Authored by the Vontobel Quality Growth Boutique, subadviser to the Virtus Vontobel Emerging Markets Opportunities, Foreign Opportunities, Global Opportunities, and Greater European Opportunities Funds.
Defining Our Principles of Portfolio Construction
A famous Michelin-star French chef once said that the perfect meal consists of just a few simple components: The main course, two independent sides, and a sauce. Each ingredient must be the highest quality.
Portfolio construction is a little like gourmet cooking where quality ingredients stand on their own without the need for a lot of embellishments. Our view is that the perfect portfolio is concentrated in the highest conviction quality names, each sized to deliver relative outperformance with lower volatility than the market.
While we have published articles on our stock selection process before, in this discussion we explain the fundamentals of our approach to portfolio construction. Before we delve into the details, let us first define what portfolio construction means to us:
Our starting point is the value proposition. To outperform the market over an economic cycle means to participate to a large extent in the upside and to limit the downside. Therefore, if we were to imagine a portfolio of a single name, it would consist of a stock with a predictable business model that both grows earnings at a faster rate than the market and has greater resilience to economic recessions.
The largest risk resides at the business level. We limit risk by seeking to invest in the right businesses; the investment process is at the core of portfolio construction. We believe we can add most of our value in stock selection by aiming to get the business model right, and the earnings growth trajectory reasonably accurate. By definition, forecasting is uncertain, and we acknowledge that we are no smarter than the market. Yet a portfolio of quality companies helps put the odds of investment success in our favor.
We are aware of our limitations and understand that even with a quality approach and a careful due diligence process, sometimes the prince turns out to be a frog. We aim to build portfolios to minimize the risk of capital loss from lapses in human judgment. We do not build our portfolios with the purpose of hedging our mistakes; if we are not sure about an investment opportunity, we simply stay away.
On the other hand, a portfolio with too many names dilutes the return to investors. We view a portfolio with too many names as a sign of sloppy thinking rather than informed focus. Our global portfolio typically holds between 30 and 60 names, and we constantly strive to be on the lower side of that range depending on the opportunity set and valuations. In our view, quality companies are rare; thus, a portfolio of fewer stocks can help deliver above average performance and help serve investors better.
Portfolio construction is a tool to minimize idiosyncratic risk. The recent Covid-19 pandemic is a case in point. A concentrated portfolio of the very best companies in only the travel and leisure sectors, for instance, certainly would not have provided the downside protection that investors should expect from us. We construct portfolios to allow for diversity among drivers of the underlying businesses we own. That way we can diversify within the quality space, rather than diversifying away from quality.
The error is in the tracking error. Tracking error is useful to measure how differently a portfolio performs relative to its benchmark. This term, however, is misleading because the words “tracking” and “error” give the false impression that risk increases when portfolio allocations deviate from the benchmark. Remember, though, that the benchmark is merely a reference point and that the weight of its components are simply a reflection of market capitalization, i.e., a measure of size. It is not a weight or a measure reflecting any prediction of future return; in fact, tracking error is at best a backward-looking tool. Thus, so-called hugging or performance that looks similar to or tracks the benchmark does nothing, in our opinion, to enhance an investor’s return prospects relative to that benchmark
We build portfolios with investors in mind, not to maximize assets under management. We measure success based on delivering outsized returns while simultaneously taking less risk, commensurate with investors’ expectations. We never aim to take unnecessary risks to reach for unrealistic returns to try to make us look smarter or to promote our business. We fully realize that behind every dollar we have under management, there is a hard-working individual who is relying on us to reach their financial goals. We take this responsibility quite seriously. And that means the true measure of our success is to deliver investors to their investment destination, safely.
Embracing Simplicity in Building Portfolios
The heart of our portfolio construction approach is fairly simple: to maximize return and minimize risk. Leonardo da Vinci said that “simplicity is the ultimate sophistication,” which applies to money management as well as to art. The graveyards of investment firms are full of managers who had all kinds of complex theories about how to invest money (think Long-Term Capital Management). Our philosophy is not underpinned by fancy algorithms or celebrity managers. We use a team-oriented approach, and we operate within a common framework for how a stock fits in the portfolio. Portfolio construction is one of the more important pillars of our success.
We strive to build portfolios that look favorably on the three characteristics that we think matter most.
The first two variables relate to risk management, and the third to alpha generation:
- Predictability of Earnings
- Diversity of Quality Drivers
- Rate of Return (see Figure 2)
1. Predictability of Earnings: We understand that quality and predictability are separate. We define predictability as our level of confidence in a company’s long-term earnings trajectory. For instance, while it may be easier to forecast Nestlé’s long-term earnings growth than the equipment-rental company Ashtead, both are currently quality businesses in our view. They both have well-defined sustainable competitive advantages and high returns on capital—critical elements of a quality business. However, these are two distinctly different business models and quality is defined accordingly: Nestlé owns dominant brands in consumer staples; Ashtead manages one of the largest networks of branches for equipment rentals in the U.S., and thus offers the best availability of equipment at competitive prices.
We measure predictability in different ways. We rank qualitatively each stock in the portfolio on a predictability rating from zero to ten. We avoid investing in stocks with predictability ratings below five and we aim to maintain an average predictability rating of seven or higher for the portfolio. We also look at historical standard deviation of earnings growth and stock prices, and maximum earnings downfall during the last decade.
