Market Data Glossary: OHLC, Volume, Open Interest, Depth and VWAP
Market data is the information used to describe past transactions, live quotations, order-book liquidity and outstanding contracts. Understanding the difference between price, volume, market depth, open interest and data latency is essential before relying on a chart or trading signal. Some information records trades that actually occurred; other fields describe orders that may never execute.
This market-data glossary focuses on interpretation rather than chart predictions. It explains standard terms and why two platforms may display different volumes, prices or apparently contradictory indications of market activity.
Market data glossary: price, volume and order-book definitions
Last traded price
The price of a recently reported transaction under a market’s reporting convention. It is a historical fill and may not be executable for a new order, particularly in a thin or fast-moving instrument.
Bid and ask quote
A pair of current buying and selling prices with associated quantities. The best bid and ask refer to a particular venue or aggregation method, and those quotes can disappear before a new instruction arrives.
Quote size
The amount available at a stated bid or ask. A tight spread with very small displayed size may not represent adequate liquidity for the intended trade.
OHLC
The open, high, low and close of a chosen aggregation period. These values summarise historical activity but omit the sequence and quantity of transactions between points.
Candlestick
A graphical way to show OHLC data. The candle body joins open and close while the full range describes high and low; its appearance changes with aggregation period and data source.
Bar interval
The period over which a candle or OHLC bar is constructed. A one-minute chart, a daily chart and a volume-based bar can present quite different information about identical underlying trades.
Trading volume
Quantity reported as transacted during a specified period. Shares, futures contracts and cryptoasset units use different denominators, and venue data may not represent the whole market.
Notional trading volume
Traded quantity multiplied by price under a defined convention. It gives a money-denominated perspective but is not the same thing as capital entering the asset or new demand.
Turnover ratio
Volume expressed relative to shares outstanding, float or another reference quantity. Its interpretation depends on the denominator and whether off-exchange activity is included.
Relative volume
Current trading volume divided by a historical reference level for a comparable interval. A midday ratio should ideally compare with past midday patterns rather than a whole-day average.
Open interest
The number of derivatives contracts still outstanding under exchange rules. A new buyer and seller can create one contract; transactions that offset existing positions can reduce open interest.
Volume versus open interest
Volume counts transactions over a period; open interest counts outstanding contracts at a snapshot. High turnover can occur without a matching increase in outstanding positions, so the two measures answer different questions.
Order book
A view of visible buy and sell instructions at price levels. It is a snapshot of prospective liquidity rather than a commitment that every displayed order will remain available.
Top of book
The current highest eligible displayed bid and lowest eligible offer in a particular market view. It excludes deeper levels and may omit hidden or inaccessible liquidity.
Depth of market
Displayed order quantities across multiple price levels. Depth is useful for analysing possible execution but can evaporate during announcements or when larger participants cancel orders.
Level 1 market data
A commonly used label for basic quotes and trade information, often including best bid, best ask and last trade. Exact fields and latency depend on the vendor and exchange.
Level 2 market data
A commonly used label for multiple order-book levels or market-maker quotes. Coverage, aggregation and entitlements vary; Level 2 does not necessarily reveal the entire market.
Market-by-price
An aggregated book showing total displayed quantity at each price rather than individual participant orders. It is efficient for viewing depth but obscures the sequence and identity of constituent orders.
Market-by-order
A more granular data feed exposing distinct orders and changes when the venue offers it. It can help research queue dynamics, although hidden orders and external liquidity remain unseen.
Bid–ask imbalance
A calculation comparing visible buy and sell quantity on selected order-book levels. It is sensitive to which levels are included and to cancellations; a strong imbalance does not guarantee the next price move.
Time and sales
A stream of reported executions with timestamps, prices and quantities. Reporting conventions, batching and corrections can differ, and a trade print alone does not establish who initiated it.
Trade aggressor
The side inferred or reported as initiating an execution by crossing available liquidity. Classification algorithms can be uncertain when quote and trade timestamps are imperfect.
Volume delta
A difference between volume attributed to buyer-initiated and seller-initiated transactions under a chosen method. It is not a direct measure of all investors buying versus selling, since every trade has both sides.
VWAP
Volume-weighted average price, the sum of traded price times quantity divided by total quantity over a specified sample. It is used as a benchmark and may vary with market coverage and excluded trades.
TWAP
Time-weighted average price, a measure averaging price observations over time according to a convention. It differs from VWAP because intervals can have different trading volumes but similar weight.
