Finding patterns in data sets

Background Info: There is a game called Roblox. It has two virtual currencies, Robux and Tickets. People can exchange them for each other, but their exchange rates vary based on how much people want for each currency. Essentially it is a virtual economy. I have made a program that records the exchange rate data every 5 minutes, so that means that there are 288 points of data every day.

Objective: So here is the Robux rate data and here is the Tickets rate data. Every 288 data points on both data sets marks 1 day (because it is recorded every 5 minutes). Basically, I want to see if each day's data in either data set has a pattern. I think there will be a pattern because people will exchange less during night, meaning the rates are less-competitive and will possible drop.

Why: The basic idea behind profiting on the market is to get Tickets at a high rate and Robux at a low rate. So if I find that each day, there seems to be higher rates of Tickets at 1:00PM, then I will trade my Robux for Tickets (Which will multiply). Then if there seems to be lower rates of Robux at 1:00AM, then I will trade my Tickets back into Robux (Which will divide).

So is there some algorithm I can use to find patterns in several data sets? Then use that pattern data to find expected rates for the next day?