Free tool · Markets literacy · Stocks · Crypto · Futures
Volume tells you how many shares changed hands. Dollar volume — price times volume, also called turnover — tells you how much money did. On most screens those two numbers rank instruments in completely different orders. Below is a free calculator for it across stocks, crypto, and futures, plus a field guide to the turnover-style metrics traders in Shanghai, Mumbai, and Seoul watch every day that almost no one teaches here.
The idea in one table
Here are two carmakers from the same trading day. Ford was one of the most-traded stocks on the board by share count — Tesla did not even make the share-volume leaderboard. Yet about seven times as much money moved through Tesla. That gap is the whole point of dollar volume.
| Stock | Price | Shares traded | Dollar volume (turnover) |
|---|---|---|---|
| TSLA | $435.79 | 45.2M | $19.69B |
| F | $17.44 | 154.2M most shares | $2.69B |
Real closing figures from May 29, 2026 — a snapshot, not live data. Ford traded about 3.4× the shares of Tesla, yet Tesla moved roughly 7× the dollar volume because each Tesla share is worth about 25× as much. Plug these same numbers into the calculator below and you will get exactly these figures.
Raw share volume flatters cheap, high-share-count names. Dollar volume — what exchanges outside the US usually just call turnover — strips out the price illusion and shows you where capital is actually concentrated. It is the cleanest one-number proxy for liquidity: how much you can buy or sell without shoving the price around.
The tool
Pick an asset class, enter price and volume, and read the turnover. Everything runs in your browser — no data leaves the page, nothing is stored. Add free float to get a turnover ratio; futures convert points to notional automatically.
Two instruments, two prices, two share counts. The calculator tells you which one has more money flowing through it — the answer is often not the one with more volume.
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Across asset classes
Dollar volume = price × shares. US screens usually surface average daily dollar volume (ADDV) and relative volume; the rest of the world calls the raw figure turnover. It is the number to size against — most desks cap a position at a small percent of ADDV so they can get out clean.
Crypto already gets this right. Exchange "24h volume" is usually quote volume — turnover in USD or USDT, not coin count. Compare that to circulating supply value and you have a turnover ratio for any token, no conversion needed.
Contract counts lie across instruments. One CL contract controls ~$70k of crude; one MES controls a fraction of that. Real dollar volume is notional: points × multiplier × contracts. That is what makes ES and CL comparable on one screen — and what relative volume on ES, NQ, and CL is built on.
The field guide
Dollar volume is one member of a much larger family — metrics that normalize raw activity, or surface behavior, into something comparable. Asian and some European markets built out rich toolkits here. The reasons they never crossed over are almost always structural, not because they are worse. Six worth knowing.
Value traded ÷ free-float market value — how fast the float churns.
Where: China, where retail watch 换手率 (huànshǒulǜ, "turnover rate") as a front-page number. A 20%+ daily rate screams froth; 1–2% is sleepy. China's market-wide turnover ratio runs near 296% a year against a world average closer to 34%.
Why not here: US flow is split across ~16 exchanges plus dozens of dark pools and internalizers. A single-venue turnover ratio is noise, so the retail culture never formed — even though it is the most direct cousin of dollar volume.
Deliverable quantity ÷ traded quantity — conviction vs. intraday churn.
Where: India. The NSE and BSE publish, for every stock every day, the share of volume actually taken to delivery versus squared off intraday. High delivery (say 60%+) means investors are building real positions; a rally on sub-15% delivery is just traders flipping to each other.
Why not here: US settlement does not surface the intraday-versus-delivery split, so the metric simply has no published data to stand on.
Per-stock leveraged-position data, published on a schedule.
Where: Japan's credit ratio (信用倍率, margin buys ÷ margin sells), China's margin balance (融资融券), and Taiwan's margin figures. A pile of leveraged longs is future selling overhang, and traders there watch it per name.
Why not here: US margin data (FINRA) is monthly, aggregate, and lagged — never per-stock, never timely. Short interest is the one cousin that survived, and it is crude by comparison.
A fixed daily ceiling per stock — and a strategy built on hitting it.
Where: China caps most stocks at ±10% a day (±20% on the STAR Market and ChiNext growth boards); Korea at ±30%; Taiwan at ±10%; India runs tiered price bands. China retail track 连板 — how many days in a row a stock has locked limit-up — as its own signal.
Why not here: the US uses market-wide circuit breakers plus Limit Up-Limit Down bands that pause a stock rather than cap it for the day, so "consecutive limit-ups" is not a thing.
Who is buying — by name, daily.
Where: China's Dragon-Tiger List (龙虎榜) publishes the top five buying and selling brokerage branches for any stock with a big move or 20%+ turnover. Korea and Taiwan publish daily net buy/sell split by foreigners, institutions, and retail — "foreign net buying" is the most-watched daily signal in Korean equities.
Why not here: US flow transparency is quarterly (13F, 45-day lag) and anonymous on the tape. There is no daily, named, per-stock attribution — by design.
A different default chart toolkit.
Where: Korea's disparity index (이격도, close ÷ moving average × 100), and the Psychological Line (PSY) and Volume Ratio (VR) common across Japan, Taiwan, and Hong Kong. Standard on Asian broker platforms.
Why not here: American technical analysis standardized early on RSI, MACD, and moving averages, and that lineage crowded out the parallel Japanese and Chinese charting tradition these came from.
The pattern
Five structural causes explain almost the whole list. None of them are about which metric is smarter.
The throughline: these metrics thrive in markets with one dominant exchange, mandated daily disclosure, fixed price bands, and heavy retail participation. The US has none of those four — so it optimized for a different toolkit. Knowing both makes you read any market more honestly.
Common questions
Price multiplied by the number of units traded — how much money changed hands, not just how many shares or contracts. One million shares of a $5 stock is $5 million of activity; one million shares of a $1,000 stock is $1 billion. Multiplying by price puts every instrument on the same dollar scale.
Share volume counts units; dollar volume counts money. They often rank instruments in completely different orders — a cheap stock can lead on share volume while a pricey one has far more money flowing through it. Dollar volume is the better read on liquidity and where capital is concentrated.
Turnover ratio is dollar volume relative to free-float value — how fast the float changes hands. Rough daily rule of thumb: under ~0.5% is quiet, 0.5–2% normal, 2–10% active, above ~20% often speculative froth. Heuristics, not rules.
Yes. Crypto exchanges already report turnover as quote-currency volume (24h USD volume). For futures, dollar volume is notional: points × contract multiplier × contracts. Comparing raw contract counts across instruments is misleading because each contract controls a different notional amount.
Market-structure education, not trading advice. Figures reflect public exchange rules and illustrative snapshots, not live data. Trading involves substantial risk of loss.