메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색

논문 기본 정보

자료유형
학술저널
저자정보
강석규 (부경대학교 해양산업정책학부)
저널정보
한국수산경영학회 수산경영론집 수산경영론집 제32권 제1호
발행연도
2001.1
수록면
1 - 14 (14page)

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색

초록· 키워드

오류제보하기
The research on the price-volume relation in the market is very important because it examines into regular phenomenon revealed by market participants including producers and middlemen. The purpose of this study is to investigate the relationship between price and trading volume in the oyster producing market. In order to accomplish the purpose of this study, the contents of empirical analysis include the time series properties of price and trading volume, the short-term and long-term relationships between price and trading volume, and the determinants of trading volume. The data used in this study correspond to daily price and trading volume covering the time period from January 1998 to April 2001. The empirical results can be summarized as follows : First, price and trading volume follow random walks and they are integrated of order 1. The first difference is necessary for satisfying the stationary conditions. Second, price and trading volume are cointegrated. This long-run relationship is stronger from trading volume to price. Third, error correction model suggests that feedback effect exists in the long-run and that price tends to lead trading volume by about five days in the short run, that is, to be required period by digging, conveying, and peeling oystershell for selling oyster. Fourth, price and price volatility is a determinant of trading volume. In particular, trading volume is a negative function of price. It is believed that the conclusion drawn from this study would provide a useful standard for the policy makers in charge of reducing the oyster price volatility risk caused by trading volume(selling quantities).

목차

등록된 정보가 없습니다.

참고문헌 (0)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0