In this research note, I share elements of the complexity of the asset manager selection process and look into whether Fintechs have developed tools to improve this process.
Last September marked the 40yr anniversary of the first index mutual fund created by whom else other than Vanguard. Even though its initial reception was not successful, this first mover fund, which began with $11million, has grown today to be the Vanguard 500 Index Fund with $400+ billion AUM! This was a structure referred to as “Bogle’s Folly” at its launch.
The entire US industry of index funds has now grown to $4 trillions.
At the same time, we have the birth and evolution of the ETF industry which is 20yrs old. That also had a couple of faulty starts before a successful product launched was achieved (see, a Brief history of EFTs). Today it accounts for roughly $2.5trillions. From which only $377billion of ETFs are index fund types and the rest, close to $2trillion, are “smart beta” types.
Despite the exponential growth of these passive-indexing investment vehicles, Investment Managers still have a function in the asset management industry. The growth in indexing is not only seen in the increase in AUM but also in an increase in the market share of indexing vehicles. Morningstar reports stunning statistics showing that in the last ten years, the market share of assets shifting to indexing has doubled!!
The rest of the market still operates with a large focus on investment manager selection. Each investment management firm has a secret sauce on how to select, retain, support, and manage, their in-house asset managers.
Manager selection especially for large institutional asset owners, remains a sophisticated multi-dimensional task. It has tangible and measurable components and equally important intangible and qualitative factors to consider.
Tangible elements:
- Investment philosophy and process
- Portfolio construction methodology
- Risk management methodology
- Performance
Intangible elements:
- Agency problems
- Adapting to new asset classes
- Partnership issues
- Malfeasance risks
There is extensive literature in the theoretical and practical front that covers these issues. The CFA institute and AIMA (focused on alternative investments), to name a few, have extensive research and empirical studies on the topic.
The wider adaptation of alternative assets classes has made the process more complex. The increased transparency of markets and more so the increased correlation between geographies and asset classes, has sometimes induced managers to drift from their initial investment philosophy. Risk management processes have also become more important and stringent, as regulatory guidelines fence activities and will be looking to daily reporting.
Benchmarking performance and gaging the trade-offs between underperformance and long term investing; remains an issue.
The questions arising about whether the manager is acting in the best interest of the investors and or the GP or LP of the fund structure; are essential. Capturing malpractices remains a nightmare.
Fintechs haven’t alleviated any of the issues related to investment manager selection for large asset owners.
Essentia Analytics, is a Fintech that tackles one facet of the complex investment manager selection process by providing a feedback loop for fund managers. It uses big data analytics from the asset manager himself and provides actionable insights in what needs to be changed. It is detecting behavioral biases, increasing self-awareness and determining actionable adjustment to the investment decision making process.
I have been looking for Fintechs that can provide real time Drift monitoring of managers: calculating Drift from their investment philosophy and their risk management parameters.
Normann is a company that focuses on the behavioral bias of active traders, the so-called myopic loss aversion, that results in irrational behavior and the “anomaly” of the equity premium puzzle. Normann has partnered with Chancery Lane Traders (proprietary trading FX) to screen traders and offer them risk management make-up services and then allocate capital to them.
Few Fintech startups found focusing in the area of investment manager selection. At the same time. there has been an additional layer of novelty and complexity added to the pool of Investment managers. The Fintech revolution has concentrated on nurturing new managers out of the crowd.
New micro-managers are emerging from different platforms:
- Copy and mirror trading platforms like eToro, Zulu Trade, Darwinex.
- Thematic investing marketplaces that allow new micro-managers to emerge by creating their own financial product (equity based), and actively manage it; like Motif Investing, and Wikifolios,
- Even social research platforms like StockTwits are stepping into this space by offering Follow functions and rankings of the subscriber micro-managers.
These emerging micro-managers are not of course into indexing; they are targeting the smart beta or alpha generation space. Their audience has been mostly retail. Social trading Guru, has been aggregating and ranking such FX micro-managers from the first group of social trading platforms.
The asset manager selection process remains complex and cherry picking from the professional pool remains the focus and challenge of asset management firms. Looking for more Fintechs that focus on facilitating this process. Artificial intelligence will clearly be the tool that can create a comprehensive profile of an investment manager and at the same time, through a comprehensive feedback loop improve his-her biases. For now, Fintechs have overlaid novelties and created new complexities by opening up the space to the new micro-managers sourced from the crowd with investment processes and biases are yet to be evaluated.