JPMorgan Chase (NYSE: JPM) is currently the largest bank in the USA by total assets. Because of this status, JPMorgan is naturally able to feel the pulse of the country’s economy. The bank’s latest earnings conference call – for the first quarter of 2024 – was held two weeks ago and contained useful insights on the state of American consumers and businesses. The bottom-line is this: Economic indicators in the US continue to be favourable and American consumers are in good shape, but there are a number of risks on the horizon, so JPMorgan’s management is preparing for a wide range of outcomes.  

What’s shown between the two horizontal lines below are quotes from JPMorgan’s management team that I picked up from the call.

---

1. Management sees economic indicators in the USA as favourable, but there are many risks on the horizon (including geopolitical conflicts, inflationary pressures, and the Fed’s quantitative tightening) so they want to be prepared for a range of outcomes; the economy always looks healthy at the inflection point; management thinks the US economy will be affected even if problems happen elsewhere

Many economic indicators continue to be favorable. However, looking ahead, we remain alert to a number of significant uncertain forces. First, the global landscape is unsettling – terrible wars and violence continue to cause suffering, and geopolitical tensions are growing. Second, there seems to be a large number of persistent inflationary pressures, which may likely continue. And finally, we have never truly experienced the full effect of quantitative tightening on this scale. We do not know how these factors will play out, but we must prepare the Firm for a wide range of potential environments to ensure that we can consistently be there for clients…

…But what I caution people, these are all the same results [referring to the comments in Point 2 and Point 6 below about consumers and businesses being in good shape] of a lot of fiscal spending, a lot of QE, et cetera. And so we don’t really know what’s going to happen. And I also want to look at the year, look at 2 years or 3 years, all the geopolitical effects and oil and gas and how much fiscal spending will actually take place, our elections, et cetera. So we’re in good — we’re okay right now. It does not mean we’re okay down the road. And if you look at any inflection point, being okay in the current time is always true. That was true in ’72, it was true in any time you’ve had it. So I’m just on the more cautious side that how people feel, the confidence levels and all that, that doesn’t necessarily stop you from having an inflection point. And so everything is okay today, but you’ve got to be prepared for a range of outcomes, which we are…

…I think that when we talk about the impact of the geopolitical uncertainty on the outlook, part of the point there is to note that the U.S. is not isolated from that, right? If we have global macroeconomic problems as a result of geopolitical situations, that’s not only a problem outside the U.S. That affects the global economy and therefore the U.S. and therefore our corporate customers, et cetera, et cetera.

2. Management is seeing consumers remain healthy with overall spend in line with a year ago, and although their cash buffers have normalised, they are still higher than pre-COVID levels; management thinks consumers will be in pretty good shape even if there’s a recession; the labour market remains healthy with wages keeping pace with inflation

Consumers remain financially healthy, supported by a resilient labor market. While cash buffers have largely normalized, balances were still above pre-pandemic levels, and wages are keeping pace with inflation. When looking at a stable cohort of customers, overall spend is in line with the prior year…

… I would say consumer customers are fine. The unemployment is very low. Home price dropped, stock price dropped. The amount of income they need to service their debt is still kind of low. But the extra money of the lower-income folks is running out — not running out, but normalizing. And you see credit normalizing a little bit. And of course, higher-income folks still have more money. They’re still spending it. So whatever happens, the customer’s in pretty good shape. And they’re — if you go into a recession, they’d be in pretty good shape.

3. Auto originations are down

And in auto, originations were $8.9 billion, down 3%, while we maintained healthy margins and market share.

4. Net charge-offs (effectively bad loans that JPMorgan can’t recover) rose from US$1.1 billion a year ago, mostly because of card-related credit losses that are normalising to historical norms; management expects consumer-spending on credit/debit cards to have strong growth in 2024

In terms of credit performance this quarter, credit costs were $1.9 billion, driven by net charge-offs, which were up $825 million year-on-year predominantly due to continued normalization in Card…

…And in Card, of course, while charge-offs are now close to normalized, essentially, we did go through an extended period of charge-offs being very low by historical standards, although that was coupled with NII also being low by historical standards…

….Yes, we still expect 12% card loan growth for the full year. 

5. The level of appetite that companies have for capital markets activity is uncertain to management

While we are encouraged by the level of capital markets activity we saw this quarter, we need to be mindful that some meaningful portion of that is likely pulling forward from later in the year. Similarly, while it was encouraging to see some positive momentum in announced M&A in the quarter, it remains to be seen whether that will continue, and the Advisory business still faces structural headwinds from the regulatory environment…

…Let me take the IPO first. So we had been a little bit cautious there. Some cohorts and vintages of IPOs had performed somewhat disappointingly. And I think that narrative has changed to a meaningful degree this quarter. So I think we’re seeing better IPO performance. Obviously, equity markets have been under a little bit of pressure the last few days. But in general, we have a lot of support there, and that always helps. Dialogue is quite good. A lot of interesting different types of conversations happening with global firms, multinationals, carve-out type things. So dialogue is good. Valuation environment is better, like sort of decent reasons for optimism there. But of course, with ECM [Equity Capital Markets], there’s always a pipeline dynamic, and conditions were particularly good this quarter. And so we caution a little bit there about pull-forward, which is even more acute, I think, on the DCM [Debt Capital Markets] side, given that quite a high percentage of the total amount of debt that needed to be refinanced this year has gotten done in the first quarter. So that’s a factor.