Figure 1: Vontobel Quality Growth Portfolio
2. Diversity of Quality Drivers: People are always surprised to be surprised. In just the last 20 years, we experienced the demise of the internet bubble, a large-scale terrorism attack on U.S. soil, two wars, a global financial collapse, and a global health pandemic. Therefore, we need to incorporate the risk of unknowns in portfolio construction. While sometimes our research points to a sector with an overly rich pool of quality ideas (e.g., travel and leisure), it would be a mistake not to consider the excessive risk we would be potentially taking by putting too much capital into only these businesses with overlapping earnings growth drivers. When faced with a choice between two similar incremental investment opportunities, we will lean toward the one with a lower correlation to the rest of the portfolio. In addition to our fundamental assessment of the diversity of drivers, we also reference a quantitative risk model from risk management analytics provider Northfield, which we describe below.
3. Rate of Return: The investment rate of return is an outcome of our profit forecast. For every stock in the portfolio, we forecast earnings growth and estimate future returns on equity. We then compare all of our holdings on a total return basis (earnings growth and free cash flow yield). While this may sound mechanical, the reality is that our assessment of the longevity of growth has a meaningful impact on the price we are willing to pay. While we are only forecasting out five years into the future, the growth sustainability beyond five years has a direct bearing on the terminal multiple we use.
Estimating the longevity of growth for a business is always a challenging exercise. There is no magic formula on which to rely. It’s an effort that requires deep business and industry knowledge, as well as confidence, to translate how the future will (or will not) look like the past, and to what degree fortunes or fundamentals will change. In the end, looking into the future requires a combination of boldness and imagination. This is where the collective experience and collaboration of our team of analysts drives our consistency and success.
Sizing the position
With the three aforementioned inputs in hand, we have enough information to size our portfolio positions. As with many comparisons, we start with a baseline point of reference. For example, in a portfolio of 50 names, the average position will be close to 2%. Names that sit close to the theoretical average characteristic of the portfolio (predictability and return) are sized closer to the baseline.
In situations where our assessment of risk and return is materially different from what we believe the market is discounting, we will size stocks at a higher/lower position compared to the baseline. While we are comfortable having a view that differs from consensus, we protect ourselves against hubris with a rule that typically limits our maximum position sizing to 7%. Moreover, we would only allow the stock to grow to a 10% maximum position, and only in rare instances.
If we were to visualize the ideal portfolio, it is helpful to imagine it along two axis (Predictability vs. Return) as shown in Figure 2. We aim to maximize the weight of the portfolio in the top right segment, high predictability/high return, and to avoid the bottom left segment, low predictability/low return. The market is quite effective in valuing the high predictability stocks; which makes it difficult to construct an entire portfolio of names in the “Leaders” box. Therefore, to add stability, we look for names in the top left (“Defenders”). And, to add upside, we look for names in the bottom right (“Money Makers”). A picture of our portfolios today would show that most of the weight is in the “Leaders” category, followed by the “Defenders” and the “Money Makers.”
Portfolio management is a dynamic exercise. We are always active in buying and selling stocks because of valuations, a change in the investment thesis, or simply when we find a better alternative for investors’ capital. Over time, a stock could become more fairly valued and shift from the "Leaders" to the "Defenders" category, or even move out of the portfolio entirely if the valuation becomes too rich. Sometimes, a “Money Maker” proves to be more predictable than we assumed, and it will shift to the “Leaders” category.
Figure 2: Optimizing Predictability and Returns
We are constantly searching the world for new ideas. This is a healthy exercise that not only expands our intellectual book value, but also prevents the portfolio from becoming stale. We are careful about introducing new names, and we only invest after a thorough process of research and team debate. We increase the sizing of new names gradually until we have followed the company for a while, and along the way gain more conviction and proof in management’s consistent performance and strategy.
Quality Control – The Northfield Model
As we mentioned briefly above, we use a quantitative, multi-factor risk model from Northfield to gauge the degree to which related risks accumulate at the portfolio level and identify potential unintended factor bets.
The quantitative model most often estimates lower risk for our portfolios than the respective benchmarks, a result one would expect since we tend to invest in companies with more predictable earnings streams and diversified earnings drivers. In rare cases, when the changes in the model’s risk predictions are not intuitive to us, we have further deliberations to make sure we catch the emergence of any unintended bets.
While a mechanical system that bases its forecasts on past volatility and correlation matrices has its limitations, we believe it is prudent to utilize any tool that has the ability to alert us to possible shifts in risk accumulation at the portfolio level. While Northfield as a quantitative model is not core to our portfolio construction decisions, it is a contributory tool in the process, and a valuable safety line against human fallibility.
In summary, our portfolio sizing framework helps us make better decisions not unlike a master chef who uses recipes as a guideline for melding flavors to create a tasty dish. We do not rely on the framework to spit out perfect answers. This would be a terrible mistake because ultimately, as we said above, investment risk always lies primarily and predominantly at the individual and aggregated business level of a portfolio. As long as computers cannot do our job as consistently well as we do (not yet at least), we will use our collective best judgment and invaluable experience to size individual positions and build portfolios. Good decisions will always depend on the quality of our people and the enduring culture of our firm.
So What is Vontobel’s Secret Sauce?
These are the long lasting values that define our firm:
- Investors First – The financial goals of investors in our portfolios provide the motivation behind all our decisions. We do not take unnecessary risks to make headline news or to grow our assets under management.
- Team Approach – Stock selection is at the heart of our process. Stock specific knowledge lies at the analyst level. We believe our success will come mostly from the quality of our security analysis and thorough research.
- Disciplined Process – We have no illusions that our style will outperform the market every year. Outperforming over time does not mean outperforming all the time. Despite that, we will not deviate from the process to conform to consensus. This goes back to rule #1.
- Humility – We are not smart enough to understand every business model in the world. If we cannot clearly define the competitive advantages, estimate the long-term earnings growth with some degree of confidence, have doubts about management’s integrity or the business accounting, we will simply take a pass. We will never put investors’ money at risk, even if only for a token position size.
Investing involves risk, including the risk of possible loss of principal.
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