A Risk and Forecasting Analysis of West Texas Intermediate Prices

David Allen and Abhay Kumar Singh

Chapter 10 in Financial Econometrics Modeling: Market Microstructure, Factor Models and Financial Risk Measures, 2011, pp 235-254 from Palgrave Macmillan

Abstract: Abstract In this chapter, we perform a two-step analysis that involves a sample of logarithmic returns formed from the daily closing prices of WTI oil prices. In the first step we employ CAViaR, a modeling approach formulated by Engle and Manganelli in 2004 which is a “value-at-risk” (VaR) modeling technique that uses quantile regression, to forecast WTI value-at-risk. In the second step we show the applicability of “support-vector regression” for oil-price prediction and compare it with more standard time-series ARIMA modeling.

Keywords: Root Mean Square Error; Quantile Regression; ARIMA Model; Return Series; West Texas Intermediate (search for similar items in EconPapers)
Date: 2011
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Persistent link: https://EconPapers.repec.org/RePEc:pal:palchp:978-0-230-29810-1_10

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DOI: 10.1057/9780230298101_10

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