The video does a great job highlighting the importance of block bootstrapping — a powerful tool for understanding the range of possible portfolio outcomes.
And you don’t need to understand all the math to benefit from it.
While not necessarily looking at the same things as the paper, you can use the block bootstrapping method yourself — free — using a wide range of assets here: Portfolio Visualizer: Monte Carlo Simulation
Block bootstrapping isn’t new or radical — in fact, Portfolio Visualizer seems to have fully adopted it.
I don’t even see the option to use the old Monte Carlo simulation method anymore — likely for the reasons explained in the video. He makes a strong case.
If you want to expand on this further, ChatGPT can help you get started in Python too.
For example, here is full code for switching from standard bootstrapping to block bootstrapping with Sklearn's random forest. You would consider doing that essentially for the same mathematical reasons expressed in the video: Improving Sklearn’s Random Forest for Stock Data with Block Bootstrapping
This is a great video — and a reminder that we can adopt and extend powerful tools from academic research.. In many cases, it’s as simple as heading over to Portfolio Visualizer's free site.
Screenshot from Portfolio Visualizer:
BTW, thanks @yuvaltaylor for your post.
Here’s my take:
If you upload any simulation data into Portfolio Visualizer’s Monte Carlo tool (via the optional upgrade), most of the concerns raised in the video no longer apply. For example, even with a 100-stock version of my simulation (along with other assets), Portfolio Visualizer estimates that I can withdraw a substantial portion of my portfolio each year — indefinitely — with zero risk of ruin.
That’s striking — and possibly the clearest endorsement for P123 I can offer.
After all, who wants to have the good fortune to live to 100, only to go broke somewhere along the way? Why even take that chance if you don't have to?
I’m confident Yuval and others would see similar results. And importantly, this uses the exact same method outlined in the video.
Having an edge makes a HUGE difference. The key is uploading a realistic simulation.