EVA Terminal · LearningРусский

Section 13 of 18

Cascades and the liquidation map

How one forced trade pushes the price into the next, why the chain breaks, what the estimated liquidation map really draws and why a liquidation total always names its exchanges. With 378 bursts from our archive.

The chain: how one liquidation triggers the next

Section 12 gave us the key point: a liquidation is not “the exchange took the money” somewhere in its books, it is a market trade. When a position runs out of margin, the exchange closes it itself, with a market order. Liquidating a long is a forced sell; liquidating a short is a forced buy. Such an order has no limit price and no patience: it takes whatever rests in the book, level by level, until the whole size is filled.

That is where the chain comes from. The price falls → the most leveraged longs run out of margin → their forced sells eat the bids → the price drops further → the next longs, with slightly less leverage or a slightly lower entry, reach their liquidation price. Each step sets up the next one. This is a liquidation cascade. The mirror case is an upward cascade of shorts: forced buys lift the price into the next shorts' liquidation prices (often called a short squeeze).

It matters how a cascade differs from an ordinary decline. In an ordinary decline every seller decides: sell now or wait, place a limit order or hit the market. In a cascade the decision was made in advance — when the trader chose the leverage. The exchange carries it out mechanically and at the worst moment: when the price is already moving against the position and the book below is thinning.

Illustrative: two steps of a cascadebids in the book, $M99,7900.499,7600.599,7200.699,6800.899,6400.799,800long liquidations $1.5M99,750long liquidations $1.0M1: → 99,7202: → 99,640Bright — bids eaten. The first sell took the price below 99,750 and triggered the second.
Illustrative: a forced sell eats the bids and takes the price to the next liquidation price.

Two steps of a cascade, with illustrative numbers

Illustrative example. The price is 99,800. Bids rest below it: 99,790 — $0.4M, 99,760 — $0.5M, 99,720 — $0.6M, 99,680 — $0.8M, 99,640 — $0.7M. At 99,800, $1.5M of longs reach liquidation; at 99,750, another $1.0M.

Step 1. The $1.5M forced sell eats 0.4 + 0.5 + 0.6 = $1.5M of bids. The last trade prints at 99,720 — the new price. The average price of this sell is about 99,752, not 99,800: each next part filled lower.

Step 2. 99,720 is already below 99,750, so the second group of longs is liquidated too. Its $1.0M eats $0.8M at 99,680 and $0.2M at 99,640. The price is 99,640. Nobody made a decision that minute: leverage and a thin book decided it all.

Had $5M of bids rested at 99,720 instead of $0.6M, the first sell would have stopped at 99,720 with room to spare, the price would not have reached 99,750, and there would be no second step. Book thickness decides whether one liquidation becomes a cascade.

Illustrative: two steps of a cascadebids in the book, $M99,7900.499,7600.599,7200.699,6800.899,6400.799,800long liquidations $1.5M99,750long liquidations $1.0M1: → 99,7202: → 99,640Bright — bids eaten. The first sell took the price below 99,750 and triggered the second.
A cascade is a property of a combination: many leveraged positions close together in price plus a thin book. One big liquidation in a thick book is just a big trade. A hundred small ones in a row in an empty book is a chain.

What a cascade looks like in EVA. The “Order book · Flow” panel has a liquidations feed: time, coin, side, price and amount. A single line is noise. A cascade is a run of lines of one side in a row, often at close prices, within seconds or minutes. The rest is usually visible too: a candle with a long body, a burst of one-sided aggression in CVD (section 7), open interest that is not rising but falling (section 10): a liquidation closes a position, so fewer contracts remain in the market. “Price sharply down + a run of long liquidations + OI falling” is the typical portrait of a downward cascade. The mirror: “price up + a run of short liquidations + OI falling” is an upward cascade.

Compare another picture: the price falls, OI rises, almost no liquidations. That is not a cascade but new positions — someone is opening shorts. Liquidations and OI together answer the question “who is moving the price — new participants or forced ones”.

Why a cascade ends — and what followed 378 bursts

A cascade cannot go on forever, and it usually stops for one of several reasons.

None of these causes is visible in advance to the exact price. A wall can be pulled (section 4), opposite buyers may not come, and exchanges do not publish how many positions sit lower. So the honest question is not “where will the cascade end” but “are there signs the fuel is running out”: the liquidations feed thins, OI stops falling, hits on the bids no longer move the price.

378 liquidation bursts: what came next

Production archive, 02.09–13.10.2026 (42 days), coins BTC, ETH and SOL. A burst is a five-minute bar in which one side's liquidation total was in the top 1% of all five-minute bars of that coin for the period and at least three times the other side. After a burst the next hour of the same coin was skipped so one cascade would not count many times. That gave 378 cases (BTC 132, ETH 126, SOL 120; longs wiped out in 193, shorts in 185).

What follows. First: liquidations do push the price where it was already going — nine bursts in ten coincided with the move. Second: “there is always a bounce after a cascade” and “a cascade always continues” are both false: after an hour it is nearly even. Third: the cascade continued when new fuel turned up — a repeat burst. But that is only visible in hindsight: at the first burst nobody knows whether a second will come. This is a breakdown that explains the mechanics, not a hint.

