Factor Structure in Commodity Futures Return and Volatility PDF Download
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Author: Peter Christoffersen
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Peter Christoffersen
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Peter Christoffersen
Publisher:
ISBN:
Category :
Languages : en
Pages : 64
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Book Description
We uncover stylized facts of commodity futures price and volatility dynamics in the post-financialization period and find a factor structure in daily commodity volatility that is much stronger than the factor structure in returns. The common factor in commodity volatility relates to stock market volatility as well as to the business cycle. Model-free realized commodity betas with the stock market were high during 2008-2010 but have since returned to the pre-crisis level close to zero. We conclude that, while commodity markets appear segmented from the equity market when considering only returns, commodity volatility indicates a nontrivial degree of market integration.
Author: M. A. H. Dempster
Publisher: CRC Press
ISBN: 1498712339
Category : Business & Economics
Languages : en
Pages : 725
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Book Description
Since a major source of income for many countries comes from exporting commodities, price discovery and information transmission between commodity futures markets are key issues for continued economic development.This book covers the fundamental theory of and derivatives pricing for major commodity markets as well as the interaction between commodi
Author: Mr.Ron Alquist
Publisher: International Monetary Fund
ISBN: 1484349377
Category : Business & Economics
Languages : en
Pages : 63
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Book Description
We present a simple macroeconomic model with a continuum of primary commodities used in the production of the final good, such that the real prices of commodities have a factor structure. One factor captures the combined contribution of all aggregate shocks which have no direct effects on commodity markets other than through general equilibrium effects on output, while other factors represent direct commodity shocks. Thus, the factor structure provides a decomposition of underlying structural shocks. The theory also provides guidance on how empirical factors can be rotated to identify the structural factors. We apply factor analysis and the identification conditions implied by the model to a cross-section of real non-energy commodity prices. The theoretical restrictions implied by the model are consistent with the data and thus yield a structural interpretation of the common factors in commodity prices. The analysis suggests that commodity-related shocks have generally played a limited role in global business cycle fluctuations.
Author: Pavel Teterin
Publisher:
ISBN:
Category : Electronic dissertations
Languages : en
Pages : 162
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Book Description
This dissertation includes three essays on volatility and information content of futures markets. This work gives new insight into the structural changes in volatility, the information content of global interest rate futures, and the time-series behavior of the volatility term structure. The first essay examines structural volatility shifts U.S. crude oil and corn futures markets. In trying to capture the interrelations present in the two markets, we take seriously the importance of properly modelling smooth structural shifts. We incorporate trigonometric functions into a multivariate GARCH model of crude and corn futures prices to obtain the empirical volatility response functions and the time-varying correlation coefficient. Although both short-term and long-term futures exhibit shifts in the mean and volatility, volatility shifts do not manifest themselves in the same manner for different maturities. In the second essay, we investigate the term structure of interest rate futures in the US, Eurozone, United Kingdom, and Switzerland and empirically document five unique results. First, implied USD futures rates contain significantly different information compared to USD spot rates. Second, the four interest rate futures contracts contain similar information that is driven by one common component. Third, implied futures rates contain more information regarding future rate changes than return premiums. Fourth, information shifts are associated with macroeconomic conditions and central bank policies. Finally, significant information shifts occurred during the 2013-2015 time frame, which were greater than those of the great recessionary period of 2008-2009. The third essay focuses on the Samuelson hypothesis, a proposition that futures volatility declines with maturity. We study the strength of the Samuelson effect over time in ten most actively traded U.S. commodity futures. Capturing the dynamics of the futures volatility term structure with three factors, we show that in most markets the slope factor is strongly negative in certain periods and only weakly or not at all negative in other periods. Consistent with the linkage between carry arbitrage and the Samuelson hypothesis, we find that high inventory levels correspond to a flatter volatility term structure. We also find that a flatter volatility term structure corresponds to lower absolute futures term premiums.
