28.02.2023 • 5/2023
Presseeinladung zur Konferenz: „Steigende Energiepreise – Wie kann der Umbau der deutschen Wirtschaft gelingen?“ am 9. März 2023 am IWH
Die Folgen von Krieg und Klimakrise fordern Deutschlands Unternehmen heraus. Wie der Wandel inmitten einer Energiekrise erfolgreich gestaltet werden kann, diskutiert eine Konferenz am Leibniz-Institut für Wirtschaftsforschung Halle (IWH) mit Gästen aus Wissenschaft, Politik und Industrie. Es sprechen unter anderem die Wirtschaftsweise Veronika Grimm und Sachsen-Anhalts Vize-Ministerpräsident Armin Willingmann.
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The Impact of Government Procurement Composition on Private R&D Activities
Viktor Slavtchev, Simon Wiederhold
Abstract
This paper addresses the question of whether government procurement can work as a de facto innovation policy tool. We develop an endogenous growth model with quality-improving in-novation that incorporates industries with heterogeneous innovation sizes. Government demand in high-tech industries increases the market size in these industries and, with it, the incentives for private firms to invest in R&D. At the economy-wide level, the additional R&D induced in high-tech industries outweighs the R&D foregone in all remaining industries. The implications of the model are empirically tested using a unique data set that includes federal procurement in U.S. states. We find evidence that a shift in the composition of government purchases toward high-tech industries indeed stimulates privately funded company R&D.
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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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Cryptocurrency Volatility Markets
Fabian Wöbbeking
Digital Finance,
No. 3,
2021
Abstract
By computing a volatility index (CVX) from cryptocurrency option prices, we analyze this market’s expectation of future volatility. Our method addresses the challenging liquidity environment of this young asset class and allows us to extract stable market implied volatilities. Two alternative methods are considered to compute volatilities from granular intra-day cryptocurrency options data, which spans over the COVID-19 pandemic period. CVX data therefore capture ‘normal’ market dynamics as well as distress and recovery periods. The methods yield two cointegrated index series, where the corresponding error correction model can be used as an indicator for market implied tail-risk. Comparing our CVX to existing volatility benchmarks for traditional asset classes, such as VIX (equity) or GVX (gold), confirms that cryptocurrency volatility dynamics are often disconnected from traditional markets, yet, share common shocks.
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Debatte um Intel-Ansiedlung: IWH veröffentlicht umstrittene Zitate im Volltext
Oliver Holtemöller
One-off Publications,
2023
Abstract
In einer öffentlichen Kontroverse über die Ansiedelung einer Chipfabrik in Magdeburg wurden Einschätzungen des Leibniz-Instituts für Wirtschaftsforschung Halle (IWH) teils stark kritisiert. Die Kritik bezieht sich auf einzelne Zitate aus einem Medienbericht. Nach Ansicht des IWH ergeben die Aussagen in ihrem ursprünglichen Zusammenhang ein anderes Bild, weshalb sie hier vollständig wiedergegeben werden.
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A Factor-model Approach for Correlation Scenarios and Correlation Stress Testing
Natalie Packham, Fabian Wöbbeking
Journal of Banking and Finance,
April
2019
Abstract
In 2012, JPMorgan accumulated a USD 6.2 billion loss on a credit derivatives portfolio, the so-called “London Whale”, partly as a consequence of de-correlations of non-perfectly correlated positions that were supposed to hedge each other. Motivated by this case, we devise a factor model for correlations that allows for scenario-based stress testing of correlations. We derive a number of analytical results related to a portfolio of homogeneous assets. Using the concept of Mahalanobis distance, we show how to identify adverse scenarios of correlation risk. In addition, we demonstrate how correlation and volatility stress tests can be combined. As an example, we apply the factor-model approach to the “London Whale” portfolio and determine the value-at-risk impact from correlation changes. Since our findings are particularly relevant for large portfolios, where even small correlation changes can have a large impact, a further application would be to stress test portfolios of central counterparties, which are of systemically relevant size.
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