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.
| Original language | English |
|---|---|
| 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 |
| Publisher | Palgrave Macmillan |
| Pages | 235-254 |
| Number of pages | 20 |
| ISBN (Electronic) | 9780230298101 |
| ISBN (Print) | 9780230283626, 9781349328901 |
| DOIs | |
| Publication status | Published - 2011 |
| Externally published | Yes |
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