The Fundamental Challenge of Fundamental Investing
In a world of big data, fundamental investment managers would do well to embrace quantitative techniques.
Investment managers fill out a lot of questionnaires. Consultant research, requests for proposals, databases, client due diligence surveys — hundreds of times a year, we are invited to characterize our firm and how we do what we do.
One of the boxes we typically need to check is whether our process is quantitative or fundamental. Lately, I’ve been wondering how much longer we will be asked this question. How will any manager be able to function in the future without adopting at least some aspects of a quantitative approach?
My firm has used quantitative techniques since the mid-’80s. We analyze the characteristics of stock market and company performance over long periods of time and distill the attributes of successful investments into a disciplined, repeatable process. Fundamental managers, in contrast, typically look at far fewer companies but believe that they can analyze them more deeply through company meetings, hands-on research and other forms of human insight.
I have no quarrel with fundamental management. Skilled fundamental investors historically have been strong at identifying intangibles like management quality, brand value and governance. But this edge relative to quantitative managers will erode going forward. There is no question that data is exploding around the world. Google’s Eric Schmidt famously said that today more information is created every 48 hours than in the entire span of history up to 2003. Financial markets are part of this trend.
Not that simply having more data makes an investment process better. Far from it. I am well aware of the dangers of so-called data mining, which basically means you can find just about anything in a large data set if you look hard enough. What I also know, however, is that this exponentially growing reservoir of information represents a potential competitive advantage for the investors that can extract true meaning from it.
This is the key question: Can the data bonanza translate to true investment insight, or is it just a rising tide of noise?
Behavioral finance has demonstrated how human reasoning falls apart in the face of too much information. Investment processes based on human insight alone must necessarily limit the amount of information they use or the number of opportunities they consider. Otherwise they risk falling prey to the many cognitive errors of judgment that have been shown to plague investors.
In my view, fundamental managers are going to have to change or they will be left behind. Quantitative approaches — designed to capture vast amounts of information and analyze it consistently and objectively — will be increasingly essential to manage the tide of financial data and insulate decision making from bias.
But black box data-crunching quant is not the answer. I believe it is possible to design a quantitative approach that replicates many of the best features of fundamental management — individual company insight, depth, conviction, forward focus, responsiveness and adaptability.
Modern quantitative investing is creative. With the right tools, the data explosion can become a trove of resources to help identify the kinds of fundamental company and market characteristics that may lead to future outperformance. Managers need to apply these insights consistently, to the largest possible universe of opportunity, and be disciplined even — or especially — when decisions are counterintuitive.
I am very excited by the opportunities afforded by the increasing reach of data. My firm is exploring ways that we might discern investor and insider sentiment from big data, including news, blogs, tweets and product reviews. We are also looking at patterns of investor behavior, such as unusual divergence among traders of the same company in different markets or through different financial instruments.
We are intrigued as well by recent research suggesting that it may be possible to capture previously unquantifiable information, such as executive sentiment. Evidence suggests that soft traits, like risk aversion and overconfidence in executive communications, can be systematically identified. There may be ways too to measure intangibles like brand and governance.
Quantifying such attributes allows you to apply these measures to a huge universe of potential investments. The wider the net, the more likely you are to discover companies that have been overlooked by other investors. A systematic approach also lets you be consistent and make truly relevant comparisons, even when looking at thousands of companies, and helps you toward the goal of being really objective.
These classic benefits of a quantitative approach can be realized while also incorporating the most attractive aspects of a fundamental approach. Perhaps the future will be the best of both worlds.
John Chisholm is CIO of Acadian Asset Management in Boston.