chapter twelve
12 Financial Planning Using Reinforcement Learning
This chapter covers
- Solving a goals-based investing problem using dynamic programming
- Solving the same goals-based problem using reinforcement learning (AI)
- Discussing how utility functions can be used in financial planning
- Applying reinforcement learning to optimize spending using utility functions
- Extending the model to include longevity risk in order to answer questions like when to take Social Security
When we looked at asset allocation in earlier chapters, we were essentially performing a single-period optimization. However, most financial planning decisions involve making decisions over multiple periods. And the decisions made today - not only how to allocate assets but how much to spend, whether to claim Social Security, when to retire, what accounts to withdraw from, etc. - affect decisions in the future. These multiperiod, dynamic models, which economists sometimes call “lifecycle models”, are much more complicated to optimize.