Volume profile
A distribution of estimated or reported trading volume across price levels for a defined period. The choice of aggregation and data source shapes the apparent high-activity zones.
Point of control
In many volume-profile tools, the price level with the greatest estimated traded volume during the chosen sample. Its meaning depends on the platform’s allocation method, not a universal exchange designation.
Tick
The minimum allowed price movement or quoting increment for a contract or instrument. A tick is not necessarily a trade, and its monetary value depends on the contract specification.
Tick volume
A count of price or quote changes rather than necessarily the number of underlying units transacted. It may be used as a proxy where consolidated actual volume is unavailable, but the metrics are not identical.
Market data latency
Delay between an event, its dissemination and display or processing by a user. For very short-horizon decisions, delayed quotes can produce misleading spread and slippage estimates.
Consolidated tape
A system aggregating eligible trade reports, and sometimes quote data, across trading venues under market-specific rules. It should not be assumed that one country’s tape design applies globally.
NBBO
In US equity-market terminology, the national best bid and offer compiled under applicable market-data and quotation rules. It is a specific regulatory concept and should not be used as a universal label for every global market.
Opening auction
A procedure that gathers orders to determine an opening price under published exchange rules. Its displayed indicative prices and imbalances can change until the auction is completed.
Closing auction
A matching process establishing a closing price for an eligible market. Closing auction volume can differ considerably from continuous intraday activity and affect benchmark execution.
Adjusted price series
Historical data modified for corporate actions such as stock splits or dividends under specified conventions. Adjusted prices can be useful for return studies but must not be treated blindly as actual past executable quotes.
Continuous futures series
A constructed history combining successive futures contracts. Its roll rule and adjustment method change the price history; the resulting continuous chart is not itself a directly tradable instrument.
Trade corrections
Exchange or reporting updates that replace or cancel erroneous prints. Backtests and historical charts may differ depending on whether cleaned records or raw streaming data are used.
Worked example: quotes, depth and a large purchase
Consider a simplified order book with 100 units offered at £50.05, 200 at £50.10 and 300 at £50.20. The best ask is £50.05, but its associated size is only 100. A market buy of 400 units would need to interact with the first two price levels and 100 units of the third, assuming that all displayed liquidity remains valid and that no other orders take priority. The resulting weighted average is (100 × £50.05 + 200 × £50.10 + 100 × £50.20) / 400 = £50.1125 before additional fees.
A chart showing a last traded price of £50.00 would not make the 400-unit purchase achievable at £50.00. The difference between last trade, top-of-book quote and cumulative executable depth is central to order execution. Nor is a static depth display a forecast: offers may be cancelled, new limit orders may arrive and hidden liquidity may interact differently from the visible book.
Worked example: volume and open interest in futures
Suppose a futures market starts the session with 10,000 outstanding contracts. During the day, 2,000 contracts trade. It does not follow that open interest is now 12,000. If two parties both initiate new opposing positions, each matched contract can add one to open interest; if both offset existing positions, a matched contract can reduce outstanding open interest. When one opens and another closes, the net change can be zero. Actual clearing rules and aggregation determine the reported figure.
Volume can be active while net outstanding exposure barely changes. An increase in open interest is also not independently bullish or bearish because every futures contract has a long and a short side. Interpreting its significance requires price context, the participant mix, contract rollover, liquidity and whether the data is contemporaneous with the trade sequence.
Why spot FX volume is difficult to compare with share volume
A listed share may have trading activity dispersed over multiple eligible exchanges and off-exchange venues, while spot foreign exchange is a decentralised market without one universal record of every transaction. Many retail FX platform indicators called volume are tick counts or activity from that particular data source. Such measures can contain useful information about local activity, but they are not identical to consolidated global turnover.
In cryptocurrencies, trading volume can be split among centralised venues, decentralised pools and on-chain movements, with differences in reporting standards and potential wash trading. A single venue’s figures should not automatically be extrapolated to the entire asset. Always identify the unit, source, method and window before comparing market-data claims.
Adjusted stock prices and corporate actions
Imagine a stock that closes at £200 before a two-for-one split. After the split, each original share becomes two shares, and an approximate mechanical reference price becomes £100, holding other market effects aside. A raw price series can appear to have halved overnight even though the shareholder’s combined economic interest is broadly unchanged. A split-adjusted historical series rescales earlier quotations to support comparison, but it is not the actual price an investor saw on the original day.
