background
The global financial system is a complex adaptive system in its essence, which is a dense network of interactive actors whose collective behavior exceeds the total of its parts. This research arena is at an exciting intersection between financing, climate science and the theory of complexity, and deals with a very important question: How can we understand and measure the financial risks that arise from complex and successive interactions caused by climate change? Researchers use advanced mathematical techniques, including factors based on factors (ABM), network sciences, and machine learning, to simulate how climatic pressures (such as drought, floods and policy transformations) via economic networks, which may lead to a potential disastrous systemic failure. Conducting more research is extremely important because our current economic and financial models, which assume balance and rational actors, are not seriously equipped to deal with the non -linear, interconnected and unconfirmed financial system and which are formed by climate shocks.

PhD opportunity
The main research question is: How can we move from traditional and fixed risk models and develop dynamic frameworks that capture uncertainty in successive climate shocks?

You will start reviewing the existing open source literature and models (see for example https://www.comses.net/codebases/?query=finance) To determine the additional developments required to combine data, for example, supply chains’ data (such as the Trade Matris in the Statistical Database) and exposure to climate change (such as AGMIP). Then you will explore the uncertainty in the successive climatic shocks associated with synchronized droughts.
The initial result will be a simulation tool that provides a new dynamic representation of financial and climate uncertainty under successive shocks. This would enable the decision to move from the transition from assessing the individual risks to the endurance test in the face of complex and successive scenarios that are impossible to set models at the present time, and support the design of strong strategies in the face of climate uncertainty.

Dr. Roger Karimadis (the main supervisor, the University of Leeds) and Dr. Sillian Cologne (co -supervisor, advanced systems analysis program, IIASA) will provide a unique mixture of experience in complex systems science, financial modeling and successive climate shocks. The successful candidate will be registered in Leeds and is expected to interact with IISA via the Internet and through short personal visits, for example via programs like YSSP and SSSM.

The applicant file
Students with pre -doctoral experience in the financial sector and have a curiosity of the science of complexity.

Other information
https://environment.leeds.ac.uk/see/staff/13034/Roger-cremades
https://eprints.LSE.ac.uk/8650/1/Surminski_using%20ADAPTIVE%20cyCle_2018.pdf