What a Drawdown Stop Does to a Skilled Portfolio Manager

We simulate managers with a known edge under a 5% cut and a 7.5% stop and follow who keeps the job and who gets paid.

A portfolio manager with a real edge starts in a new seat and has a bad first four months. By then the book is down 5% of its allocation. The fund halves the allocation the next morning, and another 2.5% of losses will end the job. The manager’s edge has not changed, and only the luck has been bad. Does a rule like this protect the fund from managers with no skill, or does it mostly remove good managers who were unlucky? And either way, who keeps the money?

To answer that, we build a small multi-manager fund in Python, fill its seats with managers whose skill we choose, and run it for five simulated years. Pasted in order into one file, the article’s Python blocks are the whole program and reproduce every number, table and chart. They need Python 3.11 or later with NumPy and Matplotlib, and run in about two minutes on a recent laptop.

How a pod works

A multi-manager fund runs many small, independent investment teams under one roof. Each of these teams is often called a pod, and a pod is usually one portfolio manager (PM) with a few analysts. The PM decides what to buy…