Brayden Warwick

I'd like to understand how does dynamic programming contribute to the understanding of financial decisions?

How would you describe the integrated financial planning architecture that underlies your theory?

So how do the fiber bundles come into your theory?

Wild.

In your paper, you assigned a weighting function to each of the domains like cash flow, weighting on cash flow, tax, retirement, and so on.

But would you think about assigning a weighting factor to each objective?

Would you potentially change the objective function depending on client preferences or would you just leave it?

at the level of assigning weights to each domain.

We talked about the natural kinkiness of financial planning.

So how do you solve for that when the objective functions aren't smooth and the topology is not smooth?

How do you actually work around that from a mathematical perspective?

Can you dig into that a little bit more?

How does the relative urgency of various schools get reflected in the model?

There are some significant costs to that.

So how should financial planners think about applying your mathematical model to real financial planning scenarios?

Does this value of integration and financial planning scale linearly with wealth?

So AI is the hot topic these days.

From your perspective, how does AI interact with the value of a human advisor?