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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.
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.
Credit boom detection methodologies (such as threshold method) lack robustness as they are based on univariate detrending analysis and resort to ratios of credit to real activity. I propose a quantitative indicator to detect atypical behavior of credit from a multivariate system - a monetary VAR. This methodology explicitly accounts for endogenous interactions between credit, asset prices and real activity and detects atypical credit expansions and contractions in the Euro Area, Japan and the U.S. robustly and timely. The analysis also proves useful in real time.
We study to what extent firms spread out their debt maturity dates across time, which we call "granularity of corporate debt." We consider the role of debt granularity using a simple model in which a firm's inability to roll over expiring debt causes inefficiencies, such as costly asset sales or underinvestment. Since multiple small asset sales are less costly than a single large one, firms may diversify debt rollovers across maturity dates. We construct granularity measures using data on corporate bond issuers for the 1991-2011 period and establish a number of novel findings. First, there is substantial variation in granularity in that many firms have either very concentrated or highly dispersed maturity structures. Second, our model's predictions are consistent with observed variation in granularity. Corporate debt maturities are more dispersed for larger and more mature firms, for firms with better investment opportunities, with higher leverage ratios, and with lower levels of current cash flows. We also show that during the recent financial crisis especially firms with valuable investment opportunities implemented more dispersed maturity structures. Finally, granularity plays an important role for bond issuances, because we document that newly issued corporate bond maturities complement pre-existing bond maturity profiles.
Sovereign bond risk premiums
(2013)
Credit risk has become an important factor driving government bond returns. We therefore introduce an asset pricing model which exploits information contained in both forward interest rates and forward CDS spreads. Our empirical analysis covers euro-zone countries with German government bonds as credit risk-free assets. We construct a market factor from the first three principal components of the German forward curve as well as a common and a country-specific credit factor from the principal components of the forward CDS curves. We find that predictability of risk premiums of sovereign euro-zone bonds improves substantially if the market factor is augmented by a common and an orthogonal country-specific credit factor. While the common credit factor is significant for most countries in the sample, the country-specific factor is significant mainly for peripheral euro-zone countries. Finally, we find that during the current crisis period, market and credit risk premiums of government bonds are negative over long subintervals, a finding that we attribute to the presence of financial repression in euro-zone countries.
This paper takes a novel approach to estimating bankruptcy costs by inference from market prices of equity and put options using a dynamic structural model of capital structure. This approach avoids the selection bias of looking at firms in or near default and therefore permits theories of ex ante capital structure determination to be tested. We identify significant cross sectional variation in bankruptcy costs across industries and relate these to specific firm characteristics. We find that asset volatility and growth options have significant positive impacts, while tangibility and size have negative impacts. Our bankruptcy cost variable estimate significantly negatively impacts leverage ratios. This negative impact is in addition to that of other firm characteristics such as asset intangibility and asset volatility. The results provide strong support for the tradeoff theory of capital structure.
On July 4, 2013 the ECB Governing Council provided more specific forward guidance than in the past by stating that it expects ECB interest rates to remain at present or lower levels for an extended period of time. As explained by ECB President Mario Draghi this expectation is based on the Council’s medium-term outlook for inflation conditional on economic activity and money and credit. Draghi also stressed that there is no precise deadline for this extended period of time, but that a reasonable period can be estimated by extracting a reaction function. In this note, we use such a reaction function, namely the interest rate rule from Orphanides and Wieland (2013) that matches past ECB interest rate decisions quite well, to project the rate path consistent with inflation and growth forecasts from the survey of professional forecasters published by the ECB on August 8, 2013. This evaluation suggests an increase in ECB interest rates by May 2014 at the latest. We also use the Eurosystem staff projection from June 6, 2013 for comparison. While it would imply a longer period of low rates, it does not match past ECB decisions as well as the reaction function with SPF forecasts.
Insurance guarantee schemes aim to protect policyholders from the costs of insurer insolvencies. However, guarantee schemes can also reduce insurers’ incentives to conduct appropriate risk management. We investigate stock insurers’ risk-shifting behavior for insurance guarantee schemes under the two different financing alternatives: a flat-rate premium assessment versus a risk-based premium assessment. We identify which guarantee scheme maximizes policyholders’ welfare, measured by their expected utility. We find that the risk-based insurance guarantee scheme can only mitigate the insurer’s risk-shifting behavior if a substantial premium loading is present. Furthermore, the risk-based guarantee scheme is superior for improving policyholders’ welfare compared to the flat-rate scheme when the mitigating effect occurs.
We show that the optimal consumption of an individual over the life cycle can have the hump shape (inverted U-shape) observed empirically if the preferences of the individual exhibit internal habit formation. In the absence of habit formation, an impatient individual would prefer a decreasing consumption path over life. However, because of habit formation, a high initial consumption would lead to high required consumption in the future. To cover the future required consumption, wealth is set aside, but the necessary amount decreases with age which allows consumption to increase in the early part of life. At some age, the impatience outweighs the habit concerns so that consumption starts to decrease. We derive the optimal consumption strategy in closed form, deduce sufficient conditions for the presence of a consumption hump, and characterize the age at which the hump occurs. Numerical examples illustrate our findings. We show that our model calibrates well to U.S. consumption data from the Consumer Expenditure Survey.