Commodities form the basis of industrial value creation and are central to the global economy. Despite their high relevance, raw materials often only account for a small proportion of the value of end products. This results in a correspondingly inelastic demand, and consequently strong price fluctuations in commodity markets. The fact that commodities are fungible, i.e. easily exchangeable due to their homogeneity and standardization, also contributes to this effect on raw materials. Due to volatile prices and the easy-tradability of exchange-traded commodities, commodities are not only a factor in production and for consumer goods but are also used for investment and as speculative instruments. The group headed by Prof. Dr. Andreas Rathgeber conducts research in this area of conflicting interests - in the context of internal as well as interdisciplinary research projects, with a variety of issues in the field of commodity finance.

On one hand, research questions cover corporate topics. In addition, the management of commodity price risks is also a focus. A variety of market participants are affected by rising and volatile commodity prices, e.g. raw material producers or processing companies, as well as intermediaries and end consumers. For this reason, corporate risk management is seen as a key factor of corporate management, in order to enable sound investment and financing decisions. In addition to hedging via financial derivatives, these include measures in operational risk management, such as the reduction of raw material requirements through recycling or the minimization of environmental risks through the use of environmentally-friendly technologies. On the other hand, the working group also deals with research topics related to capital markets. Via the introduction of structured financial products for commodities, investors also have access to previously restricted markets – which in turn raises questions regarding valuation of structured finance products, analysis of market prices, as well as the impact of FDI trading on actual commodity prices and the information content of commodity option prices. However, the associated progressive financialization of commodity markets and an increase in trading volumes also cause a number of side effects. For example, investor-driven prices and price bubbles have increasingly been a topic of discussion in recent years, which does not only apply to agricultural commodities but is also relevant for industrial and precious metals – posing risks to society, companies, and investors. In addition, comprehensive investability in commodities requires further development of existing approaches to the construction and composition of commodity indices, based on a fundamental valuation of resources.

• Economic development matters: A meta-regression analysis on the relation between environmental management and financial performance
  Hang, M.; Geyer-Klingeberg J.; Rathgeber, A.W.; Stöckl, S.
  Journal of Industrial Ecology, 2018, 22(4), pp. 720-744.
• Financialization of metal commodity markets: Does futures trading influence spot prices and volatility?
  Mayer, H.G.; Rathgeber, A.W.; Wanner, M.
  Resources Policy, 53, 2017, pp. 300-316.
• Metals: resources or financial assets? A multivariate cross-sectional analysis
  Lutzenberger, F.; Gleich, B.; Mayer, H.G.; Stepanek, C.; Rathgeber, A.W.
  Empirical Economics, 53(3), 2017, pp. 927-958.
• A truly market-value weighted commodity index
  Ludwig, M.; Mayer, H.G.; Rathgeber, A.W.; Spriegel, C.; Vogg, F.
  Journal of Asset Management, 18(3), 2017, pp. 222-242.
• The predictability of aggregate returns on commodity futures
  Lutzenberger, F.
  Review of Financial Economics, 23(3), 2014, pp. 120-130.
• Is the convenience yield a good indicator for a commodity’s supply risk
  Stepanek, C.; Walter, M.; Rathgeber, A.W.
  Resources Policy, 38(3), 2013, pp. 395-405.
• The route to rescource-efficient novel materials
  Krohns S.; Lunkenheimer P.; Meissner S.; Reller A.; Gleich B.; Rathgeber A. W.; Gaugler T.; Buhl H. U.; Sinclar D.; Loidl A.
  Nature Materials, 10(12), 2011, pp. 899-901.

In addition to the investigation of commodity-specific topics, a variety of business-related questions regarding the financial sector are examined in the context of corporate finance research. The research group focuses on questions of corporate risk management, capital structure, and determinants of the cost of capital. This research deals with companies from various sectors are scrutinized, primarily from commodity-oriented industries like energy and raw material producers.

• Measurement matters - A meta-study of the determinants of corporate capital structure
  Hang M., Geyer-Klingeberg J., Rathgber A.W., Stöckl S.
  Quarterly Review of Economics and Finance, 2018, 68, pp. 211-225.
• Industry cost of equity capital: European evidence for multifactor models 
  Lutzenberger, F. 
  The European Journal of Finance, 23(10), 2015, pp. 885-915.
• Determinants of corporate hedging: A (statistical) meta-analysis 
  Arnold, M.; Rathgeber, A.W.; Stoeckl, S. 
  Quarterly Review of Economics and Finance, 54(4), 2014, pp. 443-458.

In addition to commodity and corporate finance, the research group deals with the area of capital markets. The focus here is on derivative financial instruments such as options and related topics such as interest rate models. The examined questions include both the pricing of financial instruments with underlyings, such as stocks, indices or commodities, as well as investigations of market influencing factors, such as the market microstructure based on trading and order book data.

