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28 October 2017
“The key to investing is not assessing how much an industry is going to affect society, or how much it will grow, but rather determining the competitive advantage of any given company and, above all, the durability of that advantage. The products or services that have wide, sustainable moats around them are the ones that deliver rewards to investors.” – Warren E. Buffett
“The risk of paying too high a price for good quality stocks – while a real one – is not the chief hazard confronting the average buyer of securities. Observation over many years has taught us that the chief losses to investors come from the purchase of low quality securities at times of favorable business conditions.” – Benjamin Graham
In our previous articles, High Quality Stocks in Developed Markets and High Quality Stocks in Emerging Markets, we discussed our framework for selecting High Quality businesses and a quantitative process to select high quality businesses. In this article, we will discuss the investment returns to a similar process applied to Indian equity markets. Additionally, we will show the risk and returns to a manually selected basket of high quality businesses in India.
As we stated in the articles referred to above, a high quality business possesses significant competitive advantages that are durable. The quote above by Warren Buffett makes the same point as Buffett states that the key to investing is about two factors: one, the extent of the competitive advantage of the business and two, the durability of that advantage.
A business that enjoys significant competitive advantages and is able to sustain such advantages over extended periods shows that business has been able to keep competition at bay. Most analysts as well as business observers usually associate a depicted ability on part of the business to keep competition at bay with presence of durable competitive advantages. However, a business’s success at fending off competition doesn’t always mean that the business possesses durable competitive advantages.
We contend that there are three primary factors that help a business keep competition at bay. We discuss each one of these factors below.
An investor who is able to successfully identify businesses that are blessed with superior management or businesses that will continue to benefit from demand supply imbalances driven by market structure, will likely achieve superior investment results. However, we find that we have limited capabilities at identifying businesses blessed with either of these factors. Accordingly we choose to focus our efforts and resources where we think we indeed have superior capabilities; at identification of businesses that possess wide and deep moats.
This article discusses the application of quality-driven investing in Indian markets. In the discussion that follows, we lay out the framework for selecting high quality businesses and the risk-return of a basket of high quality stocks in Indian markets.
At Multi-Act, we have spent more than 15 years developing and refining our process for identifying high quality businesses. Our internal research process assigns every company we follow a quality rating, referred to as its “grade.” There are several components of our process, some of which lend themselves to quantitative modeling while others don’t. As discussed above, the defining trait of a high quality business is the existence of competitive advantages that are durable. The important point to note here is that this is a component that does not lend itself to quantitative modeling.
The existence and sustainability of competitive advantage are the most important criteria in our classification of a business as high quality. This is driven by our assertion that much of the investment returns that accrue to investors from the quality factor depend on the ability of the business to persist with supernormal returns on capital. This in turn depends on its ability to keep competition at bay. Given our inability to model this component, we believe that our manually selected list of quality businesses will likely generate superior risk-adjusted performance as compared to the quantitatively selected basket that is discussed here.
2. Quantitative factors
There are some key characteristics of a high quality business. A high quality business generates superior returns on capital – the stronger the competitive advantage, the lesser the impact of competition and the higher the returns on capital. Returns on capital of such businesses tend to be persistently high. Further, such businesses have a very healthy relationship between their accounting profits and their economic profits. Additionally, our high quality businesses possess good balance sheets, so financial risk isn’t a significant factor driving our investment returns.
Exhibit 1: Determination of Quality Companies
Source: Multi-Act EquiGlobe Limited (MAEG)
As shown in Exhibit 1, our process includes three characteristics that lend themselves to quantitative analysis. Within each one of the characteristics, our investment research process utilizes a multitude of measures spread over several years of the business’s history. However, for the sake of simplicity, we have chosen one measure to represent each quality characteristic.
For the purposes of this article, we measured returns on capital by return on equity (RoE). A high RoE indicates the existence of competitive advantage and the persistence of this variable suggests its sustainability.
It is possible for the management of a company to manage its RoE. To the extent that earnings are manipulated, they will impact RoE. Further, RoE is affected by corporate transactions including buybacks, acquisitions and restructurings. To ensure that the earnings component of the RoE is not a result of financial creativity, we use free cash flow over earnings (FCF/EPS) to calibrate the quality of earnings. We have found that this measure filters out companies with suspect accounting numbers. Finally, we measure financial safety by net debt over free cash flow (ND/FCF). This measure indicates the number of years of free cash flow needed to repay the debt.
Table 1 provides summary statistics on each of the quality factors by year.
Table 1. Comparison of Quality Measures
This table shows median quality measures by year for the investment universe as well as for the quality basket. This table reports the median of quality measures between 2006 and 2017. We also report the difference between quality basket and all companies in the selected universe, by year.
Our data sample consists of 1,215 companies between years 2006 and 2017. All data including fundamentals and prices are from Factset Global with returns calculated in INR. We utilized fundamental data reported such that there is a minimum three-month lag from the end of the fiscal year of the company. Table 2 provides summary statistics on number of companies and market capitalization by year.
Table 2. Number of Companies and Market Capitalization
This table shows number of companies for each year and average market capitalization for the investment universe as well as for the quality basket by year. We also report the difference between average market capitalizations of the quality basket and all companies in the universe by each year.
Given the issues with data availability as well quality of historical data for India, our sample could start in 2006 at the earliest.
