Financial Services Technology - Big Data Streams for Algorithmic Trading

As the markets become more and more competitive, traders are continually looking for a way to get a leg up.  At the same time, there have been rapid advances in financial services technology that allowed increased computation, speed and analysis.  Chief among these technologies is big data and streaming data.  While this catch-all word has many different meanings, Big Data generally means using increased computing power and specialized computing languages to rapidly compute reams of complex data into simple, easily understandable and usable pieces of data.  

The classic example of big data is for use in credit card transactions.  Company managers at super stores like Tesco and John Lewis analyze millions of credit card transactions each day to make real-time decisions about what products to promote and certain pricing decisions.  

In securities trading, the impact of big data and algorithmic trading is much more fundamental.  In the old days stock, bond, commodities and foreign exchange traders would receive calls on the telephone from clients.  The trades would be relayed down to the floor where a physical trade would take place between two brokers.  The spread between a trade was often 1/8 of a dollar per share, even on liquid stocks. 

Today, that has all changed as trades are done automatically by computers.  The spread between trades is now around a penny which means the stock brokerage business is much less profitable.  Instead, brokers are forced to take much riskier trading positions on stocks in order to make a profit.

However, algorithmic traders can provide market liquidity as a kind of independent broker.  While they may only make tenths of a penny per share in income, trading volumes of millions of shares a day amount to sizable profits.  These traders utilize the power of big data to analyze trading in the market and rapidly adjust to take advantage of the infinitesimal movements.

Traders use Big Data streaming technology on servers located directly at the Nasdaq, New York Stock Exchange or other markets.  The traders develop sophisticated proprietary algorithms that analyze the market and with every new data point, send a new trading signal with extremely rapid low-level execution orders that are entered in milliseconds.  

For example, a trader might use a big data program to detect when large block orders are entered into a market.  Anticipating that a large Buy order in a certain stock will drive the price up, the program will instantly instruct the company to buy shares of that stock as it rises which results in a profitable trade.  The block trade benefits from more liquidity in the market with the slight drawback of slightly higher price than they would otherwise get (which over time is negligible and still a better price than they would receive in years past).  

51zero are one of the premier experts in big data programming and consulting.  The team has experience in a wide array of big data services, especially for the financial services industry.  For more information, please contact us.  Our friendly consultants will be sure to explain our process and how we can best help you.