Content supplied by Loomis, Sayles & Company — an affiliate of Natixis Global Asset Management
For mutual fund investors and managers of large pensions or endowments, a major challenge is to identify those portfolio managers who are most likely to deliver superior risk-adjusted returns in the future. Understanding how an investment philosophy informs a manager’s decision making can provide meaningful insights into how and why a particular manager generates alpha. The search for alpha is the search for skill. We believe our alpha thesis, and our ability to consistently implement its tenets, constitutes a differentiated approach. The deeply held beliefs and disciplined process described in this paper guide what we do every day.
Why alpha thesis?
A performance track record cannot readily explain the level of skill employed to achieve the results, or guarantee continued success. We believe a focus on the quality of a manager’s investment philosophy, process and decision making is essential for assessing the probability of future success. Our alpha thesis encapsulates a deeply held system of persistent beliefs, a rigorous, repeatable investment process and substantive proof points.
Foundation of investment process: philosophy and pricing anomalies
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Philosophy: We are an active manager with a long-term, private equity approach to investing. Through our proprietary bottom-up research framework, we look to invest in those few high-quality businesses with sustainable competitive advantages and profitable growth when they trade at a significant discount to intrinsic value.
Pricing anomalies: At the heart of active management lies the belief that one can deliver returns in excess of benchmark returns. Over the long term, we believe that markets are efficient. Near term, however, we believe innate behavioural biases, such as herding, overconfidence or loss aversion, influence investment decisions and create asset pricing anomalies. These pricing inefficiencies converge toward intrinsic value over time. Market efficiency is thereby dynamic, existing along a continuum between fully efficient and inefficient pricing.
In our view, two important anomalies can best explain periodic mispricing: short-termism and allocative inefficiency. Short-termism is a behavioural bias inherited from our early human ancestors. Today, it causes a reflexive response to short-term market variables that, when viewed rationally, have no impact on long-term value. Allocative inefficiency, an example of herding, describes the breakdown in dynamic price discovery that results when widespread investment decision making is driven by factors other than valuation. Examples include index investing or momentum and technical trading. Overcoming these natural tendencies is difficult. Consequently, the resultant pricing anomalies persist, creating potential opportunities for active, long-term oriented, valuation-driven managers like us. Capitalising on these opportunities requires a disciplined process and a patient temperament.
Our investment philosophy represents our fundamental beliefs regarding the most effective way to generate alpha and leverages our understanding of persistent anomalies that create asset mispricing. These beliefs, or tenets, form the cornerstone of our investment decision-making process and can be linked to performance proof points, demonstrating continuity from belief to process to outcome. Collectively, this integrated system forms our alpha thesis.
Key tenets of our alpha thesis
We believe that for any alpha thesis to potentially meet its objective, it should be founded on an enduring philosophy and persistent pricing anomalies. We think our alpha thesis is unlikely to be eroded through arbitrage because it is tied to perennial behavioural biases, not specific market conditions. Below we explain each alpha thesis tenet in detail.
Long-term investor in businesses
Because we approach investing as if we are buying into a private business, a long investment horizon is central to our philosophy. This is evidenced by the strategy’s low turnover of 19.89 per cent indicating an average holding period of around five years. Measuring name changes only, our portfolio turnover is even lower. In our view, a long investment horizon affords us the opportunity to capture value from secular growth opportunities as well as capitalise on the stock market’s shortsightedness through a process called time arbitrage.
Our low turnover stands in contrast to a widespread escalation in the average manager’s portfolio turnover. In his book Common Sense on Mutual Funds, John Bogle documents that from the 1940s to the 1960s annual turnover for the typical general equity fund averaged just 17 per cent. By 1997, average annual turnover had risen to 85 per cent and by 2009 it had increased to 105 per cent — a staggering six-fold increase. Bogle states: “The industry has abandoned the wisdom of long-term investing in favour of the folly of short-term speculation.” We could not agree more.
In addition to the speculative risks, the trading costs of high portfolio turnover can negatively affect portfolio performance. A 1997 study looking at growth fund returns over 32 years (1962-1993) suggests that for every 100-point increase in turnover, annual return drops by 95 basis points, a figure closely aligned with the net cost of trading. A 2007 study updated the analysis and also confirmed that the cost of turnover negatively affected performance. The table below shows the findings for 990 large cap equity funds from 2001-2006.
