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The U.S. Energy Information Administration (EIA) regularly publishes monthly and quarterly forecasts of the price of crude oil for horizons up to two years, which are widely used by practitioners. Traditionally, such out-of-sample forecasts have been largely judgmental, making them difficult to replicate and justify. An alternative is the use of real-time econometric oil price forecasting models. We investigate the merits of constructing combinations of six such models. Forecast combinations have received little attention in the oil price forecasting literature to date. We demonstrate that over the last 20 years suitably constructed real-time forecast combinations would have been systematically more accurate than the no-change forecast at horizons up to 6 quarters or 18 months. MSPE reduction may be as high as 12% and directional accuracy as high as 72%. The gains in accuracy are robust over time. In contrast, the EIA oil price forecasts not only tend to be less accurate than no-change forecasts, but are much less accurate than our preferred forecast combination. Moreover, including EIA forecasts in the forecast combination systematically lowers the accuracy of the combination forecast. We conclude that suitably constructed forecast combinations should replace traditional judgmental forecasts of the price of oil.
Are product spreads useful for forecasting? An empirical evaluation of the Verleger hypothesis
(2013)
Notwithstanding a resurgence in research on out-of-sample forecasts of the price of oil in recent years, there is one important approach to forecasting the real price of oil which has not been studied systematically to date. This approach is based on the premise that demand for crude oil derives from the demand for refined products such as gasoline or heating oil. Oil industry analysts such as Philip Verleger and financial analysts widely believe that there is predictive power in the product spread, defined as the difference between suitably weighted refined product market prices and the price of crude oil. Our objective is to evaluate this proposition. We derive from first principles a number of alternative forecasting model specifications involving product spreads and compare these models to the no-change forecast of the real price of oil. We show that not all product spread models are useful for out-of-sample forecasting, but some models are, even at horizons between one and two years. The most accurate model is a time-varying parameter model of gasoline and heating oil spot spreads that allows the marginal product market to change over time. We document MSPE reductions as high as 20% and directional accuracy as high as 63% at the two-year horizon, making product spread models a good complement to forecasting models based on economic fundamentals, which work best at short horizons.
U.S. retail food price increases in recent years may seem large in nominal terms, but after adjusting for inflation have been quite modest even after the change in U.S. biofuel policies in 2006. In contrast, increases in the real prices of corn, soybeans, wheat and rice received by U.S. farmers have been more substantial and can be linked in part to increases in the real price of oil. That link, however, appears largely driven by common macroeconomic determinants of the prices of oil and agricultural commodities rather than the pass-through from higher oil prices. We show that there is no evidence that corn ethanol mandates have created a tight link between oil and agricultural markets. Rather increases in food commodity prices not associated with changes in global real activity appear to reflect a wide range of idiosyncratic shocks ranging from changes in biofuel policies to poor harvests. Increases in agricultural commodity prices in turn contribute little to U.S. retail food price increases, because of the small cost share of agricultural products in food prices. There is no evidence that oil price shocks have caused more than a negligible increase in retail food prices in recent years. Nor is there evidence for the prevailing wisdom that oil-price driven increases in the cost of food processing, packaging, transportation and distribution are responsible for higher retail food prices. Finally, there is no evidence that oil-market specific events or for that matter U.S. biofuel policies help explain the evolution of the real price of rice, which is perhaps the single most important food commodity for many developing countries.
We investigate the theoretical impact of including two empirically-grounded insights in a dynamic life cycle portfolio choice model. The first is to recognize that, when managing their own financial wealth, investors incur opportunity costs in terms of current and future human capital accumulation, particularly if human capital is acquired via learning by doing. The second is that we incorporate age-varying efficiency patterns in financial decisionmaking. Both enhancements produce inactivity in portfolio adjustment patterns consistent with empirical evidence. We also analyze individuals’ optimal choice between self-managing their wealth versus delegating the task to a financial advisor. Delegation proves most valuable to the young and the old. Our calibrated model quantifies welfare gains from including investment time and money costs, as well as delegation, in a life cycle setting.
Household decisions are profoundly shaped by a complex set of financial options due to Social Security rules determining retirement, spousal, and survivor benefits, along with benefit adjustments that vary with the age at which these are claimed. These rules influence optimal household asset allocation, insurance, and work decisions, given life cycle demographic shocks such as marriage, divorce, and children. Our model generates a wealth profile and a low and stable equity fraction consistent with empirical evidence. We also confirm predictions that wives will claim retirement benefits earlier than husbands, while life insurance is mainly purchased by younger men. Our policy simulations imply that eliminating survivor benefits would sharply reduce claiming differences by sex while dramatically increasing men’s life insurance purchases.
