We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.
Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!
But since our readership-audience for The Good Investors is wider than our subscriber base, we think sharing the reading list regularly on the blog itself can benefit even more people. The articles we share touch on a wide range of topics, including investing, business, and the world in general.
Here are the articles for the week ending 22 September 2024:
1. Mario Draghi outlines his plan to make Europe more competitive – Mario Draghi
Across different measures, a wide gap in GDP has opened up between the European Union and America. Europe’s households have paid the price in forgone living standards. On a per-person basis, real disposable income has grown almost twice as much in America as in the EU since 2000…
…Europe largely missed out on the digital revolution led by the internet and the productivity gains it brought: in fact, the productivity gap between the EU and America since 2000 is largely explained by the tech sector. The EU remains weak in the emerging technologies that will drive future growth. European companies specialise in mature technologies where the potential for breakthroughs is limited.
The problem is not that Europe lacks ideas or ambition. But innovation is blocked at the next stage: it is not translated into commercialisation, and innovative firms that want to scale up are hindered by inconsistent and restrictive regulations. Many European entrepreneurs prefer to seek financing from American venture capitalists and scale up in the American market…
…EU companies face electricity prices that are two to three times those in America. Natural-gas prices are four to five times higher. Over time, decarbonisation will help shift power generation towards secure, low-cost clean-energy sources. But fossil fuels will still set the energy price for most of the time for at least the remainder of this decade. Unless Europe better transfers the benefits of clean energy to end-users, energy prices will continue to dampen growth…
…As the era of geopolitical stability fades, the risk of rising insecurity becoming a threat to growth and freedom is increasing. Europe is particularly exposed. The EU relies on a handful of suppliers for critical raw materials and is heavily dependent on imports of digital technology.
2. When Chasing More Dividends Leaves You With Less – Jason Zweig
In July and August, as investors became more convinced interest rates will fall, exchange-traded funds specializing in dividend-paying stocks took in $4.5 billion in new money, estimates Ryan Issakainen, a strategist at First Trust, an ETF manager in Wheaton, Ill.
Although funds with big payouts sound safe, high income can lead to a poor outcome. You need to guard against needless tax bills, overexposure to narrow segments of the market and the chance of deep long-term losses…
…To see the potential downside of these funds, though, consider Global X SuperDividend, an ETF with $784 million in assets.
It yields nearly 11%.
That’s huge compared to the income returns of roughly 1.3% on the S&P 500, 2.1% on the Dow Jones Industrial Average and 5% on short-term U.S. Treasurys.
The SuperDividend fund’s supersized yield comes at a cost. Launched in June 2011 at $75, this week the shares traded around $22. That’s a 70% decline.
If you’d bought the ETF at its inception and held continuously through the end of August, you’d have lost 9%—after accounting for all those jumbo dividends along the way…
… A company that pays a steady stream of growing dividends is probably in robust financial health, but one that pays gigantic dividends is probably struggling and may be desperate to attract investors. Put a bunch of those into an ETF, and you get lots of income but even more risk…
…High-dividend funds often hold many more energy and financial stocks than broader portfolios do. That can raise risk.
In 2008, both First Trust’s Dow Jones Global Select Dividend and its Stoxx European Select Dividend had roughly 50% of their assets in financial stocks—right before the global financial crisis struck.
Over the 12 months ended March 31, 2009, as the MSCI World index lost 42.2% and European stocks overall sank 49.6%, First Trust’s Global Select fell 53.2% and European Select lost 63.9%—even after factoring in their dividends…
…Although a moderate dividend can be a sign of robust corporate health, a huge dividend can be a distress signal. A dividend four or five times greater than that of the overall market isn’t a green light; it’s a red flag.
3. Learning From Peter Keefe – John Garrett
The investment philosophy [at our new fund, Rockbridge Capital] is exactly the same: great businesses, great managers, bargain price. That remains unchanged.
The implementation has evolved over time. Great businesses, great managers, great price—it’s kind of like mom and apple pie. I mean, who’s opposed to it? It’s axiomatic that these things work, but I believe your approach to implementation should change over time…
…You don’t really know what makes a business great. You don’t really understand what contributes to compounding. You want a business with all the great characteristics—growth, rapid growth, sustainable growth—but you don’t know how to evaluate one business against another. You don’t know which businesses are mayflies and which are incredibly durable with multi-decade runways.