Caveats. Prices are the archive's one-minute snapshots, so a fast dip and bounce within a minute is invisible. Liquidation totals are incomplete (see lesson 4), and the “top 1%” cut-off was chosen for this study sample, not taken from EVA's algorithms.

BTC, 02.09.2026: the first case of each outcome08:50 UTC · after an hour — furtherlongs wiped out $1.47M in 5 minburst end 76,770.0 → an hour later 76,640.4−30 minend+1 h10:50 UTC · after an hour — backlongs wiped out $5.75M in 5 minburst end 76,477.6 → an hour later 76,665.0−30 minend+1 hLine — one-minute price; bars — liquidations per five minutes: longs — fall colour, shorts — rise colour.The second burst was four times larger than the first, yet the price was higher an hour later. Production archive.

Source: production archive ~/eva-terminal/archive, of_2026-09-02 … of_2026-10-13 (*.g?.jsonl.gz): liq events and one-minute prices of BTC, ETH, SOL; script dev/kurs_stat/r13.py, result zamery/kurs/r13.json

All 378 liquidation bursts (BTC, ETH, SOL, 02.09–13.10.2026)within 5 minwith the wipe-out 340 · 89.9%no 38after 1 hourfurther 180 · 47.6%back 198after 4 hoursfurther 153 · 40.5%back 225Liquidations push the price along, but after an hour it is nearly even, after 4 hours more often back.Production archive, script dev/kurs_stat/r13.py. The “top 1%” cut-off is for the study, not EVA's algorithms.
All 378 bursts: within the five minutes, after one hour and after 4 hours — shares of “further” and “back”.

The example's figure shows the first case of each outcome for BTC, not the prettiest ones. On 02.09.2026 at 08:50 UTC, $1.47M of longs were wiped out in five minutes (20 liquidations); the minute price went from 76,823.1 to 76,770.0, and an hour after the burst it was 76,640.4 — further down. The same day at 10:50 UTC, $5.75M of longs were wiped out (155 liquidations) — almost four times more — yet by the end of that five-minute bar the minute price was already 76,477.6 against 76,426.6 at its start, and in the next bar $1.07M of shorts were wiped out. An hour later — 76,665.0, higher. A bigger burst did not mean a longer fall.

The liquidation map: an estimate, not orders

The “Liquidations” chart layer puts five different things on one field, and the first rule is not to mix them up:

The estimated map answers: “if positions were opened here, with usual leverage, where would their liquidation prices be?” The logic is simple. Exchanges do not say who holds what leverage, but one can see where trading happened and where open interest grew — that is, where positions were probably opened. From such an entry price the liquidation price sits at a distance that depends on leverage (section 12). The model spreads the presumed positions across several typical leverages and draws where their liquidations would cluster.

Illustrative: what sits on the “Liquidations” layer100,00098,00096,00094,00092,00090,000entry zone: OI rosemap, 50×map, 25×map, 10×fact: already wiped outHyperliquid addressfactwhere it was wiped out — the pastmapwhere it might be — an estimateHyperliquidwhere this position goes — exactMap bands: 100% / leverage from entry, no maintenance margin. No orders on the map.
Illustrative: one entry zone — three bands of the estimated map for different leverages; next to them the fact and a hard Hyperliquid address level.

Where the map's bands come from

Illustrative example, without maintenance margin — to see the idea, not the exact figure. OI rose noticeably around 100,000: longs were probably opened there. If some of them use 10× leverage, their liquidation is about 100% / 10 = 10% lower, near 90,000; at 25× — 4% lower, near 96,000; at 50× — 2% lower, near 98,000. So one entry zone becomes three bands on the map.

With maintenance margin (section 12) each band is slightly closer to the entry, but the order is the same: the higher the leverage, the closer the liquidation is to the entry and the sooner the price gets there.

Notice how many “ifs” and “probablys” there are. The model does not know what share of positions used 10× and what share used no leverage at all; it does not know how many are already closed, who has a stop order above the liquidation, and who has shared collateral across the whole account. A band is a place where liquidations might be.

Illustrative: what sits on the “Liquidations” layer100,00098,00096,00094,00092,00090,000entry zone: OI rosemap, 50×map, 25×map, 10×fact: already wiped outHyperliquid addressfactwhere it was wiped out — the pastmapwhere it might be — an estimateHyperliquidwhere this position goes — exactMap bands: 100% / leverage from entry, no maintenance margin. No orders on the map.

What the map shows. Where liquidation prices would cluster under typical leverage. It is useful as a question: “if the price gets here, could a forced wave happen here?” Next to the fact, the map lets you compare where things were already wiped out and where there may still be something to wipe out.

What the map does not show.

Fact — where positions were already wiped out. The map — where they might be wiped out under our assumptions. A Hyperliquid address level — where a specific position will certainly be wiped out if it does not change. Three different degrees of certainty on one field.

