Tail-risk Protection Trading Strategies
Natalie Packham, Jochen Papenbrock, Peter Schwendner, Fabian Wöbbeking
Quantitative Finance,
No. 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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Inflation Dynamics During the Financial Crisis in Europe: Cross-sectional Identification of Long-run Inflation Expectations
Geraldine Dany-Knedlik, Oliver Holtemöller
IWH Discussion Papers,
No. 10,
2017
Abstract
We investigate drivers of Euro area inflation dynamics using a panel of regional Phillips curves and identify long-run inflation expectations by exploiting the crosssectional dimension of the data. Our approach simultaneously allows for the inclusion of country-specific inflation and unemployment-gaps, as well as time-varying parameters. Our preferred panel specification outperforms various aggregate, uni- and multivariate unobserved component models in terms of forecast accuracy. We find that declining long-run trend inflation expectations and rising inflation persistence indicate an altered risk of inflation expectations de-anchoring. Lower trend inflation, and persistently negative unemployment-gaps, a slightly increasing Phillips curve slope and the downward pressure of low oil prices mainly explain the low inflation rate during the recent years.
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Impulse Response Analysis in a Misspecified DSGE Model: A Comparison of Full and Limited Information Techniques
Sebastian Giesen, Rolf Scheufele
Applied Economics Letters,
No. 3,
2016
Abstract
In this article, we examine the effect of estimation biases – introduced by model misspecification – on the impulse responses analysis for dynamic stochastic general equilibrium (DSGE) models. Thereby, we use full and limited information estimators to estimate a misspecified DSGE model and calculate impulse response functions (IRFs) based on the estimated structural parameters. It turns out that IRFs based on full information techniques can be unreliable under misspecification.
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Qual VAR Revisited: Good Forecast, Bad Story
Makram El-Shagi, Gregor von Schweinitz
Journal of Applied Economics,
No. 2,
2016
Abstract
Due to the recent financial crisis, the interest in econometric models that allow to incorporate binary variables (such as the occurrence of a crisis) experienced a huge surge. This paper evaluates the performance of the Qual VAR, originally proposed by Dueker (2005). The Qual VAR is a VAR model including a latent variable that governs the behavior of an observable binary variable. While we find that the Qual VAR performs reasonable well in forecasting (outperforming a probit benchmark), there are substantial identification problems even in a simple VAR specification. Typically, identification in economic applications is far more difficult than in our simple benchmark. Therefore, when the economic interpretation of the dynamic behavior of the latent variable and the chain of causality matter, use of the Qual VAR is inadvisable.
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FDI, Human Capital and Income Convergence — Evidence for European Regions
Björn Jindra, Philipp Marek, Dominik Völlmecke
Economic Systems,
No. 2,
2016
Abstract
This study examines income convergence in regional GDP per capita for a sample of 269 regions within the European Union (EU) between 2003 and 2010. We use an endogenous broad capital model based on foreign direct investment (FDI) induced agglomeration economies and human capital. By applying a Markov chain approach to a new dataset that exploits micro-aggregated sub-national FDI statistics, the analysis provides insights into regional income growth dynamics within the EU. Our results indicate a weak process of overall income convergence across EU regions. This does not apply to the dynamics within Central and East European countries (CEECs), where we find indications of a poverty trap. In contrast to FDI, regional human capital seems to be associated with higher income levels. However, we identify a positive interaction of FDI and human capital in their relation with income growth dynamics.
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The Joint Dynamics of Sovereign Ratings and Government Bond Yields
Makram El-Shagi, Gregor von Schweinitz
Abstract
Can a negative shock to sovereign ratings invoke a vicious cycle of increasing government bond yields and further downgrades, ultimately pushing a country toward default? The narratives of public and political discussions, as well as of some widely cited papers, suggest this possibility. In this paper, we will investigate the possible existence of such a vicious cycle. We find no evidence of a bad long-run equilibrium and cannot confirm a negative feedback loop leading into default as a transitory state for all but the very worst ratings.
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Declining Business Dynamism: What We Know and the Way Forward
Ryan A. Decker, John Haltiwanger, Ron S. Jarmin, Javier Miranda
American Economic Review: Papers and Proceedings,
No. 5,
2016
Abstract
A growing body of evidence indicates that the U.S. economy has become less dynamic in recent years. This trend is evident in declining rates of gross job and worker flows as well as declining rates of entrepreneurship and young firm activity, and the trend is pervasive across industries, regions, and firm size classes. We describe the evidence on these changes in the U.S. economy by reviewing existing research. We then describe new empirical facts about the relationship between establishment-level productivity and employment growth, framing our results in terms of canonical models of firm dynamics and suggesting empirically testable potential explanations.
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Central Bank Transparency and Cross-border Banking
Stefan Eichler, Helge Littke, Lena Tonzer
Abstract
We analyze the effect of central bank transparency on cross-border bank activities. Based on a panel gravity model for cross-border bank claims for 21 home and 47 destination countries from 1998 to 2010, we find strong empirical evidence that a rise in central bank transparency in the destination country, on average, increases cross-border claims. Using interaction models, we find that the positive effect of central bank transparency on cross-border claims is only significant if the central bank is politically independent. Central bank transparency and credibility are thus considered complements by banks investing abroad.
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Nested Models and Model Uncertainty
Alexander Kriwoluzky, Christian A. Stoltenberg
Scandinavian Journal of Economics,
No. 2,
2016
Abstract
Uncertainty about the appropriate choice among nested models is a concern for optimal policy when policy prescriptions from those models differ. The standard procedure is to specify a prior over the parameter space, ignoring the special status of submodels (e.g., those resulting from zero restrictions). Following Sims (2008, Journal of Economic Dynamics and Control 32, 2460–2475), we treat nested submodels as probability models, and we formalize a procedure that ensures that submodels are not discarded too easily and do matter for optimal policy. For the United States, we find that optimal policy based on our procedure leads to substantial welfare gains compared to the standard procedure.
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Does the Technological Content of Government Demand Matter for Private R&D? Evidence from US States
Viktor Slavtchev, Simon Wiederhold
American Economic Journal: Macroeconomics,
No. 2,
2016
Abstract
Governments purchase everything from airplanes to zucchini. This paper investigates the role of the technological content of government procurement in innovation. In a theoretical model, we first show that a shift in the composition of public purchases toward high-tech products translates into higher economy-wide returns to innovation, leading to an increase in the aggregate level of private R&D. Using unique data on federal procurement in US states and performing panel fixed-effects estimations, we find support for the model's prediction of a positive R&D effect of the technological content of government procurement. Instrumental-variable estimations suggest a causal interpretation of our findings.
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