Why Quiet Markets Tend to Stay Quiet and Wild Ones Stay Wild
Posted: Mon Oct 26, 2026 1:35 pm
Volatility clustering is one of the most persistent features of price data across timeframes. Large moves tend to be followed by large moves, and small moves by small moves, even when the direction of those moves is close to unpredictable. The sign of returns shows little memory, while the size of returns shows plenty.
For a scalper, this matters more than any directional opinion. A one-minute candle with a range several times the recent average rarely arrives alone. The following candles usually remain elevated before volatility decays back toward a baseline, often unevenly and with occasional secondary bursts.
This is the reason models such as GARCH were built: they treat variance as something that depends on recent squared returns and on its own previous level. Even without fitting any model, a comparison of short-window range against a longer-window range gives a rough picture of whether the market is in an expanded or compressed state.
Practical consequences follow. Position sizing, stop distance, and profit targets calibrated to quiet conditions can become mismatched within minutes of a volatility burst. Fixed-pip parameters ignore clustering, while parameters scaled to current volatility adapt to it. Clustering also explains why spreads and slippage tend to worsen at the same time that opportunity appears to increase.
For a scalper, this matters more than any directional opinion. A one-minute candle with a range several times the recent average rarely arrives alone. The following candles usually remain elevated before volatility decays back toward a baseline, often unevenly and with occasional secondary bursts.
This is the reason models such as GARCH were built: they treat variance as something that depends on recent squared returns and on its own previous level. Even without fitting any model, a comparison of short-window range against a longer-window range gives a rough picture of whether the market is in an expanded or compressed state.
Practical consequences follow. Position sizing, stop distance, and profit targets calibrated to quiet conditions can become mismatched within minutes of a volatility burst. Fixed-pip parameters ignore clustering, while parameters scaled to current volatility adapt to it. Clustering also explains why spreads and slippage tend to worsen at the same time that opportunity appears to increase.