Session times and why 24/7 is not uniform

2026-12-24

A market being open is not the same as a market being liquid. Crypto trades continuously and its depth varies by a large factor across the day — so the same strategy executed at different hours is effectively two strategies with different cost structures.

What changes across the day

Depth. The amount resting in the book, which is what actually determines your fill on any size that matters — see spread, depth and what liquidity actually costs you.

Spread. Widens when market makers reduce exposure.

Volatility. Concentrates around session overlaps and scheduled events.

Who is trading. Different participants at different hours, which changes how the book behaves under pressure.

For crypto specifically, activity clusters around traditional financial-market hours despite the market never closing. The quiet hours are genuinely quiet, and that is when the book is thinnest.

Why it matters more than it seems

Slippage scales with size relative to depth. The same order is negligible in a deep book and expensive in a thin one. Trading a fixed size across the day means paying very different costs for the same decision — see slippage and market impact.

Stops fill worse in thin conditions. And stops trigger on adverse moves, which are more violent when there is less to absorb them. A stop placed during liquid hours can execute during illiquid ones.

Thin books amplify moves. Less depth means a given amount of flow moves price further, which is part of the mechanism behind liquidation cascades.

Your own size becomes visible. An order that is a rounding error at peak can be a meaningful fraction of the book overnight.

The asymmetry that catches people

You choose when to enter. You do not choose when your stop is hit.

So even a strategy that only enters during liquid hours can be exiting in the worst conditions of the day — and the exit is the leg where fill quality matters most, because it is the one you cannot postpone.

Two consequences:

Size for the exit, not the entry. If a position can only be exited cleanly during peak hours, it is too large to hold overnight.

Expect stop fills to be worse than the level. Particularly for positions held across quiet periods. If a materially worse fill is an account-level problem, the position is too large — see why position sizes drift upward.

Scheduled events

Some illiquidity is predictable.

Funding settlements on perpetuals occur at fixed intervals, and positioning shifts around them — see the funding rate calculator.

Dated futures expiry and roll concentrates activity and then removes it — perpetuals vs dated futures.

Scheduled venue maintenance. Announced, and still breaks anything assuming continuous availability — see exchange outages and degraded mode.

Traditional market opens and closes, which move crypto despite crypto not closing.

Predictable illiquidity is manageable illiquidity. Knowing the funding settlement times for the instruments you hold costs nothing and removes a category of surprise.

What to do about it

Measure it on your own trades. Record time of day alongside slippage and realised R — see what to record in a trading journal. If your fills are systematically worse in certain hours, that is measurable and actionable.

Prefer liquid hours for discretionary entries. The cost difference is often larger than any fee optimisation you could make.

Size positions held across quiet periods smaller. Not because the move is more likely, but because the exit is more expensive if it comes.

Do not use limit orders as stops in thin conditions. In a gap they do not execute and you remain in the position — order types explained.

Check whether your automation knows. A bot sizing identically at all hours is paying peak-hours prices for off-hours liquidity, and it will never mention it.

For automated setups

Two things worth building in:

Time-aware sizing. Reducing size during known-thin periods is a small change that directly reduces the cost of the exits you do not control.

Session awareness in the strategy itself. If a strategy was developed on data from liquid hours, running it continuously means running it in conditions it was never evaluated on — a variation of the sample-size problem in how many trades before you can judge a strategy.

FAQ

Does crypto have trading sessions?

Not formally — it trades continuously — but liquidity is far from uniform. Activity clusters around traditional financial-market hours, and the quiet periods have materially thinner books, wider spreads and worse fills. The market never closes; it does go quiet.

Why are my fills worse at certain times?

Because depth varies across the day and slippage scales with your size relative to what is resting in the book. The same order is negligible at peak and expensive overnight. Recording time of day alongside your fills makes the pattern visible.

Should I avoid trading during low-liquidity hours?

For discretionary entries, generally yes — the execution cost difference often exceeds anything fee optimisation would save. The harder problem is that you do not choose when your stop is hit, so positions held across quiet periods should be sized for an exit in those conditions.

How do I account for session times in an automated strategy?

Reduce size during known-thin periods, and check whether the strategy was evaluated on data covering the hours it now runs in. A strategy developed on liquid-hours data and run continuously is operating in conditions it was never tested against.