What Waze Can Teach Us about Investing
I recently attended a conference where participants discussed the topic of financial advisor processes in client interactions. One presenter made a great analogy that I want to extend beyond his specific use, as it also speaks to the power of creating a robust investment process and discipline in terms of how one builds and rebalances portfolios.
The presenter asked, “How many of you use Waze to help navigate your driving directions?”
Of course, almost every hand in the packed auditorium went up.
When we question Waze and deviate from the directions of its algorithm, we almost always regret it. Waze is able to help identify potential risk areas, give us a road map of how to get to our destination quickest, and then reset directions if a certain route gets clogged. Waze is powered by a sophisticated set of models that steer us in the right direction.
How Does Waze Tie to Investing?
I think of the drive toward passive investing and factor-based investing more generally to be adopting a Waze-like algorithm for good investment management approaches.
The problem with traditional discretionary managers is that they’re human and subject to the behavioral biases in decision making that all of us have. The power of using Waze and algorithms more broadly is making an investment process systematic and unemotional. We want to override Waze because we think we know a better way. But the power of creating an investment process—what factor-based investing is all about—is to lock yourself into the discipline of following that investment process without deviating from it. Computers don’t have emotion—they just evaluate the inputs and give you the best directions they can.
What Are Your Goals, and How Can You Systematize Your Investment Process?
Following a value-based investment strategy can be difficult to execute in real time. You are constantly buying what is out of favor—when it is difficult to do so—and selling what has been popular.
When styles come in and out of favor—and value investing has been out of favor for the 10 years since WisdomTree launched—how many active managers stick to the discipline of their approach? We recently wrote up a research piece reviewing the 10-year history of these earnings-weighted strategies.
As market valuations rise, this rules-based discipline to search out valuation-based opportunities becomes increasingly important, in my view. But how do you identify those opportunities?
Systematically Lower P/E Ratios at Each Rebalance
The WisdomTree Earnings Index family has systematic factor exposures both to a quality investing style—by only including profitable companies—as well as a value discipline by reanchoring portfolio weights away from just market cap and toward earnings.
This investment process results in a reduced price-to-earnings (P/E) ratio for a general market index. The differences in valuation show up most pronounced in mid- and small-cap indexes. In these market segments, the universe tends to have higher P/E ratio dispersion and more companies are unprofitable, so weighting by earnings can be more different in mid- and small caps than large caps.
Rebalancing annually back to our Earnings Stream is how we systematize the investment process and undergo a process to refresh the portfolio based on the latest valuations. We systematically reduce exposure to stocks that increased in valuation and add to exposures that have fallen in valuation.
As investors think about the markets today, as well as their overall investment approach, we encourage them to adopt a Waze-like, systematic process for approaching both their individual managers and how they construct their overall portfolios.
When you think about the risks that are in the market today, market valuations are near the top of the list. Having a process to lower overall valuations of your exposures in the market is one of most important elements of investing at today’s more heightened market multiples. This is also where WisdomTree’s fundamentally weighted Indexes were designed to help solve a common problem.