The coverage caption: which exchanges were counted

Any liquidation total is the total of what exchanges reported, and they report differently. On the “Money” tab the “Liquidations” block states under the total how many coins and which exchanges it covers. The differences between exchanges are:

So EVA's total and another service's total can differ several-fold, and neither has to be wrong. The liquidation map for OKX and for Bybit differs roughly two-fold in turnover — the venue is always named next to it. The “incomplete” mark on a coin means less data is in memory than the window — not everything is counted there.

How much is visible at “one per second”

Illustrative example. A cascade on one coin lasts 20 seconds; on Binance 25 positions close every second — 500 in all. A feed of “at most one per second” gives us at most 20 lines: 20 / 500 = 4% of the liquidations by count. By amount the share may be larger or smaller — it depends on which of the second's 25 the exchange sent. The undercount is largest exactly in the densest seconds of a cascade: in a calm minute with fewer than one liquidation per second little is lost.

Hence the comparison rule: compare the totals of two days or two services only with the same coverage caption. “Yesterday $200M, today $120M” means nothing if yesterday's caption listed six exchanges and today OKX was silent.

Common mistakes

The section test: 13 questions
Tricky questions and a review of every answer. The test, your progress and the section order are available after signing in: a section opens after passing the previous one, the pass mark is 80%. We teach you to read the market, not to guess: there are no signals or forecasts here.
Take the test — log in

The whole course

  1. How the market works: spot, futures, leverage — What exactly you buy on spot and on futures, how to calculate profit and loss with leverage — as a percentage of margin and of the position, who makers, takers and aggressors are, and why price moves only through trades.
  2. Orders and execution: price, fees, slippage — Limit, market and stop orders, take-profit; how a market order fills across several prices and how to compute the average fill price; maker and taker fees on entry and exit — charged on the position, not the margin; slippage and common calculation mistakes.
  3. The order book: bids, asks, spread and depth — How the order book works: levels, best prices, the spread and the mid price; depth and how a market order eats through levels; thin and thick books in the EVA archive; multi-exchange books and what the book does not show.
  4. Liquidity walls: what rests and what gets pulled — What a dense order and a wall are, how a filled wall differs from a pulled one, what spoofing is, how to read book imbalance by distance bands and the heatmap — and why a wall is an intention, not money.
  5. The tape: orders, merging, pace — What the tape and prints are, why an exchange sends one order as a dozen trades, how EVA merges them back, what “large” means on its own venue, how to read tape pace — and what the tape does not show.
  6. Volume and the volume profile — What bar volume says and does not say, why volumes of different exchanges do not match, how the volume profile, POC and value area (VAH/VAL) work, how to read high volume without movement, and session profiles.
  7. Delta and CVD: who was pressing — Bar delta is market buys minus market sells; CVD is delta added up. Why “there were more buyers” is the wrong phrase, how to read the slope, why futures and spot are shown separately, and what delta does not show.
  8. Divergences, absorption, CVD by trade size — When price and CVD go different ways, when market flow is met by limit orders, and which orders are pressing — small, medium or large. With honest statistics from our archive: 53 continuations against 54 reversals.
  9. Footprint: inside the candle — What happened between the open and the close: market sells and buys at each price level, the candle's POC, the diagonal imbalance and stacked imbalances — with calculations, a real BTC bar from the archive and an honest count over a week.
  10. Open interest — How many futures positions are open, how every trade changes that number, why OI in dollars misleads when the price moves, and what our archive honestly says about OI growth.
  11. Funding — Why a perpetual future has a payment between longs and shorts, who pays whom, how to compare rates of exchanges with different intervals, what it costs a position, and what our archive says about “overheated” funding.
  12. Liquidations: mechanics and maths — Why the exchange closes a position itself, what maintenance margin is, how to estimate the liquidation price and why it is closer than “100% / leverage”, how a stop differs from a liquidation, and what follows the heaviest hours.
  13. Cascades and the liquidation map — How one forced trade pushes the price into the next, why the chain breaks, what the estimated liquidation map really draws and why a liquidation total always names its exchanges. With 378 bursts from our archive.
  14. Exchange flows and whales — What a coin transfer to or from an exchange shows through our node, why a transfer is a chance to sell rather than a sale, how to read stablecoins, ETFs and exchange reserves with their delays, and who the off-exchange “whales”, US government wallets and Hyperliquid whales are. With two days, 12–13.10.2026, worked through.
  15. Macro and news — The release calendar: time, forecast, previous value and the actual from the primary source; why the market reacts to the deviation from expectations rather than the number itself; what happens to the book before a release; how to read dominance and the TOTAL caps; news and retellings of retellings. With 19 US releases from EVA's calendar worked through.
  16. Risk: position size and stop — How much you may lose on one trade, where the stop goes and how these two numbers give the position size; what leverage really does, how much of R fees eat, and why the percentages on the exchange screen are not percentages of the account.
  17. Risk: streaks, expectancy, journal — How much a system makes per trade on average, why losing streaks are inevitable, how recovery from a drawdown is computed, what to record in a trading journal and which mistakes break even profitable trading.
  18. Using EVA as a whole — The tab order and the day's order — from general to particular; the “?” sign and the “what it does not show” point; how to read “no data”, the source and the time of data; narrow alerts; replay for an honest review of an entry, and a journal in R.