Learning how to discern and implement those three criteria does evolve over time. Another thing that evolves is the recognition that there are only a tiny number of businesses you will own over the course of a career that will compound and give you that 100-bagger effect or the 300-bagger effect—what Munger called the Lollapalooza effect. Those opportunities are incredibly rare.
But you spend your entire career looking for them. On day one, when you enter the business, you might think, ‘Well, maybe I’ll find it today,’ but you’re probably not going to find it today, tomorrow, or the day after. So what has evolved for me is the realization that when you find a compounder, don’t let it go…
…Every time I’ve trimmed a position and it involved a great business, it wound up being a huge mistake.
Now, we had this conundrum recently. We own a lot of Microsoft, which we bought back in the Balmer days. So it’s been in the portfolio over 10 years. We’ve made 10 times our money in the business, and it’s appreciated to have a very significant percentage of our portfolios.
Microsoft got a big bid recently because of the artificial intelligence stuff, and I don’t know enough about artificial intelligence to have a responsible opinion. But you can argue that there’s a trillion dollars’ worth of value in Microsoft attributable to AI. Do I trim the position? Well, based on the mistakes I’ve made in the past, no. But at the same time, is a 35 or 40 multiple sustainable for a company that’s already worth three trillion dollars? It’s hard to make that argument. And particularly when you’re managing both taxable and tax-exempt capital, you can make a pretty good argument that you should trim it. But again, that’s never worked out for me. So we are where we are.”…
…Every time we’ve had a business that’s compounded more than 10x—and we’ve had a couple that have compounded at 100x—there’s always been a leader and visionary who is a person of humility, thinking about their business in multi-decade timelines. Without exception, 10, 100, 200-baggers were always a person…
… They’re not thinking about an exit or the next thing; they’re thinking in 10, 20, 30-year time periods.
These people are artists. They’re focused on building something of great value—not just to accumulate wealth, but to create something valuable to society. To borrow from Tom Gayner, these are businesses that do something for people instead of to people. They are financially interested, but the finances are a means of keeping score rather than acquiring more things or a better jet. Those are the people I shy away from. The real artists see beauty in what they’re building and are focused on creating value for all stakeholders, especially the owners of the business.
When discussing people who want to serve all stakeholders, it’s not about rank-ordering which stakeholders to reward first. It’s about understanding that a business can do well for its employees, shareholders, and vendors. Munger talked about this all the time…
…People ask, ‘What makes you different?’ Well, it’s not my process. Everybody wants great businesses and great managers and to buy them at a bargain price. Nobody says they’re not a value investor or that they don’t like what Buffett does. So I think a major differentiator in this business is temperament. If I have an advantage, it’s that I don’t feel like I’m coming unglued when the world is coming unglued. I don’t know why that is; it’s just part of my makeup, but it’s an advantage because low prices are good for investors…
…The biggest compounder I’ve ever had in the investment business was American Tower. I was fortunate enough to figure out American Tower before it was even a public company. It was a footnote in the 10-K of a company called American Radio Systems. American Radio Systems was run by a brilliant, thoughtful capital allocator who fits into this liberal arts bucket I talked about earlier. Steve Dodge went to Yale and was an English major there.
Steve did cable transactions for one of the big New York banks. He got the idea that recurring revenue businesses or contractual revenue were great. So he moved into the cable business and then into the radio business. Around the time of the Telecom Act in the mid-1990s, digital networks for cell networks were beginning to roll out. Steve had people come to him and say, ‘We’d like to hang some of these digital antennas on your radio antennas.’ They also owned a portfolio of television broadcast antennas. They needed structures in suitable locations for these antennas.
That’s the genesis of American Tower, which was just a footnote. I remember calling Steve and asking about it. He basically hung up on me. I had a good relationship with him, so I knew I was onto something.
Long story short, American Tower was spun off and went to over $40 a share. Then came the dot-com bust. There had been a land rush in the tower business, and many companies had gotten levered up.
This was when I learned one of my early lessons about leverage, although it eventually helped me. American Tower dropped to under 80 cents a share from $44. Now that’s a drawdown.
I went up to Boston, where American Tower was headquartered. Chuck Akre was with me, and we met with Steve. He said, ‘I’ll tell you anything that I can legally tell you. I want you to know upfront that I don’t have much time. I have a business that needs my attention. It needs more attention than I can possibly give it because there’s only 24 hours in a day. I think that we can save this thing and I’m not sure that we can, but I also want to tell you, I am solely responsible. This is the worst thing that’s happened to me in my business career, but you’re looking at the guy who made the mistakes that got us in the pickle that we’re in.’
