• 경영과정보연구
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• 제30권4호
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• pp.147-173
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• 2011

본 논문은 효율적 시장가설의 이례현상(anomalies)의 하나인 주가의 시계열 상관성과 관련하여 과거의 주식수익률(price change)과 함께 주가수준(price level)을 이용한 투자전략들의 성과에 초점을 맞추어 어떤 투자전략이 지속적으로 유의하며 경제적 유용성을 지니고 있는가를 검증하고 정성적으로나마 그 원인이 무엇인지를 도출하고자 한 것이다. 전체 표본기간을 대상으로 한 연구에서는 수익률 이용 반대투자전략(이후 JT반대투자전략)과 연중최고가 이용 반대투자전략(이후 GH반대투자전략)은 12개월 보유기간에서 각각 월평균 0.49%와 0.28%의 통계적으로 유의적 성과를 보였으며 나머지 보유기간에서는 비유의적인 양(+)의 값을 나타내었다. 쌍대비교 검증으로 두 투자전략의 우수성을 검증한 결과는 GH승자포트폴리오에서 JT반대투자전략이 월평균 0.50%를 시현하여 모든 JT포트폴리오들에 대하여 유의적인 설명력을 갖지 못한 GH반대투자전략보다 우수한 것으로 확인되었다. 이러한 결과들만 두고 본다면 1988년부터 2000년까지를 표본으로 한 안재욱, 김영빈(2004)의 선행 연구결과와 다소 상반되는 것이다. 그러나 체계적 위험을 고려한 위험조정수익률로 성과를 산출하면 6개월 보유 JT반대투자전략과 GH반대투자전략의 성과는 0.09%와 042%로 서로 엇갈리나 통계적으로 유의성을 갖지 못하고 반대투자전략이 유의적으로 나타난 12개월 보유기간 두 반대투자전략의 성과 역시 0.22%와 -0.06%로 유의적이지 못한 결과를 실현하여 두 방식 모두 반대투자전략이 유효한 투자전략이 될 수 없다는 사실을 확인하였다. 이를 명확히 하기 위하여 베타를 통제한 후 반대투자전략을 실행하여 검증한 결과 JT반대투자전략의 성과 검증결과는 베타의 크고 작음에 상관없이 유의적인 양(+)의 성과가 확인됨으로써 사후적인 역사적 베타에 의한 위험조정수익률의 산정과 활용에는 한계점이 있음을 알 수 있다.

• 한국시스템다이내믹스연구
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• 제2권2호
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• pp.25-40
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• 2001

This paper describes the forecast of power plant construction in a competitive korean electricity market. In Korea, KEPCO (Korea Electric Power Corporation, fully controlled by government) was responsible for from the production of the electricity to the sale of electricity to customer. However, the generation part is separated from KEPCO and six generation companies were established for whole sale competition from April 1st, 2001. The generation companies consist of five fossil power companies and one nuclear power company in Korea at present time. Fossil power companies are scheduled to be sold to private companies including foreign investors. Nuclear power company is owned and controlled by government. The competition in generation market will start from 2003. ISO (Independence System Operator will purchase the electricity from the power exchange market. The market price is determined by the SMP(System Marginal Price) which is decided by the balance between demand and supply of electricity in power exchange market. Under this uncertain circumstance, the energy policy planners such as government are interested to the construction of the power plant in the future. These interests are accelerated due to the recent shortage of electricity supply in California. In the competitive market, investors are no longer interested in the investment for the capital intensive, long lead time generating technologies such as nuclear and coal plants. Large unclear and coal plants were no longer the top choices. Instead, investors in the competitive market are interested in smaller, more efficient, cheaper, cleaner technologies such as CCGT(Combined Cycle Gas Turbine). Electricity is treated as commodity in the competitive market. The investors behavior in the commodity market shows that the new investment decision is made when the market price exceeds the sum of capital cost and variable cost of the new facility and the existing facility utilization depends on the marginal cost of the facility. This investors behavior can be applied to the new investments for the power plant. Under these postulations, there is the potential for power plant construction to appear in waves causing alternating periods of over and under supply of electricity like commodity production or real estate production. A computer model was developed to sturdy the possibility that construction will appear in waves of boom and bust in Korean electricity market. This model was constructed using System Dynamics method pioneered by Forrester(MIT, 1961) and explained in recent text by Sternman (Business Dynamics, MIT, 2000) and the recent work by Andrew Ford(Energy Policy, 1999). This model was designed based on the Energy Policy results(Ford, 1999) with parameters for loads and resources in Korea. This Korea Market Model was developed and tested in a small scale project to demonstrate the usefulness of the System Dynamics approach. Korea electricity market is isolated and not allowed to import electricity from outsides. In this model, the base load such as unclear and large coal power plant are assumed to be user specified investment and only CCGT is selected for new investment by investors in the market. This model may be used to learn if government investment in new unclear plants could compensate for the unstable actions of private developers. This model can be used to test the policy focused on the role of unclear investments over time. This model also can be used to test whether the future power plant construction can meet the government targets for the mix of generating resources and to test whether to maintain stable price in the spot market.

