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Distinguishing Trade Ticks, Quotes, and Order Book Data

Article Quant Q&A · Author: leslieg

Summary

The document clarifies that “tick data” can refer to different market event streams. Trade ticks record executions, typically with price, quantity, and time; bid/ask updates capture changes in quoted prices and sizes; order book or market depth data can include changes beyond the best prices. The terminology varies across vendors, so historical data specifications should be checked.

For modeling, the contributors suggest starting with trades and adding quote data if the strategy can make use of it. Trades provide evidence of executed transactions, whereas quotes and depth can include displayed liquidity that may not be reliable. Combining feeds requires a consistent timestamp convention: one suggestion is to use the local receipt time for trades, while another is to adjust quote timestamps for estimated latency when aligning with exchange time. Storing changes from prior values can reduce the amount of data to process. The document gives practical guidance, not a universal data schema or proof that any feed improves trading results.

Key ideas

  • Trade ticks describe executed transactions, while quote updates and order book data describe displayed liquidity.
  • Data vendors may use the term tick data differently, so verify the fields and event types supplied.
  • Use a consistent timing basis when aligning trades and quote updates.
  • Start with trade data, then evaluate whether quote or depth data helps the strategy.
  • Representing changes from prior values can reduce data volume.

Tags

Full text
# Tick data collection


# Tick data collection












I am new to this. I am confused on what consists of a tick data.

I have a trading platform in which I could collect data of exchange traded product like futures and stocks. While I am intending to use the platform for trading, I think I could collect the data directly from platform. The data consist of:

- Every traded quantity + time of transaction at exchange

- Every changes in the bid quantity, bid price, ask quantity, ask price + time at which these data reach my computer

While referring to some websites and literature regarding tick data, I am not sure:

- Is tick data consist of 1 or 2 or the combination of 1 and 2? Which data should I build my model on?

- Also, if I am using the combination of 1 and 2, any ideas on how to combine the two series as the timestamp of 1 and 2 is different (there is time lag between the traded time and the changes to bid and ask QUANTITY reflected on my comp)

Thanks

## Answer by Matt Wolf (score 4)

https://quant.stackexchange.com/a/3613

It completely depends on your specific strategy model.

Tick data are generally not just trades but changes on the bid and offer as well. You can go a step further and define tick data for stocks as any change in the bid and offer in the whole order book, not just best bid/offer.

Regarding your second question, you can treat trades as simply a field for traded price and traded volume, thats it. Bid/Offer changes you use other fields such as bid price change/offer price change, bid volume change, offer volume change. If you manage the whole order book you would need to manage simply more fields if several order book internals change at the same time stamp.

Generally I advise you to always work off deltas, meaning you just look at changes from previous prices/volume or some use changes from market bid and offer prices. This will shrink the volume you need to deal with significantly. CPU resources are always cheaper than I/O resources.

## Answer by Darren Cook (score 4)

https://quant.stackexchange.com/a/3644

The phrase tick data can be a bit ambiguous (so double-check what you are getting when buying historical data). I would assume that "tick data" only means trade ticks, number 1 in your list. Number 2 would be called "bid/ask data" or "bid/ask ticks". Number 3, mentioned by Freddy, I hear called the order book, or "market depth data".

For your second question, record the time you receive the trade tick notification, and use that time in your model. Then the combined trade/bid/ask data is consistent. (Or use the difference to estimate latency, and subtract that from your bid/ask data timestamps - that has the advantage that it should match the official exchange data, if you need to patch data later.)

Going back to your first question, I'd suggest you build your model on just trade tick data initially. Then when you later add in bid/ask data it will take more CPU (much more data to deal with), but you may get better results. Or you may not. (There is an element of bluff in bid/ask prices, and even more so in market depth data, but a trade tick is real as it means someone has put their money where their mouth is).

Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.