• 제목/요약/키워드: stock prices data

검색결과 197건 처리시간 0.024초

A Study on the Calculation and Provision of Accruals-Quality by Big Data Real-Time Predictive Analysis Program

  • Shin, YeounOuk
    • International journal of advanced smart convergence
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    • 제8권3호
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    • pp.193-200
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    • 2019
  • Accruals-Quality(AQ) is an important proxy for evaluating the quality of accounting information disclosures. High-quality accounting information will provide high predictability and precision in the disclosure of earnings and will increase the response to stock prices. And high Accruals-Quality, such as mitigating heterogeneity in accounting information interpretation, provides information usefulness in capital markets. The purpose of this study is to suggest how AQ, which represents the quality of accounting information disclosure, is transformed into digitized data in real-time in combination with IT information technology and provided to financial analyst's information environment in real-time. And AQ is a framework for predictive analysis through big data log analysis system. This real-time information from AQ will help financial analysts to increase their activity and reduce information asymmetry. In addition, AQ, which is provided in real time through IT information technology, can be used as an important basis for decision-making by users of capital market information, and is expected to contribute in providing companies with incentives to voluntarily improve the quality of accounting information disclosure.

온라인 주식게시판 정보와 주식시장 활동에 관한 상관관계 연구 (A Study about the Correlation between Information on Stock Message Boards and Stock Market Activity)

  • 김현모;윤호영;소리;박재홍
    • Asia pacific journal of information systems
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    • 제24권4호
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    • pp.559-575
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    • 2014
  • Individual investors are increasingly flocking to message boards to seek, clarify, and exchange information. Businesses like Seekingalpha.com and business magazines like Fortune are evaluating, synthesizing, and reporting the comments made on message boards or blogs. In March of 2012, Yahoo! Finance Message Boards recorded 45 million unique visitors per month followed by AOL Money and Finance (19.8 million), and Google Finance (1.6 million) [McIntyre, 2012]. Previous studies in the finance literature suggest that online communities often provide more accurate information than analyst forecasts [Bagnoli et al., 1999; Clarkson et al., 2006]. Some studies empirically show that the volume of posts in online communities have a positive relationship with market activities (e.g., trading volumes) [Antweiler and Frank, 2004; Bagnoli et al., 1999; Das and Chen, 2007; Tumarkin and Whitelaw, 2001]. The findings indicate that information in online communities does impact investors' investment decisions and trading behaviors. However, research explicating the correlation between information on online communities and stock market activities (e.g., trading volume) is still evolving. Thus, it is important to ask whether a volume of posts on online communities influences trading volumes and whether trading volumes also influence these communities. Online stock message boards offer two different types of information, which can be explained using an economic and a psychological perspective. From a purely economic perspective, one would expect that stock message boards would have a beneficial effect, since they provide timely information at a much lower cost [Bagnoli et al., 1999; Clarkson et al., 2006; Birchler and Butler, 2007]. This indicates that information in stock message boards may provide valuable information investors can use to predict stock market activities and thus may use to make better investment decisions. On the other hand, psychological studies have shown that stock message boards may not necessarily make investors more informed. The related literature argues that confirmation bias causes investors to seek other investors with the same opinions on these stock message boards [Chen and Gu, 2009; Park et al., 2013]. For example, investors may want to share their painful investment experiences with others on stock message boards and are relieved to find they are not alone. In this case, the information on these stock message boards mainly reflects past experience or past information and not valuable and predictable information for market activities. This study thus investigates the two roles of stock message boards-providing valuable information to make future investment decisions or sharing past experiences that reflect mainly investors' painful or boastful stories. If stock message boards do provide valuable information for stock investment decisions, then investors will use this information and thereby influence stock market activities (e.g., trading volume). On the contrary, if investors made investment decisions and visit stock message boards later, they will mainly share their past experiences with others. In this case, past activities in the stock market will influence the stock message boards. These arguments indicate that there is a correlation between information posted on stock message boards and stock market activities. The previous literature has examined the impact of stock sentiments or the number of posts on stock market activities (e.g., trading volume, volatility, stock prices). However, the studies related to stock sentiments found it difficult to obtain significant results. It is not easy to identify useful information among the millions of posts, many of which can be just noise. As a result, the overall sentiments of stock message boards often carry little information for future stock movements [Das and Chen, 2001; Antweiler and Frank, 2004]. This study notes that as a dependent variable, trading volume is more reliable for capturing the effect of stock message board activities. The finance literature argues that trading volume is an indicator of stock price movements [Das et al., 2005; Das and Chen, 2007]. In this regard, this study investigates the correlation between a number of posts (information on stock message boards) and trading volume (stock market activity). We collected about 100,000 messages of 40 companies at KOSPI (Korea Composite Stock Price Index) from Paxnet, the most popular Korean online stock message board. The messages we collected were divided into in-trading and after-trading hours to examine the correlation between the numbers of posts and trading volumes in detail. Also we collected the volume of the stock of the 40 companies. The vector regression analysis and the granger causality test, 3SLS analysis were performed on our panel data sets. We found that the number of posts on online stock message boards is positively related to prior stock trade volume. Also, we found that the impact of the number of posts on stock trading volumes is not statistically significant. Also, we empirically showed the correlation between stock trading volumes and the number of posts on stock message boards. The results of this study contribute to the IS and finance literature in that we identified online stock message board's two roles. Also, this study suggests that stock trading managers should carefully monitor information on stock message boards to understand stock market activities in advance.

