Abstract
We study paycheck optimization, which examines how to allocate income in order to achieve several competing financial goals. For paycheck optimization, a quantitative methodology is missing, due to a lack of a suitable problem formulation. To deal with this issue, we formulate the problem as a utility maximization problem. The proposed formulation is able to (i) unify different financial goals; (ii) incorporate user preferences regarding the goals; (iii) handle stochastic interest rates. The proposed formulation also facilitates an end-to-end reinforcement learning solution, which is implemented on a variety of problem settings.
Original language | English (US) |
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Pages (from-to) | 11-18 |
Number of pages | 8 |
Journal | Risk and Decision Analysis |
Volume | 9 |
Issue number | 1 |
DOIs | |
State | Published - Oct 20 2023 |
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Finance
- Economics and Econometrics
- Statistics, Probability and Uncertainty
Keywords
- Reinforcement learning
- financial planning
- personal finance
- wealth management