Earticle

초록

영어

The basis of cyber trading has been sufficiently developed with innovative advancement of Internet Technology and the tendency of stock market investment has changed from long-term investment, which estimates the value of enterprises, to short-term investment, which focuses on getting short-term stock trading margin. Hence, this research shows a Short-term Stock Price Forecasting System on Learning Agent System using DTA(Decision Tree Algorithm) ; it collects real-time information of interest and favorite issues using Agent Technology through the Internet, and forms a decision tree, and creates a Rule-Base Database. Through this procedure the Short-term Stock Price Forecasting System provides customers with the prediction of the fluctuation of stock prices for each issue in near future and a point of sales and purchases. A Human being has the limitation of analytic ability and so through taking a look into and analyzing the fluctuation of stock prices, the Agent enables man to trace out the external factors of fluctuation of stock market on real-time. Therefore, we can check out the ups and downs of several issues at the same time and figure out the relationship and interrelation among many issues using the Agent. The SPFA (Stock Price Forecasting System) has such basic four phases as Data Collection, Data Processing, Learning, and Forecasting and Feedback.

목차

Abstract
 1. 서론
  1.1 연구배경 및 목적
  1.2 연구 방법
 2. 이론적 고찰
  2.1 에이전트의 정의
  2.2 학습 에이전트
  2.3 의사결정 트리
  2.4 주가 변동 요인에 대한 가정
 3. 단기주가예측 에이전트 시스템 개발
  3.1 단기주가예측 에이전트 시스템 구조
  3.2 단기주가예측 에이전트 수행절차
 4. 테스트 결과
  4.1 구현 범위
  4.2 테스트 내용 및 결과
 5. 결론 및 추후 연구과제
 6. 참고문헌

키워드

저자

• 서장훈 [ Seo Jang Hoon | 명지대학교 산업시스템공학부 ]
• 장현수 [ Chang Hyeon Soo | 경기공업대 산업경영시스템과 ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  대한안전경영과학회지 [Journal of Korea Safety Management & Science]

• 간기

  계간

• pISSN

  1229-6783

• eISSN

  2288-1484

• 수록기간

  1999~2025

• 십진분류

  KDC 530 DDC 620