Modelling optimal decisions in retirement using expected utility stochastic control theory. PhD student, Johan G. Andreasson (2014-2017). Supervisors: Prof Pavel Shevchenko (Macquarie University) and Prof Alex Novikov (UTS).
Johan G. Andréasson (2014-2017), Modelling optimal decisions in retirement using expected utility stochastic control theory. Supervisors: Prof Pavel Shevchenko (Macquarie University), Prof Alex Novikov (University of Technology Sydney)
This research project aims to 1) develop a utility model that captures the characterstics of Australian retirees, and calibrate the model with empirical data, 2) investigate issues related to Australian means-tested pensions, 3) develop numerical methods maximizing expected utility model to find optimal decision for housing, investment into risky assets, consumption.
- Andréasson, J. G., Shevchenko, P. V., Novikov, A. (2017). Optimal consumption,
investment and housing with means-tested public pension in retirement. Insurance: Mathematics and Economics 75, 32-47.
- Andréasson, J. G., Shevchenko, P. V. (2017). Assessment of policy changes to means-tested Age Pension using expected utility model: Implication for decisions in retirement. Preprint available at SSRN: 2979889.
Jin Sun (UTS 2016-2020), IDTC PhD student. Supervisors: Prof Pavel Shevchenko (Macquarie University) and Prof Eckhard Platen (UTS) “Retirement incomes products”.
J. Sun, P.V. Shevchenko, M.C. Fung (2017). A Note on the Impact of Management Fees on the Pricing of Variable Annuity Guarantees. Preprint, http://ssrn.com/abstract=2967045.
MRes student: Jie Zhu, Macquarie University 2017, supervisor: Prof Pavel Shevchenko, co-supervisor Prof Ken Siu
Master Thesis: Jie Zhu (2017). Advanced Monte Carlo Methods for Pricing Bermudan Options and their Applications in Real Options Analysis.
MRes student: Danny Wan, Macquarie University 2018, supervisor: A/Prof Christophe Doche; co-supervisor: Prof Pavel Shevchenko
Master Thesis: Danny Wan (2018). Identifying pricing strategies for cyber insurance premiums