Publications

The codes underlying my publications are available via my GitHub profile, https://github.com/SimonTrimborn , or on request. Please do not hesitate to reach out! For selected projects I program R-packages out of the codes/methods/algorithms developed in the papers. For a short description of the R-packages, see the Software page.

Publications:

  1. Kim, A., S. Trimborn, W.K. Härdle (2021) VCRIX – a volatility index for crypto-currencies, International Review of Financial Analysis, 78, 101915, https://doi.org/10.1016/j.irfa.2021.101915

  2. Okhrin, O., S. Trimborn, M. Waltz (2021) gofCopula: Goodness-of-Fit tests for copulae, The R-Journal, 13:1, 467-498, https://doi.org/10.32614/RJ-2021-060

  3. Petukhina, A., S. Trimborn, W.K. Härdle, and H. Elendner (2021) Investing with Cryptocurrencies – Evaluating their Potential for Portfolio Allocation Strategies, Quantitative Finance, 1-29, https://doi.org/10.1080/14697688.2021.1880023

  4. Chen, Y., P. Guidici, B. Hadji Misheva, S. Trimborn (2020) Detecting Lead Behavior in Crypto Networks Risks, 8(1), 4, https://doi.org/10.3390/risks8010004

  5. Trimborn, S., M. Li and W.K. Härdle (2019) Investing with Cryptocurrencies – A Liquidity Constraint Investment Approach Journal of Financial Econometrics, 18 (2), 280-306, doi.org/10.1093/jjfinec/nbz016

  6. Trimborn, S. and W.K. Härdle (2018) CRIX an Index for cryptocurrencies Journal of Empirical Finance, 49, 107-122, https://doi.org/10.1016/j.jempfin.2018.08.004

  7. Elendner, H., S. Trimborn, B. Ong and T.M. Lee (2017) The Cross-Section of crypto-currencies as financial assets Handbook of Digital Finance and Financial Inclusion: Cryptocurrency, FinTech, InsurTech, and Regulation. Ed. by D. Lee Kuo Chuen and R. Deng. Vol. 1. Elsevier, https://doi.org/10.1016/B978-0-12-810441-5.00007-5

Discussion Papers

  1. Trimborn, S., Y. Chen, R.-B. Chen (2020) TriSNAR: A Three-Layer Sparse Estimator for Large-Scale Network AutoRegressive Models, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3573336

  2. Trimborn, S. , Y. Chen, and J. Zhang (2021) Discover Regional and Size Effects in Bitcoin Blockchain via Sparse-Group Network AutoRegressive Modeling, https://dx.doi.org/10.2139/ssrn.3245031

  3. Trimborn, S. , Y. Li (2021) Informative Effects of Expert Sentiment on the Return Predictability of Cryptocurrency, http://dx.doi.org/10.2139/ssrn.3834279