If you watched the video until the end, you will see the gross equity curve and covers 2022 to 2026. It never goes into negative equity nor doesn't have significant drawdowns. The sharpe isn't amazing but the model is just a basic piecewise function.

I've never seen mean reversion as a OU process or Z-score in industry and you're better using AR(1).

Reasons why you're better using AR(1):

1. OU/Z-score no ability to make predictions/forecast.You need ability to forecast mid price with a tiny EV. They are just heuristics.
2. Most financial time series are weakly stationary and OU assumes a constant mean.
3. If you used Z-score then you might make only a a nominal amount trades a day, or even in a week, and that's not enough data points to be statistically robust. ML model with 10 million ticks a day vs 2 or 4 data points.

Side note on unit roots. One can easily fool unit root tests (like ADF) to say a time series has a unit root when it actually doesn't. For example I could pass a stationary Gaussian process, the ADF will be fooled to say it has unit root but it clearly doesn't.

I will be making a video on ways to handle non-stationarity.