There was none of the usual excuses like ‘The dog ate my homework,’ or blaming the pandemic or the dot-com bust. Steve gave us none of that.
Steve figuratively raised his hand and said, ‘I messed it up, and I am sorry. I will do my best to get you and all the other shareholders out of this pickle.’
That kind of character in a moment of great crisis inspired me and others to make American Tower a more significant position, despite its distress.
We were convinced that the business wasn’t going to zero. It had one of the greatest business models in public companies’ history. A business where 100% of incremental revenue flows through to free cash flow and was growing by 20 to 30% a year. It was highly likely the business would be recapitalized. I can’t think of a financing environment where it wouldn’t be.
Steve’s character and willingness to accept responsibility were crucial in our decision to increase our position. It went up 300-fold from there.
4. Light-Based Chips Could Help Slake AI’s Ever-Growing Thirst for Energy – Amos Zeeberg
Recent results suggest that, for certain computational tasks fundamental to modern artificial intelligence, light-based “optical computers” may offer an advantage…
…In theory, light provides tantalizing potential benefits. For one, optical signals can carry more information than electrical ones—they have more bandwidth. Optical frequencies are also much higher than electrical ones, so optical systems can run more computing steps in less time and with less latency.
And then there’s the efficiency problem. In addition to the environmental and economic costs of relatively wasteful electronic chips, they also run so hot that only a tiny fraction of the transistors—the tiny switches at the heart of all computers—can be active at any moment. Optical computers could, in theory, run with more operations taking place simultaneously, churning through more data while using less energy…
…Seeing the potential advantages, researchers have long tried to use light for AI, a field with heavy computational needs. In the 1980s and 1990s, for instance, researchers used optical systems to build some of the earliest neural networks. Demetri Psaltis and two colleagues at the California Institute of Technology created a clever facial recognition system using one of these early optical neural networks (ONNs). They stored images of a subject—one of the researchers, in fact—as holograms in a photorefractive crystal. The researchers used the holograms to train an ONN, which could then recognize new images of the researcher and distinguish him from his colleagues.
But light also has shortcomings. Crucially, photons generally don’t interact with each other, so it’s hard for one input signal to control another signal, which is the essence of what ordinary transistors do. Transistors also work exceptionally well. They’re now laid down on coin-size chips by the billion, the products of decades of incremental improvements…
…The process of multiplying matrices, or arrays of numbers, undergirds a lot of heavy-duty computing. In neural networks, specifically, matrix multiplication is a fundamental step both in how networks are trained on old data and in how new data is processed in trained networks. And light just might be a better medium for matrix multiplication than electricity.
This approach to AI computation exploded in 2017, when a group led by Dirk Englund and Marin Soljačić of the Massachusetts Institute of Technology described how to make an optical neural network built on a silicon chip. The researchers encoded the various quantities they wanted to multiply into beams of light, then sent the beams through a series of components that altered the beam’s phase—the way its light waves oscillated—with each phase alteration representing a multiplication step. By repeatedly splitting the beams, changing their phase, and recombining them, they could make the light effectively carry out matrix multiplication. At the end of the chip, the researchers placed photo detectors that measured the light beams and revealed the result.
The researchers taught their experimental device to recognize spoken vowels, a common benchmark task for neural networks…
…Since that 2017 paper, the field has seen steady improvement, as various researchers have come up with new kinds of optical computers. Englund and several collaborators recently unveiled a new optical network they call HITOP, which combines multiple advances. Most importantly, it aims to scale up the computation throughput with time, space, and wavelength. Zaijun Chen, a former MIT postdoc now based at the University of Southern California, said this helps HITOP overcome one of the drawbacks of optical neural networks: It takes significant energy to transfer data from electronic components into optical ones, and vice versa. But by packing the information into three dimensions of light, Chen said, it shoves more data through the ONN faster and spreads the energy cost over many calculations. This drives down the cost per calculation. The researchers reported that HITOP could run machine-learning models 25,000 times larger than previous chip-based ONNs.
To be clear, the system is still far from matching its electronic predecessors; HITOP performs about 1 trillion operations per second, whereas sophisticated Nvidia chips can chug through 300 times as much data, said Chen, who hopes to scale up the technology to make it more competitive. But the optical chip’s efficiency is compelling. “The game here is that we lowered the energy cost 1,000 times,” Chen said…
…While optical computing has advanced quickly over the past several years, it’s still far from displacing the electronic chips that run neural networks outside of labs. Papers announce photonic systems that work better than electronic ones, but they generally run small models using old network designs and small workloads. And many of the reported figures about photonic supremacy don’t tell the whole story, said Bhavin Shastri of Queen’s University in Ontario. “It’s very hard to do an apples-to-apples comparison with electronics,” he said. “For instance, when they use lasers, they don’t really talk about the energy to power the lasers.”
