재무연구 제 권 호 (2012년 11월)
Asian Review of Financial Research, Vol., No..
pp.287~287
pp.287~287
Psychological Barriers and Option Pricing
Bong-Gyu Jang Department of Industrial and Management Engineering, POSTECH, Kyungbuk, Korea
Changki Kim Korea University Business School, Seoul, Korea
Kyeong Tae Kim Department of Industrial and Management Engineering, POSTECH, Kyungbuk, Korea
Seungkyu Lee Department of Industrial and Management Engineering, POSTECH, Kyungbuk, Korea
Dong-Hoon Shin Department of Global Finance and Banking, Inha University, Incheon, Korea
Psychological barriers are prevalent among various asset classes and it is important to consider their impacts on the prices of derivative securities. This paper shows the potential existence of such barriers on the S&P 500 Index and examines their impacts on the rate of return and the volatility of the index. It focuses on deriving analytic European option prices under the assumption that the dynamics of the stock price follow a threshold model; this paper also evaluates this model’s empirical performance in comparison with the Black- Scholes model and the constant elasticity of variance (CEV) model. The in-sample calibration result of the threshold model is found to be much superior. Furthermore it is found that the model provides an efficient hedging method in terms of dollar-value hedging errors.
Bong-Gyu Jang
Changki Kim
Kyeong Tae Kim
Seungkyu Lee
Dong-Hoon Shin
Psychological barriers are prevalent among various asset classes and it is important to consider their impacts on the prices of derivative securities. This paper shows the potential existence of such barriers on the S&P 500 Index and examines their impacts on the rate of return and the volatility of the index. It focuses on deriving analytic European option prices under the assumption that the dynamics of the stock price follow a threshold model; this paper also evaluates this model’s empirical performance in comparison with the Black- Scholes model and the constant elasticity of variance (CEV) model. The in-sample calibration result of the threshold model is found to be much superior. Furthermore it is found that the model provides an efficient hedging method in terms of dollar-value hedging errors.
