• Environmental and Resource Economics Review
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• v.30 no.4
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• pp.535-555
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• 2021

This study empirically analyzes the effects of international oil prices on domestic stock market volatility. The data used for the analysis are 10-minute high-frequency data of the KOSPI index and WTI futures price from January 2, 2015, to July 30, 2021. For using the high-frequency data, a heterogeneous autoregression (HAR) model is employed. The analysis model utilizes the advantages of high frequency data to observe the impact of international oil prices through realized volatility, realized skewness, and kurtosis as well as oil price return. In the estimation, the Box-Cox transformation is applied in consideration of the distribution of realized volatility with high skewness. As a result, it finds that the daily return fluctuation of the WTI price has a statistically significant positive (+) effect on the volatility of the KOSPI return. However, the volatility, skewness, and kurtosis of the WTI return do not appear to affect the volatility of the KOSPI return. This result is believed to be because the volatility of the KOSPI return reflects the daily change in the WTI return, but does not reflect the intraday trading behavior of investors.

• Journal of Digital Convergence
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• v.13 no.11
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• pp.45-55
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• 2015

This study used for KOSPI, KOSDAQ, entertainment culture and digital contents index that is related to cultural contents industry. There was investigated the each stock price index and return trends for a total 597 weeks to July 2015 from March 2004. They looked the content-related stocks about investment worth to comparative analysis the return, volatility, correlation, synchronization phenomena etc. of each stock index. When we saw the growth potential of the cultural contents industry forward, looked forward to the investment possibility of related stocks. Analysis Result cultural content related stocks showed a higher rate after the last 2008 global financial crisis. Recent as high interest in the cultural contents industry, we could see that the investment merit increases slowly. In the future, the cultural content industry is expected to continue to evolve. The increase of investments value in the cultural content related businesses is much expectation.

• Korean journal of communication and information
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• v.34
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• pp.244-274
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• 2006

To explore the social construction of the concept of leadership, image of media mogul depicted in the popular business newspaper, the Wall Street Journal, was analyzed. Then, the reconstructed image of the CEO was compared with the firm's stock price change to see their relationship, if any. This paper focused on the case of Steve Case (previous chairman of AOL Time Warner), who was the leader of the world largest media company. The period for the analysis was three years and five months from his inauguration(January 2000) to the resignation(May 2003). In general, CEO of a firm represents the firm itself. Thus, the image of the CEO is highly transcends to the image of the firm as well. Consequently, the image of CEO might have an impact on the firm's performance. Since business newspaper works as one of the most important information intermediaries in the stock market, the image of CEO constructed in the newspaper might be a critical indicator for the investors. The results revealed that media coverage of Steve Case was commensurate with the financial performance, particularly stock price change of the AOL Time Warner.

• Journal of Digital Convergence
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• v.11 no.11
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• pp.59-70
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• 2013

As people invest most of their asset in real estate, there is high interest in changing in housing and real estate prices in the future for a digital economy. Various variables are affecting the housing and real estate market. Among them, four variables : households, productive population, interest rate and index price are chosen and analyzed representatively. This study is aimed to build decision model of apartment prices in Seoul empirically. From the analysis result the stock index is the only variable which is significant statistically to apartments in Seoul. From this study, the households and productive population show the same direction as shown in the previous studies before but not significant statistically. Among the independent variables, the stock index is chosen as a major variable of determinant of Seoul apartment price. From the result of the research, prediction of stock market should be preceded to forecast the movement of housing and real estate market in the future.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1007-1011
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• 2006

