Tag Archives: arbitrage

Big Data and Finance, Speed versus Insight

Published: February 26, 2014

By: Kevin Coogan

Big Data will revolutionize finance and investing. Nearly all investors will, at some point, begin to take advantage of the benefits it provides. Some, however, will leverage Big Data to focus on the speed at which information is gathered and understood, while others will prefer focus on deep comprehension and new insight based on this tidal wave of data.

The importance of getting information faster than others in the market has been a staple in the financial community, since… well… forever. Obtaining a piece of knowledge a little ahead of others allows an investor to get in to or out of market positions before the relevant knowledge impacts general pricing. Entire communication systems have been and deployed, and untold amounts of money have been invested for this purpose. Each wave of innovation in communication systems leads to the inevitable rush to slice some time off of financial relays.

Big Data and its related technologies allow for increases in the speed of communication and the dissemination of information. It, therefore, is the current embodiment of the long-term financial market trend of leveraging advancements in communications to gain information just ever so marginally faster. The best example at present is how social media is being used to displace, or at least buttress, traditional financial news. This is because, in many instances, the millions of everyday people using Twitter will be able to provide information about an event faster than a few thousand professional financial journalists. Traders have discovered that they can receive information nuggets many times faster through something like Twitter than through news channels. The underlying theme in speed-based approaches to Big Data is, “Get me the same information I already like using, just do it faster. I know how to use it and interpret it, as does the rest of the market, so any time gained will be a huge advantage.”

Gaining improved insight though Big Data is just as valuable, albeit less straightforward, than gaining a speed advantage. One of the issues associated with this ‘insight’ approach is that, historically, new forms and types of information must create whole new forms of analysis through which insight can then be gained. For instance, advanced technical analysis of stock trends only became possible when stock price historical records had been kept for a considerable amount of time. Similarly, discounted cashflow analysis only became possible with the advent of reliable accounting information. Finally, macro analysis was only devised through the standardization and availability of macroeconomic data. Arguably, each of these thoroughly different analysis techniques is a cornerstone for much of the investment analysis that currently takes place. It is difficult to envision investing without them. With all of this in mind, it is not unrealistic to imagine that the insights that Big Data analysis provides will become a new type of financial cornerstone in the near future.

A more recent phenomenon, high frequency trading, is also a product of changes in the availability and speed of information. New shorter term tick data, new higher powered computers, and faster, more reliable delivery of automated trades made high frequency trading a reality.

What is next for finance now that data is ubiquitous? If the government’s aggregation of national unemployment, inflation, and other forms of data can revolutionize economic analysis, and if standardizing and regulating quarterly accounting standards and information transparency can revolutionize fundamental analysis, how much more powerful will the transformation of financial analysis be due to the advent of total data?

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