• Title/Summary/Keyword: 주식가격

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The Empirical Information Spillover Effect between the Housing Market and the Stock Market (주택시장과 주식시장 간의 정보 이전효과의 연구)

  • Choi, Chasoon
    • Land and Housing Review
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    • v.12 no.3
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    • pp.27-37
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    • 2021
  • This paper empirically examined the relationship between the housing market and the stock market to investigate the price and the asymmetric volatility spillover effects. The monthly housing price index and the monthly KOSPI were used for analysis. This research employed the EGARCH model. The analysis period was from January 1986 until June 2021 with periodization centered on the Asian Financial Crisis: before and after the crisis - the end of December 1997. The EGARCH model allows analysis of 'good news' and 'bad news' in understanding volatility. The price spillover effect was observed one way from the stock market to the housing market. On the contrary, the spillover effect was not found from the housing market to the stock market. The empirical evidence suggests that there are price and asymmetric volatility effects in the entire period of analysis in both housing and the stock markets. In the housing market, the negative effects of information were found pre-financial crisis while the positive effects, in other periods. However, in the stock market, the negative effects of information were found in the pre- and post-financial crisis periods. This means that the housing market is more affected by 'good news' than 'bad news' when information spreads to the markets while the stock market is more affected by 'bad news' than 'good news'. It is of significance to discover the variable returns by different information.

Information Flow Effect Between the Stock Market and Bond Market (주식시장과 채권시장간의 정보 이전효과)

  • Choi, Cha-Soon
    • Journal of Convergence for Information Technology
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    • v.10 no.3
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    • pp.67-75
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    • 2020
  • This paper investigated the information spillover effect between stock market and bond market with the KOSPI daily index and MMF yield data. The overall analysis period is from May 2, 1997 to August 30, 2019. The empirical analysis was conducted by dividing the period from May 2, 1997 to December 30, 2008 before the global financial crisis, and from December 30, 2008 to August 30, 2019 after the global financial crisis, and the overall analysis period. The analysis shows that the EGARCH model considering asymmetric variability is suitable. The price spillover effect and volatility spillover effect existed in both directions between the stock market and the bond market, and the price transfer effect was greater in the period before the global financial crisis than in the period after the global financial crisis. Asymmetric volatility in information between stock and bond markets appears to exist in both markets.

Analysis of KOSPI·Apartment Prices in Seoul·HPPCI·CLI's Correlation and Precedence (종합주가지수·서울지역아파트가격·전국주택매매가격지수·경기선행지수의 상관관계와 선행성 분석)

  • Choi, Jeong-Il;Lee, Ok-Dong
    • Journal of Digital Convergence
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    • v.12 no.5
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    • pp.89-99
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    • 2014
  • Correlation of KOSPI from stock market and Apartment Prices in Seoul HPPCI from real estate market has been found from this research. Furthermore, from the comparison of those indicators' flows, certain precedence was found as well. The purpose of this research is to analyze correlation and precedence among KOSPI, Apartment price in Seoul, HPPCI and CLI. As for predicting KOSPI of stock market and real estate market, it is necessary to find out preceding indices and analyzing their progresses first. For 27 years from the January 1987 to December 2013, KOSPI has been grown by 687%, while CLI showed 443%, Apartment of Seoul showed 391%, HPPCI showed 263% of growth rate in order. As the result of correlation analysis among Apartment of Seoul, CLI, KOSPI and HPPCI, KOSPI and HPPCI showed high correlation coefficient of 0.877, and Apartment of Seoul and CLI showed that of 0.956 which is even higher. Result from the analysis, CLI shows high correlation with stock and real estate market, it is a good option to watch how CLI flows to predict stock and real estate market.

