Venture capital companies have to work through a lot of confusion when it comes to allocating capital to Investment Management Fintechs. It’s natural because Active Investment Management itself is facing an upheaval when it comes to fees, increases in compliance, financial theory redundancies [1], and foremost, the lack of Alpha. A Venture firm can’t be expected to be well versed with the reality on the ground. Venture is a difficult business with extreme underlying volatility. The industry has to rely on insights, serendipity, a positive economic environment, and numerous allocations to overcome the failures because understanding the evolution of new technologies and industry trends is hard to anticipate. Above that, the weights and allocations to various startups are a function of valuation, size of the round, and a host of other factors. This creates an uncontrollable idiosyncratic bias. In many ways Venture allocations in investment management fintechs create more concentration risk than the one embedded in S&P500 or Berkshire Hathaway [2]. Venturing into the investment management space assumes double complexity, one that comes with the Venture business and the other that is intrinsic to the investment management domain.
This is why it is essential for Venture to make more effort to understand the investment management landscape. Modern finance has been on the job much before the initial work in the 1960s on CAPM [3] and has failed to deliver Alpha and beat the S&P 500 despite more than 6 Nobel Prize Laureates [4]. Paul Samuelson [5] wrote about the underperformance vs. S&P 500 back in 1974. Without the knowledge of this background, Venture is ill-equipped to understand the ecosystem of investment management fintechs today. Knowledge of the respective background offers Venture a good screening test to understand the level of awareness of an investment management fintech about the industry’s legacy challenges.
Domain knowledge and know-how are hard to acquire and finding founders who can look beyond domain knowledge into shortcomings and inefficiencies in the domain needs both insight and openness. To succeed in this search Venture needs more serious conversations and preparation, otherwise, it’s just another dead weight allocation they are adding to their portfolio, which might give them an exit but not create the desired industry disruption.
Incomplete perspectives lead to the perpetuation of many of the following false beliefs and myths.
Myth 1: S&P 500 Is Unbeatable.
There is not one but many ways to beat the S&P 500. An open method is to rank 90 days of the relative price performance of the respective 500 stocks, overweight the top and bottom quintile and underweight the rest. More than 82% of non-rebalanced portfolios for 1,2 and 3 years for any starting point beat the S&P500. This is the AlphaBlock Open Indexing Method showcased on our Sandbox on GitHub [6]. Till the time one can refute these numbers or find a bug in them, it’s safe to assume S&P 500 is beatable.
Fig. 1 – A summary of ~ 2000 portfolios built on 500 S&P 500 stocks, where the top and bottom quintile are overweighted and the rest is underweighted. 82.59% of all the data lies in the positive quadrants [Q1 and Q2] with excess returns above the S&P500.
Myth 2: There Is No Alpha Denial
Both asset owners [Pension funds, Endowments, Sovereign Funds, Foundations, Family offices] and asset managers as a group are in Alpha denial. Because if they would believe that Alpha can be harnessed, asset owners would demand it and never pay a fee for underperformance. And asset managers would do something about their falling reputation and take steps as a group to stop the asset exodus from Passive [Indexing Solutions] to Active. In the not-so-distant future Index funds will take over the fee-charging asset management business and that is because asset managers are straitjacketed because of one difficult predicament.
They cannot move away from concentration as the stock selection is their primary business and using a Smart Beta Index for building a portfolio process, may not require fundamental information, just a set of quantitative rules, that are not idiosyncratic but systematic and automated. In such a mechanical world, asset management without a desire to adapt quantitative processes might see itself becoming isolated and marginalized.
Asset owners are already moving to Passive solutions, and openness to adopting quantitative Smart Beta systems will increase the rift between new generation asset owners and legacy asset managers. We are beginning the exponential stage of this trend.
Myth 3: Investors Understand Alpha
If asset managers need assistance, what chance does an investor on the street have to comprehend Alpha? Investors need education and empowerment before they can measure an asset manager's skill and the commensurate fees that should be paid for the same. Till then they are either going to buy Passive solutions or get naively attracted to the exuberant thematic performance, which will first rise and then fall, consequently destroying wealth.
Myth 4: Crowdsourcing Can Deliver Alpha
Now with this background, Venture money should ask the following questions. If Asset Managers can’t defend their turf and Investors need more education, how can a group of lay investors get together in a room and suddenly enlighten themselves with Alpha? Let’s say some magic happens and the madness of crowds transforms into momentary genius. How sustainable are such flashes? And if they were, shouldn’t crowdsourcing have taken over the world and resolved the Alpha problem? The truth is that lay investors are impressionable, and start-ups can sell the crowdsourcing magic, to some of the investors, all of the time. Gathering a million investors in a room to sell them performance is always going to be easier than helping 100,000 investors to make educated and informed decisions. This is why there is a lot to learn from failures like Quirky, GoldCorp, and even BP.[7]
Myth 5: Finance Is Not A Physics Problem
No wall separates Physics from Finance. Robert Brown discovered the Brownian motion before it was used in Finance. The Fluid Dynamics work of Joseph Valentin Boussinesq [8] inspired Louis Bachelier to write the foundation of modern finance [9]. History is replete with research on mechanisms of psychology [10] which can explain the conflicts and concepts like Kahneman’s stranger, Maxwell’s demon, and conflicts of our inefficiently-efficient markets. Finance may wishfully want to operate as an island, wanting nothing to do with Science and philosophy. Physics has the answers to many problems in Finance and Economics, no wonder Herbert Simon, the Father of AI and behavioral finance was focused on complexity and mechanisms.[11]
Myth 6: Active Is Dead
Berkshire Hathaway is not going out of business and neither are a host of other asset managers who have unique mandates and know how to generate absolute returns, even if they can’t generate alpha all the time. An asset manager can be Active with a quantitative automated Smart Beta process and be like an underlying index with low tracking error, low turnover, and Passive character but still have high Active Shares [A metric for Activeness]. This allows him to not only show difference vs. the underlying index but also be less concentrated unlike the index, while still holding all the components of the index. There are numerous ways for Active to thrive and be paid for Alpha.
