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Humboldt-Universität zu Berlin - Statistik

Prof. Dr. Brenda López Cabrera

JP Climate, Weather and Energy Analysis

 

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Financial Statistics/Mathematics

  • Energy, Weather, Agricultural Markets
  • Quantitative Climate Finance
  • Insurance and Finance
  • Financial derivatives
  • Financial Risk Management
  • Portfolio optimization
  • Empirical and Computational Finance
  • Dimension reduction techniques
  • Time-varying parameter models and structural changes
  • Extreme value modelling

 

 

Projects

  • DFG SFB 649 "Weather Risk Management" (Jan 2013 - on)

​Abstract: Weather constitutes an important macroeconomic risk that affects a wide range of industries and the frequency and intensity of extreme weather events is expected even to increase. On the other hand, new markets have emerged on which weather risks can be exchanged and which support the development of risk management strategies. Against this background the overall objective of this project to assess the magnitude and the importance of weather related economic risks and to explore options to treat these risk with financial instruments. We focus on the agribusiness and the energy sector.

 

After the occurrence of a natural disaster, the reconstruction can be financed with catastrophic bonds (CAT bonds) or reinsurance. For insurers, reinsurers and other corporations CAT bonds provide multi year protection without the credit risk present in reinsurance. For investors CAT bonds offer attractive returns and reduction of portfolio risk, since CAT bonds defaults are uncorrelated with defaults of other securities. As the study of natural catastrophe models plays an important role in the prevention and mitigation of disasters, the main motivation of this project is the pricing of CAT bonds for earthquakes and hurricanes under different trigger mechanisms. This project also focuses on their calibration of the bonds from different sides of the contract.

 

  • IRTG - High Dimensional Non Stationary Time Series. "Dynamic Factor models (DFM) for weather time series analysis" (Jan 2013 - on)

 

 

Students