Sentiment analysis in particular has quickly gained supporters in financial services and beyond over the past 12 months. The USP of the sentiment analysis approach is that it can take unstructured or subjective data from a vast myriad of online sources and sift, sort, extract and quantify insights from this mass of data based on specific objectives and search criteria.
Importantly, AI-driven sentiment analysis can in a practical sense determine the emotional tone within a textual source, and as such can be used to gain a much more detailed understanding of the attitudes, opinions and emotions involved. How and why are increasing numbers of UK firms using sentiment analysis to innovate in financial services?
The recent showdown between retail traders organising via Reddit pages and hedge funds has provided a visceral reminder of the potential for extreme volatility latent in certain corners of the US equities market. The two main factors explaining the dizzying ride GameStop’s share price went on were the growing popularity of retail day trading – in part a function of the arrival of low-cost online brokerage platforms such as Robinhood and eToro – and the sheer depth and liquidity of the US’s capital markets.
However, it is also important to point out that a certain ‘sports betting’ culture, often merging with a sort of loose anti-establishment sentiment, further fuelled the buying frenzy that saw the market cap of a moribund company temporarily spiral upwards to absurd levels, many multiples ahead of what reality justified.
Whilst it would be difficult (but certainly not impossible) to imagine a similarly irrational yet coordinated mania erupting on the same scale in UK or European equities, the incident has underlined the extreme importance of subjective online data for understanding market movements. In fact, the growing divorce between company fundamentals and stock performance has reached such highs that the hoary old debate over active versus passive investment management has received a new lease of life.
Carson Block, founder of infamous short seller Muddy Waters Capital, has recently argued that the ‘stonks’ phenomenon provides definitive evidence of the superiority of the active approach, citing ETFs buying and selling on autopilot as an exacerbating factor in the recent volatility.
Data, data everywhere…
There is a sense of fighting the inevitable in Block’s claims, and the rout of passive funds over their active counterparts is in all likelihood set to continue in 2021. But he is right to point to the profound shift that is taking place in terms of what data matters for financial markets.
Even just a few months ago, few financial commentators would have believed that non-professional traders swapping tips back and forth on an online forum would amount to anything substantial enough to cause a price swing such as occurred with GameStop. And whilst there is still no effective challenger for the awesome functionality of the Bloomberg terminal, the rise in significance of what could be termed ‘alternative’ sources of data used by retail traders simply cannot be ignored.
The expansion in the quantity of online notice boards, data providers, research aggregators, chat forums, and all manner of other digital communal spaces has meant the amount of data that could be of relevance to understanding market movements is now bigger than ever before. All of this represents additional data on top of the company balance sheets, press releases, research notes, forward P/E ratios, and so on that traders have always relied upon to make decisions. As such, data is becoming ever more dispersed and diverse, and access to and correct evaluation of these flows of information has never been more important.