Discovery Early Career Researcher Award - Grant ID: DE200101266
Funder
Australian Research Council
Funding Amount
$420,039.00
Summary
Demystifying Puzzles in Retirement Planning. This project aims to investigate optimal retirement planning with stochastic and ambiguous mortality/longevity risks not previously considered in a unifying framework. By using an innovative approach utilising techniques from actuarial science, financial mathematics and stochastic control, this project expects to generate new knowledge in the area of personal longevity risk management. Expected outcome of the project include new insights to several pu ....Demystifying Puzzles in Retirement Planning. This project aims to investigate optimal retirement planning with stochastic and ambiguous mortality/longevity risks not previously considered in a unifying framework. By using an innovative approach utilising techniques from actuarial science, financial mathematics and stochastic control, this project expects to generate new knowledge in the area of personal longevity risk management. Expected outcome of the project include new insights to several puzzling questions in retirement studies. This should provide significant benefits to retirement education for retirees facing the risk of outliving retirement savings, thereby mitigating the pressing challenge caused by population ageing and longevity risk to pension systems in many countries.Read moreRead less
Optimal Control of Stochastic Partial Differential Equations. The problem to control a stochastic process so as to minimize a certain cost functional arises in many areas of Applied Sciences, Engineering and Mathematical Finance. An important practical question is to find, for a given cost functional, the optimizing control in a feedback form. We propose new tools to construct such optimal controls for a class of stochastic processes which are solutions to stochastic partial differential equati ....Optimal Control of Stochastic Partial Differential Equations. The problem to control a stochastic process so as to minimize a certain cost functional arises in many areas of Applied Sciences, Engineering and Mathematical Finance. An important practical question is to find, for a given cost functional, the optimizing control in a feedback form. We propose new tools to construct such optimal controls for a class of stochastic processes which are solutions to stochastic partial differential equations. As an outcome of this project we will obtain methods to determine the optimal control policies for a large variety of cost functionals and degenerated stochastic partial differential equations, in particular those arising in modelling of volatility in Finance.Read moreRead less