• 국제지역연구
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• 제14권1호
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• pp.99-119
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• 2010

본 연구는 미국의 천연가스시장과 석유시장, 그리고 유럽의 석유시장을 대상으로 두가지 분석에 주안점을 두었다. 하나는 그랜저 인과관계(Granger-causality) 검증을 통하여 수익률과 변동성 부문에 있어 이질적 상품시장간 또는 동일상품시장내 현/선물간 예측력(predictive power) 여부 확인이며, 다른 하나는 회귀분석을 통한 선물가격의 현물가격 안정화 효과이다. 상품시장간 예측력에서 수익률 부문은 현물수익률과 선물수익률이 서로 상반된 양상을 보였지만 전체적으로 통계적 유의성이 낮게 나타났다. 변동성 부문에서는 석유시장이 천연가스시장에 가지는 예측력과는 달리 천연가스시장은 석유시장에 별다른 영향을 주지 못하는 것을 확인 할 수 있었다. 동일상품시장내 예측력 분석의 수익률 부문에서는 유일하게 유럽 석유시장의 현물수익률이 선물수익률에 예측정보를 가짐을 알 수 있었다. 변동성 부문은 모든 상품시장에서 현물과 선물간 인과관계가 양방향으로 성립함을 확인하였다. 선물가격의 현물가격 안정화 효과 분석 결과, 선물변동성은 현물변동성을 증가시키는 것으로 나타났다.

• 한국전자통신학회논문지
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• 제6권4호
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• pp.567-572
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• 2011

본 연구의 목적은 완전 경쟁시장에 가까운 중고 아파트 시장의 실거래정보를 이용하여 분양 아파트의 적정 분양가와 계약률을 측정하고자 하는 것이다. 이를 위해 중고아파트 시장을 기준으로 신규주택 시장과의 연관성을 살펴 보았으며 종전 선행 연구의 문제점을 보완한 실증 분석을 실시하였다.

• 응용통계연구
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• 제21권5호
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• pp.755-763
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• 2008

This paper approaches the problem of option pricing in an incomplete market, where the underlying asset price process follows a compound Poisson model. We assume that the price process follows a compound Poisson model under an equivalent martingale measure and it converges weakly to the Black-Scholes model. First, we express the option price as the expectation of the discounted payoff and expand it at the Black-Scholes price to obtain a pricing formula with three unknown parameters. Then we estimate those parameters using the market option data. This method can use the option data on the same stock with different expiration dates and different strike prices.

• 경영과정보연구
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• 제25권
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• pp.321-337
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• 2008

The house price rise suddenly is not only Economic stability but economic, mental state of a heavy burden to people. This paper is a house finance environment analyzed in this research about the rise factor of the house price and the result to present the plan to the natural disposition. The financial institute has an influence on the disguised demand extension of the house and The mortgage Lending in commercial Banks with the earnings as the stability high than the industry loaning. A house finance environment changes and will go from economic factor of the variety of the life style, the housing conditional according to the income level, a children education condition, and the population structure many this little. The disposition of the house need changes according to this and will have an influence on the house price. Necessary for a house market environment house policy of the market need which the consistency reflects so that we are suitable and is desired.

• 한국컴퓨터정보학회논문지
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• 제22권11호
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• pp.111-116
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• 2017

This paper proposes a data mining approach to predicting stock price direction. Stock market fluctuates due to many factors. Therefore, predicting stock price direction has become an important issue in the field of stock market analysis. However, in literature, there are few studies applying data mining approaches to predicting the stock price direction. To contribute to literature, this paper proposes comparing single classifiers and ensemble classifiers. Single classifiers include logistic regression, decision tree, neural network, and support vector machine. Ensemble classifiers we consider are adaboost, random forest, bagging, stacking, and vote. For the sake of experiments, we garnered dataset from Korea Stock Exchange (KRX) ranging from 2008 to 2015. Data mining experiments using WEKA revealed that random forest, one of ensemble classifiers, shows best results in terms of metrics such as AUC (area under the ROC curve) and accuracy.

