An <i>N</i>‐factor Gaussian model of oil futures prices

Cortázar, Gonzalo; Naranjo, Lorenzo

doi:10.1002/fut.20198

Cited by 109 publications

(13 citation statements)

References 33 publications

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“…This fact occurred for Model 1 and Model 2. The presence of an non-significant market price of risk in factor models appears in many studies, see for example Schwartz and Smith (2000), Schwartz (1997) and Cortazar and Naranjo (2006). Again, we emphasize that the speed of mean reversion is significant in both cases for Model 1 and Model 2 justifying the hypothesis of a mean-reverting process for the VIX.…”

Section: Resultssupporting

confidence: 59%

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Estimation of VIX futures through Gaussian factor models

2022

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In this paper we investigate VIX dynamics through a two-factor Gaussian model, following Avellaneda and Papanicolaou (2019). Two strategies were adopted. First, we considered constant market price of risk. Second, we included time-varying market price of risk. In both cases, we estimated the model following two different approaches. In the first, we used a sample encompassing seven VIX future contracts and also the spot VIX. In the second, we dropped the spot VIX from the sample. We found that this removal provided a better adjustment between empirical and estimated data.

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Section: Resultssupporting

confidence: 59%

“…Regarding this point we cite Schwartz and Smith (2000), Geman and Nguyen (2005), Cortazar and Naranjo (2006), to mention a few.…”

Section: The Datamentioning

confidence: 99%

Estimation of VIX futures through Gaussian factor models

2022

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“…The mean-reverting processes are also called Ornstein-Uhlenbeck process. Cortazar and Naranjo (2006) proposed an N-factor Gaussian model to investigate the stochastic behaviour of oil future prices. The estimation was based on the Kalman fi lter.…”

Section: Review Of the Literaturementioning

confidence: 99%

Recent movement of oil prices and future scenarios

Aiube

Levy

2019

Nova econ.

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The recent movement of oil prices has brought many forecasts about what is coming in the near future. This is natural since the plunge in prices has been dramatic after 2014 and oil is an essential source of energy worldwide. This paper examines the probabilities of spot price scenarios. We model prices through stochastic processes focusing on the Schwartz-Smith model. The calibration is based on the term structure of future prices. Since the conditional distribution is log-normal we define the probability of a certain value of the spot price in a given time horizon. We found that the recovery of crude oil prices will be slow in the next four years. Moreover, the scenario of prices under US$ 20/barrel has the same probability as being greater than US$ 50/barrel. The methodology has many applications, mainly for government planning and for oil companies in their capital budget decisions.

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“…These models imply that the futures prices for different maturities should be perfectly correlated, defying the existing evidence. In an attempt to produce more realistic results, researchers have turned to multi-factor models (Schwartz, 1997;Schwartz and Smith, 2000;Cortazar and Schwartz, 2003;Cortazar and Naranjo, 2006). These multi-factor models assume that the spot price is the sum of short-and long-term components.…”

Section: Introductionmentioning

confidence: 99%