• 제목/요약/키워드: stock turn over rate

검색결과 3건 처리시간 0.017초

한국(韓國)의 물가모형(物價模型) (A Long Run Classical Model of Price Determination)

  • 박우규;김세종
    • KDI Journal of Economic Policy
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    • 제14권4호
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    • pp.3-26
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    • 1992
  • 본고(本稿)에서는 물가변동(物價變動)의 구조(構造), 주요거시정책변수(主要巨視政策變數)의 변동이 물가에 미치는 영향 및 파급구조(波及構造) 등을 파악하고 물가안정을 위한 적절한 정책대응방안을 제시하기 위하여 물가모형(物價模型)을 작성하였다. Keynesian 거시경제모형(巨視經濟模型) 형태로 작성하되, 임금(賃金), 이자율(利子率), 물가(物價)와 같은 주요가격변수(主要價格變數)를 내생화(內生化)하고 잠재(潛在)GNP의 추정 역시 내생화(內生化)함으로써 가격 및 실물변수의 장기적(長期的) 상호변동관계(相互變動關係)를 파악하였다. 어떠한 충격에 의해 초과수요(超過需要)(실질GNP-잠재GNP)가 변화하면 이는 임금(賃金), 금리(金利), 물가(物價), 실질실효환율(實質實效換率) 등과 같은 가격변수에 영향을 미치고 이는 다시 초과수요(超過需要)를 변동시키는 실물(實物)-가격(價格)-실물(實物)의 순환변동관계(循環變動關係)에 의해 물가가 변동되는 것으로 나타났다. 본 모형(模型)은 Keynesian모형(模型)이나, 장기(長期)에는 고전파적(古典派的)(Classical) 정책함의를 가지는바, 통화공급증가(通貨供給增加), 재정지출증가(財政支出增加), 환율절하(換率切下) 등은 단기(短期)에는 경기부양효과를 가지나 장기(長期)에는 이러한 경기부양효과가 소멸되는 반면 물가(物價)는 높은 수준을 유지하는 결과를 초래하는 것으로 나타났다.

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물류창고에서 블록별 저장방식 및 주문 처리에 관한 연구 (The Block-Based Storage Policy and Order Processing in Logistics Warehouse)

  • 김명훈;김종화
    • 한국컴퓨터정보학회논문지
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    • 제8권4호
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    • pp.159-164
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    • 2003
  • 물류창고의 적재위치는 창고를 이동하는 물품의 총 자재취급비용에 의해 직접전인 영향을 받는다. 본 논문의 목적은 물류 창고에서의 총 오더피킹 시간을 감소하기 위한 물품 저장방식인 블록 저장방식을 개발하고자 한다. 블록저장방식은 랙들을 블록으로 분할하고, 각 물품은 회전율과 도크와 블록간의 평균 거리를 기준으로 할당한다. 제시한 저장방식의 수행도를 평가하기 위해 다양한 주문 결합 방법들을 이용하여 기존의 등급별 저장방식과 비교 연구한다.

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WHICH INFORMATION MOVES PRICES: EVIDENCE FROM DAYS WITH DIVIDEND AND EARNINGS ANNOUNCEMENTS AND INSIDER TRADING

  • Kim, Chan-Wung;Lee, Jae-Ha
    • 재무관리논총
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    • 제3권1호
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    • pp.233-265
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    • 1996
  • We examine the impact of public and private information on price movements using the thirty DJIA stocks and twenty-one NASDAQ stocks. We find that the standard deviation of daily returns on information days (dividend announcement, earnings announcement, insider purchase, or insider sale) is much higher than on no-information days. Both public information matters at the NYSE, probably due to masked identification of insiders. Earnings announcement has the greatest impact for both DJIA and NASDAQ stocks, and there is some evidence of positive impact of insider asle on return volatility of NASDAQ stocks. There has been considerable debate, e.g., French and Roll (1986), over whether market volatility is due to public information or private information-the latter gathered through costly search and only revealed through trading. Public information is composed of (1) marketwide public information such as regularly scheduled federal economic announcements (e.g., employment, GNP, leading indicators) and (2) company-specific public information such as dividend and earnings announcements. Policy makers and corporate insiders have a better access to marketwide private information (e.g., a new monetary policy decision made in the Federal Reserve Board meeting) and company-specific private information, respectively, compated to the general public. Ederington and Lee (1993) show that marketwide public information accounts for most of the observed volatility patterns in interest rate and foreign exchange futures markets. Company-specific public information is explored by Patell and Wolfson (1984) and Jennings and Starks (1985). They show that dividend and earnings announcements induce higher than normal volatility in equity prices. Kyle (1985), Admati and Pfleiderer (1988), Barclay, Litzenberger and Warner (1990), Foster and Viswanathan (1990), Back (1992), and Barclay and Warner (1993) show that the private information help by informed traders and revealed through trading influences market volatility. Cornell and Sirri (1992)' and Meulbroek (1992) investigate the actual insider trading activities in a tender offer case and the prosecuted illegal trading cased, respectively. This paper examines the aggregate and individual impact of marketwide information, company-specific public information, and company-specific private information on equity prices. Specifically, we use the thirty common stocks in the Dow Jones Industrial Average (DJIA) and twenty one National Association of Securities Dealers Automated Quotations (NASDAQ) common stocks to examine how their prices react to information. Marketwide information (public and private) is estimated by the movement in the Standard and Poors (S & P) 500 Index price for the DJIA stocks and the movement in the NASDAQ Composite Index price for the NASDAQ stocks. Divedend and earnings announcements are used as a subset of company-specific public information. The trading activity of corporate insiders (major corporate officers, members of the board of directors, and owners of at least 10 percent of any equity class) with an access to private information can be cannot legally trade on private information. Therefore, most insider transactions are not necessarily based on private information. Nevertheless, we hypothesize that market participants observe how insiders trade in order to infer any information that they cannot possess because insiders tend to buy (sell) when they have good (bad) information about their company. For example, Damodaran and Liu (1993) show that insiders of real estate investment trusts buy (sell) after they receive favorable (unfavorable) appraisal news before the information in these appraisals is released to the public. Price discovery in a competitive multiple-dealership market (NASDAQ) would be different from that in a monopolistic specialist system (NYSE). Consequently, we hypothesize that NASDAQ stocks are affected more by private information (or more precisely, insider trading) than the DJIA stocks. In the next section, we describe our choices of the fifty-one stocks and the public and private information set. We also discuss institutional differences between the NYSE and the NASDAQ market. In Section II, we examine the implications of public and private information for the volatility of daily returns of each stock. In Section III, we turn to the question of the relative importance of individual elements of our information set. Further analysis of the five DJIA stocks and the four NASDAQ stocks that are most sensitive to earnings announcements is given in Section IV, and our results are summarized in Section V.

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