변이형 오토인코더와 어텐션 메커니즘을 결합한 차트기반 주가 예측 (Chart-based Stock Price Prediction by Combing Variation Autoencoder and Attention Mechanisms)

  • 배상현;최병구
    • 경영정보학연구
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    • 제23권1호
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    • pp.23-43
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    • 2021
  • 최근 인공지능 기법을 활용하여 캔들스틱 차트를 분석함으로써 주식가격 예측의 정확성을 높이고자 하는 다양한 연구가 진행되어 왔다. 그러나 이러한 연구들은 주식가격 예측을 위한 학습에 있어 캔들스틱 차트의 시계열적 특성을 고려하지 못한다는 점과 시장 참여자들의 감정 상태를 고려하지 못한다는 점 등이 문제로 지적되고 있다. 본 연구에서는 시장 참여자들의 감정상태를 반영하기 위해 변동성지수(VIX: volatility index) 차트를 캔들스틱 차트와 함께 고려하여 학습시키고 이를 변이형 오토인코더(VAE: variational auto encoder)와 어텐션 메커니즘(attention mechanisms)을 결합한 새로운 방법으로 분석하여 캔들스틱 차트의 시계열적 특성을 고려함으로써 기존 연구의 한계를 극복하고자 한다. 본 연구에서 제안한 방법의 성능 비교를 위해 S&P 500 기업 가운데 50개를 임의로 추출하여 제안한 방법을 통해 이들의 주식가격을 예측하고 이를 합성곱 신경망(CNN: convolutional neural network) 또는 장단기메모리(LSTM: long-short term memory) 등과 같은 기존 방법들과 비교하였다. 비교 결과 기존 방법들에 비해 본 연구에서 제안한 방법이 더 우수한 성능을 보이는 것으로 나타났다. 본 연구는 시장 참여자들의 감정 상태와 캔들스틱 차트의 시계열적 특성을 고려함으로써 주식 가격 예측의 정확성을 높였다는 점에서 그 의의가 있다.

소유지배 괴리도가 주가급락위험에 미치는 영향 (The Effect of Control-Ownership Wedge on Stock Price Crash Risk)

