An analysis of macroeconomic and other market-wide drivers suggests that this trend factor is stronger in periods of low funding liquidity as measured by the TED spread. The trend factor is not encompassed by extant factors and is priced cross-sectionally. It outperforms the well-known momentum factor by more than nine times the Sharpe ratio and has less downside risk. The trend factor generates statistically and economically large returns during the post-financialization period 2004-2020. This paper identifies a trend factor that exploits the short-, intermediate-, and long-run moving averages of settlement prices in commodity futures markets. Research by Yufeng Han, Ph.D., Belk College of Business, University of North Carolina at Charlotte and Lingfei Kong, Ph.D., Olin School of Business, Washington University in St. The findings survive the consideration of transaction costs, alternative commodity scoring schemes, and long estimation windows. Focusing on the problem of a commodity investor that seeks exposure to the carry, hedging pressure, momentum, skewness, and basis-momentum factors, they demonstrate that the BOI portfolio outperforms not only a battery of parametric style-integrations motivated by the portfolio optimization literature, but also the highly effective equal-weight integrated portfolio. The authors of this paper develop a new Bayesian optimized integration (BOI) method that accounts for estimation risk in the style-weighting decision. A practical decision that a commodity style-integration investor faces at each rebalancing time is the relative weight of the predictive- or sorting-signal that underlies each standalone style. and Nan Zhao, Bayes Business School, City, University of London, U.K.Ĭommodity style-integration is appealing because by forming a unique long-short portfolio with simultaneous exposure to mildly correlated factors, a larger risk premium can be captured over time than with any of the underlying standalone styles. Research by Ana-Maria Fuertes, Ph.D., Bayes Business School, City, University of London, U.K. The authors conclude that the evidence of oil return predictability documented in previous studies may be misleading, as it stems from the use of within-month averages of daily oil prices in calculating monthly returns whereas end-of-month returns are more relevant for risk management and investment decision making as reflecting actual change in asset value. On the contrary, no evidence of predictability is found for end-of-month oil returns. It shows that monthly average oil returns are forecastable, in line with evidence documented in previous studies. This article re-examines the previously documented evidence of crude oil return predictability from several popular economic predictors and technical indicators and their combinations. Research by Thomas Conlon, Ph.D., Michael Smurfit Graduate Business School, University College Dublin, Ireland John Cotter, Ph.D., Michael Smurfit Graduate School of Business, University College Dublin, Ireland and Emmanuel Eyiah-Donkor, Ph.D., Rennes School of Business, France. The following research digest articles were contributed by Ana-Maria Fuertes, Ph.D., Professor in Finance and Econometrics, Bayes Business School, City, University of London, U.K. refiners are largely sufficient to absorb any temporary production disruptions. Our results suggest that oil reserves held by U.S. We also find no effect on imports, exchange rates or the import price of oil. Temporary oil supply shocks appear to have minor price effects, mainly for gasoline prices and CPI inflation. We find no evidence that temporary oil supply shocks affect state-level employment or indirectly affect industrial production in sectors not immediately related to oil production. We examine the effects of these temporary oil supply shocks for real economic activity in the U.S. Hurricanes disrupt oil production in the Gulf of Mexico because producers shut in oil platforms to safeguard lives and to prevent damage. By Johan Brannlund, Ph.D., Assistant Director of Scientific Computing, Bank of Canada Geoffrey Dunbar, Ph.D., Senior Research Advisor, Bank of Canada and Reinhard Ellwanger, Ph.D., Senior Economist, Bank of Canada
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