This paper employs stochastic simulations of the New Area-Wide Model—a microfounded open-economy model developed at the ECB—to investigate the consequences of the zero lower bound on nominal interest rates for the evolution of risks to price stability in the euro area during the recent financial crisis. Using a formal measure of the balance of risks, which is derived from policy-makers’ preferences about inflation outcomes, we first show that downside risks to price stability were considerably greater than upside risks during the first half of 2009, followed by a gradual rebalancing of these risks until mid-2011 and a renewed deterioration thereafter. We find that the lower bound has induced a noticeable downward bias in the risk balance throughout our evaluation period because of the implied amplification of deflation risks. We then illustrate that, with nominal interest rates close to zero, forward guidance in the form of a time-based conditional commitment to keep interest rates low for longer can be successful in mitigating downside risks to price stability. However, we find that the provision of time-based forward guidance may give rise to upside risks over the medium term if extended too far into the future. By contrast, time-based forward guidance complemented with a threshold condition concerning tolerable future inflation can provide insurance against the materialisation of such upside risks.
Empirical evidence suggests that asset returns correlate more strongly in bear markets than conventional correlation estimates imply. We propose a method for determining complete tail correlation matrices based on Value-at-Risk (VaR) estimates. We demonstrate how to obtain more efficient tail-correlation estimates by use of overidentification strategies and how to guarantee positive semidefiniteness, a property required for valid risk aggregation and Markowitz{type portfolio optimization. An empirical application to a 30-asset universe illustrates the practical applicability and relevance of the approach in portfolio management.
We analyze the equilibrium in a two-tree (sector) economy with two regimes. The output of each tree is driven by a jump-diffusion process, and a downward jump in one sector of the economy can (but need not) trigger a shift to a regime where the likelihood of future jumps is generally higher. Furthermore, the true regime is unobservable, so that the representative Epstein-Zin investor has to extract the probability of being in a certain regime from the data. These two channels help us to match the stylized facts of countercyclical and excessive return volatilities and correlations between sectors. Moreover, the model reproduces the predictability of stock returns in the data without generating consumption growth predictability. The uncertainty about the state also reduces the slope of the term structure of equity. We document that heterogeneity between the two sectors with respect to shock propagation risk can lead to highly persistent aggregate price-dividend ratios. Finally, the possibility of jumps in one sector triggering higher overall jump probabilities boosts jump risk premia while uncertainty about the regime is the reason for sizeable diffusive risk premia.
This study presents an empirical analysis of capital and liability management in eight cases of bank restructurings and resolutions from eight different European countries. It can be read as a companion piece to an earlier study by the author covering the specific bank restructuring programs of Greece, Spain and Cyprus during 2012/13.
The study portrays for each case the timelines between the initial credit event and the (last) restructuring. It proceeds to discuss the capital and liability management activity before restructuring and the restructuring itself, launches an attempt to calibrate the extent of creditor participation as well as expected loss by government, and engages in a counterfactual discussion of what could have been a least cost restructuring approach.
Four of the eight cases are resolutions, i.e. the original bank is unwound (Anglo Irish Bank, Amagerbanken, Dexia, Laiki), while the four other banks have de-facto or de-jure become nationalized and are awaiting re-privatization after the restructuring (Deutsche Pfandbriefbank/Hypo Real Estate, Bankia, SNS Reaal, Alpha Bank). The case selection follows considerations of their model character for the European bank restructuring and resolution policy discussion while straddling both the U.S. (2007 - 2010) and the European (2010 - ) legs of the financial crisis, which each saw very different policy responses....
We provide an assessment of the determinants of the risk remia paid by non-financial corporations on long-term bonds. By looking at 5,500 issues over the period 2005-2012, we find that in recent years the sovereign debt market turbulence has been a major driver of corporate risk. Compared with the three-year period 2005-07 before the global financial crisis, in the years 2010-12 Italian, Spanish and Portuguese firms paid on average between 70 and 120 basis points of additional premium due to the negative spillovers from the sovereign debt crisis, while German firms got a discount of 40 basis points.