Jump dynamics with structural breaks for crude oil prices

Abstract This study investigates the joint phenomena of permanent and transitory components in conditional variance and jump intensity along with verification of structural breaks for crude oil prices. We adopt a Component-ARJI model with structural break analysis, utilizing daily data on West Texas Intermediate crude oil spot and futures contracts. The analytical results verify the existence of permanent and transitory components in conditional variance, with the permanent component of conditional variance increasing with the occurrence of a sudden major event (such as the Iraqi Invasion of Kuwait, Operation Desert Storm and the war between the US and Iraq), and a relatively greater increase in the transitory component over the same period. Notably, jump intensity fluctuates with an increase in the transitory component of conditional variance in response to abnormal events. It is the transitory component which serves as the primary influential factor for jumps in returns; therefore, speculators are willing to take large risks, particularly with respect to anticipating future price movements, or gambling, in the hopes of rapidly making substantial gains; thus, speculators prefer the temporary volatility component and engage in trade activities. However, investors prefer the permanent volatility component, because they may well be better off relocating their assets into more stable portfolios to outperform the market portfolio over the long run.

[1]  David H. Papell,et al.  The Structure of Unemployment , 2000, Review of Economics and Statistics.

[2]  Jungseok Park,et al.  Oil price shocks and stock markets in the U.S. and 13 European countries , 2008 .

[3]  J. Maheu,et al.  Conditional Jump Dynamics in Stock Market Returns , 2002 .

[4]  Gonzalo Cortazar,et al.  Implementing a stochastic model for oil futures prices , 2003 .

[5]  Eduardo S. Schwartz,et al.  Stochastic Convenience Yield and the Pricing of Oil Contingent Claims , 1990 .

[6]  P. Collin‐Dufresne,et al.  Stochastic Convenience Yield Implied from Commodity Futures and Interest Rates , 2005 .

[7]  Lynda Khalaf,et al.  On Jumps and Arch Effects in Natural Resource Prices. An Application to Stumpage Prices from Pacific Northwest National Forests , 2000 .

[8]  J. Zidek,et al.  ON SEGMENTED MULTIVARIATE REGRESSION , 1997 .

[9]  D. McMillan,et al.  Intra‐day volatility components in FTSE‐100 stock index futures , 2000 .

[10]  Permanent and Transitory Components in the Chinese Stock Market: The ARJI-Trend Model , 2009 .

[11]  W. Fuller,et al.  LIKELIHOOD RATIO STATISTICS FOR AUTOREGRESSIVE TIME SERIES WITH A UNIT ROOT , 1981 .

[12]  Robert F. Dittmar,et al.  Quadratic Term Structure Models: Theory and Evidence , 2000 .

[13]  Lynda Khalaf,et al.  On Jumps and Arch Effects in Natural Resource Prices: An Application to Pacific Northwest Stumpage Prices , 2002 .

[14]  Nicholas G. Polson,et al.  The Impact of Jumps in Volatility and Returns , 2000 .

[15]  Thomas H. McCurdy,et al.  News Arrival, Jump Dynamics and Volatility Components for Individual Stock Returns , 2003 .

[16]  R. Pindyck.  The Dynamics of Commodity Spot and Futures Markets: A Primer , 2001 .

[17]  P. Perron,et al.  Computation and Analysis of Multiple Structural-Change Models , 1998 .

[18]  Eduardo S. Schwartz.  The stochastic behavior of commodity prices: Implications for valuation and hedging , 1997 .

[19]  Shyh-Wei Chen,et al.  GARCH, jumps and permanent and transitory components of volatility: the case of the Taiwan exchange rate , 2004, Math. Comput. Simul..

[20]  R. Pindyck.  The long-run evolution of energy prices , 1999 .

[21]  Robin L. Lumsdaine,et al.  Multiple Trend Breaks and the Unit-Root Hypothesis , 1997, Review of Economics and Statistics.

[22]  René Garcia,et al.  Série Scientifique Scientific Series an Analysis of the Real Interest Rate under Regime Shifts , 2022 .

[23]  P. Perron,et al.  Estimating and testing linear models with multiple structural changes , 1995 .

[24]  Stacie Beck.  Autoregressive conditional heteroscedasticity in commodity spot prices , 2001 .

[25]  T. Ané.  Short and long term components of volatility in Hong Kong stock returns , 2006 .

[26]  J. Mei,et al.  What makes the stock market jump? An analysis of political risk on Hong Kong stock returns , 2001 .

[27]  Volatility Relationship between Crude Oil and Petroleum Products , 2007 .

[28]  Lynda Khalaf,et al.  Simulation-based exact jump tests in models with conditional heteroskedasticity , 2003 .

[29]  M. Wohar,et al.  Structural Breaks and Predictive Regression Models of Aggregate U.S. Stock Returns , 2006 .

[30]  Michael S. Johannes,et al.  The Statistical and Economic Role of Jumps in Continuous-Time Interest Rate Models , 2004 .

[31]  R. Engle,et al.  A Permanent and Transitory Component Model of Stock Return Volatility , 1993 .

[32]  Eduardo S. Schwartz,et al.  Short-Term Variations and Long-Term Dynamics in Commodity Prices , 2000 .

[33]  Erol M. Balkan.  Political instability, country risk and probability of default , 1992 .