The potential uses for big data are infinite it seems and this goes for theRead More
Big data allows qualitative factors in investment management to be quantified
The potential uses for big data are infinite it seems and this goes for the investment management industry as much as any other area. A new report shows that factors that were traditionally considered qualitative can now be quantified through this very handy new area of expertise.
Big Data & Investment Management: The Potential To Quantify Traditionally Qualitative Factors, which has been produced by Citi Business Advisory Services does what it says on the tin. Potential is the most important word here, as so far investment managers have not embraced big data wholeheartedly, but that could all be about to change.
It is something that every investment manager in the land should be clambering to address, as it could give them a competitive advantage. Having an information edge could put them ahead of those using traditional analytic techniques, reports Value Walk.
There are two main reasons for this: big data raises the amount of data that can be included in investment models; and improves the speed at which the data can be processed. Both of these elements could be particularly vital for investment managers moving forward.
If a third persuasive argument was to be added, it would be the fact that the variety of data that can be analysed has come on leaps and bounds in recent years. This is as a direct result of the growth of the internet; the advancement of social media; and the new Internet of Things, which can provide sensory readouts of physical objects.
In the process of additional content sources being developed, a certain amount of datafication has occurred. If this is a word you have not yet come across – and why should you, as it’s a fairly new addition to the vocabulary of the subject – consulting the report may help. It defines this term as “the ability to render into data many aspects of the world that have never been quantified before”.
With larger amounts of data, its increased variation and the speed at which it can be analysed all improving, an acceleration in systematic trading models innovation is expected. Things are likely to move on far quicker than they have at any time in the last ten years. At the same time, the quantitative investment space is braced to see similar steps forward, as the gap between traditional quantitative norms and modern qualitative research becomes smaller.
While a number of firms were surveyed in the making of the report, several pointed out that some of these changes remain purely aspirational at present. There are a number of obstacles that are getting in the way of big data adoption for investment managers, but should these be overcome, the future could certainly look bright.