Tick Data vs OHLC
A comparison of two fundamental data granularity levels in financial markets: tick data captures every individual trade and quote change in sequence, while OHLC (open-high-low-close) data aggregates price information into fixed time intervals, sacrificing granularity for compactness and ease of analysis.
The choice between tick data and OHLC data is one of the most consequential decisions in quantitative trading and research, touching on storage costs, computational requirements, statistical power, and the types of questions a researcher can meaningfully answer.
Tick data refers to the raw, timestamped record of every transaction that occurs in a market. Each record typically contains a timestamp (often to millisecond or microsecond precision), the price at which the trade occurred, the volume traded, and exchange identifiers. In addition to trade ticks, quote ticks capture changes to the best bid and offer prices even when no trade occurs. At NSE on an active trading day in a liquid large-cap stock, the combined trade and quote tick stream can generate tens of thousands of records per second.
OHLC data condenses this stream into intervals — typically one minute, five minutes, fifteen minutes, one hour, one day, or one week. For each interval, only four prices are recorded: the first price traded (open), the highest price traded (high), the lowest price traded (low), and the last price traded (close), along with the total volume for the interval. A full year of daily OHLC data for a single stock might occupy a few kilobytes, whereas the corresponding tick data could occupy several gigabytes.
The analytical implications are profound. Strategies based on daily OHLC data — most classic technical analysis patterns, fundamental screening based on daily closing prices, and daily momentum factors — can be developed and tested on datasets that are cheap to acquire and fast to process. NSE's publicly available Bhavcopy files provide free daily OHLC data going back many years, making daily-frequency research highly accessible.
Strategies operating at intraday frequency — scalping, statistical arbitrage, market making, or intraday momentum — require tick data. The granularity exposes patterns invisible in OHLC data, such as the distribution of trade sizes, the dynamics of the order book during the first and last minutes of trading, and the precise sequence of price movements during news events. However, tick data vendors charge significant subscription fees, and handling tick data computationally requires infrastructure beyond the reach of most individual researchers.
A critical limitation of OHLC aggregation is that it loses the sequence of prices within a bar. Two five-minute bars with identical OHLC values could represent very different intrabar price paths — one where price rose steadily throughout, and another where price fell sharply and then recovered. This matters enormously for some strategies and not at all for others.
For Indian retail traders, NSE provides one-minute OHLC data through its website and through authorised data vendors, representing a useful middle ground between daily OHLC and full tick data for intraday strategy research.