Market regimes: why a strategy that worked stops working

What we measure to classify one

• Trend — where price sits relative to its own longer averages, across the instruments we track.
• Volatility — how large recent moves have been compared with their own history.
• Breadth — how many of the tracked instruments are participating, rather than one carrying the rest.
• Dispersion and correlation — how much things are moving together, which is when diversification quietly stops working.

All four are computed by deterministic code from stored price history. No model is asked to judge the market, and no third-party opinion is imported as fact.

Our current reading

No regime reading is published at the moment. Our own price history is still accumulating, and we would rather show nothing than label the market from data that is too short to support it.

Three things a regime label is not

1. It is not a forecast. It describes conditions that have already been measured. The next regime announces itself late, always.
2. It is not a signal. We do not publish trades, and a regime reading is not an instruction to do anything with your money.
3. It is not permanent. Regimes are revised as data arrives. A label that changes is the method working, not the method failing.

Why this matters for what you already own

The practical use of regime thinking is not timing. It is understanding that a portfolio built entirely for one environment — steadily rising prices, low volatility, cheap money — is making a bet it has not been asked to justify. That is the same question behind everything on the wealth-protection side of this firm: what happens to what you hold if conditions stop being the ones it was built for?

Evidence and sources

1. 1. Hamilton, A New Approach to the Economic Analysis of Nonstationary Time Series (1989) — The regime-switching framework underneath most modern regime classification.
2. 2. Ang & Bekaert, International Asset Allocation with Regime Shifts (2002) — Evidence that correlations and volatility behave differently across regimes.
3. 3. Moreira & Muir, Volatility-Managed Portfolios (2017) — Why scaling exposure to measured volatility is treated as an overlay, not a prediction.