Finance has always relied heavily on data. Earnings statements, forecasting, and portfolio management are just some of the areas that make use of data to quantify their decisions. Because of this, financial data analysis and its related field, financial engineering, are extremely broad fields that are difficult to summarize in a short amount of space.
However, lately, quantitative finance, high-frequency trading, and similar fields have gotten a lot of press and really come into their own. As I mentioned, some people hate them and the added volatility that the markets seem to have. Others maintain that they bring the necessary liquidity that helps the market function better.
All of these fields apply statistical or machine learning methods to financial data. Some of these techniques can be quite simple. Others are more sophisticated. Some of these analyses are used to inform a human analyst or manager to make better financial decisions. Others are used...
