WG1 Research Articles

Khowaja, K., Saef, D., Sizov, S., & Härdle, W. K. (2020). Data Analytics Driven Controlling: bridging statistical modeling and managerial intuition. Available at arXiv: arXiv:2012.06577

Ben Amor, S., Althof, M., & Härdle, W. K. (2021). FRM Financial Risk Meter for Emerging Markets. Available at arXiv: https://arxiv.org/abs/2102.05398

Ren, R., Lu, M., Li Y., & Härdle, W. K. (2021). Financial Risk Meter Based on Expectiles. Available at SSRN: http://dx.doi.org/10.2139/ssrn.3809329;

Eccles, P., Grout, P., Siciliani, P., & Zalewska, A. A. (2021). The impact of machine learning and big data on credit markets. Available at SSRN: 3890364

Paraschiv, F., Schmid, M., & Wahlstrøm, R. R. (2021). Bankruptcy Prediction of Privately Held SMEs Using Feature Selection Methods. Available at SSRN 3911490.

Wahlstrøm, Ranik Raaen, Florentina Paraschiv, and Michael Schürle (2021) "A Comparative Analysis of Parsimonious Yield Curve Models with Focus on the Nelson-Siegel, Svensson and Bliss Versions." Computational Economics: 1-38. https://link.springer.com/article/10.1007/s10614-021-10113-w

Jalan, A., Matkovskyya, R., Potì, V. (2021) Shall the winning last? A study of recent bubbles and persistence. https://doi.org/10.1016/j.frl.2021.102162

Klochkov Y, Härdle WK, Petukhina A, Zhivotovskiy N, (2021) Robustifying Markowitz, IRTG 1792 Discussion Paper 2021-018. https://www.wiwi.hu-berlin.de/de/forschung/irtg/results/discussion-papers/discussion-papers-2017-1/irtg1792dp2021-018/view

Liu, F., Packham, N., Lu, M. J., & Härdle, W. (2021). Hedging cryptos with Bitcoin futures (No. 2022-001). IRTG 1792 Discussion Paper.
https://www.wiwi.hu-berlin.de/de/forschung/irtg/results/discussion-papers/discussion-papers-2017-1/irtg1792dp2022-001.pdf

Hu, J., & Härdle, W. K. (2021). Networks of News and the Cross-Sectional Returns. Available at SSRN 3904012.

Wang, R., Althof, M., & Härdle, W. K. (2021). A financial risk meter for China. Available at SSRN 3965498.

Matic, J. L., Packham, N., & Härdle, W. K. (2021). Hedging cryptocurrency options. Available at SSRN 3968594.

Saef, D., Nagy, O., Sizov, S., & Härdle, W. K. (2021). Understanding jumps in high frequency digital asset markets. Available at SSRN 3944865.

MB Lin, K. Khowaja, CYH Chen, WK Härdle (2021) Blockchain mechanism and distributional characteristics of cryptos , Advances in Quantitative Analysis of Finance & Accounting (AQAFA), Vol. 18, DOI：10.6293/AQAFA.202112_(18).0006

W. Li, F. Paraschiv, G. Sermpinis (2021) A Data-driven Explainable Case-based Reasoning Approach for Financial Risk Detection Available at SSRN: https://ssrn.com/abstract=3912753, to appear in Quantitative Finance

K. Khowaja, M. Shcherbatyy, WK Härdle (2021) Surrogate Models for Optimization of Dynamical Systems, "Foundations of Modern Statistics", Springer Proceedings in Mathematics & Statistics, to appear 2021

F. Liu, N. Packham, M-J Lu, WK Härdle (2021) Hedging Cryptos with Bitcoin Futures. Available at SSRN: https://ssrn.com/abstract=4150849or

M.Azzone, E.Barucci, G.Giuffra Moncayo, D.Marazzina (2022), A machine learning model for lapse prediction in life insurance contracts, Expert Systems with Application, Vol. 191: 116261. https://doi.org/10.1016/j.eswa.2021.116261.

E.Barucci, G.Giuffra Moncayo, D.Marazzina (2022), Cryptocurrencies and stablecoins: a high-frequency analysis, Digital Finance. https://doi.org/10.1007/s42521-022-00055-9

V. Poti (2022) Discussion on: “Programmable money: next generation blockchain based conditional payments” by Ingo Weber and Mark Staples. Digit Finance.

A. Kabasinskas (2022) Discussion on: “Programmable money: next generation blockchain based conditional payments” by Ingo Weber and Mark Staples. Digital Finance (2022). https://doi.org/10.1007/s42521-022-00062-w

O. Filipovska (2022) Discussion on: “Programmable money: next generation blockchain based conditional payments” by Ingo Weber and Mark Staples. Digital Finance(2022). https://doi.org/10.1007/s42521-022-00065-7

J. Osterrieder (2022) Discussion on: “Programmable money: next generation blockchain based conditional payments” by Ingo Weber and Mark Staples. Digital Finance(2022). https://doi.org/10.1007/s42521-022-00063-9

A.M. Rodrigues, R. Hu, (2022) Discussion on: “Programmable money: next generation blockchain based conditional payments” by Ingo Weber and Mark Staples. Digital Finance. https://doi.org/10.1007/s42521-022-00061-x

M.C. Burda (2022) Discussion on: “Programmable money: next generation blockchain-based conditional payments” by Ingo Weber and Mark Staples. Digital Finance. https://doi.org/10.1007/s42521-022-00064-8

W. Li, WK Härdle, S. Lessmann (2022) A Data-driven Case-based Reasoning in Bankruptcy Prediction. Available at SSRN

K. Khowaja, C.Huang, WK Härdle (2022) Uniform Confidence Bands for Generalized Random Forests (April 8, 2022). Available at SSRN: https://ssrn.com/abstract=4079006

F. Paraschiv,L. Wei, (2022) Modelling the evolution of wind and solar power infeed forecasts. In: Journal of Commodity Markets, 2022 (25): 100189 https://doi.org/10.1016/j.jcomm.2021.100189

R. Wahlstrøm, F. Paraschiv, M. Schürle (2022) A Comparative Analysis of Parsimonious Yield Curve Models with Focus on the Nelson-Siegel, Svensson and Bliss Versions. In: Computational Economics, 2022 (59): 967-1004 https://doi.org/10.1007/s10614-021-10113-w

N. Bussmann, A. Tanda, E. P. Y. Yu (2022). Can ESG Shape Cost of Capital? A Bibliometric Review and Empirical Analysis Through ML. A Bibliometric Review and Empirical Analysis Through ML (July 27, 2022).
https://dx.doi.org/10.2139/ssrn.4173890

Fintech and Artificial Intelligence in Finance

Pictures from events!