Big Data in the Face-paced World of Finance

In 1998 the SEC began to allow online trading of financials securities. It took traders very little time to realize that data, and lots of it, was going to be absolutely essential to making money. Some firms realized that a tiny advantage in data, be it in speed of transfer or quality of data, could lead to huge increases in profits and revenue. Thus began high-speed and algorithmic trading.

Today the market runs on big data. There are a couple of ways it is involved, and all of them have the potential to make or lose trillions of dollars.

Algorithms

The first way big data is involved in the financial industry is via algorithmic trading. This is where computer programs take all available data for a specific stock or market and sift through that data to determine good times to buy and sell as well as good securities to buy and sell. If the program can identify a pattern, that pattern can be exploited and a lot of money can be made.

When it comes to algorithmic trading, the more data the better. Patterns can be found scattered throughout data, and most algorithms will look for multiple patterns that point to a good purchase. The more data available, the more patterns that can be identified and examined. All a firm needs is a small data advantage over a competing firm and that can be exploited thousands of times a day to make huge profits.

The Three Vs

The three Vs of big data (volume, variety, and velocity) have major application in the financial industry.

The volume of data available has exploded in recent years. Institutions are left with huge amounts of data to parse through and decide what is relevant and can affect a securities price, and what has no relevance and can be ignored. Institutions that can access more data tend to be able to make higher returns.

Variety is also exploding in financial data. Some stock brokers are offering things like social signals, where their algorithms sort through thousands of mentions about a particular security, analyze the words, and build a general sentiment for that security. Here are some of the different kinds of data options different brokers are now offering.

Velocity is becoming huge as well. Some brokers are building their entire strategy around making trades just a tiny bit (milliseconds) faster than their competition. There is an entire industry built around this practice, also known as high-frequency trading. Traders that can access stock prices just a hair before other brokers can sneak in, purchase shares at a lower price than the current asking price, and then sell just as quickly to the user that is willing to pay a slightly higher price. Do this a thousand times a day and profits can rack up quickly.

The reason big data is pushing growth so hard in the finance sphere is likely the money that can be made. Just a few advantages can bring huge rewards. Who knows what the coming years will bring, but one can be sure progress will continue.