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.
|Title of host publication||Financial econometrics modeling|
|Subtitle of host publication||market microstructure, factor models and financial risk measures|
|Editors||Greg N. Gregoriou, Razvan Pascalau|
|Place of Publication||Hampshire, UK|
|Number of pages||20|
|ISBN (Print)||9780230283626, 9781349328901|
|Publication status||Published - 2011|