Collaboration with Finrisk
Research Projects in cooperation NCCR FINRISK
Project C1 - Credit Risk and Non-Standard Sources of Risk in Finance (run by NCCR FINRISK and supervised by Prof. Rajna Gibson Brandon, Director of GFRI).
One of the central questions in finance is to determine how agents and corporations make decisions under uncertainty. Some of the sources of uncertainty affecting investors’ portfolio decisions and corporations’ investment and financing decisions are well understood. This is particularly true for market risks such as equity, interest rate, commodity and exchange rate risks. Yet, market risks represent only a small subset of the total risk exposures that one experiences when trading, investing or making financing decisions in financial markets. The purpose of this project is to focus on credit risk and on non-standard sources of risk that occur once we allow for market frictions, informational distortions and agency problems. By nonstandard sources of risks, the project researchers refer in particular to liquidity risk, operational risk, catastrophe risk, demographic risk and to model risk. One of the distinguishing features of all these risk factors is that modern finance theory has not yet come up with satisfactory models for the pricing of these risk factors and for their management. An exception is the measurement and management of credit risk that received large academic attention during the late 90’s driven in part by the Basel II reform of bank’s capital adequacy requirements.
Project D2 - Financial Econometrics for Risk Management (run by NCCR FINRISK and supervised by Prof. Olivier Scaillet, Deputy Director of GFRI).
Theoretical econometrics considers questions about the statistical properties of estimators and tests. The goal of this project is to develop econometric methods that will allow for a better assessment and monitoring of financial and insurance risks.
One aim of this project is to improve the econometric modeling (dynamic or marginal) of the distribution of risk and the dependencies that can occur between different sources of risk, employing both parametric and nonparametric methods. The types of risk that the proposed methods encompass are rather general and include credit risk, market risk or operational risk.
A second aim of this project is to investigate the impact of small samples when conducting inference. It will cover a range of econometric testing procedures whose underlying assumptions deviate from the typical asymptotic theory and account for the fact that, in practice, data is often limited.
All the econometric tools can be used in many areas in finance as they can be applied to various types of data such as interest rates, exchange rates, and stock returns. As such, they should allow for a better understanding of how to control financial losses for banks, insurance companies or other large investors.
