Let’s start with market data. This is any data that you receive from the market typically generated from trades. This is perhaps the most important form of data relevant to quantitative analysis. Market data is temporal in nature, it’s a series of trading events that happen in a moment of time, each moment is called a tick. A ticker contains the time of the event, information about which stock or ticker symbol is traded trade data and quote data. The trade data is the price and the amount of the transaction. The quote data is the price and size of the bid and ask. A bid is request to buy stock at a price for a set amount of shares. A ask is the other side of the trade it’s the request to sell stock at a price for a set amount of shares. In large marketplaces the number of trades can easily hit 200 trades per second. This is a massive amount of data when using historical tech data. Analyzing individual texts may not be visible with this much data. So, we bucket these texts into equally space time integrals such as minutes or days. For each bucket, we can compute open high low close prices and total volume of transactions. This sort of minute or day level data is much easier to work with. You have the ability to ignore the timestamps and treat the data as equally spaced sequences. In some cases, you may still need to use the timestamps. But we’ll save that for another lesson. In the next video, you will learn about another type of finance data called corporate actions.