Dr. Branka Hadji Misheva

• DataInc – Intelligent Data Integration and Cleaning / Team member / Project ongoing
• Strengthening Swiss Financial SMEs through Applicable Reinforcement Learning / Team member / Project ongoing
• Decentralized financing of Fairtrade producers using a blockchain-based solution / Team member / Project ongoing
• COST Action – Fintech and Artificial Intelligence in Finance - Towards a transparent financial industry / Project leader / Project completed
• Towards Explainable Artificial Intelligence and Machine Learning in Credit Risk Management / Project leader / Project completed
• Advanced/AI-supported Rating Models for P2P systems / Project leader / Project completed
• Hybrid Approach for Robust Identification and Measurement of Investors Driving Corporate Sustainability and Innovation. Design of Policy Tools for Evaluating the Impact of Specific Investors and Assessing the Quality of Companies’ Investor Bases. / Team member / Project completed
• Digitalisation non-bankable assets (specifically: art) / Team member / Project completed
• Deep Learning & Neuronal Networks: Selbstständige KI-Agenten zur Entwicklung von neuartigen Handelsstrategien im Asset Management auf Basis von Self-Play / Team member / Project completed
• 4th Conference Finance and Industry 2019 / Team member / Project completed
• European Workshops in Finance / Team member / Project completed
• FIN-TECH – Financial Supervision and Technology Compliance Training Programme / Project leader / Project completed
• Big Data Analytics Research / Project leader / Project completed
• Currency hedging for SMEs and pension funds / Team member / Project completed
• Mathematics and Fintech: The next revolution in the digital transformation of the finance industry / Team member / Project completed

• Posth, Jan-Alexander; Kotlarz, Piotr Kamil; Hadji Misheva, Branka; Osterrieder, Jörg; Schwendner, Peter,

  2021.

  The applicability of self-play algorithms to trading and forecasting financial markets.

  Frontiers in Artificial Intelligence.

  4(668465).

  Available from: https://doi.org/10.3389/frai.2021.668465

• Hadji Misheva, Branka; Jaggi, David; Posth, Jan-Alexander; Gramespacher, Thomas; Osterrieder, Joerg,

  2021.

  Audience-dependent explanations for AI-based risk management tools : a survey.

  Frontiers in Artificial Intelligence.

  4(794996).

  Available from: https://doi.org/10.3389/frai.2021.794996

• Chen, Ying; Giudici, Paolo; Hadji Misheva, Branka; Trimborn, Simon,

  2020.

  Lead behaviour in Bitcoin markets.

  Risks.

  8(1), pp. 4.

  Available from: https://doi.org/10.3390/risks8010004

• Ahelegbey, Daniel Felix; Giudici, Paolo; Hadji Misheva, Branka,

  2019.

  Factorial network models to improve P2P credit risk management.

  Frontiers in Artificial Intelligence.

  2, pp. 8.

  Available from: https://doi.org/10.3389/frai.2019.00008

• Ahelegbey, Daniel Felix; Giudici, Paolo; Hadji Misheva, Branka,

  2019.

  Latent factor models for credit scoring in P2P systems.

  Physica A: Statistical Mechanics and its Applications.

  522, pp. 112-121.

  Available from: https://doi.org/10.1016/j.physa.2019.01.130

• Giudici, Paolo; Hadji Misheva, Branka; Spelta, Alessandro,

  2019.

  Network based credit risk models.

  Quality Engineering.

  32(2), pp. 199-211.

  Available from: https://doi.org/10.1080/08982112.2019.1655159

• Giudici, Paolo; Hadji Misheva, Branka; Spelta, Alessandro,

  2019.

  Network based scoring models to improve credit risk management in peer to peer lending platforms.

  Frontiers in Artificial Intelligence.

  2(3).

  Available from: https://doi.org/10.3389/frai.2019.00003

• Hirsa, Ali; Osterrieder, Jörg; Hadji Misheva, Branka; Posth, Jan-Alexander,

  2021.

  Deep reinforcement learning on a multi-asset environment for trading.

  arXiv.

  Available from: https://doi.org/10.21256/zhaw-22850

• Posth, Jan-Alexander; Hadji Misheva, Branka; Kotlarz, Piotr Kamil; Osterrieder, Jörg; Schwendner, Peter,

  2020.

  The applicability of self-play algorithms to trading and forecasting financial markets : a feasibility study.

  SSRN.

  Available from: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3737714

Ahelegbey, D.F., Giudici, P. and Hadji Misheva, B. (2019) Latent factor models for credit scoring in P2Psystems. Physica A 522, pp.112-121

Giudici, P. and Hadji Misheva, B. (2018). P2P lending scoring models: Do they predict default? Journal of Digital Banking, 2(4):353-368

Hadji Misheva, B., Giudici, P. and Pediroda, V. (2018). Network-based models to improve credit scoring. 2018IEEE 5th International Conference on Data Science and Advanced Analytics accuracy

Giudici, P. and Hadji Misheva, B. (2017). Scoring models for P2P lending platforms: An evaluation of predictive performance. Conference proceedings: Statistics and Data Science: New Challenges, New Generations

Giudici, P. and Hadji-Misheva, B. (2017). P2P Lending Scoring Models: Do they Predict Default? Journal of Digital Banking.

Bucevska, V. and Hadji-Misheva, B. (2015). Determinants of Profitability in the Banking Industry: EmpiricalEvidence from Selected Balkan Countries. Eastern European Economics Journal

go back