As trading costs have just hit zero, and passive investing overtook active in August, the investment industry is braced for further pressure to deliver alpha after fees. In my view, the potential to build great models today is huge, but constrained by the research cultures of most firms. Here is what gives me hope.
Data. a) availability of amazingly unique data that 20 years ago you couldn’t imagine would exist b) a growing appreciation of longer history (for example, a growing list of academic papers and Jamie’s site) c) a growing ‘recent’ history - a 20-year backtest in 1999 now has doubled in size! (for example, see AQR’s, Robeco, and Fama-French factor data)
Computing hard- and soft- ware & Moore’s Law (good story on Two Sigma).
Broad acceptance of Quant as a way to invest (see the latest Economist cover)
Significantly untapped synergies from introducing elements of architecture-design-style & cross-firm-collaboration into the established quant cultures of silo-engineering (for example see my prior thoughts on Creative Quant & Need for Innovation).
Our understanding of human biases that ruin investing keeps informing new technologies that help avoid millennia-old mistakes (for example, Canvas, Tulip, MarketPsych, Essentia, Syntoniq and innovation featured at Wealth-Stack)
Availability of domain experts and specialists whose refined contextual knowledge provides ample opportunity for seemingly infinite depth and differentiation to any quant who chooses to take a risk, dive in, and think differently. The more I meet people who have spent their careers becoming experts in their domain, the more I see the huge potential for many quantamental models that could capture their methods and insights.
For example, just during the past month I got to speak with many unique experts - each one could be a fascinating research collaborator - exploring, deconstructing, and modelling their approaches:
An M&A expert who has a unique way of seeing the risk of deals blowing up based on game theory dynamics in an industry.
A international equity portfolio manager who looks at specific elements of firm culture that results in firm’s ability to maintain pricing power.
A large commercial real estate operator who has developed a deeper understanding of certain local real estate loans than the banks that issue them.
A private equity investor who combines his understanding of people, a specific industry, and powerful sales strategies to transform and grow companies.
A short seller whose eye naturally sees business plan holes, schemes and pyramids everywhere he looks.
A financial historian whose laser-sharp memory and engaging storytelling style make the most obscure bubbles of history appear current and relevant today.
An ESG consultant who can ask the most eye-opening questions, which help see the value of the previously ‘unmeasured’ dimensions.
An experienced fundamental portfolio manager who can break down any business into rudimentary elements completely unseen by traditional ‘factor models’.
A machine learning pro who can not resist talking about reinforced learning models.
A head of quant who questions the most basic findings and reconstructs the entire phenomenon from the underlying holdings.
An investment consultant who teaches meditation as a tool to unlock creativity and alpha.
Head of asset allocation who thinks creatively about ‘now-casting’ and ‘the language of narratives’.
A value investor specializing in special situations who could probably recalculate financial statements of any public company by hand.
And this is just a small sample. How often do traditional quants get a chance to really absorb and model such insights?
The words of the quant giant summarize it best:
“So, Eric, is the Golden Age of Quant Over? Everybody has the same data,
same models....” - A veteran reporter
“Not at all, in fact it’s just beginning.” - Eric Sorensen from Panagora
PS. and as a bonus, perhaps even Value and Momentum will start working again