• Market Pricing of Credit Linked Notes - The Influence of the Financial Crises
  Walter, M.; Häckel, B.; Rathgeber, A.W.
  Journal of Credit Risk, 12(1), 2016, pp. 43-74.
• Pricing anomaly at the first sight: same borrower in different currencies faces different credit spreads – an explanation by means of a quanto option
  Rathgeber, A.W.; Rudolph, D.; Stöckl, S.
  Review of Derivatives Research, 18(2), 2015, pp. 107-143.
• Pricing fx forwards in OTC markets – new evidence for the pricing mechanism when faced with counterparty risk
  Leonhardt, A.; Rathgeber, A.W.; Stadler, J.; Stöckl, S.
  Applied Economics, 47(27), 2015, pp. 2860-2877

Another set of applied methods is meta-analysis, which is the "analysis of analyses". Originally created to increase the statistical power of small-panel trials in medical research, meta-analysis provides an overall understanding of a field via a statistical summary of primary studies. The rapid growth of empirical publications and the heterogeneity of results in many areas of research has also increased the importance of reliably aggregating findings from different primary studies. Meta-analysis allows this systematic secondary data analysis as well as identification and statistical quantification of the effect of differences in study design on consequent study results. Furthermore, it allows for the measurement and correction of distorting effects, such as the so-called publication bias or misspecification of models. Within meta-analysis, various methods are used, including univariate/multivariate approaches, meta-regression, and meta-analytical structural equation models.

The research group headed by Prof. Rathgeber applies the methodology of meta-analysis to core questions of empirical and commodity finance, such as determining the drivers of corporate risk management, the determinants of capital structure decisions, or the impact of shocks in commodity prices on share prices. As part of this research, the team collaborates with international scientists from the Meta-Analysis of Economics Research Networks ( MAER-Net).

• Measurement matters - A meta-study of the determinants of corporate capital structure
  Hang M., Geyer-Klingeberg J., Rathgber A.W., Stöckl S. 
  Quarterly Review of Economics and Finance, 2018.
• What do we really know about corporate hedging? A meta-analytical study
  Geyer-Klingeberg, J.; Hang, M.; Rathgeber, A.W.; Stoeckl, S.; Walter, M. 
  Business Research, 2018, 11(1), pp. 1-31.
• Do stock markets react to soccer games? A meta-regression analysis.
  Geyer-Klingeberg J.; Hang M.; Walter M.; Rathgeber A.W. 
  Applied Economics, 2018, 50(19), pp. 2171-2189.
• Determinants of corporate hedging: A (statistical) meta-analysis
  Arnold, M.; Rathgeber, A.W.; Stoeckl, S.
  Quarterly Review of Economics and Finance, 54(4), 2014, pp. 443-458.

Lévy processes, named after mathematician Paul Lévy, are stochastic processes with stationary and independent increments, e.g. the Wiener Process. Such increments, which are normally distributed over the Wiener process, are infinitely divisible in Lévy processes. Closely related to this property of Lévy processes is the fact that the characteristic function of the boundary distribution of Lévy processes can be described by the Lévy-Chintschin formula. This formula contains the so-called Lévy-Triple, with drift, diffusion, and jump components. Thus, the Wiener process comprising the first two components is as much a Lévy process as the Poisson process, which has only the jump component. The latter results in the marginal distribution of Lévy processes containing only fat tails and thus the kurtosis of the marginal distribution is significantly greater than three. Thus, Lévy processes are suitable for modeling the behavior of returns of non-normally distributed returns. This is not only true for stock returns but even more so for time series of commodity prices. For example, energy resources or different types of grain are particularly characterized by strong leptokurtic distributions, while raw animal materials are more platykurtic. Lévy processes have been used for some years to model behavior of interest rates or stock returns. However, the application of Lévy processes to the field of raw materials is only partially explored and is one of three main research areas of the research group. The second is the adaptation of Lévy processes to time series and simulation of processes in order to enable measurement of risk. The third area is the valuation of derivatives if those returns follow Lévy processes. Via such models, the inverse leverage effect of commodity options can be explained.

• Fitting generalized hyperbolic processes - new insights for generating initial values
  Rathgeber, A.W.; Stadler, J.; Stöckl, S. 
  Communications in Statistics - Simulation and Computation, 46(7), 2017, pp. 5752-5762.

• Modeling share returns - An empirical study on the Variance Gamma model
  Rathgeber, A.W.; Stadler, J.; Stöckl, S. 
  Journal of Economics and Finance, 40(4), 2016, pp. 653-682.
• Optionsbewertung unter Lévy-Prozessen: eine Analyse für den deutschen Aktienindex
  Rathgeber, A.W.
  Kredit und Kapital, 40(3), 2007, pp. 451-484.