Risky Oil: It's All in the Tails
Christiane Baumeister, Florian Huber, Massimiliano Marcellino
NBER Working Paper,
Nr. 32524,
2024
Abstract
The substantial fluctuations in oil prices in the wake of the COVID-19 pandemic and the Russian invasion of Ukraine have highlighted the importance of tail events in the global market for crude oil which call for careful risk assessment. In this paper we focus on forecasting tail risks in the oil market by setting up a general empirical framework that allows for flexible predictive distributions of oil prices that can depart from normality. This model, based on Bayesian additive regression trees, remains agnostic on the functional form of the conditional mean relations and assumes that the shocks are driven by a stochastic volatility model. We show that our nonparametric approach improves in terms of tail forecasts upon three competing models: quantile regressions commonly used for studying tail events, the Bayesian VAR with stochastic volatility, and the simple random walk. We illustrate the practical relevance of our new approach by tracking the evolution of predictive densities during three recent economic and geopolitical crisis episodes, by developing consumer and producer distress indices that signal the build-up of upside and downside price risk, and by conducting a risk scenario analysis for 2024.
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Das IWH auf der ASSA-Jahrestagung 2020 in San Diego
Das IWH auf der ASSA-Jahrestagung 2020 in San Diego Die American Economic Association (AEA) organisiert vom 3. bis 5. Januar 2020 die jährlich stattfindende ASSA-Tagung in San…
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Department Profiles
Research Profiles of the IWH Departments All doctoral students are allocated to one of the four research departments (Financial Markets – Laws, Regulations and Factor Markets –…
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Department Profiles
Research Profiles of the IWH Departments All doctoral students are allocated to one of the four research departments (Financial Markets – Laws, Regulations and Factor Markets –…
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Correlation Scenarios and Correlation Stress Testing
Natalie Packham, Fabian Wöbbeking
Journal of Economic Behavior and Organization,
January
2023
Abstract
We develop a general approach for stress testing correlations of financial asset portfolios. The correlation matrix of asset returns is specified in a parametric form, where correlations are represented as a function of risk factors, such as country and industry factors. A sparse factor structure linking assets and risk factors is built using Bayesian variable selection methods. Regular calibration yields a joint distribution of economically meaningful stress scenarios of the factors. As such, the method also lends itself as a reverse stress testing framework: using the Mahalanobis distance or Highest Density Regions (HDR) on the joint risk factor distribution allows to infer worst-case correlation scenarios. We give examples of stress tests on a large portfolio of European and North American stocks.
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Shareholder Bargaining Power and the Emergence of Empty Creditors
Stefano Colonnello, M. Efing, Francesca Zucchi
Journal of Financial Economics,
Nr. 2,
2019
Abstract
Credit default swaps (CDSs) can create empty creditors who potentially force borrowers into inefficient bankruptcy but also reduce shareholders’ incentives to default strategically. We show theoretically and empirically that the presence and the effects of empty creditors on firm outcomes depend on the distribution of bargaining power among claimholders. If creditors would face powerful shareholders in debt renegotiation, firms are more likely to face the empty creditor problem. The empirical evidence confirms that more CDS insurance is written on firms with strong shareholders and that CDSs increase the bankruptcy risk of these same firms. The ensuing effect on firm value is negative.
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Tail-risk Protection Trading Strategies
Natalie Packham, Jochen Papenbrock, Peter Schwendner, Fabian Wöbbeking
Quantitative Finance,
Nr. 5,
2017
Abstract
Starting from well-known empirical stylized facts of financial time series, we develop dynamic portfolio protection trading strategies based on econometric methods. As a criterion for riskiness, we consider the evolution of the value-at-risk spread from a GARCH model with normal innovations relative to a GARCH model with generalized innovations. These generalized innovations may for example follow a Student t, a generalized hyperbolic, an alpha-stable or a Generalized Pareto distribution (GPD). Our results indicate that the GPD distribution provides the strongest signals for avoiding tail risks. This is not surprising as the GPD distribution arises as a limit of tail behaviour in extreme value theory and therefore is especially suited to deal with tail risks. Out-of-sample backtests on 11 years of DAX futures data, indicate that the dynamic tail-risk protection strategy effectively reduces the tail risk while outperforming traditional portfolio protection strategies. The results are further validated by calculating the statistical significance of the results obtained using bootstrap methods. A number of robustness tests including application to other assets further underline the effectiveness of the strategy. Finally, by empirically testing for second-order stochastic dominance, we find that risk averse investors would be willing to pay a positive premium to move from a static buy-and-hold investment in the DAX future to the tail-risk protection strategy.
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Shareholder Bargaining Power and the Emergence of Empty Creditors
Stefano Colonnello, M. Efing, Francesca Zucchi
Abstract
Credit default swaps (CDSs) can create empty creditors who potentially force borrowers into inefficient bankruptcy but also reduce shareholders‘ incentives to default strategically. We show theoretically and empirically that the presence and the effects of empty creditors on firm outcomes depend on the distribution of bargaining power among claimholders. Firms are more likely to have empty creditors if these would face powerful shareholders in debt renegotiation. The empirical evidence confirms that more CDS insurance is written on firms with strong shareholders and that CDSs increase the bankruptcy risk of these same firms. The ensuing effect on firm value is negative.
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Towards Unrestricted Public Use Business Microdata: The Synthetic Longitudinal Business Database
John M. Abowd, Ron S. Jarmin, Satkartar K. Kinney, Javier Miranda, Jerome P. Reiter, Arnold P. Reznek
International Statistical Review,
Nr. 3,
2011
Abstract
In most countries, national statistical agencies do not release establishment-level business microdata, because doing so represents too large a risk to establishments’ confidentiality. One approach with the potential for overcoming these risks is to release synthetic data; that is, the released establishment data are simulated from statistical models designed to mimic the distributions of the underlying real microdata. In this article, we describe an application of this strategy to create a public use file for the Longitudinal Business Database, an annual economic census of establishments in the United States comprising more than 20 million records dating back to 1976. The U.S. Bureau of the Census and the Internal Revenue Service recently approved the release of these synthetic microdata for public use, making the synthetic Longitudinal Business Database the first-ever business microdata set publicly released in the United States. We describe how we created the synthetic data, evaluated analytical validity, and assessed disclosure risk.
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The Great Risk Shift? Income Volatility in an International Perspective
Claudia M. Buch
CESifo Working Paper No. 2465,
2008
Abstract
Weakening bargaining power of unions and the increasing integration of the world economy may affect the volatility of capital and labor incomes. This paper documents and explains changes in income volatility. Using a theoretical framework which builds distribution risk into a real business cycle model, hypotheses on the determinants of the relative volatility of capital and labor are derived. The model is tested using industry-level data. The data cover 11 industrialized countries, 22 manufacturing and services industries, and a maximum of 35 years. The paper has four main findings. First, the unconditional volatility of labor and capital incomes has declined, reflecting the decline in macroeconomic volatility. Second, the idiosyncratic component of income volatility has hardly changed over time. Third, crosssectional heterogeneity in the evolution of relative income volatilities is substantial. If anything, the labor incomes of high- and low-skilled workers have become more volatile in relative terms. Fourth, income volatility is related to variables measuring the bargaining power of workers. Trade openness has no significant impact.
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