As Traders we all need reliable & accurate data to fuel the software package(s) we use to analyse the instruments we trade in. Whether we depend heavily on technical analysis or trade on price alone, or by reference to fundamental analysis, we need to have price & other data to analyse our chosen instruments on our software & then trade them.
The data must fit our chosen time frame. It may be that end of day (EOD) data is what we need. It may be that we need intraday data. Either way the data needs to cover quotes from the exchanges that the instruments we wish to trade are quoted on so that we can analyse their price & trade them.
It is essential that the data feed chosen fits with & is supported by the charting software chosen. It is for example pointless to try to feed intraday data into an EOD package & vice versa.
There are over 180 financial data sources worldwide. These cover more than 1.5M instruments. There are financial markets worldwide. The data flow is enormous & complex.
Data is readily available for the following markets:
 News data
 Fundamental research data
 Economic data
 Price data
The exchanges own data relating to transactions they facilitate. It is available to members & sold to quote vendors (QV) who either resell or package it for others to resell. They collate data from many sources & resell to large institutional clients, online financial portals, resellers & individuals.
Exchange data is not uniformly available at the same level of detail but a higher price secures more content.
 Level 1
The minimum level of detail acceptable for analysis & trading is what is referred to as Level 1 - e.g London Stock Exchange Level 1 content includes: Opening price, mid, best bid and offer, trade high and low, mid price high and low Individual trades Closing prices Prices in real time Order book Volume Weighted Average Price (VWAP), all trades VWAP Cumulative volumes, uncrossing price and volume Daily Official List prices
e.g. London Stock Exchange Level II quote includes: the Market Maker ID (MMID) and time. Bid, bid size, ask, and ask size data display the highest bid or lowest ask quote (Inside Market). signifies the next best quote (1st Outer). the second best quote (2nd Outer). the third best quote (3rd Outer). other data.
The importance of immediacy of data access depends on the trading timeframe. Trades measured in weeks do not require the same immediacy as trades lasting minutes.
There are two main types of delivery:
 End of day (EOD)
This consists of the opening, high, low & closing price along with volume traded for the day.
 Intra day (ID)
ID data may be streamed or available as snapshots. Both types are accessible in real time (RT) or delayed. Certain broker feeds provide what amounts to "virtual" RT streamed data. It is a fast moving series of sampled snapshots of what passes through the exchanges covered. It does not cover all transactions & there is debate over its suitability for analysis purposes.
The importance of the delay (latency) from price quotation to transaction confirmation is proportional to trading timescale. The shorter the time frame, the less is latency tolerable due to its potentially adverse contribution to uncertainty & slippage.
Every processing & distribution system that data interacts with on its journey to & from a traderâ€™s desk adds latency. Every system from the trade matching engine & CPU that the contract is traded on, the Exchange Quote systems, the QVsâ€™ internal systems, the QV global distribution systems, - any hardware or software in the distribution, access or processing systems at any stage of the triple journey from exchange to trader, trader to exchange & exchange to trader â€“ introduces latency. Depending on delivery systems used, data will have been through at least 10 computers before it reaches the trader. The return journey initiating a trade & ending with the trades matching engine will be similar as will the confirmation (fill) journey. Traders should know that the use of separate charting & dealing feeds places them between systems each having separate rules & latency. These advantages/disadvantages must be carefully weighed against trading needs
A trader making many intra day scalping transactions (say in index futures) with multiple contracts should, & is more likely to be, interested in how to minimise latency & spend money on it than someone trading small quantities of stocks over a time frame of weeks.
Data latency increases with number of systems & physical distance travelled. The lowest possible latency data feed would be that provided to a fictitious trader in an Exchange building trading on its internal market data system. This is not realistic or a possible scenario. It is likely that QV feeds will nearly always be slower than Direct Access (DA) but they should show every tick â€“ which broker feeds may not.
Traders must consider their need for low latency data in setting up their systems & weigh its cost when budgeting the costs of doing business. There is more information in the data feed delivery modes section.
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