Jumps and Stochastic Volatility in Oil Prices

Jumps and Stochastic Volatility in Oil Prices
Author: Karl Larsson
Publisher:
Total Pages: 31
Release: 2014
Genre:
ISBN:

In this paper we examine the empirical performance of affine jump diffusion models with stochastic volatility in a time series study of crude oil prices. We compare four different models and estimate them using the Markov Chain Monte Carlo method. The support for a stochastic volatility model including jumps in both prices and volatility is strong and the model clearly outperforms the others in terms of a superior fit to data. Using this model and our estimation methodology we obtain detailed insight into two periods of market stress that are included in our sample; the Gulf war and the recent financial crisis. We also address the economic significance of model choice in two option pricing applications. First we compare the implied volatilities generated by the different estimated models. As a final application we price the real option to develop an oil field. Our findings indicate that model choice can have a material effect on the option values.

Multivariate Stochastic Volatility-Double Jump Model

Multivariate Stochastic Volatility-Double Jump Model
Author: Marcio Poletti Laurini
Publisher:
Total Pages: 40
Release: 2017
Genre:
ISBN:

We propose a new multivariate model to capture the presence of jumps in mean and conditional variance in the returns of oil prices and companies in this sector. The model is based on the presence of common factors associated with jumps in mean and variance, as it performs a decomposition of the conditional variance of each asset as the sum of the common factor plus a specific transitory factor in a multivariate stochastic volatility structure. The estimation is made through Bayesian methods using Markov Chain Monte Carlo. The model allows recovering the changes in prices and volatility patterns observed in this sector, relating the jumps with the events observed in the period 2000-2015. We apply the model to estimate risk management measures, hedging and portfolio allocation and performing a comparison with other multivariate models of conditional volatility. Based on the results, we may conclude that the proposed model has a better performance when used to calculate portfolio VaR, since it does not reject the hypothesis of correct nominal coverage with certain specifications presented in this work. Furthermore, we conclude that the model can be used to hedge oil price risks, through the optimal hedge ratio for a portfolio containing an oil company as-set (stock) and the oil price contract. When compared to the standard methodology based on GARCH models, our model performs well in this application.

Recent Dynamics of Crude Oil Prices

Recent Dynamics of Crude Oil Prices
Author: Noureddine Krichene
Publisher: International Monetary Fund
Total Pages: 32
Release: 2006-12
Genre: Business & Economics
ISBN:

Crude oil prices have been on a run-up spree in recent years. Their dynamics were characterized by high volatility, high intensity jumps, and strong upward drift, indicating that oil markets were constantly out-of-equilibrium. An explanation of the oil price process in terms of the underlying fundamentals of oil markets and world economy was provided, viewing pressure on oil prices mainly as a result of rigid crude oil supply and an expanding world demand for crude oil. A change in the oil price process parameters would require a change in the underlying fundamentals. Market expectations, extracted from call and put option prices, anticipated no change, in the short term, in the underlying fundamentals. Markets expected oil prices to remain volatile and jumpy, and with higher probabilities, to rise, rather than fall, above the expected mean.

A Maximal Affine Stochastic Volatility Model of Oil Prices

A Maximal Affine Stochastic Volatility Model of Oil Prices
Author: W. Keener Hughen
Publisher:
Total Pages: 33
Release: 2017
Genre:
ISBN:

This study develops and estimates a stochastic volatility model of commodity prices that nests many of the previous models in the literature. The model is an affine three-factor model with one state variable driving the volatility and is maximal among all such models that are also identifiable. The model leads to quasi-analytical formulas for futures and options prices. It allows for time-varying correlation structures between the spot price and convenience yield, the spot price and its volatility, and the volatility and convenience yield. It allows for expected mean-reversion in the short term and for an increasing expected long term price, and for time-varying risk premia. Furthermore, the model allows for the situation in which options' prices depend on risk not fully spanned by futures prices. These properties are desirable and empirically important for modeling many commodities, especially crude oil.

Handbook Of Energy Finance: Theories, Practices And Simulations

Handbook Of Energy Finance: Theories, Practices And Simulations
Author: Stephane Goutte
Publisher: World Scientific
Total Pages: 827
Release: 2020-01-30
Genre: Business & Economics
ISBN: 9813278390

Modeling the dynamics of energy markets has become a challenging task. The intensification of their financialization since 2004 had made them more complex but also more integrated with other tradable asset classes. More importantly, their large and frequent fluctuations in terms of both prices and volatility, particularly in the aftermath of the global financial crisis 2008-2009, posit difficulties for modeling and forecasting energy price behavior and are primary sources of concerns for macroeconomic stability and general economic performance.This handbook aims to advance the debate on the theories and practices of quantitative energy finance while shedding light on innovative results and technical methods applied to energy markets. Its primary focus is on the recent development and applications of mathematical and quantitative approaches for a better understanding of the stochastic processes that drive energy market movements. The handbook is designed for not only graduate students and researchers but also practitioners and policymakers.

