July 7th, 2020
Letter to investors: Update for three months ended June 30, 2020
Dear Fellow Investors,
Hope this letter finds you safe.
A lot has already been written about Covid, and investment strategies through the Covid period; and I do not intend to belabour that topic. That is, besides communicating that we had more calls with companies and experts during the last quarter than we did in the previous full year. At the end of a little more than three hundred calls and virtual meetings, we came to a rather startling conclusion— the future continues to be as uncertain now, as it has always been.
Nevertheless, this discussion has brought us back to the very fundamental question: How well can we predict the future, and how should our investment decisions reflect that?
A bit of historical contour might help. The notion that future is NOT completely predictable is a rather recent phenomenon. In the late 17th century, after Newton had theorized the laws of motion and universal gravitation, everything had seemed predictable. We could predict the motion of planets, the eclipses and appearances of comets years and centuries in advance with total accuracy. The French physicist, Pierre Simon Laplace, went a step ahead with a thought experiment, manifesting a super-intelligent being (now known as Laplace’s demon), who was aware of the motion of every particle in the universe. “If this intellect were vast enough to submit the data to analysis… for such an intellect, nothing would be uncertain and the future, just like the past would be present before its eyes”, said Laplace in A Philosophical Essay on Probabilities. That was total determinism—as if, the future is totally determinable, and we just need enough information to decipher that.
Nevertheless, Newton himself stated that his theory would explain everything in the world of a ‘fixed point attraction’ (say like the planet earth revolving the sun). But, introduce a third body (say, a moon – we have two forces of gravity now), and the equations go for a toss (known as the three-body problem—for fun, I recommend you search for the ‘motion of a double pendulum’). Well, it wasn’t clear for almost 200 years, until Henri Poincare, another French physicist, glimpsed in the late 19th century (in what later became Chaos theory) that there is no fixed solution to the three-body problem. Well, the claim that the future is determinable was fading quickly.
Chaos came into limelight in the 1960s when the American mathematician, Ed Lorenz tried to simulate the atmosphere on his computer. He had twelve variables and twelve equations, and his computer would solve for them, and show how the weather would look like. One day however, he halted the simulation mid-way, and manually entered the outcomes for the run to continue further the next day. The outcome then was totally different compared to previous runs (a totally different weather pattern). Ed had initially thought it was a tech problem (maybe the vacuum tube had broken), but later realized, that while manually entering the variables mid-way, he entered the numbers rounded to three decimals, whereas computer memory was working with six decimals.
This essentially meant that the difference of ‘one part in a thousand’, led to totally different outcomes. This later came to be known as the ‘Butterfly effect’— i.e. a butterfly flutters its wings in a rainforest in Brazil, which can lead to a tornado in California.
Essentially, the future was now not only unknown, but for some outcomes, a very tiny change in initial conditions leads to a dramatically different outcome (high sensitivity to initial conditions became the hallmark of the Chaos theory). This is precisely the reason why, despite the most sophisticated computing power now available, the weather can be forecasted for only up to seven days. By the eighth day, the forecast is as good as the long-term average for that day of the week.
If you are keen to explore this idea further, please read James Gleick’s book ‘Chaos – the amazing science of the unpredictable’. For this newsletter however, let us change track to what these findings imply for our choice of investments.
What does it mean for the investments’ framework?
To mitigate the fact that the future is not only unknown, but tiny changes could lead to dramatically unexpected outcomes, a principle of investing called the ‘margin of safety’ was popularized by investor Benjamin Graham and his followers, most notably Warren Buffet. ‘Margin of safety’ is a principle of investing in which an investor only purchases securities when their market price is significantly below their intrinsic value. Whereas the ‘intrinsic value’ can be arrived at by several methods, all of them essentially involves forecasting the future and discounting it to present value. The general idea is, that if you are paying much lower compared to intrinsic value, even if intrinsic value eventually turns out to be lower, there would be limited downside to your investments.
Over the last few years however, this theory (broadly considered to be part of the ‘value investment’ framework) has not delivered a successful outcome. Consider the example of this FMCG company listed in India. Over the last ten years, it has delivered a c23.5% CAGR in its stock price (up nine times in ten years), and now trades at a price-to-earnings ratio of c74times last reported adjusted earnings. During the same time, its net income has grown by c12.7% CAGR (and at 9.6% CAGR over the last twenty years).
Now, in order to justify just the current market price, a reverse discounted cash flow model makes the following assumptions: (a) In the initial forecast period of ten years, its free cash flows will grow at a CAGR of 20%, and (b) Terminal value is calculated assuming cost of equity of 10% and perpetual growth rate of 5%.
These are extraordinarily high estimates for any business to meet (last decade growth is only 12.7% CAGR). Under these assumptions, the company’s FCF will increase 10X (ten times) its current free cash flow by the year 2040, and 16X by 2050. And, that is built into the stock prices now! For the stock to deliver returns higher than its assumed cost of equity, it will have to positively surprise the street on the assumptions listed on point a and b above.
