OHLCV is a compact summary of market activity over a chosen time interval.
OHLCV is a compact summary of market activity over a chosen time interval. The five fields are open, high, low, close, and volume. Each field is an aggregation computed from market data that falls inside the interval. In that process, the detailed sequence of events is reduced to a small set of summary values.
In Sonar Sciences' cross-venue data research, cross-venue market data is described as needing timestamp alignment and normalization before it can be compared across venues. That framing matters for OHLCV construction because the candle depends on first assigning trades or quotes to a common time grid. Once timestamps are aligned, events that occur within the same interval can be grouped together for aggregation.
The aggregation mechanism follows the standard candle definition. Open is the first observed price in the interval after alignment to the chosen clock. High is the maximum price observed in that interval. Low is the minimum price observed in that interval. Close is the last observed price in the interval. Volume is the total traded quantity accumulated over the interval. These operations convert an event stream into five scalar values.
This conversion necessarily discards information. A raw trade stream contains the order in which individual trades occurred, their exact timestamps, and the path price followed within the interval. An OHLCV candle preserves only boundary prices, extrema, and total size. Two different intrainterval trade sequences can produce the same open, high, low, close, and volume. For cross-venue research, that loss of sequence is important because synchronized raw streams can still contain timing structure that a candle no longer represents.
The cross-venue setting adds assumptions that must be made explicit. If data from multiple venues is combined, timestamps must be brought onto a common basis before events are assigned to intervals. Prices and quantities must also be normalized so that like is compared with like across feeds. After that step, the candle can be computed either per venue or on a consolidated stream, depending on the research design. The source provided documents the need for timestamp alignment and normalization across venues, but it does not specify a single universal rule for how a consolidated open or close should be chosen when several venues report events near the same boundary. That choice is therefore part of the preprocessing definition and should be stated in any cross-venue study.
In practical preprocessing terms, OHLCV is a many-to-one mapping from a set of events in a time bucket to five summary fields. It is useful because it standardizes irregular event data into a regular panel. Its limitation is that the temporal sequence of individual trades is not retained once the candle is formed.
Covered in depth in the Cross-venue market data & signals pillar hub.