K-shape 군집화 기반 블랙-리터만 포트폴리오 구성

• 영문명: Black-Litterman Portfolio with K-shape Clustering
• 발행기관: 한국산업경영시스템학회
• 저자명: 김예지 조풍진
• 간행물 정보: 『산업경영시스템학회지』제46권 제4호, 63~73쪽, 전체 11쪽
• 주제분류: 공학 > 산업공학
• 파일형태: PDF
• 발행일자: 2023.12.31

영문 초록

This study explores modern portfolio theory by integrating the Black-Litterman portfolio with time-series clustering, specificially emphasizing K-shape clustering methodology. K-shape clustering enables grouping time-series data effectively, enhancing the ability to plan and manage investments in stock markets when combined with the Black-Litterman portfolio. Based on the patterns of stock markets, the objective is to understand the relationship between past market data and planning future investment strategies through backtesting. Additionally, by examining diverse learning and investment periods, it is identified optimal strategies to boost portfolio returns while efficiently managing associated risks. For comparative analysis, traditional Markowitz portfolio is also assessed in conjunction with clustering techniques utilizing K-Means and K-Means with Dynamic Time Warping. It is suggested that the combination of K-shape and the Black-Litterman model significantly enhances portfolio optimization in the stock market, providing valuable insights for making stable portfolio investment decisions. The achieved sharpe ratio of 0.722 indicates a significantly higher performance when compared to other benchmarks, underlining the effectiveness of the K-shape and Black-Litterman integration in portfolio optimization.

목차

1. 서론

2. 이론적 배경

3. 시계열 군집화 기반 포트폴리오 구성

4. 백테스팅 결과 및 분석

5. 결론

키워드

Portfolio Theory Black-Litterman Portfolio Time-series Clustering K-shape Clustering Investment Strategy