What fuels the culture of short-termism so prevalent today? This innate behavioural bias is exacerbated by the constant, ubiquitous stream of financial “news”. Investors too focused on the short term end up overreacting to company and economic information that we do not believe affects long-term intrinsic value. Fisher Black calls this activity “noise” trading and posits that it obscures the value estimate of near-term stock prices.
This is an example of how the widespread use of non-value-focused decision making can compromise near-term price discovery. We believe that noisy stock prices will converge toward fundamentally driven intrinsic value over time. Therefore, we attempt to identify intrinsic value and exploit the long-term differential between this value and the market’s current perception.
Develop a deep understanding of each investment
“….risk varies inversely with knowledge.” – David F Swensen, Yale University chief investment officer
Seven-step research framework
1. Sustainable competitive advantage
• Identify unique elements of a company’s business model (e.g. network effect, low-cost advantage, strong brand awareness and high switching costs).
• Can this company defend and sustain its competitive advantage over the long term?
2. Competitive analysis
• Identify unique elements of the industry: assess barriers to entry, industry rivalry, power of buyers and suppliers and substitution threats.
• Look for the strongest company in the value chain.
3. Financial analysis
• Assess balance sheet health (low or no debt is ideal), capital intensity, business mix and margin structure.
• Require sustainable free cash flow growth, an ability to meet reinvestment needs and cash flow return on investment above the cost of capital.
• Partner with management teams who share our long-term perspective, manage the business with vision and integrity and whose incentive is aligned with long-term shareholder interests.
• Evaluate management’s ability to allocate capital to investments creating long-term value.
5. Growth drivers
• Evaluate sources and sustainability of profitable growth.
• Focus on long-term secular and structural growth drivers — dynamics that aren’t likely to change in five years or more.
• Forecast the growth rate independent of company guidance or Street expectations.
6. Intrinsic value ranges
• A company’s value depends on its long-term ability to generate profitable free cash flow growth.
• The present value of future free cash flows is our core methodology for estimating intrinsic value.
• Conduct sensitivity analysis of key variables to assess downside risk and focus on high-impact drivers of value.
• Best-, base-, bear- and worst-case valuation scenarios guide the timing of buy/sell decisions and help guard against decision-making pitfalls.
7. Expectations analysis
• Assess the valuation assumptions implied by the current stock price to differentiate fundamental drivers of value from market sentiment drivers of price. Understand where and how our perspective diverges from that of the market.
Our proprietary seven-step research framework is the cornerstone of our investment decision-making process and drives our security selection. The research framework, detailed below, represents our long-standing insights about investing and is structured around three key criteria: Quality-Growth-Valuation. Through the disciplined and thorough implementation of bottom-up fundamental analysis, we seek to understand the drivers, opportunities and limits of each business.
Our valuation analysis, which is at the heart of our research and decision making, is only as good as our ability to understand and identify high-quality companies and evaluate the sustainability of profitable growth. Actively managed portfolios differ from their benchmarks and reflect expectations that diverge from consensus. Importantly, our research framework helps us determine whether our view differs from the consensus and, if so, why. Our contrarian posture requires the ability to act counter to potentially irrational, herd-like and reflexive behaviour in the marketplace triggered by emotions such as fear and greed. Overcoming these instincts demands a resolve engendered by experience, a disciplined decision-making process and the temperament to maintain positions that are at odds with popular opinion.
Our investment team culture promotes intellectual honesty, curiosity and independent thinking. An environment in which all assumptions can be challenged by any member of our team can improve our understanding of each investment idea. All research work is vetted through team discussions and includes attempts to disprove the investment thesis as a way to test its validity. This practice helps us overcome the bias in human behaviour toward overconfidence that could lead us to overstate the investment’s potential and minimise downside risk. It is crucial to clearly grasp what could go wrong with a company, not just what can go right.
All aspects of our investment thesis must be present simultaneously for us to make an investment. Often our research is completed well in advance of the opportunity to invest. We are patient investors and maintain coverage of high-quality businesses in order to take advantage of meaningful price dislocations if and when they occur.
In a typical year, we may analyse 30 companies and invest in only a select few. For example, in 2009 we bought four companies, in 2010 three and in 2011 only two. As a result of this rigorous approach, ours is a selective, high-conviction portfolio of 30-40 names. We agree with Warren Buffett’s assertion that risk comes from not knowing what you’re doing. In part because we focus on fewer companies and make even fewer decisions, we believe we enjoy an analytical edge.