Research on Determine Buying and Selling Timing of US Stocks Based on Fear & Greed Index (Fear & Greed Index 기반 미국 주식 단기 매수와 매도 결정 시점 연구)

  • Sunghyuck Hong
    • Journal of Industrial Convergence
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    • v.21 no.1
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    • pp.87-93
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    • 2023
  • Determining the timing of buying and selling in stock investment is one of the most important factors to increase the return on stock investment. Buying low and selling high makes a profit, but buying high and selling low makes a loss. The price is determined by the quantity of buying and selling, which determines the price of a stock, and buying and selling is also related to corporate performance and economic indicators. The fear and greed index provided by CNN uses seven factors, and by assigning weights to each element, the weighted average defined as greed and fear is calculated on a scale between 0 and 100 and published every day. When the index is close to 0, the stock market sentiment is fearful, and when the index is close to 100, it is greedy. Therefore, we analyze the trading criteria that generate the maximum return when buying and selling the US S&P 500 index according to CNN fear and greed index, suggesting the optimal buying and selling timing to suggest a way to increase the return on stock investment.

Performance Evaluation of the ACD Models for Analysing the Transaction Data of the KOSPI Stocks (주식 거래 자료 분석을 위한 ACD 모형 성능 비교)

  • Kim, Sahm;Jung, Da-Woon
    • Communications for Statistical Applications and Methods
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    • v.16 no.1
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    • pp.21-29
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    • 2009
  • Engle and Russell (1998) proposed the ACD(Autoregressive Conditional Duration) model to explain the relationship between the prices and the duration times of the stocks. In this paper, we first introduce the various types of the ACD models such as the linear ACD, log ACD and Box-Cox ACD models and we evaluate the performance of the models for analysing the transaction data of the stocks in Korea.

An Analysis about the Output Decision by the Managers given a compensation scheme under the Cournot Competition (생산물 시장이 과점상태일 경우 보상체계에 따른 경영자의 생산량 결정에 대한 분석)

  • Park, Kyung-Wook
    • The Korean Journal of Financial Management
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    • v.16 no.2
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    • pp.53-70
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    • 1999
  • 본 논문은 기업의 자본구조가 결정되어 있고 경영자에게 특정한 형태의 보상이 주어진 상태에서 경영자의 생산량 결정에 대하여 분석하였다. 생산물 시장이 쿠르노 경쟁상태에 있음을 가정할 때 스톡옵션과 상여금을 경영자 보상으로 갖는 경우 주식 가치 극대화를 위한 생산량과 다른 생산량을 선택하게 됨을 보여 주고 있다. 스톡옵션의 경우에는 옵션행사의 한계 경제상태와 기업 부실화의 한계 경제상태가 일치하지 않기 때문에 경영자는 주식 가치 극대화를 위한 생산량과는 다른 선택을 하게 되며 상여금의 경우에도 상여금 지급의 한계 경제상태에 따라서 주식 가치 극대화를 위한 생산량과는 다른 선택을 하게 된다. 또한 스톡옵션 행사가격과 상여금 지급의 목표이익이 증가하면 경영자의 최적 생산량은 증가한다. 반면에 스톡옵션 행사가격과 상여금 지급의 목표이익이 증가하면 경쟁기업 경영자의 최적 생산량은 감소한다. 그러나 상여금의 경우에는 경영자가 주주의 이해와 일치하는 의사결정을 내리도록 하여 주는 목표이익이 존재하지만 스톡옵션의 경우에는 이와 같은 보상체계가 존재하지 않는다.

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Correlation Analysis Among the Price of Apartments in Seoul, Stock Market and main Economic Indicators (서울지역 아파트가격과 주식시장 및 주요 경제지표와의 상관관계 분석)

  • Choi, Jeong-Il;Lee, Ok-Dong
    • Journal of Digital Convergence
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    • v.12 no.2
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    • pp.45-59
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    • 2014
  • Real estate has been the most preferable investment asset since 1980's has begun. Especially the ups and downs of housing price influence significantly on the household and national economy for a digital economy. In this analysis, monthly movement of apartment price of Seoul and its correlation with KOSPI, construction concerned shares, securities concerned shares, interest rate and exchange rate for 320 months(from January, 1987 to August, 2013) are shown. From the analysis, correlation coefficient of the price of apartment in Seoul and KOSPI is 0.8566 which is highly positive while the price of apartment in Seoul and interest rate are shown strong negative correlation which is -0.7846. The rise of stock market does affect the rise of the price of apartments in Seoul, on the contrary, the price goes down when the interest rate goes up.

