Chained Decisions in Reinforcement Learning

I am working on a project of portfolio optimization with reinforcement learning. I would like incorporate a dependent decision process:

1. Decide which asset should be bought.
2. Decide about the amount which should be bought.

I already found papers using this idea, but no hints regarding the implementation. I read about goal-dedicated hierarchical reinforcement learning, but it doesn't fit my needs, as no goal has to be met by the second decider. Has anybody an idea how I could implement my idea using OpenAI Gym and Stable-Baselines3?