평균/VaR 최적화 모형에 의한 전환사채 주식전환 비중 결정
Determination Conversion Weight of Convertible Bonds Using Mean/Value-at-Risk Optimization Models
박구현(홍익대학교)
30권 3호, 55~70쪽
초록
In this study we suggested two optimization models to determine conversion weight of convertible bonds. The problem of this study is same as that of Park and Shim [1]. But this study used Value-at-Risk (VaR) for risk measurement instead of CVaR, Conditional-Value-at-Risk. In comparison with conventional Markowitz portfolio models, which use the variance of return, our models used VaR. In 1996, Basel Committee on Banking Supervision recommended VaR for portfolio risk measurement. But there are difficulties in solving optimization models including VaR. Benati and Rizzi [5] proved NP-hardness of general portfolio optimization problems including VaR. We adopted their approach. But we developed efficient algorithms with time complexity or less for our models. We applied examples of our models to the convertible bond issued by a semiconductor company Hynix.
Abstract
In this study we suggested two optimization models to determine conversion weight of convertible bonds. The problem of this study is same as that of Park and Shim [1]. But this study used Value-at-Risk (VaR) for risk measurement instead of CVaR, Conditional-Value-at-Risk. In comparison with conventional Markowitz portfolio models, which use the variance of return, our models used VaR. In 1996, Basel Committee on Banking Supervision recommended VaR for portfolio risk measurement. But there are difficulties in solving optimization models including VaR. Benati and Rizzi [5] proved NP-hardness of general portfolio optimization problems including VaR. We adopted their approach. But we developed efficient algorithms with time complexity or less for our models. We applied examples of our models to the convertible bond issued by a semiconductor company Hynix.
- 발행기관:
- 한국경영과학회
- 분류:
- 경영학