The FIRN PhD Student Brown Bag Network Committee is hosting monthly Brown Bag Seminars during 2022 targeted to Finance PhD students from our member institutions.
Each seminar consists of an informal presentation of research at all stages, followed by a discussion and a Q&A session. This provides a great opportunity for PhD students to practice and get relevant skills for their upcoming career as well as create valuable connections with potential future colleagues. Presenters and discussants will receive certificates that accredit their contribution. The participants will also have a chance to win a $100 random prize at the end of the year.
If you would like to present your current research work or serve as a discussant, please fill out the EOI form. Additionally, registration is required for all seminar participants. Registration can be done by clicking on the link below each seminar you would like to attend. All sessions are held via zoom and a zoom link will be sent to those who register.
HDR students are also encouraged to register here to receive updates about incoming seminars and events. If you need further information, please contact the FIRN PhD Student Brown Bag Network Committee by email via email@example.com
Next Brown Bag Seminar
Tuesday 6th September, 11.30am (AEST)
Presenter: Bingyang Ye, PhD student, University of Technology Sydney
Discussant: Yang Shi, PhD student, University of Melbourne
Moderator: Yi Chen, PhD student, Macquarie University
Presenter: Christopher Bebbington, Curtin University
Discussant: Qinqin Xia, Macquarie University
Moderator: Antoine Girardeau, Curtin University
Title: The Implications & Determinants of an Investors’ Initial Choice within Retirement Savings Schemes
Abstract: We study the implications and determinants of investors’ initial choice upon joining a retirement savings scheme. That is, the first investment option investors allocate their retirement wealth towards. Using a unique dataset of over 14,000 investors, we observe that, on average, investors would have superior outcomes if they had initially elected a higher risk to return investment strategy. Applying a Finite Mixture Model, we observe five homogenous subpopulations, which display varying responses to the same stimuli. We document investors displaying a “fight or flight” response to rising market volatility, contrarian behaviour, anchoring, and investor behaviour that is not consistent with typical notions of risk aversion. Our results demonstrate that behavioural biases can detrimentally affect the retirement balances of investors upon retirement.
click here to register your attendance