Official COST FinAI Publications
Here you find a list of all academic publications that were created in the context of our COST FinAI Action.
Please kindly add the appropriate acknowledgement. For academic articles, that would be:
- This publication is based upon work from COST Action 19130, supported by COST (European Cooperation in Science and Technology), www.cost.eu
COST FinAI Publications
1. COST FinAI presentations and executive summaries
Academic peer-reviewed papers
Articles published in the book of the conference’s proceedings
1. Barjaktarović, L., Barjaktarović, M., Konjikušić, S., Echo state networks usage of stock price predictions, The Book of Proceedings Singidunum University International Scientific Conference FINIZ 2020 - People in the Center of Process Automation, p. 97-102, [https:doi.org/10.15308/finiz-2020-97-102; available at: http://portal.finiz.singidunum.ac.rs/paper/42580]
Working papers
1. Devine, M.T, Russo, M., Cuffe, P., Blockchain electricity trading using tokenised power delivery contract.
2. K. Khowaja, D. Saef, S. Sizov, and W. K. Härdle. Data Analytics Driven Controlling: bridging statistical modeling and managerial intuition. IRTG 1792 Discussion Paper 2020-026, 2020.
3. Paraschiv, F., Schmid, M., Wahlstrøm, R. R. (2021) Bankruptcy prediction of privately held SMEs using feature selection methods.
4. Wahlstrøm, R. R., Paraschiv, F., Schürle, M. A (2021) Comparative Analysis of Parsimonious Yield Curve Models with Focus on the Nelson-Siegel, Svensson and Bliss Models. Available at SSRN: http://dx.doi.org/10.2139/ssrn.3600955
5. Wei, L., Paraschiv, F. (2021) Modelling the Evolution of Wind and Solar Power Infeed Forecasts. Available at SSRN: [1]
6. Wei, L., Denis, M.B. (2021) Day-ahead electricity prices prediction applying hybrid models of LSTM-based deep learning methods and feature selection algorithms under consideration of market coupling.
7. Escobar, D., Paraschiv, F., Schürle, M. (2021) Pricing electricity futures with distortion functions under model ambiguity.
8. Ren, R., Althof, M., & Härdle, W. K. (2020). Tail Risk Network Effects in the Cryptocurrency Market during the COVID-19 Crisis. Available at SSRN: http://dx.doi.org/10.2139/ssrn.3753421.
9.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.