서지주요정보
모듈화된 신경망을 이용한 한국 종합주가지수 예측에 관한 연구 = Predicting Korea composite stock price index using modular neural network
서명 / 저자 모듈화된 신경망을 이용한 한국 종합주가지수 예측에 관한 연구 = Predicting Korea composite stock price index using modular neural network / 박종엽.
발행사항 [대전 : 한국과학기술원, 1995].
Online Access 원문보기 원문인쇄

소장정보

등록번호

8006044

소장위치/청구기호

학술문화관(문화관) 보존서고

MMIS 95011

휴대폰 전송

도서상태

이용가능(대출불가)

사유안내

반납예정일

등록번호

9002047

소장위치/청구기호

서울 학위논문 서가

MMIS 95011 c. 2

휴대폰 전송

도서상태

이용가능(대출불가)

사유안내

반납예정일

리뷰정보

초록정보

In todays, worldwide stock markets have experienced dramatic volatility in their returns. Traditionally, two main approaches- time series analysis and fundamental analysis - exist in predicting stock price. But the results of statistical analysis are not quite satisfactory to meet our expectation. Besides, they have some limitation of applications according to the data characteristics and also require comparatively strict assumptions on the distribution. As a result, artificial intelligence (AI) technologies are introduced in this area. Over the past four decades, the field of AI has made a great progress toward computerizing human reasoning. Especially, neural network (NN) have newly received special interests. Because of its non-linear learning and smooth interpolation capabilites, NN are supplementing or taking the place of statistical and conventional expert system (ES) approaches in many financial decision making. Stock market prediction is one of the such problems. So, we choose NN as a means to test whether it could produce a successful model in which their generalization capabilities could be used for stock market prediction. Five types (NN1, NN2, NN3, NN4, NN5) of independent modular networks are developed to predict KOSPI (Korea Composite Price Index)'s up/down direction after four weeks. These type of network only differ in learning period. 156 number of networks have learned and predicted. NN5 - arithmetic average derived by varying period - showed higher accuracy (79.45%) than MLRs. In buying and selling simulation, buying-and-selling using NN5 and MLR2 produced higher return than buy-and-hold strategy, particularly, NN5 can attain 2.4 times higher return than buy-and-hold's one. Today, Korean investor institutions are bustling to face with open market environment and the departure of stock price index futures on KOSPI 200. The development of trading system which supplement the limitation of this study can lighten their endeavor.

서지기타정보

서지기타정보
청구기호 {MMIS 95011
형태사항 vii, 88 p. : 삽화 ; 26 cm
언어 한국어
일반주기 저자명의 영문표기 : Jong-Yeob Park
지도교수의 한글표기 : 한인구
지도교수의 영문표기 : In-Goo Han
학위논문 학위논문(석사) - 한국과학기술원 : 경영정보공학과,
서지주기 참고문헌 : p. 76-88
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