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Estimation accuracy of implied volat...

Nian, Minhuan.

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Estimation accuracy of implied volatility directly from "nearest-to-the-money" commodity option premiums.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Estimation accuracy of implied volatility directly from "nearest-to-the-money" commodity option premiums./
作者:	Nian, Minhuan.
面頁冊數:	95 p.
附註:	Adviser: Charles E. Curtis, Jr.
Contained By:	Dissertation Abstracts International67-05A.
標題:	Economics, Agricultural. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3215801
ISBN:	9780542674204

Estimation accuracy of implied volatility directly from "nearest-to-the-money" commodity option premiums.
Nian, Minhuan.

Estimation accuracy of implied volatility directly from "nearest-to-the-money" commodity option premiums. - 95 p.

Adviser: Charles E. Curtis, Jr.

Thesis (Ph.D.)--Clemson University, 2006.

Volatilities play an important role in financial engineering and especially in the valuation of various forms of options. However, unlike prices, volatility is not directly observable in the market. They can only be estimated in the context of a model. Among all the options pricing models, Black-Scholes type pricing models have been widely used. The primary focus for this research is to test the accuracy of the Direct Implied Volatility Estimate (DIVE), the Historical Volatility Estimate (HV), and the Quadratic Formula Volatility Estimate (QIVE) against the implied volatility derived from Black's (1976) model, and to examine for potential accuracy loss of using them for "nearest-to-the-money" corn and cotton option premiums for the years 1990 to 2005, both in aggregate level and within each individual year. In order to pay particular attention to the futures contracts expiring at harvest time, December corn and cotton contracts are chosen. This study also tests and compares the stationarity and seasonality patterns presented in DIVE, QIVE against the two benchmarks HV and IV for December corn and cotton contracts. Stationarity tests show all four types of volatility estimate series are stationary time series data. Statistical results indicate that DIVE and QIVE are both accurate estimates for IV in both the aggregate and intra-year levels with same seasonality patterns at 5% significance level. 30-day HV estimate is not an accurate estimate for IV because its variance and mean are tested to be significantly different from the variance and mean of IV at 5% significance level.

ISBN: 9780542674204Subjects--Topical Terms:

626648
Economics, Agricultural.

Estimation accuracy of implied volatility directly from "nearest-to-the-money" commodity option premiums.
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300 $a 95 p.
500 $a Adviser: Charles E. Curtis, Jr.
500 $a Source: Dissertation Abstracts International, Volume: 67-05, Section: A, page: 1846.
502 $a Thesis (Ph.D.)--Clemson University, 2006.
520 $a Volatilities play an important role in financial engineering and especially in the valuation of various forms of options. However, unlike prices, volatility is not directly observable in the market. They can only be estimated in the context of a model. Among all the options pricing models, Black-Scholes type pricing models have been widely used. The primary focus for this research is to test the accuracy of the Direct Implied Volatility Estimate (DIVE), the Historical Volatility Estimate (HV), and the Quadratic Formula Volatility Estimate (QIVE) against the implied volatility derived from Black's (1976) model, and to examine for potential accuracy loss of using them for "nearest-to-the-money" corn and cotton option premiums for the years 1990 to 2005, both in aggregate level and within each individual year. In order to pay particular attention to the futures contracts expiring at harvest time, December corn and cotton contracts are chosen. This study also tests and compares the stationarity and seasonality patterns presented in DIVE, QIVE against the two benchmarks HV and IV for December corn and cotton contracts. Stationarity tests show all four types of volatility estimate series are stationary time series data. Statistical results indicate that DIVE and QIVE are both accurate estimates for IV in both the aggregate and intra-year levels with same seasonality patterns at 5% significance level. 30-day HV estimate is not an accurate estimate for IV because its variance and mean are tested to be significantly different from the variance and mean of IV at 5% significance level.
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