Trading volume for U.S. listed options totaled about 4.55 billion contracts in 2011 while OPRA’s message volume has been steadily increasing at an annual rate around 40%. To say that the options market is all about Big Data is like noting that Mount Everest is all about snow. It states the obvious but also the ominous. On a human scale, you cannot consume or make sense of what’s inside that avalanche of data without the right technology and analysis any more than you can climb to Everest’s peak without the right gear. Big Data is the core, Big Data is the catalyst.
US equity options volume is expected to double over the next 12 months. Increased demand is a big driver of growth but the expected acceleration is due to a number of factors. Two such drivers are the advent of new products and new venues such as the CBOE’s all-electronic C2 Options Exchange which saw a steady 18% year over year growth.
Another booming area is the CBOE’s short-expiration Weekly options products on more than 30 different classes of the most active stocks, indexes and ETFs. These products with rapidly changing deltas can move in the money with short notice causing their trade volume to spike dramatically. Volume on those Weekly’s accounted for up to 11% of their underlying index volume in the second half of 2011.
VIX-based options have also been a big hit, with a total of 8.5 million VIX options contracts traded in June. The CBOE SKEW Index measuring the S&P 500 out-of-the-money options spiked in early spring 2011 highlighting a greater demand for these outliers. And of course the increased growth is due to more and more strikes in all underlying assets.
The use and proliferation of options has seen explosive growth as a strategic investment tool for more sophisticated hedging, portfolio management and for additional leverage on the performance of the underlier.
The incredible growth of the options market is undeniable. Today’s options market represents the quintessential example of Big Data in Finance. Big Data is a trendy new catch phrase in business today, but nailing down an exact definition proves to be rather elusive. This is likely because the term has largely been associated with loosely structured content, originating from web search companies and social media. For the financial industry, the need for reliability and accuracy is what distinguishes social Big Data from financial Big Data.
Gleaning meaningful value from unstructured and social content is to judge sentiment, the mood of the human psyche portraying an emotion from the voices of millions. Any one or group of data points in the analysis cannot necessarily be valued as accurate or inaccurate only the determinants in behaviors. Any loss is of minor importance because analysis is looking for mood shifts on the order of a turning ocean liner. In fact, the science of social data involves not what to keep, but what to throw away.
In finance, data accuracy is vital to determining outcomes. Asset prices cannot be inaccurate or missing and they must be adjusted for any corporate actions such as stock splits. The reliability of resulting analytics such as implied volatility, delta and gamma calculations for option strategies and portfolio re-balancing depend on them.
The infrastructure technology for the options market has also become specialized to cope with the fire hose volumes and very large capacity storage of Big Data. As we see more volume and market data flow across the OPRA feeds, we can expect that additional flow will lead to greater message traffic entering the market place as orders and executions. The increased throughput will burden older technology in an attempt to handle the load. Firms will realize it is not simply a matter of buying new versions of old technology to keep up with the problems of throughput.
I’ve occasionally heard the comment that the open source platform Hadoop defines Big Data. To say that any technology defines Big Data is an obvious case of the tail wagging the dog. It’s the demands around industry use cases that create and foster technological innovation. That’s what drove the creation of Hadoop. Hadoop is a nascent technology that resulted from the desire to obtain analytical value from the vast amount of social data. It is not optimal for the volumes and speeds of high frequency financial data.
For the algorithmic world, direct exchange feeds for Options are becoming more desirable for their depth of book and lower latency along with greater use of real-time analytics. Option premiums are manufactured from two main ingredients: intrinsic and time value and the measure of how much money we should make factoring in the implied volatility. The Weekly’s short-expiration implies option strategies can respond to news announcements such as an earnings report in a make or break fashion. The underliers reaction to the news can signal an immediate move to take a profit or stop a loss. Big Data analytics is a defining characteristic of options market data and the wealth of analysis far exceeds all other asset classes.
Big Data will become de facto terminology in the coming year. Understanding its definition for finance is vitally important since the explosive growth of the options market is likely to continue unabated.
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