An empirical model of daily highs and lows of West Texas Intermediate crude oil prices
There is a large collection of literature on energy price forecasting, but most studies typically use monthly average or close-to-close daily price data. In practice, the daily price range constructed from the daily high and low also contains useful information on price volatility and is used frequently in technical analysis. The interaction between the daily high and low and the associated daily range has been examined in several recent studies on stock price and exchange rate forecasts. The present paper adopts a similar approach to analyze the behaviour of the West Texas Intermediate (WTI) crude oil price over a ten-year period. We find that daily highs and lows of the WTI oil price are cointegrated, with the error correction term being closely approximated by the daily price range. Two forecasting models, one based on a vector error correction mechanism and the other based on a transfer function framework with the range taken as a driver variable, are presented for forecasting the daily highs and lows. The results show that both of these models offer significant advantages over the naïve random walk and univariate ARIMA models in terms of out-of-sample forecast accuracy. A trading strategy that makes use of the daily high and low forecasts is further developed. It is found that this strategy generally yields very reasonable trading returns over an evaluation period of about two years.
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- S. M. Ahmed & M. I. Ansari, 1997. "Modelling the efficiency of the Canadian foreign exchange market: a bivariate transfer function analysis," Applied Economics, Taylor & Francis Journals, vol. 29(1), pages 63-70.
- Yan-Leung Cheung & Yin-Wong Cheung & Alan T.K. Wan, 2008.
"A High-Low Model of Daily Stock Price Ranges,"
CESifo Working Paper Series
2387, CESifo Group Munich.
- Cheung, Yan-Leung & Cheung, Yin-Wong & He, Angela W.W. & Wan, Alan T.K., 2010. "A trading strategy based on Callable Bull/Bear Contracts," Pacific-Basin Finance Journal, Elsevier, vol. 18(2), pages 186-198, April.
- Angela He & Alan Wan, 2009. "Predicting daily highs and lows of exchange rates: a cointegration analysis," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(11), pages 1191-1204.
- Parkinson, Michael, 1980. "The Extreme Value Method for Estimating the Variance of the Rate of Return," The Journal of Business, University of Chicago Press, vol. 53(1), pages 61-65, January.
- Gallant, A. Ronald & Hsu, Chien-Te & Tauchen, George, 2000.
"Using Daily Range Data to Calibrate Volatility Diffusions and Extract the Forward Integrated Variance,"
00-04, Duke University, Department of Economics.
- A. Ronald Gallant & Chien-Te Hsu & George Tauchen, 1999. "Using Daily Range Data To Calibrate Volatility Diffusions And Extract The Forward Integrated Variance," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 617-631, November.
- Tim Krehbiel & Lee C. Adkins, 2005. "Price risk in the NYMEX energy complex: An extreme value approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 25(4), pages 309-337, 04.
- Weller, Barry R & Kurre, James A, 1987. "Applicability of the Transfer Function Approach to Forecasting Employment Levels in Small Regions," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 21(1), pages 34-43, March.
- Fernandes, Marcelo & de Sa Mota, Bernardo & Rocha, Guilherme, 2005. "A multivariate conditional autoregressive range model," Economics Letters, Elsevier, vol. 86(3), pages 435-440, March.
- Morana, Claudio, 2001. "A semiparametric approach to short-term oil price forecasting," Energy Economics, Elsevier, vol. 23(3), pages 325-338, May.
- Michael Ye & John Zyren & Carol Blumberg & Joanne Shore, 2009. "A Short-Run Crude Oil Price Forecast Model with Ratchet Effect," Atlantic Economic Journal, International Atlantic Economic Society, vol. 37(1), pages 37-50, March.
- Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
- Albertson, Kevin & Aylen, Jonathan, 1999. "Forecasting using a periodic transfer function: with an application to the UK price of ferrous scrap," International Journal of Forecasting, Elsevier, vol. 15(4), pages 409-419, October.
- Diebold, Francis X & Mariano, Roberto S, 2002.
"Comparing Predictive Accuracy,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 20(1), pages 134-44, January.
- Ye, Michael & Zyren, John & Shore, Joanne, 2005. "A monthly crude oil spot price forecasting model using relative inventories," International Journal of Forecasting, Elsevier, vol. 21(3), pages 491-501.
- Feng Ren & David E. Giles, 2007.
"Extreme Value Analysis of Daily Canadian Crude Oil Prices,"
Econometrics Working Papers
0708, Department of Economics, University of Victoria.
- Feng Ren & David Giles, 2010. "Extreme value analysis of daily Canadian crude oil prices," Applied Financial Economics, Taylor & Francis Journals, vol. 20(12), pages 941-954.
- Yu, Lean & Wang, Shouyang & Lai, Kin Keung, 2008. "Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm," Energy Economics, Elsevier, vol. 30(5), pages 2623-2635, September.
- Sassan Alizadeh & Michael W. Brandt & Francis X. Diebold, 2002. "Range-Based Estimation of Stochastic Volatility Models," Journal of Finance, American Finance Association, vol. 57(3), pages 1047-1091, 06.
- Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
- Agnolucci, Paolo, 2009. "Volatility in crude oil futures: A comparison of the predictive ability of GARCH and implied volatility models," Energy Economics, Elsevier, vol. 31(2), pages 316-321, March.
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