Perhaps more than any other industry, banking and financial market services must acquire and retain monumental volumes of data that they need to make business-critical decisions, particularly when it comes to trading, where reliable information gives a crucial edge.
Within a data driven world and the possibilities of increased profitability therein, it is not surprising to find that almost half of all companies in this arena are currently evaluating strategies as to how they can successfully exploit data. A recent study by IBM found that 71% of financial businesses considered information and analytics key to creating a competitive advantage.
The potential of data in financial services is immense, but such is the huge volume of data that without the ability to effectively evaluate it, and discard what isn’t relevant, it can be equally suffocating. Much like panning for gold; whilst there may be tiny nuggets of information to be found that can offer valuable advantages to the analyst who knows where to look, there is also a great deal of material which can cloud the vision.
As a consequence, the demand for tools and skillsets that will allow for the efficient analysis of data has never been higher. In fact, research by McKinsey & Co indicates that it may be dramatically understated, and up to 190,000 additional specialists may be needed in the USA alone by 2018.
Measuring Social Sentiment
One of the deepest mines of unstructured, large-scale data is social media, where countless reams of communications are made every day – for instance, there are upwards of 9000 Tweets made every second. Finding patterns and trends in that data, establishing their relevance and learning how to apply it, can be of huge value to a company. A 2010 scientific paper by researchers at Cornell University revealed that tracking sentiment over large-scale Twitter feeds may be able to predict the ups and downs of the Dow Jones Index by upwards of 87% accuracy. Though eventually discredited, the interest it stirred does indicate the seriousness with which finance professionals are considering the impact of social media data.
￼For example, if you are tracking social sentiment across the oil and gas industry, you might want to aggregate keywords for that sector. Then, by removing duplications, sorting Tweets into positive and negative opinion, and applying appropriate weightings dependent on the amount of influence that user has in the Twitter-sphere, could give you a crude idea of the potential trajectory of stocks and funds.
Deriving financial advice from social sources will continue to grow as a topic. Another report, this time by the DVFA, discovered that 53% of European investment professionals (the majority of them German), felt that social media would play an ever-greater role in investment decision-making, whilst a study of affluent American investors made by Cogent Research found that around 70% of them had made investment decisions based on information gleaned from social media.
Traders often need to make decisions within incredibly short time-spans in order to capitalise on opportunities. Their customer base is demanding, operating 24/7 globally. Twitter offers real-time data with an immediacy that few other news outlets, and other platforms, can match. It also brings depth, with coverage from virtually every country, sector of society and industry taking part. This information helpfully condensed into 140 characters, easily absorbed by traders watching a constant stream of messages and developing events.
The trick, however, is interpreting this deluge of information into usable data. It’s not enough just to listen to the conversations that are taking place. Businesses need to be able to understand how what is being said can affect, and benefit them.
As such, there are now many providers within the marketplace that collate vast quantities of social media postings on a daily basis, analyse it and present it to financial services firms tailored to their clients’ operational requirements. Companies can anonymously get the information they need without influencing the conversation. Combined with the more structured data they already possess from other sources, this is another weapon in the armoury for traders seeking to reduce risk and maximise profitability.
Where To From Here
The stock markets have always been driven in part by human emotions, and all kinds of emotion are laid bare on social media for anyone to analyse if they have them time, money and knowledge to do so.
There are abundant possibilities within social data and media for investment professionals in gathering the information they need to make the right decisions at the right time. But it demands the use of credible information providers who know how to interpret the data effectively.
Investment in resources, both human and technological, can bring huge volumes of data down to scale ready for sifting is essential for businesses looking for competitive advantage.
McKinsey & Co
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