The Information Content Of Implied Volatility From Options On Agricultural Futures Contracts
Agricultural risk managers need forecasts of price volatility that are accurate and meaningful. This is especially true given the greater emphasis on firm level risk measurement and management (e.g., Value-at-Risk and Enterprise Risk Management). Implied volatility is known to provide a readily available, market based forecast of volatility. Because of this, it is often considered to be the "best" available (e.g., optimal) volatility forecast. However, many studies have provided evidence contrary to this claim for many markets (Figlewski). This research examines the forecasting performance of implied volatility derived from the Black-1976 option pricing model in predicting 1-week volatility of nearby live cattle futures prices. Unlike many studies of implied volatility, this research takes a practical approach to evaluating implied volatility, namely from the perspective of an agribusiness risk manager who uses implied volatility in risk management applications, and thus needs to understand its forecasting performance. This research also uses a methodology that avoids overlapping forecast horizons. As well, the methodology focuses on forecast errors that can reduce interpretive issues that can arise from traditional forecast evaluation procedures. Results suggest that implied volatility derived from nearby options contracts on live cattle futures is a biased and inefficient forecast of 1-week nearby futures price volatility, but encompasses all information provided by a time series forecast (i.e., GARCH). As well, our results suggest that implied volatility has improved as a forecast of 1-week volatility over time. These results provide practical information to risk managers on the bias, efficiency, and information content of implied volatility from live cattle options markets, and provide practical suggestions on how to adjust the bias and inefficiency that is found in this forecasting framework.
|Date of creation:||2002|
|Date of revision:|
|Contact details of provider:|| Web page: http://www.agebb.missouri.edu/ncrext/ncr134/|
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
- Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-54, May-June.
- Bailey, DeeVon & Brorsen, B. Wade, 1998. "Trends In The Accuracy Of Usda Production Forecasts For Beef And Pork," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 23(02), December.
When requesting a correction, please mention this item's handle: RePEc:ags:ncrtwo:19071. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (AgEcon Search)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.