본 연구에서는 어류 생태계 유지를 위해 필요한 생태학적 추천유량을 산정하고, 어류의 서식처 환경인 여울과 웅덩이의 형성조건을 검토함으로써 '작용'인 '흐름'과 '응답'인 '하상구조'와의 상관 관계를 규명하고자 하였다. 본 연구의 대상하천인 금호강에서는 하상변동이 활발한 자연 상태를 벗어나 하상의 이동성 상당히 둔화된 상태이며, 저수로내 여울과 웅덩이도 대표어종이 서식할 수 있는 자갈하상 구조에 변화가 일어나고 있는 것으로 분석되었다. 이것은 금호강 상류에 영천댐 건설의 영향이 어느 정도 미치고 있음을 유황분석 결과를 통해 간접적으로 파악할 수 있었다. 댐과 같은 수공구조물의 건설로 인하여 하도가 고정화된 상태에서 장기간에 걸치게 되면 여울과 웅덩이와 같은 하상구조가 축소되거나 소멸되어 금호강에서의 대표어종 서식처 환경에 영향을 미칠 것으로 추정된다. 금번 연구결과, 금호강에서 어류의 생식에 필요한 생태학적 추천유량 $8.2m^3/sec$가 필요하였으며, 어류의 서식처 환경인 여울과 웅덩이를 지속적으로 유지되기 위해서는 $250m^3/sec$ 이상의 유량이 연간 한번 이상 흘러야 하고, 2.5년 내지 3년 마다 약 $500m^3/sec$ 정도의 유량이 흐를 필요가 있다고 분석되었다. 본 연구 대상지점에서 흐름과 하상구조를 하천생태계와 연계해서 볼 때, 생태추천유량은 어디까지나 대표어종이 서식할 수 있는 최소조건에 불과하다. 대표어종이 장기간에 걸쳐 서식할 수 있는 하상구조가 존재하기 위해서는 대표어종이 선호하는 여울과 웅덩이가 필요하다. 결국 대표어종이 서식하기 위한 필요충분조건은 생태추천유량 확보와 아울러 대표어종이 선호하는 하상구조를 유지하기 위해서는 하도의 이동성을 유발할 유황변화가 필요하다는 것이 입증되었다.대상으로 연중 발생하는 큰 호우사상에 대해 임의의 강우관측소를 결측지점으로 가정하고 주변의 강우관측소로부터 각각의 방법을 이용해 가중치들을 산정하여 결측지점의 강우량 값을 보정하고자 하였다. 또한 각각의 방법을 이용하여 얻어진 결과에 대해 실측값과 보정값의 오차정도를 평균절대오차법(Mean Absolute Error)과 제곱평균제곱근오차법(Root Mean Squared Error)에 의해 산정하여 보정 방법간의 효율성을 검토하고자 하였다.9년, 그리고 2010년${\sim}$2019년까지 총 4구간으로 나누어 결과를 도출하였으며 예상한 바와 같이 후반기 20년 동안에 세 가지 지표가 취약해 지는 것을 확인할 수 있었고, 특히 2000년부터 2009년까지 10년 동안에는 더욱 취약해짐을 확인할 수 있었다.를 보임에 따라 그 정책적 효과는 때로 역기능적인 결과로 초래하였다. 그럼에도 불구하고 이 연구결과를 통하여 최소한 주식시장(株式市場)에서 위탁증거금제도는 그 제도적 의의가 여전히 있다는 사실이 확인되었다. 또한 우리나라 주식시장에서 통상 과열투기 행위가 빈번히 일어나 주식시장을 교란시킴으로써 건전한 투자풍토조성에 저해된다는 저간의 우려가 매우 커왔으나 표본 기간동안에 대하여 실증분석을 한 결과 주식시장 전체적으로 볼 때 주가변동율(株價變動率), 특히 초과주가변동율(超過株價變動率)에 미치는 영향이 그다지 심각한 정도는 아니었으며 오히려 우리나라의 주식시장은 미국시장에 비해 주가가 비교적 안정적인 수준을 유지해 왔다고 볼 수 있다.36.4%)와 외식을 선호(29.1%)${\lrcorner}$ 하기 때문에 패스트푸드를 이용하게 된 것으로 응답 하였으며, 남 여 대학생간에는 유의한 차이(p<0.05)가 인정되었다. 응답자의 체형은 ${\ulco

• Management & Information Systems Review
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• v.36 no.3
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• pp.203-217
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• 2017

This study aims to verify the effects of unrealized gain or loss, that is the fair value evaluation item of insurance company's assets and liabilities, to capital markets focusing on fair value evaluation of insurance company's liabilities, which is the core of IFRS 17 that will be implemented in 2021. For this purpose we carried out regression analysis to verify the effects of changed other comprehensive income(OCI) and accumulated OCI, published in quarterly financial statements of listed insurance companies, on stock price utilizing Ohlson(1995)'s extended test model. The results of the empirical analysis are as follows. First, changed OCI showed a significant negative(-) effects on stock price. Second, accumulated OCI revealed a significant positive(+) effects on stock price. Furthermore, extended test model classifying changed OCI and accumulated OCI in a basic model represented the highest $R^2$ number and public announcement policy of OCI, a kind of unrealized gain or loss item, implied that it could give positive impact on accounting information. But still the direction that unrealized gain or loss affects on firm value must be carefully reviewed and considered in the future via more detailed study by the user of information. Therefore this study is meaningful in that it can predict usefulness of information on insurance company's fair value evaluation via empirical test accompanied by introduction of newly established IFRS 17 and it also can suggest direction of information production suitable for capital market.

