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Quandl and the Alternative Data Revolution

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Alpha, as a measure of active management skills in the fund’s world, gauge the manager’s ability to beat the market. Skills aside, it is also largely related to information sources that the manager uses, such as market news, stock ideas, marketing forecasts, investing strategies, earnings reports, transcripts, and filings.

But thanks to the explosion in Big Data, a whole new world of possibilities is opening up for alpha generation.

According to JP Morgan’s comprehensive May 2017 paper “Big Data and AI Strategies – Machine Learning and Alternative Data Approach to Investing,” about 90% of the data in the world was created in just the previous two years alone. That’s a phenomenal stat!

And it seems that things are only going to heat up. Indeed, the report also projects that the total amount of accumulated data in the digital universe will explode over the next few years, from 4.4 zettabytes (or trillion gigabytes) in late-2015 to an estimated 44 zettabytes by 2020.

With such mind-boggling numbers, it’s fair to say we are experiencing nothing short of a data revolution. And lying firmly at the heart of this revolution is the availability of alternative datasets.

The ‘alternative’ in alternative datasets can effectively refer to anything that is considered non-market data. Whether it’s satellite information that tracks oil shipments, weather data for agricultural commodities or customer feedback that reflects a company’s service performance, alternative data is crucially helping its users gain that ‘informational edge’ that ultimately puts them at an advantage for generating alpha.

But where does one source such data?

That’s where companies like Quandl come in. Founded in 2012, Quandl is now the leading provider of alternative data, which it provides to over 250,000 users worldwide, in addition to conventional financial and economic data. And those users are currently downloading a whopping 10 million Quandl datasets in total every single day.

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“Alternative Data is Untapped Alpha”

Usually, Quandl will procure such datasets either by partnering with a specific “domain expert,” or through the fruits of its own research. It then assesses each dataset for “predictive power, reliability and compliance,” with only the best ones being added to the platform. Finally, those chosen datasets are prepared for sale to clients.

Today, Quandl can boast of having seven of the world’s 10 biggest quant funds and 14 of the 15 largest investment banks among such clients, who can utilize alternative data across a variety of trading strategies, such as statistical arbitrage and global macro trading.

An example of Quandl’s procurement in action can be found in its recently formed partnerships with leading auto insurance providers, which are allowing the company to compile datasets that enable investors to track weekly Tesla sales in real-time, as well as demographic data about Tesla buyers. According to Quandl CEO Tammer Kamel, “Investors are clamoring to know whether Tesla will meet their production targets….Our exclusive partnerships with auto insurance providers power the answer to that question. We want our clients to be the first to know whether or not Tesla is on track to meet its goals.”

And then in April, has partnered with numerous organizations, Quandl launched its very own Corporate Aviation Intelligence (CAI) platform, which provides investors with access to corporate jet flight information. The data covers tens of thousands of private aircraft all over the world that in turn enable clients to determine possible business activity being carried out by corporates, such as M&As, corporate investments, partnerships, and expansions, depending on the destinations to which they are traveling.

Such data is proving crucial to investors, who are now able to gain that investing edge. Signs that a drilling project initiated last year by energy company Apache Corp had failed, for instance, were confirmed through radio signal data that Quandl had managed to obtain and sell to investors. As explained by the Financial Post, “Investors who had purchased Quandl’s data were able to figure that out 10 days before everyone else, allowing them to sell or short the stock ahead of the pack. Apache’s stock price underperformed the S&P Commodity Producers Oil & Gas Exploration & Production Index by 4.3 percent from April 12 to 24”.

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And as acknowledged by Quandl itself, “The biggest opportunity for investors in this decade comes from the signals buried in the data generated by the digital economy. Alternative data is the deepest, least utilized alpha source in the world today.” Mr. Kammel calls this data “the original alpha source, knowing something the market doesn’t know. It’s beautiful…If you can come to them with a genuine information advantage, where they can know something their peers in the market do not know that’s tradable, that’s hugely valuable.”

Useful user tools

One of Quandl’s most appealing features is the wealth of tools that are available for users to conduct detailed data analysis, and that is also compatible with major programming languages:

  1. Financial Data– Quandl also offers conventional market datasets, many of which are free, while others require a subscription. This data comprises stock price history, commodities data, regional market data and much more.
  1. Excel Add-In – this free add-in allows you to pull Quandl datasets directly into an Excel spreadsheet. The company’s YouTube channel provides useful video guides of how this feature works in more detail.
  1. Python– you can pull-in data using Quandl’s Python API. You will have to sign up to obtain the API key which then gives you access to all free datasets.
  1. R– the Quandl R package is free to use and allows access to all free datasets from hundreds of publishers directly into R. Again, a sign-up is required to obtain the API key.
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Quandl is not the only company that’s providing alternative data. On the contrary, a whole raft of firms has now entered this expanding marketplace, such as RS Metrics, while a thriving community has also emerged, comprising of institutional investors and data providers that are committed to supporting the availability of alternative data. The community’s vast database of alternative data providers currently in business underlines just how fast this sector is now expanding.

Of course, it’s no guarantee that alternative data will always be useful to its users. Nevertheless, the capture of data that once hid in plain sight means that money managers now have the opportunity to exploit wholly new types of inputs for alpha generation. And that would strongly imply that a new era is now upon us.

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Justin Chan
Dr Justin Chan founded datadriveninvestor.com, a tech application platform designed to help fund managers, individual investors and data scientists uncover outstanding sources of alpha from data. Previously, he specialized in strategy development in a number of hedge funds and served as a senior quantitative strategist at GMO. An expert in microstructure, market liquidity, and behavioral finance, Dr. Chan holds a doctoral degree from UCLA and served as a finance professor at Singapore Management University. He can be reached at justinchan@datadriveninvestor.com.

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