Research papers

Scientific articles with peer-review

• Haas, M. G., & Peter, F. J. (2024). Implementing Intraday Model-Free Implied Volatility for Individual Equities to Analyze the Return–Volatility Relationship. Journal of Risk and Financial Management, 17(1), 39. https://doi.org/10.3390/jrfm17010039 🔗
• De Martiis, A., & Peter, F. J. (2023). When companies don’t die: Analyzing zombie firms in a low interest rate environment . Aussenwirtschaft - The Swiss Review of International Economic Relations, 73(1), 67–86. 🔗
• Peter, F. J., & Styppa, K. (2023). Predicting millionaires from Ethereum transaction histories using node embeddings and artificial neural nets. Expert Systems with Applications, 223, 119834. https://doi.org/10.1016/j.eswa.2023.119834 🔗
• Heil, T., Peter, F. J., & Prange, P. (2022). Measuring 25 years of global equity market co-movement using a time-varying spatial model. Journal of International Money and Finance, 128, 102708. https://doi.org/10.1016/j.jimonfin.2022.102708 🔗
• Kind, A., Oster, P., & Peter, F. J. (2021). The Determinants of Banks’ AT1 CoCo Spreads. European Financial Managment, 28(2), 567–604. https://doi.org/10.1111/eufm.12314 🔗
• Peter, F. J., & Dimpfl, T. (2021). Nothing but Noise? Price Discovery between Cryptocurrency Exchanges. Journal of Financial Markets, 54, 100584. https://doi.org/10.1016/j.finmar.2020.100584 🔗
• Behrendt, S., Peter, F. J., & Zimmermann, D. (2020). An encyclopedia for stock markets? Wikipedia searches and stock returns  . International Review of Financial Analysis, 72, 101563. https://doi.org/10.1016/j.irfa.2020.101563 🔗
• Dirkx, P., & Peter, F. J. (2020). The Fama-French Five-Factor Model Plus Momentum: Evidence for the German Market. Schmalenbach Business Review, 72(4), 661–684. https://doi.org/10.1007/s41464-020-00105-y 🔗
• Behrendt, S., Peter, F. J., Zimmerann, D., & Dimpfl, T. (2019). RTransferEntropy - Quantifying Information Flow between Different Time Series Using Effective Transfer Entropy. SoftwareX, 10, 100265. https://doi.org/10.1016/j.softx.2019.100265 🔗
• Dimpfl, T., & Peter, F. J. (2019). Group transfer entropy with an application to cryptocurrencies. Physica A, 516, 543–551. https://doi.org/10.1016/j.physa.2018.10.048 🔗
• Dimpfl, T., & Peter, F. J. (2018). Analyzing volatility transmission using group transfer entropy. Energy Economics, 75, 368–376. https://doi.org/10.1016/j.eneco.2018.08.008 🔗
• Dimpfl, T., & Peter, F. J. (2016). Price discovery in the markets for credit risk: a Markov switching approach. Studies in Nonlinear Dynamics and Econometrics, 20, 223–249. https://doi.org/10.1515/snde-2015-0032 🔗
• Dimpfl, T., & Peter, F. J. (2014). The impact of the financial crisis on transatlantic information flows: An intraday analysis. Journal of International Financial Markets, Institutions & Money, 31, 1–13. https://doi.org/10.1016/j.intfin.2014.03.004 🔗
• Dimpfl, T., & Peter, F. J. (2013). Using transfer entropy to measure information flows between financial markets. Studies in Nonlinear Dynamics and Econometric, 17, 85–102. https://doi.org/10.1515/snde-2012-0044 🔗
• Grammig, J., & Peter, F. J. (2013). Telltale Tails: A New Approach to Estimating Unique Market Information Shares. Journal of Financial and Quantitative Analysis, 48, 459–488. https://doi.org/10.1017/s0022109013000215 🔗
• Kehrle, K., & Peter, F. J. (2013). Who moves first? An intensity-based measure for information flows across stock exchanges. Journal of Banking and Finance, 37, 1629–1642. https://doi.org/10.1016/j.jbankfin.2012.12.011 🔗

Scientific articles

• Heil, T., Marthiensen, N., & Peter, F. J. (2022). 255 Shades of Grey: Using Grey-Scaled Images and Convolutional Neural Nets to Forecast Tomorrow’s Stock Returns. SSRN Electronic Journal, 4273860. https://doi.org/10.2139/ssrn.4273860 🔗

Working papers

• De Martiis, A., Heil, T., & Peter, F. J. (2020). Are you a Zombie? Understanding the Determinants of Distressed and Zombie Companies. https://doi.org/10.2139/ssrn.3625473 🔗
• Behrendt, S., Dimpfl, T., Peter, F. J., & Zimmermann, D. (2018). RTransferEntropy: Measuring information flow between time series with effective transfer entropy in R. 🔗

Graduation works

Doctoral theses

• Prange, P. (2023). Investigating Market Linkages and Investor Behavior in Times of Turmoil and Uncertainty. https://doi.org/10.48586/zu/11554 [reviewer: Peter, Franziska J.; reviewer: Jung, Robert; reviewer: Tyrell, Marcel] 🔗
• Behrendt, S. (2020). Investigating new sources of information and nonlinearities on financial markets. https://doi.org/10.48586/zu/11590 [reviewer: Peter, Franziska J.; reviewer: Dimpfl, Thomas; reviewer: Wamser, Georg] 🔗
• Rostásy, C. (2019). European integration and cross-border financial governance in the aftermath of the global financial crisis : challenges and prospects of post-crisis policy responses to systemic risk in the European Union. https://doi.org/10.48586/zu/11592 [reviewer: Willke, Helmut; reviewer: Botzem, Sebastian; reviewer: Peter, Franziska J.] 🔗