Total-return series introduce further conventions for cash dividends and reinvestment. For signal design, one series may be used to examine economic performance while actual raw or contract prices and tick rules determine execution. The same caution applies to constructed continuous futures data: adjusted back-history can remove roll discontinuities but must not be mistaken for a tradable contract.
How market data errors distort analysis
Unadjusted splits can produce false volatility spikes. Incorrect timestamps can make a supposed signal appear to predict information that had already reached the market. Omitting delisted companies from a historical equity universe creates survivorship bias. A consolidated trade feed may contain corrections, while a retail chart can have missing bars or synthetic values around market closures.
For short-term strategies, delayed quotes can lead to imaginary fills. For longer-term research, mixing total-return and price-only indexes can misstate relative performance. A sound research record specifies the vendor, time zone, adjustment methodology, source venue, data latency and any cleaning or exclusions performed before conclusions are drawn.
Reading liquidity without overinterpreting the book
Order-book imbalance is tempting because a screen may show many more bids than offers. Yet visible quantity can be withdrawn quickly, and some markets hide part of resting liquidity. Spoofing and other forms of manipulation are prohibited in relevant jurisdictions but the mere appearance of a large order does not establish that it will trade. A snapshot has little value without time, cancellation behaviour and actual executions.
Depth is also conditional on price and size. A market may have enough quantity for a modest order while offering poor liquidity for a portfolio-sized position. Comparing the same number of displayed units across two instruments can be meaningless if contract notionals differ substantially. Convert quantities into comparable economic exposure before drawing liquidity conclusions.
Building a trustworthy market-data checklist
Before using a dataset for research, document the source, scope and time convention. Determine whether prices are live, delayed or historical; whether timestamps identify trades, quotes or publication; and whether the dataset includes auctions, off-exchange trades or only one venue. Check if prices use the instrument’s trading currency, whether volume is shares or contracts, and how corrections are applied. These details are not administrative footnotes: each can change what an analytical indicator actually measures.
Consider a hypothetical study of a strategy designed to trade at the daily close. If the chart provider publishes the completed closing bar only after the closing auction, a backtest that assumes all signals were known and executable at that very close may be unrealistic. Likewise, a study using today’s surviving index constituents in a 10-year history can exclude delisted failures. The apparent strength of the resulting signal may reflect data construction rather than a genuine repeatable relationship.
A quality assurance process should compare samples against exchange or official-source publications where practical, test missing observations and abnormal spikes, and identify changes in vendor methodology. For corporate events, determine whether the research uses raw, split-adjusted or total-return series and whether all formulas and execution prices follow consistent conventions. This record makes results reproducible and helps expose hidden sources of false precision.
Explore related glossary guides
Definitions are most useful when connected to neighbouring concepts. See Trading Glossary A–Z, Trading Order Types, Trading Costs, Technical Analysis for complementary market terms, risk considerations and examples.
Frequently asked questions
Does high trading volume mean a price will rise?
No. Volume describes how much was traded, not whether buying or selling interest will dominate future prices. Every completed trade has both a buyer and a seller; price movement depends on available liquidity and changing willingness to transact at different levels.
Can open interest reveal whether more traders are long than short?
Not on its own. Futures open interest counts matched contracts, and each creates corresponding long and short positions. Positioning reports can add information about participant categories, but are different datasets with their own reporting limitations.
Is the best displayed quote a guaranteed fill?
No. Quotes have finite size, may change before order arrival, and can be subject to queue and venue access. A new order’s ultimate price can differ significantly, especially when its quantity exceeds top-of-book depth.
Are all candlestick charts built from identical data?
No. Venue coverage, sessions, time zones, aggregation method and adjustments can differ. A candle is a summary of the underlying feed and should not be treated as a universal, source-independent record.
What does VWAP tell a trader?
It provides an average price weighted by observed traded quantity over a specified window. Comparing an execution with VWAP can be useful, but benchmark choice, order urgency, market participation and trade exclusions all affect interpretation.
Related education
Study How Financial Market Prices Are Formed, Market Liquidity and Slippage and Stock Market Liquidity and Volume.
Sources and further verification
The SEC Investor.gov stock quotes explanation, the SEC glossary and the CME futures glossary provide authoritative terminology. Exchange feed specifications and provider terms define what a particular dataset actually reports.
Educational information only; not personal financial advice or a representation that any data series predicts market direction. Market access, data quality and leverage create material risks.