Discovery Early Career Researcher Award - Grant ID: DE200100896
Funder
Australian Research Council
Funding Amount
$427,008.00
Summary
How to beat model uncertainty with more information. Experience of the 2008 financial crisis exposed a weakness in our over-reliance on mathematical models. The main aim of this project is to develop mathematical tools to investigate the role of information in reducing model uncertainty. The project will undertake pressing research in robust finance, which is now one of the most active and dynamic topics in financial mathematics. It expects to quantify the value of information under uncertainty ....How to beat model uncertainty with more information. Experience of the 2008 financial crisis exposed a weakness in our over-reliance on mathematical models. The main aim of this project is to develop mathematical tools to investigate the role of information in reducing model uncertainty. The project will undertake pressing research in robust finance, which is now one of the most active and dynamic topics in financial mathematics. It expects to quantify the value of information under uncertainty in mathematical modelling. It will generate new knowledge in probability theory and stochastic processes providing a significant mathematical contribution in its own right.Read moreRead less
Frontiers of Risk Modelling: Dependence and Extremes of Levy Processes. This project plans to continue an ongoing theoretical study into continuous-time stochastic processes, concentrating on developing tools for the further analysis and understanding of extremal and multivariate phenomena with applications to portfolio analysis, value-at risk calculations and complex financial instruments, with particular emphasis on practical applications of the methodologies in the insurance and finance indus ....Frontiers of Risk Modelling: Dependence and Extremes of Levy Processes. This project plans to continue an ongoing theoretical study into continuous-time stochastic processes, concentrating on developing tools for the further analysis and understanding of extremal and multivariate phenomena with applications to portfolio analysis, value-at risk calculations and complex financial instruments, with particular emphasis on practical applications of the methodologies in the insurance and finance industries. Expected outcomes would be of direct interest to these industries as well as having significant mathematical interest.Read moreRead less
Improving risk management based on short-term stochastic forecast for financial decisions. The project targets the problems of strategy selection in the framework of mathematical finance. The aim is to find ways to reduce the impact of forecast errors in the presence of uncertainty. Related forecasting algorithms and solutions of optimization problems will be obtained.