Research Projects Currently Funded
DFG Project: Cryptocurrency Valuation - An Asset Pricing Perspective
Currently, the German Research Foundation (DFG) is funding our project "The Value of Crypto Currencies - An Asset Pricing Perspective", in which we cooperate with Prof. Dr. Erik Theissen from the University of Mannheim.
Bitcoin, the first cryptocurrency, was originally designed to be a form of electronic cash that enables online payment without intermediation by financial institutions. While Bitcoin and other cryptocurrencies still serve that purpose, they are nowadays widely considered as financial assets and are held as investments or for speculative purposes. The CME and the Cboe, two of the world's largest derivatives exchanges, trade Bitcoin futures, and some authors consider cryptocurrencies a new asset class. Despite their growing popularity cryptocurrencies are not well understood. Why is someone ready to pay a five-digit dollar amount for a piece of data representing a unit of virtual cash? Why is private money without commodity backing valuable at all? Are we simply witnessing an enormous bubble or do modern cryptocurrencies rely on unique design features that justify at least part of the demand - for instance, the cryptographic techniques inducing a high degree of counterfeit safety or the protocols that set an upper bound on cryptocurrency supply acting as commitment device not to issue too much virtual money? Are such design features crucial value drivers? What else explains a cryptocurrency’s value and volatility?
Although, at a technical level, the unique features of cryptocurrencies and the underlying blockchain (or distributed ledger) technology have been extensively discussed from a computer science and a legal perspective, there is a lack of economic research to answer the questions above. We therefore seek to deepen the understanding of cryptocurrencies from an economic and finance perspective. More specifically: We want to develop an economic model that explains, from economic primitives, why cryptocurrencies have a non-zero value at all and understand which of the various design features of cryptocurrencies affect their value. There are three sub-goals that specify the overriding question: (1) We want to provide an overview and basic understanding of the unique design features of a cryptocurrency and to identify those that are relevant for the pricing and risk profile of cryptocurrencies. At this point, we will rely on both a literature review and an own exploratory empirical analysis of the variety of cryptocurrencies traded. (2) We plan to develop an economic model that allows to formally analyze the effects of those design features that are identified in step 1 as most important for a cryptocurrency’s value and volatility. Within this modelling approach, we intend to consider two main agent groups, the consumers and the miners, and their intergroup dynamics to derive price implications. (3) We seek to empirically assess the relevance of our model predictions using the cross-sectional variation between different cryptocurrencies.
The expected outcomes are not only novel from a theoretical perspective, but also highly relevant for informing the ongoing public debate on the merits and dangers of cryptocurrencies.
Working papers and publications on this DFG project:
- Schuster, P.; Theissen, E.; Uhrig-Homburg, M. (2020). Financial applications of block chain technology. Schmalenbach's journal for economic research, (72), 125-147.
DFG Project: The Macroeconomic Determinants of the Term Structure of Illiquidity Premia
Currently, the German Research Foundation (DFG) is funding our project "The Maturity Structure of Illiquidity Premiums and their Macroeconomic Determinants".
IIlliquid bonds have a premium to compensate bond investors for the lack of liquidity. Our results from the first part of the project, however, suggest that a clear connection between illiquidity premiums and typical liquidity measures like the bid-ask spread is only significant during economic crises. Therefore, we ask the natural follow-up question, why existing liquidity measures seem to work only well in stress periods. Building on this question, we analyze how the measurement of liquidity in general should be adapted to the economic conditions. From a conceptual point of view, at least two reasons point towards a measurement of liquidity that depends on the economic context. First, typical liquidity measures calculated from completed transactions provide only an incomplete picture. The reason is that transactions that have not been executed due to extreme illiquidity do not show up in the data. Second, for bond illiquidity premiums, expected transaction costs at the future trading date are the relevant costs and not today's transaction costs. Since transaction costs increase strongly in times of economic stress, it remains unclear whether current liquidity in calm periods is a good proxy for expected future transaction costs. In the proposed second part of the project, we first want to develop a forecasting model for expected transaction costs. For that, the remaining maturity of the bond as a natural ceiling on the holding horizon plays a central role, leading to a term structure of liquidity measurement. In the second step, we use the liquidity measures derived from the forecasting model to re-assess the impact of illiquidity on bond prices. The explanatory power of the newly developed liquidity measure in this exercise also serves as a criterion to evaluate and compare different measures. Since we are not aware of an approach to measure liquidity dependent on the economic environment in any security market, we plan to extend our analysis to the stock market in the last step. We expect that our results have practical influence in at least two ways. First, our forecast model provides expected trading costs for bonds, for which there are few or no data. From a practical perspective, information on trading costs is very important for these illiquid securities. Second, our new measures allow establishing a connection between the liquidity of a security and the associated price impact at an arbitrary point during the business cycle. Financial institutions could then apply, for example, scenario analyses, to predict the impact of a deterioration of liquidity in times of crisis, which would improve risk management.
Working papers and publications on this DFG project:
- Reichenbacher, M.; Schuster, P.; Uhrig-Homburg, M. (2020), Expected Bond Liquidity.
- Gehde-Trapp, M.; Schuster, P.; Uhrig-Homburg, M. (2018), The Term Structure of Bond Liquidity. Journal of financial and quantitative analysis, 53 (5), 2161-2197. doi:10.1017/S0022109018000364.
- The Internet Appendix is available here. Previous Title: A Heterogeneous Agents Equilibrium Model for the Term Structure of Bond Market Liquidity.
- Schestag, R.; Schuster, P.; Uhrig-Homburg, M. (2016), Measuring Liquidity in Bond Markets. the review of financial studies, 29 (5), 1170-1219. doi:10.1093/rfs/hhv132.
- Supplementary data and algorithms can be found here.
- Schuster, P.; Uhrig-Homburg, M. (2016), How Times of Stress Change the Behavior of Illiquidity Premiums. FIRM Yearbook 2016, ed.: Frankfurter Institut für Risikomanagement und Regulierung, 218-220, Gesellschaft für Risikomanagement und Regulierung e.V., Frankfurt a. M.
- Fiesel, S.; Uhrig-Homburg, M.; Ulrich, M. (2016), Monetary Policy During Liquidity Dry-Ups.
- Fiesel, S.; Uhrig-Homburg, M. (2016), Illiquidity Transmission in a Three-Country Framework : A Conditional Approach. Schmalenbach Business Review, 17 (3-4), 261-284. doi:10.1007/s41464-016-0016-5.
- Schuster, P.; Uhrig-Homburg, M. (2015), Limits to arbitrage and the term structure of bond illiquidity premiums. Journal of banking and finance, 57, 143-159. doi:10.1016/j.jbankfin.2014.10.016.
- Data on illiquidity premiums available here.
Marliese Uhrig-Homburg and Philipp Schuster were interviewed by the journal lookKIT on the DFG project "The maturity structure of illiquidity premiums and their macroeconomic determinants" (To the article).