Generalize or specialize?
The financial sector concentrated in New York and London was hardly the worldwide sector in 2022. Frankfurt, Hong Kong (SVR), Mumbai, Shanghai, Singapore, Tokyo, Toronto – such cities were removed from being the worldwide investment centers that they’re today.
Of course, the differences between finance then and now usually are not just geographical. The financial theories, asset classes, products and technologies that we take with no consideration – the Capital Asset Pricing Model (CAPM), private equity, index funds, online trading, etc. – were still years away in 1947, or at the very least of their infancy. So while specialization was an option, generalization was the order of the day.
The case for specialists
Adam Smith describes the advantages of specializing in . He writes “[t]The greatest improvements in the productive powers of labor and the greater part of skill, dexterity, and judgment” affect “the effects of the division of labor.” labor economists broadly agree with this assessment: specialization will proceed to extend since it is in all of our interests.
Today, global multi-asset managers can put money into a whole bunch, if not hundreds, of (underlying) investment vehicles in a dozen or more asset classes in quite a few countries and markets world wide. Specialization has change into more of a necessity than an option.
If we measure the extent of specialization of skilled investors on a continuum, it was at or near zero within the Forties and Fifties; Most were generalists, and investing was arguably more art than science. As the career has evolved over the past few a long time, skill requirements have also evolved.
In modern finance, most industry roles now involve a point of specialization. Investment professionals are assumed to have expertise in an asset class, industry or region, or otherwise have role-specific knowledge, allowing them to distinguish between, for instance, a European REIT analyst and an Asian emerging market debt portfolio manager.
Over time, as Smith’s division of labor theory predicted, the optimal skill mix in finance has shifted rightward from the zero-specialization end of the continuum. Four aspects within the investment industry have driven this transformation:
1. Internationalization
New markets require more sophisticated knowledge. For example, accessing the onshore renminbi (RMB) bond market requires expertise in local market conventions and dynamics, whether policy orientation or industry and company fundamentals. It also requires the flexibility to speak this data to a world investor base. Such attributes are sometimes difficult to search out.
2. New asset classes and products
Alternative investments are perhaps probably the most significant “new” asset class to emerge within the last 75 years. The endowment model developed by Yale’s longtime chief investment officer David Swensen was key to their rise. His approach included significant allocation to less liquid assets corresponding to private equity, real estate and absolute return strategies.
Here too, an investment team needs targeted expertise to access these assets. For example, private equity investors need to grasp the contract structures and terms in addition to the industries and corporations during which they need to speculate.
This spread of latest products further promotes specialization. Such innovations like Exchange Traded Funds (ETFs) are investor-friendly as they reduce fund management fees and improve liquidity for investors. Others – for instance, collateralized debt obligations (CDOs) – can have been poorly thought out or misused. But whatever their strengths or weaknesses, mastering them requires greater than just the knowledge of a generalist.
3. Industry concentration
The asset management sector has consolidated through the years. This trend will not be going away. The Willis Towers Watson Report 2021 found that the highest 20 asset managers controlled 44% of the industry’s assets under management (AUM), in comparison with just 29% in 1995. As corporations grow, their product lines often expand as well. This requires latest and more developed talent. The size of those corporations also helps provide the resources to support a military of specialists.
The maturity of the fund industry in a market and its total AUM correlate with its level of concentration. The US mutual fund industry is more concentrated than the European one, which is more concentrated than the Asia Pacific region.
4. Quantitative investing
How many began entering the investment career en masse within the Nineteen Eighties. They apply the best mathematical precision to value derivatives, measure and predict risk, and even predict investment returns.
The Black-Scholes model was a harbinger of the quantum revolution. According to Myron Scholes, who developed the model with Fischer Black, quantitative investing requires way more specialized training in math, science and statistics than was the case for economics majors on the time. But whatever the depth of underlying skills, quant investing is hardly a flawless discipline.
In general, the more aspects an investment team has to think about, the more team members with strong expertise might be needed now and in the long run.
The case for generalists
Despite the appeal of specialization, professionals on an investment team must collaborate with teammates and other stakeholders to be effective individually and collectively. There are still many generalists within the investment business who are sometimes an integral a part of the investment process.
Generalists dominate boutiques where extensive skill differentiation will not be an option. While Buffett has built a formidable investment empire, many small investment managers are still sole proprietors. Given today’s costs of running independent investment shops, their number will likely proceed to say no, but some will survive and proceed to offer idiosyncratic value to their investor base.
Of course, those that persevere usually are not “generalists without specialization.” Boutique firms are likely to be unique not directly, which defines their value proposition.
In extreme cases, when specialists in a team don’t work together, generalists need to step in. Our field research on artificial intelligence (AI) projects and large data adoption at financial institutions shows that generalists often coordinate and lead the efforts of investment and data science specialists who’ve completely different educational backgrounds. Encouraging their collaboration could be an infinite challenge. These generalists with investment and data science skills can span either side, making them exceptional value. They are very “special”, even when on this context they’re classified as generalists.
Of course, investment and data science specialists also play a vital role: they’re those doing the work. The generalists make this work easier and shut the gap between their areas of experience. Therefore, each roles are a vital a part of the AI and data science adoption process.
Taking that away
The several types of specialization in today’s investment management industry have quite a lot of implications for whether generalists or specialists are most in demand. To acquire the optimal skills for his or her defined roles on an investment team, investment professionals must understand where their team operates on the specialization spectrum now and where it would operate in the long run.
Academic researchers largely agree with this assessment. For example as Florenta Teodoridis, Michael Bikard and Keyvan Vakili write in: “. . . Generalists appear to be relatively successful as long as the pace of change is not too rapid, but their productivity decreases as the pace of change increases [and] Specialists appear to perform better when the pace of change accelerates.”
However, we place more emphasis on the event phase. In an emerging industry, generalists are in greater demand. The same applies on the subject of the introduction of AI and large data in today’s investments. But as complexity and the pace of change increase over time, the necessity for specialists also increases.
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Photo credit: ©Getty Images/Ryan McVay
