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Alternative measures of volatility in agricultural futures markets

Wang, Yuanfang
http://rave.ohiolink.edu/etdc/view?acc_num=osu1111610770

Abstract Details

2005, Doctor of Philosophy, Ohio State University, Agricultural, Environmental and Development Economics.
The three essays of this thesis focus on modeling and forecasting agricultural futures market volatility utilizing two nonparametric volatility measures, realized volatility and range-based volatility. Special attention is given to comparing the performance of time series models used previously in the literature with these two measures. The first essay investigates the properties of realized volatility in the soybean futures market. The results indicate that the distributional properties of realized volatility based on 5-minute returns largely correspond with existing literature. The findings of three volatility measures confirm that the Mixture-of-Distributions-Hypothesis (MDH) is valid. In contrast, the standardized daily returns display some different properties compared with stock and exchange rate data. Moreover, the parametric ARFIMA and GARCH models reflect same patterns as described in nonparametric analysis. The second essay compares the performance of GARCH models, range-based GARCH models, and log-range based simple regression models in terms of their forecasting abilities. Realized volatility is used as the forecasting evaluation criterion. In-sample fitting results reveal that range-based GARCH models outperform standard GARCH models. Out-of-sample tests indicate that GARCH models extended with daily ranges work better than the log-range based ARMA models. The third essay examines the economic value of realized volatility in the context of hedging. Specifically, it provides an analysis of incorporating information contained in intraday prices into multivariate GARCH models and evaluates the statistical performance of the augmented GARCH models. Then, effectiveness of different optimal hedge ratios depending on different estimation procedures is compared by examining the in-sample and out-of-sample performance of the ratios. Results reveal that the use of the augmented GARCH models, while statistically appropriate, provides only marginal gains to the hedger.
Matthew Roberts (Advisor)
GARCH; VOLATILITY; hedge ratios; GARCH models; hedge; realized volatility; hedging

Recommended Citations

Citations

  • Wang, Y. (2005). Alternative measures of volatility in agricultural futures markets [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1111610770

    APA Style (7th edition)

  • Wang, Yuanfang. Alternative measures of volatility in agricultural futures markets. 2005. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1111610770.

    MLA Style (8th edition)

  • Wang, Yuanfang. "Alternative measures of volatility in agricultural futures markets." Doctoral dissertation, Ohio State University, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=osu1111610770

    Chicago Manual of Style (17th edition)

osu1111610770
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© 2005, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.