Anyone could follow our seven-step process. Yet, each person will very likely produce different outcomes. Why? Because we believe that investing is ultimately an art. While a disciplined research framework is foundational to a successful investment strategy, our process does not mechanically supply “the” answer. Rather, it leads us to ask a set of questions that help us discern, through our insights, whether a business meets our key investment criteria. Developing a deep understanding of each investment can also help us manage risk through knowledge.
Selective investing focused on high-quality businesses
Our Quality-Growth-Valuation investment process begins with the art of trying to identify high-quality companies — those with unique, difficult-to-replicate business models and sustainable competitive advantages. A successful business will attract competition and capital, which over time could shrink profit margins. A quality business — one with a wide economic moat — can sustain and even extend its competitive advantages so that its profitable growth opportunities are not eroded by the competition. Quality companies also tend to exhibit sound balance sheets, strong returns on invested capital, healthy cash flow growth and highly capable management teams who can efficiently allocate capital.
A focus on investing in high-quality companies can not only help capture upside potential but can help manage downside risk as well. This is an important factor given the number of negative return periods the Russell 3000 Index experienced over a 25-year study period, shown in the table below:
Looking at high-quality and low-quality stocks as defined by Standard & Poor’s (S&P), we examined the annual return for each group and compared it with the returns of the Russell 3000. Our analysis shows that the high-quality group of companies’ limited participation in down markets was a significant differentiating factor for superior risk-adjusted returns.
As recapped in the table above, while annualised performance of the two baskets was comparable after 25 years, the return-to-risk ratio of the high-quality group of stocks was 70.77 per cent, compared with the 44.30 per cent return-to-risk ratio of the low-quality basket. The chart below provides a long-term perspective of the groups’ performance.
While S&P’s quality rankings can provide an interesting overview of how a “quality” universe has performed historically, we do not rely on a third-party methodology to define quality. The companies we invest in must first meet a number of demanding quality standards. At the end of the day, our job is to allocate investment capital to the best opportunities. Our approach is different from benchmark-centric portfolios that tend to begin their investment process by considering the influence of the benchmark’s top holdings on relative performance. Because our philosophy and process often result in positions and position sizes that differ from the benchmark, our portfolio typically has an active share measure of 80 per cent or greater.
Why is active share important? In their 2009 paper, “How Active is Your Manager?”, Antti Petajisto and Martijn Cremers found that high active share correlates well with excess returns and that the most active managers, those with active share of 80-100 per cent, persistently generated excess returns above their benchmarks even after subtracting management fees. It stands to reason that only portfolios that differ from the benchmark could produce superior returns versus the benchmark. While high active share does not ensure outperformance, we believe it is a necessary condition for generating alpha and outperforming one’s benchmark net of fees over the long term. Ultimately, of course, the stocks we select for our portfolio are the sources of any outperformance.
Sustainability of profitable growth drives long-term value creation
Growth is the next component we consider in our Quality-Growth-Valuation investment process. We are looking not only for above-average growth, but sustainable and profitable growth. Easier said than done; empirical evidence shows only 10 per cent of companies can sustain above-average growth rates over a four-year period. Our systematic approach to measuring a company’s growth prospects begins with quantifying the total size of the market into which they can sell their goods and services as well as their current market share. We then assess the company’s pricing power, if any, their margin expansion potential, capital requirements and operating leverage. Our objective is to define the company’s competitive advantage period in order to determine how long into the future we will estimate the key variables for the business. Our proprietary models are built through bottom-up fundamental analysis. It is important to note that our growth estimate is developed independent of company guidance or Street expectations. To assess the sustainability of the company’s growth rate, we evaluate the drivers of that growth. We are looking for long-term secular and structural growth drivers — dynamics that are not likely to change for five years or longer. The transition of consumer shopping from in-store to online — still only at high-single-digit penetration rates in the global consumer market — is an example of a long-term secular driver of growth. Developing insights about a company’s growth potential is essential to measuring its future cash flows, its profitability and, ultimately, its intrinsic value.
