and return on investment, and venture capitalists are rewarded with annual salary, performance-based incentive, and promotion with work performance such as investment, exit, and fund formation. Compared to the recent rapidly growing venture investment market, investment manpower is insufficient, and venture capital is making great efforts to foster manpower and establish infrastructure and systems for long-term service, but research has been conducted mainly from a quantitative perspective. Accordingly, this study aims to empirically analyzed the impact of investment experience, delegation of authority, job fit, and peer relationships on fund formation and return on investment according to the characteristics of the venture capital industry. The results of these empirical studies suggested that future venture capital needs a job environment and manpower operation strategy so that venture capitalists with high job fit and investment experience can work for a long time.

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A Study on Developing a VKOSPI Forecasting Model via GARCH Class Models for Intelligent Volatility Trading Systems (지능형 변동성트레이딩시스템개발을 위한 GARCH 모형을 통한 VKOSPI 예측모형 개발에 관한 연구)

  • Kim, Sun-Woong
    • Journal of Intelligence and Information Systems
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    • v.16 no.2
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    • pp.19-32
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    • 2010
  • Volatility plays a central role in both academic and practical applications, especially in pricing financial derivative products and trading volatility strategies. This study presents a novel mechanism based on generalized autoregressive conditional heteroskedasticity (GARCH) models that is able to enhance the performance of intelligent volatility trading systems by predicting Korean stock market volatility more accurately. In particular, we embedded the concept of the volatility asymmetry documented widely in the literature into our model. The newly developed Korean stock market volatility index of KOSPI 200, VKOSPI, is used as a volatility proxy. It is the price of a linear portfolio of the KOSPI 200 index options and measures the effect of the expectations of dealers and option traders on stock market volatility for 30 calendar days. The KOSPI 200 index options market started in 1997 and has become the most actively traded market in the world. Its trading volume is more than 10 million contracts a day and records the highest of all the stock index option markets. Therefore, analyzing the VKOSPI has great importance in understanding volatility inherent in option prices and can afford some trading ideas for futures and option dealers. Use of the VKOSPI as volatility proxy avoids statistical estimation problems associated with other measures of volatility since the VKOSPI is model-free expected volatility of market participants calculated directly from the transacted option prices. This study estimates the symmetric and asymmetric GARCH models for the KOSPI 200 index from January 2003 to December 2006 by the maximum likelihood procedure. Asymmetric GARCH models include GJR-GARCH model of Glosten, Jagannathan and Runke, exponential GARCH model of Nelson and power autoregressive conditional heteroskedasticity (ARCH) of Ding, Granger and Engle. Symmetric GARCH model indicates basic GARCH (1, 1). Tomorrow's forecasted value and change direction of stock market volatility are obtained by recursive GARCH specifications from January 2007 to December 2009 and are compared with the VKOSPI. Empirical results indicate that negative unanticipated returns increase volatility more than positive return shocks of equal magnitude decrease volatility, indicating the existence of volatility asymmetry in the Korean stock market. The point value and change direction of tomorrow VKOSPI are estimated and forecasted by GARCH models. Volatility trading system is developed using the forecasted change direction of the VKOSPI, that is, if tomorrow VKOSPI is expected to rise, a long straddle or strangle position is established. A short straddle or strangle position is taken if VKOSPI is expected to fall tomorrow. Total profit is calculated as the cumulative sum of the VKOSPI percentage change. If forecasted direction is correct, the absolute value of the VKOSPI percentage changes is added to trading profit. It is subtracted from the trading profit if forecasted direction is not correct. For the in-sample period, the power ARCH model best fits in a statistical metric, Mean Squared Prediction Error (MSPE), and the exponential GARCH model shows the highest Mean Correct Prediction (MCP). The power ARCH model best fits also for the out-of-sample period and provides the highest probability for the VKOSPI change direction tomorrow. Generally, the power ARCH model shows the best fit for the VKOSPI. All the GARCH models provide trading profits for volatility trading system and the exponential GARCH model shows the best performance, annual profit of 197.56%, during the in-sample period. The GARCH models present trading profits during the out-of-sample period except for the exponential GARCH model. During the out-of-sample period, the power ARCH model shows the largest annual trading profit of 38%. The volatility clustering and asymmetry found in this research are the reflection of volatility non-linearity. This further suggests that combining the asymmetric GARCH models and artificial neural networks can significantly enhance the performance of the suggested volatility trading system, since artificial neural networks have been shown to effectively model nonlinear relationships.

The Effect of Brand Extension of Private Label on Consumer Attitude - a focus on the moderating effect of the perceived fit difference between parent brands and an extended brand - (PL의 브랜드확장이 소비자태도에 미치는 영향에 관한 연구 : 모브랜드 적합도 인식 차이의 조절효과를 중심으로)

