Projects

Financial cycle: design, modelling and forecasting within machine learning framework

prof. Ing. Štefan Lyócsa, PhD.

Members of project
prof. Iftekhar Hasan, PhD., prof. Roman Horváth, PhD., prof. Ing. Eva Horvátová, CSc., Ing. Zuzana Košťálová, PhD., prof. Ing. Štefan Lyócsa, PhD., Ing. Nina Sljuka

• Basic informations
• Characteristics

• Duration of the project: 07/2023 - 12/2026
  ID number: APVV-22-0472

• Financial instability is associated with periods when businesses find it difficult to access capital, the investment is constrained, and confidence among economic agents, including households, is falling, forcing them to make significant adjustments to their current and future budgets. The peak and subsequent bust of the financial cycle is associated with such periods of financial instability. The financial cycle thus captures changes in the behaviour of economic agents, in particular changes in risk appetite. The way the financial cycle is estimated should reflect the specificities of individual financial systems, leading policy makers to demand tailor-made solutions for each country. The main objective of the proposed applied research project is to propose new financial cycle indicators that will be used to monitor and predict future risks for financial stability in Slovakia. Our solution will provide the beneficiary with several new financial cycle indicators, prediction models based on machine learning and estimates of the most important factors influencing the future development of the financial cycle. The proposed solution should provide a decision support system that is both beneficial for the financial sector but also has the ambition to contribute to the debate on future macroprudential policy measures.