  • 채수준;유혜영
    • 산경연구논집
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    • 제9권7호
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    • pp.53-59
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    • 2018
  • Purpose - This study examines the effect of control-ownership wedge on stock crash risk. In Korea, controlling shareholders have exclusive control rights compared to their cash flow rights. With increasing disparity, controlling shareholders abuse their power and extract private benefits at the expense of the minority shareholders. Managers who are controlling shareholders of the companies tend not to disclose critical information that would prevent them from pursuing private interests. They accumulate negative information in the firm. When the accumulated bad news crosses a tipping point, it will be suddenly released to the market at once, resulting in an abrupt decline in stock prices. We predict that stock price crash likelihood due to information opaqueness increases as the wedge increases. Research design, data, and methodology - 831 KOSPI-listed firm-year observations are from KisValue database from 2005 to 2011. Control-ownership wedge is measured as the ratio (UCO -UCF)/UCO where UCF(UCO) is the ultimate cash-flow(control) rights of the largest controlling shareholder. Dependent variable CRASH is a dummy variable that equals one if the firm has at least 1 crash week during a year, and zero otherwise. Logistic regression is used to examine the relationship between control-ownership wedge and stock price crash risk. Results - Using a sample of KOSPI-listed firms in KisValue database for the period 2005-2011, we find that stock price crash risk increases as the disparity increases. Specifically, we find that the coefficient of WEDGE is significantly positive, supporting our prediction. The result implies that as controlling shareholders' ownership increases, controlling shareholders tend to withhold bad news. Conclusions - Our results show that agency problems arising from the divergence between control rights and cash flow rights increase the opaqueness of accounting information. Eventually, the accumulated bad news is released all at once, leading to stock price crashes. It could be seen that companies with high control-ownership wedge are likely to experience future stock price crashes. Our study is related to a broader literature that examined the effect of the control-ownership wedge on stock markets. Our findings suggest that the disparity is a meaningful predictor for future stock price crash risk. The results are expected to provide useful implications for firms, regulators, and investors.

해운선사 주가와 해상운임지수 사이의 위험 전이효과 (Risk Spillover between Shipping Company's Stock Price and Marine Freight Index)

  • 최기홍
    • 한국항만경제학회지
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    • 제39권1호
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    • pp.115-129
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    • 2023
  • 본 연구는 2010년 1월 4일부터 2022년 10월 31일까지의 일별 자료를 기반으로 Copula-CoVaR 방법을 통해 해운선사 주가에 미치는 BDI의 위험 전이효과를 분석하였다. 주요 실증분석 결과와 정책적 함의는 다음과 같다. 첫째, copula 결과에 따르면, BDI와 해운선사 주가 사이는 약한 의존성이 존재하는 것으로 나타났으며, PAN, KOR, YEN은 동적 Student-t copula가 가장 적합한 모형으로 선정되었으며, HMM은 rotated Gumbel copula, KSS는 Gumbel copula가 선정되었다. 둘째, CoVaR의 결과에서, 모든 해운선사에서 상·하방 CoVaR가 상·하방 VaR과 크게 다르다는 것을 확인하였다. BDI가 해운선사에 상당한 위험 전이효과가 있다는 것을 의미한다. 또한 위험 전이효과는 일반적으로 하방 위험이 상방 위험보다 낮으므로, 하방과 상방 위험 전이효과는 비대칭적인 것으로 나타났다. 따라서 정책입안자들은 BDI 충격으로 인한 체계적인 위험을 방지하기 위해 외부 위험 감독을 강화하고, 국내 여건에 맞는 차별화된 정책을 수립해야한다. 그리고 투자자들은 BDI 변동으로 인한 외부 위험을 투자 결정에 반영하고 위험을 피하기 위해 최적의 투자 포트폴리오를 구성해야 한다. 한편, 투자자들은 투자를 결정할 때 상·하방 위험의 비대칭적 특성을 고려하여 투자 포트폴리오를 조정해야 할 것을 제안한다.

뉴스와 주가 : 빅데이터 감성분석을 통한 지능형 투자의사결정모형 (Stock-Index Invest Model Using News Big Data Opinion Mining)

  • 김유신;김남규;정승렬
    • 지능정보연구
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    • 제18권2호
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    • pp.143-156
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    • 2012
  • 누구나 뉴스와 주가 사이에는 밀접한 관계를 있을 것이라 생각한다. 그래서 뉴스를 통해 투자기회를 찾고, 투자이익을 얻을 수 있을 것으로 기대한다. 그렇지만 너무나 많은 뉴스들이 실시간으로 생성 전파되며, 정작 어떤 뉴스가 중요한지, 뉴스가 주가에 미치는 영향은 얼마나 되는지를 알아내기는 쉽지 않다. 본 연구는 이러한 뉴스들을 수집 분석하여 주가와 어떠한 관련이 있는지 분석하였다. 뉴스는 그 속성상 특정한 양식을 갖지 않는 비정형 텍스트로 구성되어있다. 이러한 뉴스 컨텐츠를 분석하기 위해 오피니언 마이닝이라는 빅데이터 감성분석 기법을 적용하였고, 이를 통해 주가지수의 등락을 예측하는 지능형 투자의사결정 모형을 제시하였다. 그리고, 모형의 유효성을 검증하기 위하여 마이닝 결과와 주가지수 등락 간의 관계를 통계 분석하였다. 그 결과 뉴스 컨텐츠의 감성분석 결과값과 주가지수 등락과는 유의한 관계를 가지고 있었으며, 좀 더 세부적으로는 주식시장 개장 전 뉴스들과 주가지수의 등락과의 관계 또한 통계적으로 유의하여, 뉴스의 감성분석 결과를 이용해 주가지수의 변동성 예측이 가능할 것으로 판단되었다. 이렇게 도출된 투자의사결정 모형은 여러 유형의 뉴스 중에서 시황 전망 해외 뉴스가 주가지수 변동을 가장 잘 예측하는 것으로 나타났고 로지스틱 회귀분석결과 분류정확도는 주가하락 시 70.0%, 주가상승 시 78.8%이며 전체평균은 74.6%로 나타났다.