Author: Massimo Guidolin
Publisher:
ISBN:
Category :
Languages : en
Pages : 37
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Book Description
We test whether three well-known commodity-specific variables (basis, hedgingpressure, and momentum) may improve the predictive power for commodity futuresreturns of models otherwise based on macroeconomic factors. We compute recursive,out-of-sample forecasts for fifteen monthly commodity futures return series, whenestimation is based on a stepwise model selection approach under a probability-weightedregime-switching regression that identifies different volatility regimes.Comparisons with an AR(1) benchmark show that the inclusion of commodity-specificfactors does not improve the forecasting power. We perform a back-testing exercise of amean-variance investment strategy that exploits any predictability of the conditionalrisk premium of commodities, stocks, and bond returns, also taking into accounttransaction costs caused by portfolio rebalancing. The risk-adjusted performance of thisstrategy does not allow us to conclude that any forecasting approach outperforms theothers. However, there is evidence that investment strategies based on commodity-specificpredictors outperform the remaining strategies in the high-volatility state.
Author: Miguel Dorta
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
This study develops a multi-period log-return quantile forecasting procedure to evaluate the performance of eleven nearby commodity futures contracts (NCFC) using a sample of 897 daily price observations and at-the-money (ATM) put and call implied volatilities of the corresponding prices for the period from 1/16/2008 to 7/29/2011. The statistical approach employs dynamic log-returns quantile regression models to forecast price densities using implied volatilities (IVs) and factors estimated through principal component analysis (PCA) from the IVs, pooled IVs and lagged returns. Extensive in-sample and out-of-sample analyses are conducted, including assessment of excess trading returns, and evaluations of several combinations of quantiles, model specifications, and NCFC's. The results suggest that the IV-PCA-factors, particularly pooled return-IV-PCA-factors, improve quantile forecasting power relative to models using only individual IV information. The ratio of the put-IV to the call-IV is also found to improve quantile forecasting performance of log returns. Improvements in quantile forecasting performance are found to be better in the tails of the distribution than in the center. Trading performance based on quantile forecasts from the models above generated significant excess returns. Finally, the fact that the single IV forecasts were outperformed by their quantile regression (QR) counterparts suggests that the conditional distribution of the log-returns is not normal.
Author: Carl Chiarella
Publisher:
ISBN:
Category :
Languages : en
Pages : 30
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Book Description
By employing a continuous time stochastic volatility model, the dynamic relation between price returns and volatility changes in the commodity futures markets is analysed. An extensive daily database of gold and crude oil futures and futures options is used to estimate the model that is well suited to assess the return-volatility relation for the entire term structure of futures prices. The empirical results indicate a positive relation in the gold futures market and a negative relation in the crude oil futures market, especially over periods of high volatility principally driven by market-wide shocks. However, the opposite reaction occurs over quiet volatility periods when typically commodity-specific effects dominate. As leverage effect, volatility feedback effect and inventory effect do not adequately explain this reaction especially for the crude oil futures, the convenience yield effect is proposed. Accordingly, commodity futures markets in backwardation entail a positive relation, while futures markets in contango entail a negative relation.
Author: Jean-Paul Chavas
Publisher: University of Chicago Press
ISBN: 022612892X
Category : Business & Economics
Languages : en
Pages : 394
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Book Description
"The conference was organized by the three editors of this book and took place on August 15-16, 2012 in Seattle."--Preface.
Author: A K Gupta
Publisher: CRC Press
ISBN: 1351433008
Category : Mathematics
Languages : en
Pages : 382
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Book Description
Useful in physics, economics, psychology, and other fields, random matrices play an important role in the study of multivariate statistical methods. Until now, however, most of the material on random matrices could only be found scattered in various statistical journals. Matrix Variate Distributions gathers and systematically presents most of the recent developments in continuous matrix variate distribution theory and includes new results. After a review of the essential background material, the authors investigate the range of matrix variate distributions, including: matrix variate normal distribution Wishart distribution Matrix variate t-distribution Matrix variate beta distribution F-distribution Matrix variate Dirichlet distribution Matrix quadratic forms With its inclusion of new results, Matrix Variate Distributions promises to stimulate further research and help advance the field of multivariate statistical analysis.