In addition, see the table below for how small changes in assumptions lead to dramatic change in valuations of the business. For example, if we assume that free cash flow growth during explicit forecast period falls to 10% (instead of current assumption of 20%), and terminal growth rate falls to 3% (versus base case of 5%), then the valuation of the business falls by 62%. And so on, for the various other permutations.
Obviously, there is little margin of safety in buying this business. But given (a) the lack of quality large investible businesses in India and (b) the rising inflow of money in the insurance and mutual fund industry, the value of mutual funds’ combined investment in this business stands at close to USD2b, and combined investment of mutual fund and insurance stands well over USD4b—at the highest level it has ever been since the listing of that business.
Eerie similarity to the 1960s
The example of the FMCG business above is reminiscent of the Nifty Fifty bubble in the US during the late 1960 and early 1970s. The Nifty Fifty was a group of 50 stocks identified by market commentators, although it was never an official benchmark.
The companies shared similar characteristics: high quality franchisees benefitting from surging economic growth and strong balance sheets, while delivering healthy profits and good return on equity. It was said by many investors at the time that Nifty Fifty stocks should be bought and never sold.
By the early 1970s, they had become the darling of many institutional investors and staples of their portfolios. The price to earnings ratio of some of these businesses went to stunning levels – Johnson & Johnson (57X), McDonalds, Disney and Baxter Labs (71X), International Flavours & Fragrances (69X), Avon Products (61X), Polaroid Corp (95X) and MGIC Investment Corp (69X).
The long party then ended in the early 1970s, catalysed by rising interest rates, high oil prices, political instability over the Watergate scandal and the end of the Bretton Woods monetary system. The Nifty Fifty stocks held up well even as the US markets entered a bear markets in 1973, but later came on to intense selling pressure. At their lows, they traded between 71% (Xerox) and 91% (Polaroid) lower compared to their recent highs.
A large part of what I describe above has been well documented before. However, what was the changing point in the early 1960s is eerily like what we witness in India these days. By the end of 1960s, the number of Americans holding shares increased seven times compared to the height of bubble in 1929. The decade also saw the rise of a new breed of investor – the professional fund manager. By mid 1960s, the mutual fund industry had ballooned to USD35b of AUM and started accounting for over quarter of all transactions in the stock market.
Compare that to India. Given that (a) the real estate markets have been sluggish over the last decade or so, (b) interest rates have steadily fallen and (c) demonetization of currency has limited investment avenues, the mutual fund industry in India has done well to channelize the individual savings into equity. Over the last decade or so, the AUM for equity mutual funds in India has increased by a large quantum. Given lack of large quality businesses in India, mutual funds have resorted to buying into quality businesses with little eye for valuations. Below is the list of a few such businesses where we note that re-rating has driven close to 50-70% of the stock returns over the last decade. Of course, Chaos theory dictates that, not only looking into the future, but deriving outcomes from past is equally fraught with risks. So, even this study must be read with that consideration in mind.
That brings us to the Buoyant portfolio. Readers will note that Buoyant portfolio generates a higher return on equity and capital while continuing to trade at almost half the benchmark valuation on price to earnings and enterprise value to EBITDA. The beta of the portfolio is also similar to the benchmark.
For the quarter ended June 2020, Buoyant PMS returned 23% net of all fees and expenses. The performance of various periods since inception is listed in the table below.
Buoyant’s average cash position for the quarter stood at 10.6% The composite performance above is average across all client portfolios and individual returns will differ due to variations in holdings, the subscription timing and other client-specific circumstances (as mentioned in disclosures on page 6). You should have received your individual account statements via email by now. Please get in touch with us with questions, if any.
Top holdings: ICICI Bank, Security & Intelligence Services, Welspun Corporation, HDFC Bank
Buoyant Investors: Thank you!
As always, we would like to thank all of you for your investment and partnership with Buoyant Capital. Your collective belief in our ability to make right investment decisions, your support and patience at testing times and your overall emotional stability are extremely valuable to us. We wish and hope for our continued and lasting partnership in coming times.
Jigar Mistry, for Buoyant Capital
Average returns are calculated across all the client accounts (aggregate portfolio) based on underlying data provided to us by Kotak Mahindra Bank’s Fund Accounting team – the designated fund accounting partner. Returns are not audited. Individual returns will differ from the average returns presented in this note depending on the composition of portfolio, timing of deposit, withdrawals and fee structure specific to each account. Please contact either of us with any questions about your statement, returns, fees or anything else related to your account.
Information in this newsletter is not intended to be, nor should it be construed as investment, tax or legal advice, or an offer to sell, or a solicitation of any offer to make investments with Buoyant Capital. Prospective investors should rely solely on Disclosure Document filed with SEBI.
Any description involving investment examples, statistical analysis or investment strategies are provided for illustration purposes only – and will not apply in all situations and may be changed at the discretion of principal officer.
Certain information has been provided and/or based on third-party sources and although believed to be reliable, has not been independently verified; the investment managers make no express warranty as to its completeness or accuracy, nor can it accept responsibility for errors appearing herein.