← Market Flow Research 🌙
Sell drain

Drain Out of the Sell Wall: Liquidity Leaving Before the Move

We isolated drain out of the sell wall — one feature, no partner, no composite — and measured what it predicts second by second across six coins. The answer is the size of the next move, never its side.

Research note · 2026 · AI-assisted, human-reviewed

① The shape of drain out of the sell wall

Before asking what drain out of the sell wall predicts, we look at what it is: how the quantity is distributed across its own range, per coin. The profile is heavily skewed — long stretches of very little, punctuated by rare, very large readings. Every threshold later in the study is a quantile of this shape, not a round number picked by hand.

Profile of drain out of the sell wall per coin
Profile of drain out of the sell wall per coin

② What it predicts, across horizons

Rank correlation of drain out of the sell wall with the size of the next move peaks at the fastest horizon (+0.37 on BTC at 5s) and decays monotonically toward the daily scale (+0.07). Direction is a different story: the same sweep against signed returns tops out around 0.05. Size, yes; side, no.

Link between drain out of the sell wall and the next move, by horizon
Link between drain out of the sell wall and the next move, by horizon

③ Where each coin peaks

The best window differs by coin but always sits at the short end — 5s to 5s. Anything slower than that is reading yesterday's news.

Peak predictive window per coin
Peak predictive window per coin

④ Price impact per unit

Per +1σ of drain out of the sell wall, price moves by a fraction of a basis point, and the sign is not stable across bands. This is the quantitative version of 'it does not push price in a usable direction'.

Price impact per +1σ of drain out of the sell wall
Price impact per +1σ of drain out of the sell wall

⑤ What counts as normal

Normal levels of drain out of the sell wall grow by orders of magnitude from a second to a day, so 'high' is always relative to a window. This chart is the baseline every later threshold is measured against.

Normal levels of drain out of the sell wall by timeframe, BTC
Normal levels of drain out of the sell wall by timeframe, BTC

⑥ Memory

Autocorrelation of drain out of the sell wall starts at 0.29–0.45 at the finest scale and rises to 0.75–0.82 at intermediate windows. The quantity clusters in time: a busy minute follows a busy minute far more often than chance allows.

Autocorrelation of drain out of the sell wall by timeframe
Autocorrelation of drain out of the sell wall by timeframe

⑦ Where the seconds live

Most seconds carry almost no drain out of the sell wall; the interesting behaviour is confined to a thin tail. Working with means here would describe a market that does not exist.

Distribution of drain out of the sell wall across bands, BTC
Distribution of drain out of the sell wall across bands, BTC

⑧ How large the extremes get

A peak second of drain out of the sell wall runs many times above its own normal. That ratio is what makes threshold rules feasible at all — the extremes are unmistakable once the baseline is right.

Spike-to-normal ratio for drain out of the sell wall
Spike-to-normal ratio for drain out of the sell wall

⑨ Spike, normal, lull

Every moment gets labelled relative to its own baseline. The three states separate cleanly in volatility and poorly in direction — the same result the whole project keeps producing.

Behaviour of spike / normal / lull states
Behaviour of spike / normal / lull states

⑩ The states over price

The labelling drawn directly over a BTC price window: where drain out of the sell wall changes state, and what price does around it.

Research, not financial advice.

Drain out of the sell wall states over a price window, BTC
Drain out of the sell wall states over a price window, BTC
🤖 This research — data collection, analysis, charts and the narrated video — was produced with the assistance of AI, then reviewed by a human. We forecast volatility, not direction, and log every prediction. Research, not financial advice.

Comments

Discussion is powered by GitHub. Enable it by adding secrets/giscus.json (repo IDs from giscus.app).

← All research