Myth 8: Passive Is The Only Business
Unlike popular belief, Passive is falling apart because it is inefficient. Passive on average charges 30 basis points and trails the benchmark by 50 basis points on average over 10 years. So Passive in real terms is not matching performance with the benchmark, it is trailing the benchmark. When Machines take over, which they invariably will, because they are light, lean, replicating, incremental, and automated, the big Passive players like Vanguard might find it hard to defend their 30 bp moats and Indexing companies like S&P DJ Indices may find it hard to enforce a single bp fee from asset managers. You may want to read about Vanguard’s push into the Active business. The Investment management fintechs are not nibbling into the big Passive pie, they are taking big bites, driving the new DIY [Do It Yourself] segment. How did you think Direct Indexing became an overnight $ 350 billion industry? [12] And when you connect asset owners, into a zero management fee, zero advisory fees, and zero transaction fees through an app, you are not only creating the next generation of asset management that knows how to scale by charging for Alpha, but it is also aware of the size it can reach.
Myth 9: Concentration Is Not A Risk
Both Passive and Active, investment management is a concentration contest. SPY’s size-weighted method concentrates 30% of the weight on 2% of the stocks [10 out of 500]. Active managers can charge a fee only if they are differentiated from the markets. This forces them to become stock selectors. The effort and resources spent in identifying ideas, naturally lead to concentration. The overweighting, game of intuition [amplification] works till it eventually fails, either as a crash or as a drag on performance. Concentration is the biggest risk in markets today and fintechs that comprehend this aspect are better suited to benefit from the machine investing revolution as they are focussed on extracting more Alpha per unit of risk while avoiding concentration risk.
Fig. 2 – Both Active and Passive carry concentration risk. SPY [S&P 500 ETF], BRK [Berkshire Hathaway], and FGT [Finsbury Growth and Investment Trust] are extremely concentrated.
Myth 10: Open Problems Can’t Have Open Solutions
Open problems having open solutions can seem mystical but it’s the reality of nature, which does not hide, what it does, and how it does. Even then, we find it so hard to replicate its process. The problem of Alpha has an open solution, which even when out there won’t eliminate inefficiency or allow the Free Lunch Alpha to be arbitraged away because as human beings we are trapped in our causal explanations. We can only relate to the conspicuous and the obvious, not to implicit and invisible. We live in an informational causal world and this is why markets will always remain inefficient because humans will interpret the information differently at different times. This is why both markets and nature will always remain open but still complex. This is why even if there was an open solution for masses to generate Alpha [Myth 1], it won’t get arbitraged away, just because its causal explanation is mathematical not News.
The Legacy VS. The DIY Fintech
Fig. 3 – The old and new DIY investment management model driven by just Fee on Alpha.
Fig. 4 - The range of lowest and highest annual fees charged as Expense Ration, Advisory Fees and Brokerage Fees. BIZD ETF is one of the highest expense ratio at 10.92%. We are not taking Layers Fee in consideration.
Fig. 5 - Even the lowest fee scenario is designed to trail and underperform the market. The highest fee worst case scenario can decimate wealth over a period of 10 years. We have assumed an annualized 4% return for a 10 year bull market and a negative annualized 1% for a 10 year bear market return.
Classification Of Fintechs
Advisors – e.g. Betterment
Crowd Sourcing Asset Managers – e.g. Delphia, Numerai
Layers – e.g. Composer
Open Indexing + Layer – e.g. AlphaBlock
Quadrant Analysis Of Broad Market Participants
Fig. 6 – The current Passive is not Passive but concentrated and behaves more like Active. An Open Indexing solution can reduce the concentration while keeping tracking error low. Both legacy and active managers are concentrated, with high tracking errors and opaque machine learning methods.
Bibliography
[1] Kovarsky. P, “Fabozzi: Finance Must Modernize or Face Irrelevancy”, CFA Institute, 2019
[2] Pal. M, “Warren, SPY, Machines, and the Concentration Risk!”. AlphaBlock
[3] Fischer. B, Jensen. M, Scholes. M, “Capital Asset Pricing Model”, Studies in the Theory of Capital Markets. New York, 1972
[4] Harry Markowitz [1990], William Sharpe [1990], Daniel Kahneman [2002], Robert Shiller [2013], Eugene Fama [2013], Richard Thaler [2017]
[5] Samuelson. P, “Challenge to judgment”, The Journal of Portfolio Management Fall 1974
[6] AlphaBlock Sandbox on Github, alphablockorg
[7] Dahlander. L, Piezunka. H, “Why Crowdsourcing Fails”, Springer, 2020
[8] Darrigol. O, “Joseph Boussinesq's legacy in fluid mechanics”, Comptes Rendus Mécanique, 2017
[9] Bachelier. L, “Théorie de la speculation”, Annales Scientifiques de l'École Normale Supérieure, 1900a.
[10] Pal. M, “Mechanisms of Psychology”, SSRN, 2022
[11] Simon. A, “Architecture of Complexity”, Proceedings of the American Philosophical Society, 1962
[12] Kate. D, “Direct indexing is the hot new investing strategy”, CNBC, 2021