  • Kim, Jong-Keun;Kim, Hyang-Mi;Lee, Jong-Ho
    • Journal of Distribution Research
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    • v.16 no.4
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    • pp.1-27
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    • 2011
  • Introduction: Sales of private labels(PU have been growing m recent years. Globally, PLs have already achieved 20% share, although between 25 and 50% share in most of the European markets(AC. Nielson, 2005). These products are aimed to have comparable quality and prices as national brand(NB) products and have been continuously eroding manufacturer's national brand market share. Stores have also started introducing premium PLs that are of higher-quality and more reasonably priced compared to NBs. Worldwide, many retailers already have a multiple-tier private label architecture. Consumers as a consequence are now able to have a more diverse brand choice in store than ever before. Since premium PLs are priced higher than regular PLs and even, in some cases, above NBs, stores can expect to generate higher profits. Brand extensions and private label have been extensively studied in the marketing field. However, less attention has been paid to the private label extension. Therefore, this research focuses on private label extension using the Multi-Attribute Attitude Model(Fishbein and Ajzen, 1975). Especially there are few studies that consider the hierarchical effect of the PL's two parent brands: store brand and the original PL. We assume that the attitude toward each of the two parent brands affects the attitude towards the extended PL. The influence from each parent brand toward extended PL will vary according to the perceived fit between each parent brand and the extended PL. This research focuses on how these two parent brands act as reference points to one another in the consumers' choice consideration. Specifically we seek to understand how store image and attitude towards original PL affect consumer perceptions of extended premium PL. How consumers perceive extended premium PLs could provide strategic suggestions for retailer managers with specific suggestions on whether it is more effective: to position extended premium PL similarly or dissimilarly to original PL especially on the quality dimension and congruency with store image. There is an extensive body of research on branding and brand extensions (e.g. Aaker and Keller, 1990) and more recently on PLs(e.g. Kumar and Steenkamp, 2007). However there are no studies to date that look at the upgrading and influence of original PLs and attitude towards store on the premium PL extension. This research wishes to make a contribution to this gap using the perceived fit difference between parent brands and extended premium PL as the context. In order to meet the above objectives, we investigate which factors heighten consumers' positive attitude toward premium PL extension. Research Model and Hypotheses: When considering the attitude towards the premium PL extension, we expect four factors to have an influence: attitude towards store; attitude towards original PL; perceived congruity between the store image and the premium PL; perceived similarity between the original PL and the premium PL. We expect that all these factors have an influence on consumer attitude towards premium PL extension. Figure 1 gives the research model and hypotheses. Method: Data were collected by an intercept survey conducted on consumers at discount stores. 403 survey responses were attained (total 59.8% female, across all age ranges). Respondents were asked to respond to a series of Questions measured on 7 point likert-type scales. The survey consisted of Questions that measured: the trust towards store and the original PL; the satisfaction towards store and the original PL; the attitudes towards store, the original PL, and the extended premium PL; the perceived similarity of the original PL and the extended premium PL; the perceived congruity between the store image and the extended premium PL. Product images with specific explanations of the features of premium PL, regular PL and NB we reused as the stimuli for the Question response. We developed scales to measure the research constructs. Cronbach's alphaw as measured each construct with the reliability for all constructs exceeding the .70 standard(Nunnally, 1978). Results: To test the hypotheses, path analysis was conducted using LISREL 8.30. The path analysis for verification of the model produced satisfactory results. The validity index shows acceptable results(${\chi}^2=427.00$(P=0.00), GFI= .90, AGFI= .87, NFI= .91, RMSEA= .062, RMR= .047). With the increasing retailer use of premium PLBs, the intention of this research was to examine how consumers use original PL and store image as reference points as to the attitude towards premium PL extension. Results(see table 1 & 2) show that the attitude of each parent brand (attitudes toward store and original pL) influences the attitude towards extended PL and their perceived fit moderates these influences. Attitude toward the extended PL was influenced by the relative level of perceived fit. Discussion of results and future direction: These results suggest that the future strategy for the PL extension needs to consider that positive parent brand attitude is more strongly associated with the attitude toward PL extensions. Specifically, to improve attitude towards PL extension, building and maintaining positive attitude towards original PL is necessary. Positioning premium PL congruently to store image is also important for positive attitude. In order to improve this research, the following alternatives should also be considered. To improve the research model's predictive power, more diverse products should be included in study. Other attributes of product should also be included such as design, brand name since we only considered trust and satisfaction as factors to build consumer attitudes.

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Empirical Analysis on Bitcoin Price Change by Consumer, Industry and Macro-Economy Variables (비트코인 가격 변화에 관한 실증분석: 소비자, 산업, 그리고 거시변수를 중심으로)

  • Lee, Junsik;Kim, Keon-Woo;Park, Do-Hyung
    • 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.

Unfair Restrain on Competition in Air Cargo Fuel Surcharge Case (공정거래법상 부당한 경쟁제한의 의미 - 항공화물 유류할증료 담합사건을 중심으로 -)

  • Lee, Chang Jae
    • The Korean Journal of Air & Space Law and Policy
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    • v.30 no.1
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    • pp.117-149
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    • 2015
  • On May 16, 2014 the Supreme Court of Korea rendered its decision with respect to litigation filed by All Nippon Airways Co., Ltd. ("ANA") for revocation of an order of correction and payment of a penalty imposed by the Korea Fair Trade Commission ("KFTC"). On or around September 2002, ANA and various airlines operating air cargo service from Japan to Korea were allegedly to have agree to introduce of fuel surcharge into their rates on cargo fares in an attempt to recoup falling profits from rising of oil price. As this hard core cartel was per se prohibited under Korean competition law (The Monopoly Regulation And Fair Trade Act), KFTC began an investigation and consequently with fruitful results imposed an amount of penalty and issued an order of prohibition. ANA protested against this imposition by filing suit against KFTC under the reasons that (1) their agreement was simply pursuant to the relevant laws and regulations including Air Transport Agreement between Korea and Japan, (2) there was an administrative guidance from Japanese government to allow this agreement, (3) extraterritorial application of Korean competition law to the agreement in this matter was improper as it was made within Japan and targeted only for the shipment from Japan to Korea: accordingly there is not a direct and serious effect between the agreement and any result of anti-competitive. This article aims to review ANA's allegation and the judgement delivered by Korean court under some issues respectively; (1) whether there is an effectively actual anti-competitive cartel between airlines including plaintiff, (2) whether filed rate doctrine is reasonable and applicable in this case for precluding wrongfulness, (3) what is the reasonable limitation of boundaries in extraterritorial application of Korean competition law. Additionally, this article also suggests to concern particular features of air transport business as an regulated industry in judging the unfair restrain on competition.