Even when we believe we have identified a quality company with high, sustainable growth rates, we are not yet satisfied: we also require profitable growth. Just because a company can demonstrate growth in revenues, for example, does not mean it is generating profitable growth. Without profitable growth, there is no increase in shareholder value and therefore no investment opportunity. We believe the present value of future cash flows is a superior measure of economic performance and shareholder value. It is our core method for calculating a company’s intrinsic value, which drives the timing of our investment decisions. The underlying question is whether the cash flow returns generated by management’s investments in the business are greater than or less than the cost of the capital spent on those investments. To determine if the company is increasing total capital (not simply replacing capital invested) and thereby creating shareholder value, we calculate cash flow return on investment. Many other investors rely on earnings-per-share (EPS) and price-to-earnings (P/E) multiples to understand a company’s growth rate, recognise investment opportunities and predict a stock’s future price. Both of these metrics are earnings-based accounting ratios that, in our opinion, limit their reliability since earnings can be different from economic performance and actual cash flows. What’s more, reported earnings can be easily manipulated to the company’s short-term advantage and, given Wall Street’s obsession with quarterly earnings, company managements have been known to do so.
Credit Suisse Holt captured this notion of sustainable and profitable returns by applying its proprietary measures of quality to identify companies that were able to earn superior cash flow return on invested capital (CFROI) over a longer-than-anticipated period. They found that such companies (“eCap” companies) significantly outperformed the market during downturns while keeping pace during up markets, as illustrated in the chart below.
Growth is important, but not growth at any price. And for us, not even growth at a reasonable price will do. We are seeking companies that can generate sustainable and profitable growth and invest only when they are selling at a significant discount to our estimate of intrinsic value.
Invest with a margin of safety
Valuation analysis is the final component in our Quality-Growth-Valuation investment process. Investing with a margin of safety requires not only a disciplined understanding of a company’s intrinsic value but a clear recognition of what the market price implies about consensus expectations for that company’s value. Comparing the stock price we believe represents intrinsic value to the market price helps expose pricing inefficiencies. We seek to create a margin of safety by investing at a purchase price that is at a meaningful discount to our estimate of a company’s intrinsic value. When buying a business, we require at least a 2:1 anticipated upside-to-downside, reward-to-risk opportunity. Holding all else equal, the larger the discount between market price and our estimate of intrinsic value, the greater we view our margin of safety. Counter to the buy discipline of many growth equity managers, we believe the risk of investing in a great company is actually lower after its stock price has fallen, assuming our long-term investment thesis remains intact. Over time, if the market price increases (consensus expectations change) and converges with our estimate of intrinsic value, positive returns are generated. In this way, adhering to this tenet helps us manage downside risk and could increase upside potential.
We believe the discounted net present value of future cash flows is the best estimate of a company’s intrinsic value (price). Because humans tend to anchor too readily to a single outcome or frame decisions too narrowly, we not only forecast our most likely intrinsic value scenario, our base-case price, we also test our assumptions. Through sensitivity analysis on the key variables appropriate to each business, we seek to determine which can drive the largest changes in valuation. We thereby establish a range of outcomes, or scenarios, that we label best case, base case, bear case and worst case. The best-case price represents the scenario in which the company executes successfully on all fronts. The bear-case price represents the scenario of what could likely go wrong with our base case. Our worst-case price represents the scenario when all goes wrong for the company. By linking our scenario analysis to key business drivers such as market penetration rates or profit margins, we hope to better understand the sources of both value creation and downside risks so that we may make better-informed, more objective decisions.
Our next step is to develop an understanding of the consensus expectations about a company’s future cash flows implied by its current stock price. We call this expectations analysis, which reverse-engineers the net present value cash flow calculation. That is, we start with the current stock price and solve for implied drivers of cash flow growth and profitability. Recognising the consensus expectations reflected in the current stock price is crucial because generating alpha is not solely about absolute price-to-value differences. Understanding how our analysis of key variables differs from the price-implied consensus helps us understand how and why the market price, over time, converges toward, or deviates from, our intrinsic value.
With our range of intrinsic value price scenarios and our understanding of price-implied consensus expectations, we have the information we need to make investment decisions. When investing in a company, we look for the most attractive reward-to-risk opportunities. This can occur when the stock price falls into our bear- and worst-case valuation scenarios due to a short-term market inefficiency that in no way affects our long-term investment thesis. In most cases, we gradually scale into a position, taking advantage of dips in the stock price. Conversely, as the price of a company reaches our base-case price — when the reward-to-risk opportunity becomes less attractive — we typically begin to reduce our weight in the company and eventually sell the position altogether. In short, valuation drives the timing of our investment decisions.
