Conference Report: Quandl

On its second day in Toronto, PolyFinances met with Mr. Michael Cornacchia, Marketing Manager and Mrs Pegah Salbi, Director of Market Data at Quandl. During this meeting, alternative data and their impact on finance were discussed.


Quandl is a young Canadian company that was founded in 2011 and began operations in 2013. It specializes in the distribution of financial databases of all kinds for its clients. The founders of Quandl created the company to allow analysts to access databases quickly, ensuring that they are up to date and especially in a format that allows them to be used as is. In the beginning, the company offered free databases with basic financial data. It was from the end of 2014 that Quandl began offering paid databases (their Premium option) to obtain much more detailed information. The company now offers two categories of databases which are the basic financial data and the alternative data (Quandl, n.d.). Being a database sale and purchasing marketplace, Quandl is fortunate to be the exclusive owner of a few databases that are not available anywhere else than by their platform.

Alternative Data

The emergence of alternative data is the new trend in the field of finance. This mode is not very old and most of this data was unknown just 10 years ago. However, with the emergence of Big Data and the sheer amount of data produced today (if we look at all the data created in the existence of the man from its creation until 2013, 90% of these data was created in 2012-2013 [Science Daily, May 22, 2013]), we have at our disposal an endless collection of data. This data can be used by portfolio managers or hedge funds to obtain a benefit, hence the interest of alternative data in finance.

First Generation (2010-2015)

The first generation of alternative data first focused on sentiments. This is reflected in algorithms that analyze tweets published on Twitter in relation to certain companies. With these algorithms, it is possible to determine whether the public’s opinion of a company is rather positive or rather negative.
To the feelings is added the transactions of customers. Indeed, by having information on the consumption habits of people, it is possible to make more informed decisions. Finally, satellite images are the last of the major categories of alternative data. Images from delivery ports or shopping center parking allow analysts to come to conclusions that are not possible with traditional data.

Second Generation (2015-Today)

The second generation settles on the foundations laid by the first generation by adding various categories. Here are the most notable:

  • B2B transactions (Business to Business)
    • Geolocation
    • Supply chain and logistics
    • Business exhaust
    • Value Added Resellers

The example of business exhaust is very interesting. An example of exhausts would be the waste produced by a company. Indeed, if a company produces much more waste than usual, this can be caused by an increase in production and therefore profits. Knowing this, an investor can invest in the company even before it announces in the next quarterly report that it has increased its production.

Third Generation (Coming Soon)

The third generation is not yet on our doorstep. However, knowing the ever-increasing number of connected objects, the Internet of Things is an avenue that will be very interesting to exploit in the future. Another avenue of data would be the use of drones that could give a wide range of information to their owners (imagery, geolocation, etc.).

Alternative Data benefits

Because of this conference, one thing is clear: The use of massive data will play a key role in the economy and finance of the coming years and portfolio managers and hedge funds should not miss the turn to keep their competitive advantage. However, these alternative data have several disadvantages:

The viability is not guaranteed

Not all alternative databases provide information that is useful for analyzing a company. Considering the ever-increasing volume of data produced, most of this data may be useless for identifying good companies. It will therefore be important to be aware of what data is used and to ensure that it is effective.

High pace of changes

Alternative data as it has been seen, change very quickly. This pace of change presents challenges for investors with a longer investment horizon.


The disadvantage of alternative data is that when the data used is readily available to the public, users lose the competitive advantage of using it, since it must be considered that everyone has the same information. Thus, the return or “alpha” of a particular alternative dataset tends to decay over time.

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