• International Journal of Computer Science & Network Security
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• 제22권2호
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• pp.185-192
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• 2022

Forecasting and time series modelling plays a vital role in the data analysis process. Time Series is widely used in analytics & data science. Forecasting stock prices is a popular and important topic in financial and academic studies. A stock market is an unregulated place for forecasting due to the absence of essential rules for estimating or predicting a stock price in the stock market. Therefore, predicting stock prices is a time-series problem and challenging. Machine learning has many methods and applications instrumental in implementing stock price forecasting, such as technical analysis, fundamental analysis, time series analysis, statistical analysis. This paper will discuss implementing the stock price, forecasting, and research using prophet and LSTM models. This process and task are very complex and involve uncertainty. Although the stock price never is predicted due to its ambiguous field, this paper aims to apply the concept of forecasting and data analysis to predict stocks.

• 유통과학연구
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• 제11권10호
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• pp.73-79
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• 2013

Purpose - This study examines the impact of oil price volatility on economic activities in Korea. The new millennium has seen a deregulation in the crude oil market, which invited immense capital inflow into Korea. It has also raised oil price levels and volatility. Drawing on the recent theoretical literature that emphasizes the role of volatility, this paper attends to the asymmetric changes in economic growth in response to the oil price movement. This study further examines several key macroeconomic variables, such as interest rate, production, and inflation. We come to the conclusion that oil price volatility can, in some part, explain the structural changes. Research design, data, and methodology - We use two methodological frameworks in this study. First, in regards to the oil price uncertainty, we use an Exponential-GARCH (Exponential Generalized Autoregressive Conditional Heteroskedasticity: EGARCH) model estimate to elucidate the asymmetric effect of oil price shock on the conditional oil price volatility. Second, along with the estimation of the conditional volatility by the EGARCH model, we use the estimates in a VECM (Vector Error Correction Model). The study thus examines the dynamic impacts of oil price volatility on industrial production, price levels, and monetary policy responses. We also approximate the monetary policy function by the yield of monetary stabilization bond. The data collected for the study ranges from 1990: M1 to 2013: M7. In the VECM analysis section, the time span is split into two sub-periods; one from 1990 to 1999, and another from 2000 to 2013, due to the U.S. CFTC (Commodity Futures Trading Commission) deregulation on the crude oil futures that became effective in 2000. This paper intends to probe the relationship between oil price uncertainty and macroeconomic variables since the structural change in the oil market became effective. Results and Conclusions - The dynamic impulse response functions obtained from the VECM show a prolonged dampening effect of oil price volatility shock on the industrial production across all sub-periods. We also find that inflation measured by CPI rises by one standard deviation shock in response to oil price uncertainty, and lasts for the ensuing period. In addition, the impulse response functions allude that South Korea practices an expansionary monetary policy in response to oil price shocks, which stems from oil price uncertainty. Moreover, a comparison of the results of the dynamic impulse response functions from the two sub-periods suggests that the dynamic relationships have strengthened since 2000. Specifically, the results are most drastic in terms of industrial production; the impact of oil price volatility shocks has more than doubled from the year 2000 onwards. These results again indicate that the relationships between crude oil price uncertainty and Korean macroeconomic activities have been strengthened since the year2000, which resulted in a structural change in the crude oil market due to the deregulation of the crude oil futures.

• Journal of Information Technology Applications and Management
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• 제19권2호
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• pp.217-231
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• 2012

In the past, companies should make enormous facility investment and acquire a right to do business in order to join communication markets, but now they can do business without important facilities, such as communication networks. Such a movement to ease regulations about companies which want to newly join the communication industry is expected not only to change a competition frame of the mobile communication market but also to greatly affect the entire communication industry. Through this study aiming to look into a way to calculate a reasonable wholesale price related to the government's introduction of the Mobile Virtual Network Operator (MVNO) system, I came up with a following result. I applied the operating profit percentage and the ratio of operating gain to cost to the cost plus model and retail minus model, respectively, to calculate the wholesale price and found that when I calculated with the cost plus model applying the operating profit percentage, I could get the highest wholesale price. On the other hand, I got the lowest wholesale price with the retail minus model by applying the operating profit percentage. Division of expenses and calculation of profit percentage are important factors in calculating the wholesale price and such results are expected to help accurate calculation of the MVNO wholesale price.