Market Regime
A regime, in backtest terminology, is the prevailing market condition.
Let's take one more example from sport. Lawn tennis can be played on a clay court and on a hard court.
Nadal, a great lawn tennis player, was far more successful on clay. Here are his career numbers:
- Clay: 90.5% (484 wins, 51 losses), the highest clay court win percentage in the Open Era
- Hard court: 77.8% (387 wins, 111 losses)
Same player. Same training. Same racket. Different conditions, different outcomes.
The stock market also goes through different types of phases. Sometimes it trends upwards. Sometimes it moves sideways for months. Sometimes it is simply very volatile and everything moves too fast.
Some strategies work beautifully in a trending market and do not work at all in a sideways one. This is the reason we care about regime, which is just a name for market phases.
So we should ideally run our backtests across different market conditions, and look at the results per regime rather than as one blended average.
That last point is worth sitting with. A metric table that mixes trending-market trades and sideways-market trades into one average can hide the fact that the strategy only works half the time. The blended number looks acceptable. The two halves it is made of tell a completely different story, and one of them is the half you are about to trade into.
How is a regime defined?
There are several parameters you can use. If we want to use the VIX, the volatility index, to classify market behaviour, we can define regimes like this:
- Low volatility regime: VIX below 15
- Moderate volatility regime: VIX between 15 and 25
- High volatility regime: VIX above 25
There are other ways to define a regime as well. You can use the trend of the index itself, the slope of a long moving average, or how many stocks in the market are making new highs. Each one slices the market into phases differently, and none of them is the single correct answer.
What matters is not which definition you pick. It is that you pick one, and then you check your strategy against it honestly, instead of assuming your edge travels everywhere.
In the next lesson we take a real world example and look at actual backtest numbers, across a few different strategies and timeframes, so you can see what all of these metrics look like on real data instead of in a formula.