Staying on course: the evolution of quant investing
40 years of fundamentals
The rapid evolution of technology has not altered what is, in my view, the core challenge of equity investing: understanding fundamentals. I believe that although quant investing has changed dramatically over the past four decades, the essence of good investing remains the same.
Our Equity QI (EQI) approach to equity markets has been consistent over the past 40 years; it is grounded in replicating what a traditional analyst does, just at greater scale, speed and in a systematic and repeatable way; our investment platform values approximately 20,000 stocks every single day.
This consistency is underpinned by our deep belief in modelling fundamentals, not prices or returns. Ultimately, in the long term, if you can get the fundamentals right, there is some locus which the price has to be anchored to. This long-view thinking anchors our resistance to transient fads that often permeate financial markets, including superficial applications of artificial intelligence (AI).
While we adopted AI tools early (our first neural network was built eight years ago), we continue to avoid blindly embracing black-box models, which lack transparency as to what has been learned. Rather, we implement a ‘white box’ framework; this refers to a layer of linear regression built atop the neural network, designed to offer transparency into variable importance.
This commitment to transparency reflects our cautiously optimistic outlook for AI. Using prominent AI tools and technologies such ChatGPT may seem like magic to some, but it is important to consider that the data going into those tools is pristine. Equity markets are full of noise, and training AI on equity market data without robust fundamental context could be a recipe for failure.
Our approach combines technology with purpose; EQI recently integrated five terabytes of global patent data - millions of pages of filings - into our investment models. This allows us to convert text at scale into matrices that we can then use in our models, such as our ability to calculate a cosine-to-narrative score to assess corporate innovation, especially as a proxy for future intangibles.
This enhancement is designed to help us model the evolution in corporate balance sheets. Forty years ago, companies were balance-sheet heavy. Now it’s all intangibles. Research and development (R&D) and capitalising R&D isn’t good enough anymore. Investors need to understand the patents, the innovation, and what that says about future fundamentals. Understanding innovation is not only about future earnings, but also about identifying how companies position themselves in relation to carbon transition and sustainability.
Our quant platform was an early adopter of environment, social and governance (ESG), as we sought to embed it into our core strategy. The carbon repricing in markets hasn’t happened yet. When it does, it will happen quickly, and by the time we realise it’s happened, it’s too late to chase - hence the early adoption.
We returned to the patent data to deepen our ESG understanding, and get into this green patent space, to help us identify companies working on carbon transition that could impact the future fundamentals of their income statement or balance sheet in a positive way. Our belief is that this is not only good investing, but also good stewardship—technology serving a larger thesis, not simply chasing buzzwords like ‘AI’ or ‘sustainability.’
Earnings and their forward trajectory remain of great importance for equity investors; it’s not just about fundamentals. It’s the forecast, how delivered earnings compare to the forecast – the earnings surprise. We build forecasting modules to anticipate earnings surprises. We seek to remain in that kind of beauty parade mindset; it’s not just what you’re delivering, it’s how the market views what that delivery is relative to the forecast.
Our approach places less emphasis on price momentum. While there is actually information in price, EQI exited momentum strategies years ago in favour of earnings estimate revisions. We believe there’s much more stability around that, and again it’s anchored in fundamentals.
This measured approach reflects our view of technology’s role to enhance core investment beliefs, not to replace them – and our mindset also extends to infrastructure. EQI’s entire platform, from the code base to the signals, is proprietary. There is no third party - our code base has evolved non-stop for over 40 years.
I refer to an academic paper titled The Boats That Did Not Sail1, which examined stock price volatility in London and Amsterdam during the 18th century. Its finding? In the absence of information, volatility increased. This is the human condition - in the absence of information, people inject volatility. It is this behavioural insight that reinforces our belief that systematic investing, rooted in fundamentals, offers a path through noisy markets.
EQI’s story, then, is not one of reinvention. It is a case study in intellectual and technological evolution, grounded in a durable investment philosophy to stay on course. It’s not about trying to reinvent ourselves, rather, it’s about doing what we’ve always been doing. In a world that often prizes novelty over nuance, we believe this serves as a reminder that consistency, clarity and curiosity are still some of the most valuable traits in investment management.
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