利率與股價波動率對個股選擇權評價之影響:以台灣個股選擇權為例

Autor: WU MING YING, 吳明穎
Rok vydání: 2005
Druh dokumentu: 學位論文 ; thesis
Popis: 93
Among all the factors that influence the price of Stock Option, volatility is a significant one. If we can precisely predict the future trend of stock option as well as the price, we can assist the mass populace and corporations to increase their arbitrage opportunity. In the abstract, I choose Black-Scholes pricing model as the pricing model for stock option theory, target at stock option and then exploit historical volatility model, implied volatility model plus ARMA-GARCH model to get the assessment of volatility of stock option. After that, I apply the assessments of volatility from different models into Black-Scholes pricing model to get the theoretical price of Black-Scholes model, and then I employ MAE, MPE, and RMSE as the index for the error in pricing assessment to make a comparison of the errors in pricing from different assessment models of volatility. In Black-Scholes pricing model, risk-free interest rate is supposed to be fixed. Since the rate is influenced by market information, and it is not reasonable in practice if we suppose risk-free interest rate to be a fixed number. Therefore, in this research, r and R are separately applied into the model to observe the influence each exerts in theoretical price. Supported by practical evidence, this abstract indicates: The results of BS-IV(R) and BS-IV(r) are quite similar, which prove that only little influence would be made in B-S pricing model if we only change risk-free interest rate variable. However, we find that MAE and MSE of BS-IV(r) are smaller than those of BS-IV(R), which demonstrates the error in theoretical price can be reduced if we put daily market information into B-S pricing model. Simulating the option evaluation model, when the option price is on the money and out of money, BS-IV (R) and BS-IV (r) will be closest to the closing price of the option. Although in the money and deeply in the money options may show some discrepancies, except for two stocks such as China Steel and United Microelectron, the average option price is still in the price range of 10% of the option’s closing price. For these five stocks listed on Table 2.2, the results are more accurate when we use BS-IV(R)、and BS-IV(r) models. Within these two models, BS-IV(r) is better preferred and has less discrepancy than BS-IV(R). Using BS-HV and BS-ARMA-GARCH models for analysis, we find that ARMA-GARCH model which is affected by the rate of return will be similar to the historic fluctuation evaluation. Hence, as long as the option price is in the money using the BS-HV and BS- ARMA-GARCH, the results are flaw and inaccurate. The reason can be because of amateur investors’ lack of understanding of option market and the liquidity risk involved, resulting that the stock market is far more popular than the option market.
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