• The Korean Journal of Financial Management
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• v.21 no.1
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• pp.205-229
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• 2004

The deviation from put-call parity condition may affect market prices since it provides an opportunity of arbitrage to many participants. This study uses the KOSPI200 index data and examines the interdependence among spot, futures, and options contracts by examining whether the deviations from the parity have significant roles in price formation. Whenever the parity condition is violated, the deviation tends to affect the prices significantly in most markets. The results show that positive values of deviation are associated with the fall of the prices in the spot and put option contracts and the rise of the call option premiums, thus decreasing the deviations. Also, the decreasing impact of deviations lasts for at Beast an hour in most markets. Futures prices, however, do not show clear relations with the deviations, which suggests the possibility that futures markets lead other markets.

• The Korean Journal of Financial Management
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• v.16 no.2
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• pp.27-51
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• 1999

본 연구는 사업구조조정을 위하여 기업이 자발적으로 자산을 매각할 때, 부채변제 목적으로 자산을 매각하는 경우를 제외한 재투자 목적으로 자산을 매각한 경우에 없어 자산매각에 따른 주가변동인 공시효과를 살펴보고 또한 이런 공시효과가 매각기업의 매각직전 경영성과인 Tobin's Q에 따라 달리 나타날 수 있으므로 이에 따른 공시효과의 차이를 비교해 본다. 그 다음에, 기업이 자산매각을 통하여 확보한 유동성을 새로 재투자할 기회를 갖는 자산매각의 경우에 있어, 이런 기회가 사업을 집중화할 목적인지 혹은 아닌지에 따라 장기간의 경영성과인 Tobin's Q와 어떤 영향관계를 갖는 지와, 또 매각자산의 상대적 매각규모가 장기간의 경영성과와 어떤 영향관계를 갖는 지를 분석한다. 분석결과, 자산매각에 대한 중시효과는 통계적으로 유의한 정의 비정상수익률을 실현하였으며, 자산매각직전의 경영성과를 나타내는 Tobin's Q값의 우열에 따리 분류한 4사분위별 집단의 비정상수익률은 Tobin's Q값이 낮거나 높은 기업일수록 정의 비정상수익률을 크게 실현하였다. 그리고 사업을 집중화할 목적으로 자산매각을 실시한 경우와 그렇지 않은 경우에 없어서 경영성과는 두 집단간에 유의적인 차이를 나타냈으나, 매각이후 각 연도기말의 Tobin's Q값들 사이에 대한 전년도와의 차이는 통계적인 유의성을 찾을 수가 없었다. 그렇지만 기업의 경영성과인 Tobin's Q는 집중화 집단이 비집중화 집단보다 크게 나타났었다. 또한 자산매각 이후에 없어, Tobin's Q와 집중화등기 및 상대적 매각규모는 유의적인 정의 관계를 나타냈다.었다.가 높은 한국, 영국, 독일에서는 환율이 주가에 비해 선행하여 변동한다고 볼 수 있다.하는 것이 필요할 것이다. 초과가치가 크게 나타나는 것으로 분석되어, 다각화 기업이 더 많은 부채부담능력을 가질 수 있고, 부채의 세금절감효과에 의해 기업가치를 증가시킬 수 있음을 알 수 있었다.있는 과정이므로 장기기대 주가의 미지성이 평균회귀 과정의 기각을 유도하게 된다. 우리나라의 투자자들은 무위험자산과 위험을 동시에 고려하여 투자활동을 전개하고 있음이 발견되었다. 선형의 효용함수를 갖는 위험중립적 태도의 투자자가 아니다. 위험기피형 효용함수 아래에서 투자활동을 수행하고 있는 합리적 투자자들이라 할 수 있다. 뿐 만 아니라 자신의 평생에 걸친 소비를 소비가 이루어지는 각 기마다 가급적 일정하게 하는 소비행동을 목표로 삼고 소비와 투자에 대한 의사결정을 내리고 있음이 실증분석을 통하여 밝혀졌다. 투자자들은 무위험 자산과 위험성 자산을 동시에 고려하여 포트폴리오를 구성하는 투자활동을 행동에 옮기고 있다.서, Loser포트폴리오를 매수보유하는 반전거래전략이 Winner포트폴리오를 매수보유하는 계속거래전략보다 적합한 전략임을 알 수 있었다. 다섯째, Loser포트폴리오와 Winner포트폴리오를 각각 투자대상종목으로써 매수보유한 반전거래전략과 계속거래 전략에 대한 유용성을 비교검증한 Loser포트폴리오와 Winner포트폴리오 각각의 1개월 평균초과수익률에 의하면, 반전거래전략의 Loser포트폴리오가 계속거래전략의 Winner포트폴리오보다 약 5배정도의 높은 1개월 평균초과수익률을 실현하였고, 반전거래전략의 유용성을