Before proceeding with our calculations, we performed exclusions for size and for suitability and data applicability. Every year, we start with the largest 1,000 companies excluding some industries as discussed below. Additionally, we applied a condition that the stock should have minimum average monthly turnover of 10,000 shares. Taken together, these conditions were intended to reduce the size factor’s contribution to our investment returns and ensure that stocks that qualified through our process were, in fact, tradable.
Further, we excluded some industries that do not lend themselves to existence of sustainable competitive advantages[ref]The following industries were excluded for the purposes of this paper: Financial Conglomerates, Investment Banks/Brokers, Life/Health Insurance, Major Banks, Multi-Line Insurance, Property/Casualty Insurance, Real Estate Investment Trusts, Regional Banks, and Specialty Insurance.[/ref] in our assessment. This is not to say that there cannot be a business with sustainable competitive advantage in these industries. However, the probability of finding a business with sustainable competitive advantage in these industries is significantly lower. Further, calculating cash-flow data presents a practical problem with some of these industries, especially in the case of banking and insurance where cash flow is affected by changes to loans, investments, and deposits and thus loses its sanctity. Accordingly, we have excluded these industries from our samples.
We calculated the quality factors discussed earlier for all the remaining stocks in our data sample. For companies where FCF is a negative number, years to repay debt is an insensible number. To allow us to still effectively model the factor, we used an outsized number of 50 years. We then applied absolute cutoffs that a business must meet in order to qualify as HQ business. Businesses that met these cutoffs were selected as our quality basket.
4. Risk and Returns of the quality basket
We now turn to risk and returns of quality businesses. Figure 1 shows the performance of the quality basket on a total return basis (including dividends) as compared to that of the NIFTY 50 index. The quality basket generated a compounded annual return of 19.9% as compared to 11.0% for NIFTY 50 index. What is more, annualized standard deviations of monthly returns were lower for the quality basket at 19.6% as compared to 22.9% for the benchmark index.
Figure 2 shows drawdown[ref]The peak-to-trough decline during a specific record period of an investment, fund or commodity. A drawdown is usually quoted as the percentage between the peak and the trough. (Source: Investopedia)[/ref] profiles of the quality basket and of the benchmark index. Clearly, the quality basket is significantly less risky when compared to NIFTY 50 index, as drawdowns aren’t only shallower; recovery to peak is quicker as well. We estimate the quality basket’s relative risk to be 76%[ref]The worst drawdown of the quality basket is 38% while that of the benchmark index is 61%. The relative risk is estimated as log(1-38%)/log(1-61%) = 50%. At 50% of the benchmark’s risk, relative risk of the quality basket is half that of the benchmark index. This means that it takes about two back-to-back losses of 38% to produce one 61% loss. For more on this, refer to: http://www.hussmanfunds.com/wmc/wmc141013.htm[/ref] to that of the benchmark index.
5. Risk and Return’s of MAEG’s “manual” high quality India index
As stated earlier, a key component of our quality selection process does not lend itself to quantitative modelling. In this section, we analyze performance of our actual quality basket, a basket that has to pass through our human analytical rigor as well as our systematic process. We refer to this basket as India Moats Index.
Figure 3 shows performance of the India Moats Index on a total return basis as compared to that of the benchmark index. The India moats index generated compounded annual return of 25.0% as compared to 11.0% for the benchmark index. The annualized standard deviations of returns were lower for the India moats index at 19.9% as compared to 22.9% for the benchmark index.
Figure 4 shows drawdown profiles of the India moats index and of the benchmark index. Clearly, the India moats Index is significantly less risky when compared to NIFTY 50 index as drawdowns aren’t only shallower; recovery to peak is quicker as well. We estimate the quality basket’s relative risk to be 81% of that of the benchmark index.
6. Why will this anomaly persist?
As we have shown, high quality stocks as defined by us generate superior investment returns and do so with lower risk. The relevant question for us as investors is will this anomaly persist. In our opinion, for an anomaly to persist, it needs to be rooted in the behavioral biases of market participants. As is seen in Figure 5, the high quality basket as a strategy results in extended periods of under-performance on a one-year investment horizon basis. This tendency to under-perform the benchmark over extended periods of time is even more pronounced when one looks at the drawdown of excess returns as seen in Figure 6.
Essentially, an investor focused on high quality stocks needs to have high amounts of patience. Increasingly, the time horizons for most market participants have become shorter with most Funds assessed for their performance on a quarterly basis if not monthly. Clearly, a fund manager who follows an investment strategy like the one discussed here, runs an elevated level of risk of losing her job.
A high quality stocks based investment strategy can lead to extended periods of under-performance. Patience is of utmost importance for an investor to successfully follow such a strategy.
Baijnath Ramraika, CFA, is a cofounder and the CEO & CIO of Multi-Act Equiglobe (MAEG) Limited and is Executive Director at Sapphire Capital. As a portfolio manager, he manages the Global Moats Fund and the India Moats Fund. Contact him at firstname.lastname@example.org.
Prashant K. Trivedi, CFA, is a cofounder of MAEG and the founding chairman of Multi-Act Trade and Investments Pvt. Ltd. MAEG is an investment manager and manages the Global Moats Fund, an investment fund that invests in a global portfolio of high quality businesses with sustainable competitive advantages.
Multi-Act is a financial services provider operating an investment advisory business and an independent equity research services business based in Mumbai, India.
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