Implied volatility from options on gold futures: do statistical forecasts add value or simply paint the lilly?
AbstractConsistent with findings in other markets, implied volatility is a biased predictor of the realized volatility of gold futures. No existing explanation—including a price of volatility risk—can completely explain the bias, but much of this apparent bias can be explained by persistence and estimation error in implied volatility. Statistical criteria reject the hypothesis that implied volatility is informationally efficient with respect to econometric forecasts. But delta hedging exercises indicate that such econometric forecasts have no incremental economic value. Thus, statistical measures of bias and information efficiency are misleading measures of the information content of option prices.
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Bibliographic InfoPaper provided by Federal Reserve Bank of St. Louis in its series Working Papers with number 2003-018.
Date of creation: 2004
Date of revision:
This paper has been announced in the following NEP Reports:
- NEP-ECM-2003-09-24 (Econometrics)
- NEP-ETS-2003-09-24 (Econometric Time Series)
- NEP-FIN-2003-09-24 (Finance)
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- Jeremy Berkowitz & Lorenzo Giorgianni, 2001.
"Long-Horizon Exchange Rate Predictability?,"
The Review of Economics and Statistics,
MIT Press, vol. 83(1), pages 81-91, February.
- Mark, Nelson C, 1995. "Exchange Rates and Fundamentals: Evidence on Long-Horizon Predictability," American Economic Review, American Economic Association, vol. 85(1), pages 201-18, March.
- Jonathan H. Wright, 2000.
"Log-periodogram estimation of long memory volatility dependencies with conditionally heavy tailed returns,"
International Finance Discussion Papers
685, Board of Governors of the Federal Reserve System (U.S.).
- Jonathan Wright, 2002. "Log-Periodogram Estimation Of Long Memory Volatility Dependencies With Conditionally Heavy Tailed Returns," Econometric Reviews, Taylor & Francis Journals, vol. 21(4), pages 397-417.
- Tim Bollerslev, 1986.
"Generalized autoregressive conditional heteroskedasticity,"
EERI Research Paper Series
EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
- Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
- Ball, Clifford A. & Torous, Walter N. & Tschoegl, Adrian E., 1985. "An empirical investigation of the EOE gold options market," Journal of Banking & Finance, Elsevier, vol. 9(1), pages 101-113, March.
- Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
- Barone-Adesi, Giovanni & Whaley, Robert E, 1987. " Efficient Analytic Approximation of American Option Values," Journal of Finance, American Finance Association, vol. 42(2), pages 301-20, June.
- Latane, Henry A & Rendleman, Richard J, Jr, 1976. "Standard Deviations of Stock Price Ratios Implied in Option Prices," Journal of Finance, American Finance Association, vol. 31(2), pages 369-81, May.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003.
"Modeling and Forecasting Realized Volatility,"
Econometric Society, vol. 71(2), pages 579-625, March.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2001. "Modeling and Forecasting Realized Volatility," Center for Financial Institutions Working Papers 01-01, Wharton School Center for Financial Institutions, University of Pennsylvania.
- Anderson, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Labys, Paul, 2002. "Modeling and Forecasting Realized Volatility," Working Papers 02-12, Duke University, Department of Economics.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2001. "Modeling and Forecasting Realized Volatility," NBER Working Papers 8160, National Bureau of Economic Research, Inc.
- Hull, John C & White, Alan D, 1987. " The Pricing of Options on Assets with Stochastic Volatilities," Journal of Finance, American Finance Association, vol. 42(2), pages 281-300, June.
- Lamoureux, Christopher G & Lastrapes, William D, 1993. "Forecasting Stock-Return Variance: Toward an Understanding of Stochastic Implied Volatilities," Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 293-326.
- Robert F. Engle & Joshua Rosenberg, 1998.
"Testing the Volatility Term Structure using Option Hedging Criteria,"
New York University, Leonard N. Stern School Finance Department Working Paper Seires
98-031, New York University, Leonard N. Stern School of Business-.
- Robert F. Engle & Joshua Rosenberg, 1966. "Testing the Volatility Term Structure Using Option Hedging Criteria," New York University, Leonard N. Stern School Finance Department Working Paper Seires 96-24, New York University, Leonard N. Stern School of Business-.
- Kilian, Lutz, 1999. "Exchange Rates and Monetary Fundamentals: What Do We Learn from Long-Horizon Regressions?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(5), pages 491-510, Sept.-Oct.
- Christopher J. Neely & Paul A. Weller, 2001. "Predicting exchange rate volatility: genetic programming vs. GARCH and RiskMetrics," Working Papers 2001-009, Federal Reserve Bank of St. Louis.
- Steven P. Feinstein, 1988. "A source of unbiased implied volatility forecasts," Working Paper 88-9, Federal Reserve Bank of Atlanta.
- Pong, Shiuyan & Shackleton, Mark B. & Taylor, Stephen J. & Xu, Xinzhong, 2004. "Forecasting currency volatility: A comparison of implied volatilities and AR(FI)MA models," Journal of Banking & Finance, Elsevier, vol. 28(10), pages 2541-2563, October.
- Black, Fischer & Scholes, Myron S, 1972. "The Valuation of Option Contracts and a Test of Market Efficiency," Journal of Finance, American Finance Association, vol. 27(2), pages 399-417, May.
- N. Gregory Mankiw & Matthew D. Shapiro, 1985.
"Do We Reject Too Often? Small Sample Properties of Tests of Rational Expectations Models,"
NBER Technical Working Papers
0051, National Bureau of Economic Research, Inc.
- Gregory Mankiw, N. & Shapiro, Matthew D., 1986. "Do we reject too often? : Small sample properties of tests of rational expectations models," Economics Letters, Elsevier, vol. 20(2), pages 139-145.
- Black, Fischer, 1976. "The pricing of commodity contracts," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 167-179.
- Christensen, B. J. & Prabhala, N. R., 1998. "The relation between implied and realized volatility," Journal of Financial Economics, Elsevier, vol. 50(2), pages 125-150, November.
- Blair, Bevan J. & Poon, Ser-Huang & Taylor, Stephen J., 2001. "Forecasting S&P 100 volatility: the incremental information content of implied volatilities and high-frequency index returns," Journal of Econometrics, Elsevier, vol. 105(1), pages 5-26, November.
- Jorion, Philippe, 1995. " Predicting Volatility in the Foreign Exchange Market," Journal of Finance, American Finance Association, vol. 50(2), pages 507-28, June.
- Christopher J. Neely & Drew B. Winters, 2005. "Year-end seasonality in one-month LIBOR derivatives," Working Papers 2003-040, Federal Reserve Bank of St. Louis.
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