Speculation and Volatility Spillover in the Crude Oil and Agricultural Commodity Markets

Speculation and Volatility Spillover in the Crude Oil and Agricultural Commodity Markets
Author: Xiaodong Du
Publisher:
Total Pages: 23
Release: 2009
Genre: Agricultural prices
ISBN:

This paper assesses the roles of various factors influencing the volatility of crude oil prices and the possible linkage between this volatility and agricultural commodity markets. Stochastic volatility models are applied to weekly crude oil, corn, and wheat futures prices from November 1998 to January 2009. Model parameters are estimated using Bayesian Markov chain Monte Carlo methods. The main results are as follows. Speculation, scalping, and petroleum inventories are found to be important in explaining oil price variation. Several properties of crude oil price dynamics are established, including mean-reversion, a negative correlation between price and volatility, volatility clustering, and infrequent compound jumps. We find evidence of volatility spillover among crude oil, corn, and wheat markets after the fall of 2006. This could be largely explained by tightened interdependence between these markets induced by ethanol production.

Volatility of Oil Prices

Volatility of Oil Prices
Author: Mr.Peter Wickham
Publisher: International Monetary Fund
Total Pages: 20
Release: 1996-08-01
Genre: Business & Economics
ISBN: 1451954727

This paper examines the behavior of crude oil prices since 1980, and in particular the volatility of these prices. The empirical analysis covers “spot” prices for one of the key internationally traded crudes, namely Dated Brent Blend. A GARCH (generalized autoregressive conditional heteroscedastic) model, which allows the conditional variance to be time-variant, is estimated for the period which includes the oil price slump of 1986 and the surge in prices in 1990 as a result of the Iraqi invasion of Kuwait. The paper also discusses the growth of futures and derivative markets and the dynamic links between spot and futures markets.

Affine-Structure Models and the Pricing of Energy Commodity Derivatives

Affine-Structure Models and the Pricing of Energy Commodity Derivatives
Author: Ioannis Kyriakou
Publisher:
Total Pages: 39
Release: 2019
Genre:
ISBN:

We consider a seasonal mean-reverting model for energy commodity prices with jumps and Heston-type stochastic volatility, as well as three nested models for comparison. By exploiting the affine form of the log-spot models, we develop a general valuation framework for futures and discrete arithmetic Asian options. We investigate five major petroleum commodities from the European market (Brent crude oil, gasoil) and US market (light sweet crude oil, gasoline, heating oil) and analyze the effects of the competing fitted stochastic spot models in futures pricing, Asian options pricing and hedging. We find evidence that price jumps and stochastic volatility are important features of the petroleum price dynamics.

Nonparametric Statistical Methods

Nonparametric Statistical Methods
Author: Myles Hollander
Publisher: John Wiley & Sons
Total Pages: 872
Release: 2013-11-25
Genre: Mathematics
ISBN: 1118553292

Praise for the Second Edition “This book should be an essential part of the personal library of every practicing statistician.”—Technometrics Thoroughly revised and updated, the new edition of Nonparametric Statistical Methods includes additional modern topics and procedures, more practical data sets, and new problems from real-life situations. The book continues to emphasize the importance of nonparametric methods as a significant branch of modern statistics and equips readers with the conceptual and technical skills necessary to select and apply the appropriate procedures for any given situation. Written by leading statisticians, Nonparametric Statistical Methods, Third Edition provides readers with crucial nonparametric techniques in a variety of settings, emphasizing the assumptions underlying the methods. The book provides an extensive array of examples that clearly illustrate how to use nonparametric approaches for handling one- or two-sample location and dispersion problems, dichotomous data, and one-way and two-way layout problems. In addition, the Third Edition features: The use of the freely available R software to aid in computation and simulation, including many new R programs written explicitly for this new edition New chapters that address density estimation, wavelets, smoothing, ranked set sampling, and Bayesian nonparametrics Problems that illustrate examples from agricultural science, astronomy, biology, criminology, education, engineering, environmental science, geology, home economics, medicine, oceanography, physics, psychology, sociology, and space science Nonparametric Statistical Methods, Third Edition is an excellent reference for applied statisticians and practitioners who seek a review of nonparametric methods and their relevant applications. The book is also an ideal textbook for upper-undergraduate and first-year graduate courses in applied nonparametric statistics.