Liquidity, depth and slippage: what market cap omits

Liquidity is the ability to trade a given size quickly without moving the price much. It is not a single number, it is not a property of an asset in the abstract, and it is not implied by size. Two assets with identical market capitalization can differ by orders of magnitude in how much can be sold in an hour at a tolerable price.

Four questions hiding behind one word

Market microstructure separates liquidity into distinct properties that are often conflated. Tightness is the cost of a round trip at minimum size, visible as the spread. Depth is how much size sits near the touch, measured as market depth within a stated distance from the mid price. Immediacy is how quickly size can be executed rather than worked over hours. Resilience is how fast depth is replenished after a large trade consumes it. An asset can score well on one and badly on another: a tight spread on one unit of size tells a reader nothing about the cost of trading a thousand times that.

Depth, and why it is a snapshot rather than a stock

The standard measurement takes an order book snapshot and sums the notional resting within a stated band, commonly one or two percent either side of the mid. Three caveats travel with the figure. It is venue-specific, and depth on a venue that a particular participant cannot access is not depth available to them. It is revocable, because quotes can be cancelled faster than an order can arrive. And it is reflexive: depth is thickest when volatility is low and thins precisely when large trades most need it, so a measurement taken in calm conditions overstates what is available in stressed ones. On a decentralized exchange the equivalent calculation is deterministic, since the curve of a liquidity pool defines the cost of any size in advance, but concentrated liquidity means the answer depends on where providers placed capital rather than on how much they placed.

Spread, price impact and slippage are three different costs

These terms are used interchangeably in casual writing and mean separate things. The spread is the immediate cost of crossing from bid to offer at small size. Price impact is the movement caused by the order itself as it consumes successive levels, and it is a function of order size relative to depth. Slippage is the difference between the price expected when the order was sent and the price achieved, which includes price impact but also includes movement that happened while the order was in flight and would have happened anyway. On-chain, slippage tolerance is an explicit parameter, and setting it wide enough to guarantee execution is what makes a sandwich attack profitable for the attacker.

A practical way to feel the difference: an order that is small relative to the book pays roughly half the spread and nothing else. An order that is several multiples of the visible depth pays the spread, then a rising sequence of worse prices, then whatever the market does in response once other participants infer that a large seller or buyer is present. The last component is the one that does not appear in any pre-trade estimate.

Why market capitalization says nothing about any of this

Market capitalization is the last traded price multiplied by circulating supply. The price is set at the margin, by whatever quantity traded most recently, and multiplying a marginal price by the entire supply produces a number that no one could realize. That criticism applies to equities too, but three differences make the digital-asset version weaker still.

• Circulating supply is an estimate, not a registrar's number. It depends on judgment calls about founder allocations, foundation holdings, locked or vesting tokens and burned coins, and different data providers reach different answers using different methodologies.
• Equity markets have a long-standing separation between shares outstanding and free float, and institutional convention sizes positions against average daily volume rather than capitalization. The equivalent discipline is less established here, and headline rankings are built on capitalization.
• A large share of supply may be contractually unable to trade for years, while fully diluted valuation counts tokens that do not exist yet. Comparing FDV against market cap through the ratio between them shows how much of the eventual supply is still pending, which is a supply question rather than a liquidity one, but it is often confused for one.

The blunt version: capitalization is a scaling factor for comparing assets, not a measure of money invested and not a measure of money that could be withdrawn.

The liquidity that never appears in a book

A material share of institutional size never touches a public venue. Over-the-counter trading matches a buyer and a seller bilaterally at a negotiated price, often through a desk that warehouses the risk and unwinds it gradually. The trade is invisible to book depth, usually absent from reported volume, and may print at a price well away from the screen without the screen moving at all. This cuts both ways for interpretation. It means visible depth understates the size that can genuinely be transacted for a participant with access to those desks. It also means that a very large transfer of ownership can occur with no observable market impact, so the absence of a price move is not evidence that nothing large happened.

Turnover as a proxy, and how it breaks

The nearest single-figure proxy is turnover, reported here as 24-hour turnover and 30-day turnover. It answers roughly what fraction of the notional value changes hands in a period, and it is far more informative than capitalization alone. Its failure modes are worth naming. The numerator is reported volume, which is only as honest as the venues included, so fabricated activity inflates it. The denominator inherits every circulating-supply estimate problem above. And an extremely high reading is as much a warning as a low one, since it usually indicates a small float being traded intensively rather than a deep market. Reading turnover alongside average 30-day volume separates a genuinely active market from a single day of unusual activity.

The honest summary is that no single number captures liquidity, and that the useful practice is to hold three together: how much trades on a normal day, how concentrated that trading is across venues, and how the asset behaved on its worst day rather than its typical one. The screener allows sorting by turnover and volume rather than by size alone, compare places two assets side by side on the same fields, and methodology documents how supply and volume are defined here.