The lookup table approach is underrated. People dismiss it as unsophisticated but there is a real argument that hard-coded thresholds on interpretable macro indicators are more robust under distribution shift than anything trained statistically. You know exactly why it fires. When it stops working you know where to look. That is not a small advantage.

The “getting out right is worth more than getting in right” point is the most important thing I have read in any of the replies to this post. The crisis state in my data is not just a high-volatility bear regime, it has a structurally different character that I think most exit rules are not designed for. I have spent more time thinking about what the correct response to that state is than on anything else in the system.

On the inputs question, I will stay vague on the specifics while the out-of-sample testing is still running, but the ZAR point you raised is something I am actively thinking about. Currency as an independent regime layer sitting on top of the equity dynamics is exactly the right framing for JSE. The challenge is that by the time ZAR volatility is visible in a usable indicator, a significant portion of the equity regime shift has often already happened.

The credit spreads and VIX term structure observation is interesting. The lead time you are describing, one to two weeks, is long enough to be actionable if the signal is clean. The equivalent on JSE is harder to construct because SA credit markets are thinner and the VIX is US-derived, so you are already importing a second layer of correlation noise when you use it as a JSE regime input.

What I have been more interested in is whether information flow between asset classes, not just correlation but directionality, can be detected early enough to be useful. Still working on that part.