Data
In our example, we will use the Russian stock market prices from the period of 2015-2016, which are placed in Chapter08/data/ch08-small-quotes.tgz and have to be unpacked before model training.
Inside the archive, we have CSV files with M1 bars, which means that every row in each CSV file corresponds to a single minute in time, and price movement during that minute is captured with four prices: open, high, low, and close. Here, an open price is the price at the beginning of the minute, high is the maximum price during the interval, low is the minimum price, and the close price is the last price of the minute time interval. Every minute interval is called a bar and allows us to have an idea of price movement within the interval. For example, in the YNDX_160101_161231.csv file (which has Yandex company stocks for 2016), we have 130k lines in this form:
<DATE>,<TIME>,<OPEN>,<HIGH>,<LOW>,<CLOSE>,<VOL>
20160104,100100,1148.9,1148.9,1148...
