Equity Research jobs are now Tougher Than Ever: it’s Time To Work Smarter
It’s 3 years since I examined similarities between the imminent GDPR and MIFID, or to give its full name Markets In Financial Instruments Directive (II). These sweeping regulations tackle two huge, increasingly convergent industries — financial markets and personal data.
What’s been the impact of this ‘double whammy’? The results are starting to come in and tell different stories. On one hand, GDPR has been a watershed in terms of corporate awareness but even legislators now admit benefits have been slow to reach consumers.
Meanwhile, MIFID has not unleashed the harmful industry effects many feared, and its shakeup of established practices signposts opportunities for startups to add automation and productivity wins not seen for decades.
First, let’s look at those similarities: both were political and economic in nature, driven by the desire to create a European powerhouse to rival the US, and a level playing field for new, smaller entrants.
With GDPR, geographic location is no protection if you trade in the data of European citizens (plus the UK). Similarly, if a fund manager wants to buy anything with an underlying product listed in the EU, then it falls in MIFID’s scope.
For both regimes, transparency and audit are central to revealing the hidden costs of services. The aspect of MIFID I want to cover is how asset managers pay for research (analyst notes, reports, calls) they use to make investment decisions.
Research unbundling provisions in MIFID aim to reduce potential conflicts of interest for those investment firms offering both execution and research services. They also address a related risk of producing excessive amounts of low-quality research manifested as multiple pieces all providing similar recommendations, and poor forecasting.
Market participants, frequently quoting survey data claim that since MIFID, the total amount of research produced has fallen, there are fewer analysts producing reports on companies and the quality has worsened. They also identified the possibility that unbundling disproportionately affected smaller market players, the very opposite of what MIFID hoped to achieve.
Damning stuff. But this interpretation is under fire with the publication of more empirical information from ESMA, the EU’s securities markets regulator, as part of their second report on Trends, Risks & Vulnerabilities.
The study shows a reduction in the overall volume of research output across the industry, and absolute numbers of analysts covering a firm, but this has been modest (0.2- 0.6 fewer analysts/firm) and affecting coverage of larger, older and more ‘predictable’ companies.
Combined with a trend to consistent and in some cases improved forecast accuracy, this suggests a previous overproduction of research in some (large cap) sectors already identified in previous studies:
“well over 40,000 research notes — from comprehensive reports to minor updates linked to corporate announcements — are sent out every week by the top 15 global investment banks, of which less than 5% are opened” (Kwan and Quinlan. 2017)
Counter to the doomsayers, it seems this reduction is part of a trend since the last economic crisis, and that MIFID’s unbundling of research is enabling investment firms (and their clients) to have clarity on the cost vs benefit when assessing whether research is useful to them, hence the focus on smaller-cap players.
Having access to so much research and information in the time before MIFID and GDPR didn’t usually equal better results for either professional investors or personal data buyers. So how do we achieve more now, with less?
One Senior Analyst I spoke with summed up the problem:
“I spend 75% of my time extracting the same information to assemble derivative reports, daily, weekly, monthly. We can’t outsource this effectively as you need to know what to look for, and understand what it means…”
The solution is better tech. Personal productivity tools tailored to the sector like those released in the first wave of investment data automation are needed to manage the sheer volume of linguistic information analysts must cope with.
New developments in User Experience, Augmented Intelligence and Sentiment Analysis can free analysts from drudge work, to focus on their value-added skills and operate at a higher level while maintaining output.
I’ve seen first-hand how blockchain technologies like smart contracts and machine-to-machine transactions exploded when given purpose through the movement of DeFi — Decentralised Finance.
In the face of this new competition, financial institutions are looking for ways to employ automation, focus on their key, human strengths and remain relevant to a younger demographic of customers.
Before the Bloomberg terminal, Foreign Exchange traders had to negotiate deals over the ‘phone — one dealer at a time. Today, sitting on the desk of 325,000, the terminal has become an instantly recognised icon of the financial markets.
Now the legal framework with MIFID is in place, new productivity tools for research have every opportunity to reach as big an addressable market in the next three years as that for personal terminals which Mike Bloomberg & Merrill Lynch identified back in 1981.