Ultimately, our job as an investment manager is to allocate capital to the most compelling reward-to-risk opportunities. Therefore, the more attractive we view the reward-to-risk opportunity, the larger our capital allocation and position weight. In comparison, we have observed that the largest positions of a cap-weighted benchmark may have the least margin of safety — or worse, market prices above intrinsic value — yet are given the largest capital allocations in many benchmark-centric portfolios.
There is one last essential component to successfully implementing this tenet: it demands the temperament — and concomitant discipline — to be a contrarian who can buy into fear and sell into greed. It is not easy to stand alone, apart from the crowd. As Ben Graham said: “Have the courage of your knowledge and experience. If you have formed a conclusion from the facts and if you know your judgment is sound, act on it — even though others may hesitate or differ.”
Define risk as a permanent loss of capital
Because we define risk as a permanent loss of capital, we take an absolute-return approach to investing and seek to actively manage our downside risk. More commonly, risk is framed in terms of relative returns and tracking error versus a particular benchmark. While benchmarking investment performance to a specific index began as a tool to help understand and judge portfolio manager performance, this relative-return orientation has morphed into the baseline for acceptable risk and return. Risk may be carefully measured in this way, but it is not carefully or actively managed. We believe defining risk in relative terms obfuscates the fact that the benchmark itself is a risky asset. This is particularly true with cap-weighted indices because downside risk increases significantly when the stocks of a particular sector experience a run-up in prices that are above (in the case of a bubble, far above) their fundamental intrinsic value. If a portfolio manager ties his investment decisions to benchmark holdings and risk factors, he must necessarily take on this additional downside risk. This concept helps resolve the seeming contradiction between our active risk management and the concentrated nature of our portfolio. Because our strategy is to invest in a stock only when its market price is at a significant discount to our estimate of a company’s intrinsic value, we pursue both the possibility of greater upside potential and potentially lower downside risk.
Diversification is another important tool in managing portfolio risk or volatility. However, we do not think diversification is the simple notion of more is better. Many investors wonder whether a 30-40 stock portfolio can be sufficiently diversified. Studies dating back to 1960s have sought to determine how many stocks a portfolio must hold to maximise the benefits of diversification. Results have ranged from 18-30 stocks. A 2010 study by Citigroup demonstrated that a portfolio of 30 stocks was able to diversify more than 85 per cent of the market risk. The diversification benefit of adding more stocks to the portfolio declined significantly as the number of stocks increased. For example, adding 70 more stocks to a 30-stock portfolio improved diversification benefits by just nine per cent.
Regarding the benefits of diversification, legendary growth investor Phil Fisher notes: “Too few people, however, give sufficient thought to the evils of the other extreme [over-diversification]. This is the disadvantage of having eggs in so many baskets that a lot of the eggs do not end up in really attractive baskets, and it is impossible to keep watching all the baskets after the eggs get put into them.”
Cognizant of this risk, we instead seek to enhance risk management by diversifying the business drivers to which our holdings are exposed. Examples include growth in e-commerce, increased consumer spending in emerging markets, the shift to outsourcing and the ageing population. Because business drivers are imperfectly correlated, the positive impact of one may offset the negative impact of another. This fosters more efficient diversification of risk and helps us keep our attention focused on searching for those few stocks that meet our disciplined criteria.
We agree with Phil Fisher that one of the riskiest things investors can do is to invest in a business they do not thoroughly understand. As a bottom-up fundamental investor, risk management is therefore integrated with our analysis of business models, competitive advantages, operating efficiency, corporate management integrity, profitable growth and valuation analysis. In short, our active risk management process is an integral part of our active investment process.
For any investor, the goal is to identify those portfolio managers who are most likely to deliver superior risk-adjusted returns in the future. In our view, a performance track record cannot readily explain the level of skill employed to achieve the results, or guarantee continued success. We believe a focus on the quality of a manager’s investment philosophy, process and decision making offers a better method for evaluating the probability of future success. Our alpha thesis encapsulates a deeply held system of persistent beliefs, a rigorous, repeatable investment process and substantive proof points. As we see it, alpha generation and managing absolute levels of risk are inextricable goals, and each tenet of our alpha thesis is designed — individually and collectively — to promote this dual objective for our clients.
Aziz V Hamzaogullari, CFA, large-cap growth portfolio manager
Hollie C Briggs, CFA, large-cap growth product manager
Loomis, Sayles & Company