Actuarial studies; Computational economics; Numerical optimization techniques; Superannuation.
Gaurav Khemka is a Senior Lecturer of Actuarial Studies. His research uses numerical stochastic dynamic programming to analyse the life-cycle decision-making process. With a particular focus on superannuation and retirement income modelling and policy, Gaurav is interested in the ways in which retirement outcomes for Australians can be improved through better product development and government policy. To this end, he made submissions to the Retirement Income Review and the Inquiry into the Implications of Removing Refundable Franking Credits. Gaurav’s research has been published in a number of top-ranked academic journals including Insurance: Mathematics and Economics, The Economic Record and Journal of Population Research. His work on existing decision support systems to improve financial wellbeing over an individual’s lifecycle was funded by the Centre for International Finance and Regulation.
(with Brue Chapman) 2021, ‘Understanding HECS-HELP Price Misunderstandings’. Australian Journal of Public Administration. 1−17.
(with Mogens Steffensen and Geoffrey Warren) 2021, ‘How sub-optimal are age-based life-cycle investment products?’. International Review of Financial Analysis. Volume 73, 101619.
(with Geoff Warren and Yifu Tang), 2020, ‘The ‘Right’ Level for the Superannuation Guarantee: Identifying the Key Considerations’. Accounting and Finance. Forthcoming.
(with Adam Butt and Geoffrey Warren) 2019, ‘What dividend imputation means to Australian retirees?’. Economic Record, Volume 95 Issue 309, Pages 181-199.
(with Bridget Browne, William Lim and David Pitt) 2019, ‘A method for calculating the implied no-recovery three-state transition matrix using observable population mortality incidence and disability prevalence rates for the elderly.’ Journal of Population Research, Volume 36 Issue 3, Pages 245-282.
(with Adam Butt and Luke Strickland), 2018, ‘How academic research can inform default superannuation fund design and individual financial decision-making’. AJAF (formerly known as JASSA): The Australasian Journal of Applied Finance, Issue 1, Pages 40-49.
(with Steven Roberts and Timothy Higgins) 2017, ‘The impact of changes to the unemployment rate on Australian disability income insurance claim incidence’. Risks. Volume 5 no 1, Issue 17.
(with Adam Butt) 2017, ‘Non-parametric integral estimation using data clustering in stochastic dynamic programming: an introduction using lifetime financial modelling’. Risks. Volume 5 no 4, Issue 57.
(with Steven Roberts) 2015, ‘Impact of Economic Cycles on Australian Mortality’, Journal of Population Research, Volume 32, Issue 2 (2015), Pages 139-155.
(with Adam Butt) 2015, ‘The effect of objective formulation on retirement decision making’, Insurance: Mathematics and Economics, Volume 64, September 2015, Pages 385–395.
(with Steven Roberts and Anthony Asher) 2018, ‘Enhancing well-being in retirement: addressing negative shocks’. Working Paper.
(with Anthony Asher, Adam Butt and Ujwal Kayande) 2016, ‘Formulating appropriate utility functions and personal financial plans’. Working Paper.
Centre for International Finance and Regulation Research Grant, 'Developing coherent and usable decision support systems to improve financial wellbeing over an individual’s lifecycle', 2014/15. (joint with Anthony Asher, Adam Butt and Ujwal Kayande)
Service Roles at ANU
Convenor of Bachelor of Actuarial Studies (Sem 2, 2021 - present)
Actuarial Seminar Convenor (2017 - 2020)
Service Roles with the Actuaries Institute
Course Leader for Investments in Commercial Actuarial Practice
Member of the Exemption Committee (CT3 Exemptions)
Gaurav Khemka teaches Actuarial studies. He is also involved in teaching the Commercial Actuarial Practice course for the Institute of Actuaries.
STAT 8058: Risk Modelling 2
ACST4060/8060: Enterprise Risk Management 1
ACST4061/8061: Enterprise Risk Management 2
ACST 4033/ACST 8033: Actuarial Control Cycle B
FINM 3003/7003: Continuous Time Finance
FINM 7008: Applied Investments
STAT 1003: Statistical Techniques