Lab systems need to be scaled up before they can show competitive advantages. “How big do you have to make it to get a win?” McMahon asked. The answer: exceptionally big. That’s why no one can match a chip made by Nvidia, whose chips power many of the most advanced AI systems today. There is a huge list of engineering puzzles to figure out along the way—issues that the electronics side has solved over decades. “Electronics is starting with a big advantage,” said McMahon.
Some researchers think ONN-based AI systems will first find success in specialized applications where they provide unique advantages. Shastri said one promising use is in counteracting interference between different wireless transmissions, such as 5G cellular towers and the radar altimeters that help planes navigate. Early this year, Shastri and several colleagues created an ONN that can sort out different transmissions and pick out a signal of interest in real time and with a processing delay of under 15 picoseconds (15 trillionths of a second)—less than one-thousandth of the time an electronic system would take, while using less than 1/70 of the power.
5. Warren Buffett Case Study: Arbitrage – Dirtcheapstocks
By 1981, Arcata was the second largest printing services organization in the U.S. In addition, Arcata owned 77,500 acres of Northern California timberlands, which it used for timber harvesting, reforestation and milling.
Arcata was to be acquired by KKR. The stock was trading around $33/share at the time of the deal announcement. KKR’s $37 offer represented a reasonable premium over the current share price. But there was one other interesting bit of information.
“In 1978 the U.S. Government had taken title to 10,700 acres of Arcata timber, primarily old-growth redwood, to expand Redwood National Park. The government had paid $97.9 million, in several installments, for this acreage, a sum Arcata was contesting as grossly inadequate. The parties also disputed the interest rate that should apply to the period between the taking of the property and final payment for it. The enabling legislation stipulated 6% simple interest; Arcata argued for a much higher and compounded rate.” – Warren Buffett
“Buying a company with a highly speculated, large-sized claim in litigation creates a negotiating problem, whether the claim is on behalf of or against the company. To solve this problem, KKR offered $37.00 per Arcata share plus two-thirds of any additional amounts paid by the government for the redwood lands.” – Warren Buffett…
…“We started buying Arcata stock, then around $33.50, on September 30 and in eight weeks purchased about 400,000 shares, or 5% of the company. The initial announcement said that the $37.00 would be paid in January 1982. Therefore, if everything had gone perfectly, we would have achieved an annual rate of return of about 40% — not counting the redwood claim, which would have been frosting.” – Warren Buffett
“All did not go perfectly. In December it was announced that the closing would be delayed a bit. Nevertheless, a definitive agreement was signed on January 4. Encouraged, we raised our stake, buying at around $38.00 per share and increasing our holdings to 655,000 shares, or over 7% of the company. Our willingness to pay up – even though the closing had been postponed – reflected our leaning toward ‘a whole lot’ rather than ‘zero’ for the redwoods.” – Warren Buffett…
…“On March 12, KKR said its earlier deal wouldn’t work, first cutting its offer to $33.50, then two days later raising it to $35.00. On March 15, however, the directors turned this bid down and accepted another group’s offer of $37.50 plus one-half of any redwood recovery.” – Warren Buffett…
…“The trial judge appointed two commissions, one to look at the timber’s value, the other to consider the interest rate questions. In January 1987, the first commission said the redwoods were worth $275.7 million and the second commission recommended a compounded, blended rate of return working out to about 14%.” – Warren Buffett
“In August 1987 the judge upheld these conclusions, which meant a net amount of about $600 million would be due Arcata. The government then appealed. In 1988, though, before this appeal was heard, the claim was settled for $519 million. Consequently, we received an additional $29.48 per share, or about $19.3 million. We will get another $800,000 or so in 1989.” – Warren Buffett
The final result: 39% IRR…
…The greatest investor to ever live earns a 39% IRR in a low-risk arb deal. The most striking part of this case is not the return generated – but the lack of risk taken.
Arcata was a profitable, growing business. Take a look at its five-year history leading up to the deal.
Arcata had strong operating businesses that earned sufficient sums to cover its interest burden with plenty of comfort.
Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. We currently have a vested interest in Microsoft. Holdings are subject to change at any time.