글로벌 금융위기 이후 한국 주식유통시장의 위험가격에 관한 연구 (The Price of Risk in the Korean Stock Distribution Market after the Global Financial Crisis)

  • 손경우;유원석
    • 유통과학연구
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    • 제13권5호
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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.

Does the Pricing Mechanism Affect the IPO Flipping Activity in Pakistan?

  • ANWAR, Ayesha;MOHD-RASHID, Rasidah
    • The Journal of Asian Finance, Economics and Business
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    • 제8권1호
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    • pp.237-246
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    • 2021
  • This paper explores the relationship between price mechanism and flipping activity of initial public offerings (IPOs) in Pakistan's emerging economy. This study uses a cross-sectional data set of 95 firms listed on Pakistan Stock Exchange from 2000 to 2019. This study employs the ordinary least square and quantile regression techniques to capture the relationship between price mechanism and flipping activity. The results show that book-built IPOs flip substantially less than fixed-price IPOs. This is consistent with the signaling theory assertion that roadshows are arranged by underwriters to capture investors' demand and set the offer prices of IPOs. If investors learn the fair values of quality IPOs, then the offer prices will be close to the intrinsic values, thus reducing flipping. The findings also provide conclusive evidence for understanding the usefulness of and the more relevant information regarding the pricing mechanism. In particular, it provides a better understanding of how companies actually use the pricing mechanism information in the flipping of IPO shares. The results of this study are also valuable to underwriters, and regulators, for instance, provides underwriters with the discretion to allocate the IPO shares and the SECP, in revising regulation on the disclosure of IPO pricing methods.

해운선사 주가와 해상 운임지수의 영향관계 분석 (Analysis of the Relationship Between Freight Index and Shipping Company's Stock Price Index)

  • 김형호;성기덕;전준우;여기태
    • 디지털융복합연구
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    • 제14권6호
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    • pp.157-165
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    • 2016
  • 본 연구의 목적은 해운실물경기 지수가 국내 해운선사 주가에 미치는 영향을 분석하는 것이다. 분석에 사용된 변수는 한국 H회사의 주가와 해운실물경기 지수인 BDI(Baltic Dry Index), CCFI(China Containerized Freight Index), HRCI(Howe Robinson Containership Index)다. 분석기간은 2012년부터 2015년이며, 해운선사 주가지수, BDI, CCFI, HRCI의 4년간의 주간 데이터를 활용하였다. VAR 모형을 이용하여 CCFI와 HRCI가 국내해운선사의 주가지수에 미치는 영향을 분석하였고, VECM 모형을이용하여 BDI가 국내해운선사의 주가지수에 미치는 영향을 분석하였다. VAR 모형 분석결과, CCFI, HRCI는 주가지수에 부(-)의 영향을 미치는 것으로 분석되었으며, VECM 모형 분석결과, BDI는 주가지수에 부(-)의 영향을 미치는 것으로 나타났다. 해운실물경기지수에 부의(-) 영향을 받은 국내 해운선사는 해운실물경기지수에 부의(-) 영향을 받은 국내 해운선사는 해운시황에 적절한 대응을 하지 못한 것을 의미한다. 따라서 국내 해운기업은 중장기적인 모니터링을 통해 해운시황에 대처하는 전략이 필요하다.

Nonlinear Regression for an Asymptotic Option Price

  • Song, Seong-Joo;Song, Jong-Woo
    • 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.