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.103-128
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• 2021

Recently, investors' interest and the influence of stock-related information dissemination are being considered as significant factors that explain stock returns and volume. Besides, companies that develop, distribute, or utilize innovative new technologies such as artificial intelligence have a problem that it is difficult to accurately predict a company's future stock returns and volatility due to macro-environment and market uncertainty. Market uncertainty is recognized as an obstacle to the activation and spread of artificial intelligence technology, so research is needed to mitigate this. Hence, the purpose of this study is to propose a machine learning model that predicts the volatility of a company's stock price by using the internet search volume of artificial intelligence-related technology keywords as a measure of the interest of investors. To this end, for predicting the stock market, we using the VAR(Vector Auto Regression) and deep neural network LSTM (Long Short-Term Memory). And the stock price prediction performance using keyword search volume is compared according to the technology's social acceptance stage. In addition, we also conduct the analysis of sub-technology of artificial intelligence technology to examine the change in the search volume of detailed technology keywords according to the technology acceptance stage and the effect of interest in specific technology on the stock market forecast. To this end, in this study, the words artificial intelligence, deep learning, machine learning were selected as keywords. Next, we investigated how many keywords each week appeared in online documents for five years from January 1, 2015, to December 31, 2019. The stock price and transaction volume data of KOSDAQ listed companies were also collected and used for analysis. As a result, we found that the keyword search volume for artificial intelligence technology increased as the social acceptance of artificial intelligence technology increased. In particular, starting from AlphaGo Shock, the keyword search volume for artificial intelligence itself and detailed technologies such as machine learning and deep learning appeared to increase. Also, the keyword search volume for artificial intelligence technology increases as the social acceptance stage progresses. It showed high accuracy, and it was confirmed that the acceptance stages showing the best prediction performance were different for each keyword. As a result of stock price prediction based on keyword search volume for each social acceptance stage of artificial intelligence technologies classified in this study, the awareness stage's prediction accuracy was found to be the highest. The prediction accuracy was different according to the keywords used in the stock price prediction model for each social acceptance stage. Therefore, when constructing a stock price prediction model using technology keywords, it is necessary to consider social acceptance of the technology and sub-technology classification. The results of this study provide the following implications. First, to predict the return on investment for companies based on innovative technology, it is most important to capture the recognition stage in which public interest rapidly increases in social acceptance of the technology. Second, the change in keyword search volume and the accuracy of the prediction model varies according to the social acceptance of technology should be considered in developing a Decision Support System for investment such as the big data-based Robo-advisor recently introduced by the financial sector.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1213-1229
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• 2016

Cho and Shin (2016) recently demonstrated that an integrated HAR model has a forecast advantage over the HAR model of Corsi (2009). Recalling that realized volatilities of financial assets have asymmetries, we add a leverage term to the integrated HAR model, yielding the LIHAR model. Out-of-sample forecast comparisons show superiority of the LIHAR model over the HAR and IHAR models. The comparison was made for all the 20 realized volatilities in the Oxford-Man Realized Library focusing specially on the DJIA, the S&P 500, the Russell 2000, and the KOSPI. Analysis of the realized volatility data sets reveal apparent long-memory and asymmetry. The LIHAR model takes advantage of the long-memory and asymmetry and produces better forecasts than the HAR, IHAR, LHAR models.