Prediction of Cryptocurrency Price Trend Using Gradient Boosting (그래디언트 부스팅을 활용한 암호화폐 가격동향 예측)

  • Heo, Joo-Seong;Kwon, Do-Hyung;Kim, Ju-Bong;Han, Youn-Hee;An, Chae-Hun
    • KIPS Transactions on Software and Data Engineering
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    • v.7 no.10
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    • pp.387-396
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    • 2018
  • Stock price prediction has been a difficult problem to solve. There have been many studies to predict stock price scientifically, but it is still impossible to predict the exact price. Recently, a variety of types of cryptocurrency has been developed, beginning with Bitcoin, which is technically implemented as the concept of distributed ledger. Various approaches have been attempted to predict the price of cryptocurrency. Especially, it is various from attempts to stock prediction techniques in traditional stock market, to attempts to apply deep learning and reinforcement learning. Since the market for cryptocurrency has many new features that are not present in the existing traditional stock market, there is a growing demand for new analytical techniques suitable for the cryptocurrency market. In this study, we first collect and process seven cryptocurrency price data through Bithumb's API. Then, we use the gradient boosting model, which is a data-driven learning based machine learning model, and let the model learn the price data change of cryptocurrency. We also find the most optimal model parameters in the verification step, and finally evaluate the prediction performance of the cryptocurrency price trends.

The Signaling Effect of Stock Repurchase on Equity Offerings in Korea (자기주식매입의 유상증자에 대한 신호효과)

  • Park, Young-Kyu
    • The Korean Journal of Financial Management
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    • v.25 no.1
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    • pp.51-84
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    • 2008
  • We investigate the signaling effect of repurchase preceding new equity issue using Korean data. In a short time span, firms announce stock repurchases and equity offerings. The proximity of two events in Korean firms indicates that those are not independent of each other. In this paper, we test the signaling effect of repurchase on equity offerings on the two measures. One is announcement effect, which is measured as CAR(0, +2). The other is the effectiveness which is measured as CAR(0, +30) because the price movement during this window influences on the price of new issues. Previous studies that stock repurchase convey positive signal to equity offerings-Billet and Xue(2004) and Jung(2004)-construct sample without the limit of time interval between two events. This causes the unclear relation between those because of the long time interval. In this study we consider only samples of being within one year each other to reduce this problem and clarify the signal of repurchase on equity offerings. Korean firms are allowed to repurchase own shares with two different method. One is direct repurchase as same as open market repurchase. The other is stock stabilization fund and stock trust fund which trust company or bank buy and sell their shares on the behalf of firms. Generally, the striking different characteristic between direct repurchase and indirect repurchase is following. Direct repurchase is applied by more strict regulation than indirect repurchase. Therefore, the direct repurchase is more informative signal to the equity offering than the indirect repurchase. We construct two sample firms- firms with direct repurchase preceding-equity offerings and indirect repurchase-preceding equity offering, and one control firms-equity offerings only firms-to investigate the announcement effect and the effectiveness of repurchases. Our findings are as follows. Direct repurchase favorably affect the price of new issues favorably. CAR(0, +2) of firms with direct repurchase is not different from that of equity offerings only firms but CAR(0, +30) is higher than that of equity offerings only firms. For firms with indirect repurchase and equity offerings, Both the announcement effect and the effectiveness does not exist. Jung(2004) suggest the possibilities of how indirect stock repurchase can be regarded as one of unfair trading practices on based on the survey results that financial managers of some of KSE listed firms have been asked of their opinion on the likelihood of the stock repurchase being used in unfair trading. This is not objective empirical evidence but opinion of financial managers. To investigate whether firms announce false signal before equity offerings to boost the price of new issues, we calculate the long-run performance following equity offerings. If firms have announced repurchase to boost the price of new issues intentionally, they would undergo the severe underperformance. The empirical results do not show the severer underperformance of both sample firms than equity offerings only firms. The suggestion of false signaling of repurchase preceding equity offerings is not supported by our evidence.

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