And then the question of M&A, I think, is probably the single most important question, not only because of its impact on M&A but also because of its knock-on impact on DCM through acquisition financing and so on. And there’s the well-known kind of regulatory headwinds there, and that’s definitely having a bit of a chilling effect. I don’t know. I’ve heard some narratives that maybe there’s like some pent-up deal demand. Who knows how important politics are in all this. So I don’t know.  

6. Management is seeing that businesses are in good shape

Businesses are in good shape. If you look at it today, their confidence is up, their order books drop, their profits are up.

7. Management thinks that the generally accepted economic scenario is nearly always wrong and that no one can accurately predict an inflection point in the economy

And the other thing I want to point out because all of these questions about interest rates and yield curves and NII and credit losses, one thing you projected today based on what — not what we think in economic scenarios, but the generally accepted economic scenario, which is the generally accepted rate cuts of the Fed. But these numbers have always been wrong. You have to ask the question, what if other things happen? Like higher rates with this modest recession, et cetera, then all these numbers change. I just don’t think any of us should be surprised if and when that happens. And I just think the chance of that happen is higher than other people. I don’t know the outcome. We don’t want to guess the outcome. I’ve never seen anyone actually positively predict a big inflection point in the economy literally in my life or in history.

8. Management thinks the US commercial real estate market is fine, at least when it comes to JPMorgan’s portfolio; management thinks that if interest rates rise, it could be roughly neutral or really bad for the real estate market, depending on the reason for the increase in interest rates

First of all, we’re fine. We’ve got good reserves against office. We think the multifamily is fine. Jeremy can give you more detail on that if you want.

But if you think of real estate, there’s 2 pieces. If rates go up, think of the yield curve, the whole yield curve, not Fed funds, but the 10-year bond rate, it goes up 2%. All assets, all assets, every asset on the planet, including real estate, is worth 20% less. Well obviously, that creates a little bit of stress and strain, and people have to roll those over and finance it more. But it’s not just true for real estate, it’s true for everybody. And that happens, leveraged loans, real estate will have some effect.

The second thing is the why does that happen? If that happens because we have a strong economy, well, that’s not so bad for real estate because people will be hiring and filling things out. And other financial assets. If that happens because we have stagflation, well, that’s the worst case. All of a sudden, you are going to have more vacancies. You are going to have more companies cutting back. You are going to have less leases. It will affect — including multifamily, that will filter through the whole economy in a way that people haven’t really experienced since 2010. So I’d just put in the back of your mind, the why is important, the interest rates are important, the recession is important. If things stay where they are today, we have kind of the soft landing that seems to be embedded in the marketplace, everyone — the real estate will muddle through.

9. Consumers whose real incomes are down are slowing their spending, but they account for only a small proportion of the overall population, and they are not levering up irresponsibly

And there are some such people whose real incomes are not up, they’re down, and who are therefore struggling a little bit, unfortunately. And what you observe in the spending patterns of those people is some meaningful slowing rather than what you might have feared, which is sort of aggressive levering up. So I think that’s maybe an economic indicator of sorts, although this portion of the population is small enough that I’m not sure the read-across is that big. But it is encouraging from a credit perspective because it just means that people are behaving kind of rationally and in a sort of normal post-pandemic type of way as they manage their own balance sheets. 

---

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. I don’t have a vested interest in any company mentioned. Holdings are subject to change at any time.

Jeremy and I have not invested in an oil & gas company for years. The reason can be traced to the very first stocks I bought when I started investing. Back then, in October 2010, I bought six US-listed stocks at one go, two of which were Atwood Oceanics and National Oilwell Varco (or NOV). Atwood was an owner of oil rigs while NOV supplied parts and equipment that kept oil rigs running. 

I invested in them because I wanted to be diversified according to sectors. I thought that oil & gas was a sector that was worth investing in since the demand for oil would likely remain strong for a long time. My view on the demand for oil was right, but the investments still went awry. By the time I sold Atwood and NOV in September 2016 and June 2017, respectively, their stock prices were down by 77% and 31% from my initial investments. 

It turned out that while global demand for oil did indeed grow from 2010 to 2016 – the consumption of oil increased from 86.5 million barrels per day to 94.2 million barrels – oil prices still fell significantly over the same period, from around US$80 per barrel to around US$50. I was not able to predict prices for oil and I had completely missed out on the important fact that these prices would have an outsized impact on the business fortunes of both Atwood and NOV.

In its fiscal year ended 30 September 2010 (FY2010), Atwood’s revenue and net income were US$650 million and US$257 million, respectively. By FY2016, Atwood’s revenue had increased to US$1.0 billion, but its net income barely budged, coming in at US$265 million. Importantly, its return on equity fell from 21% to 9% in that period while its balance sheet worsened dramatically. For perspective, Atwood’s net debt (total debt minus cash and equivalents) ballooned from US$49 million in FY2010 to US$1.1 billion in FY2016.

As for NOV, from 2010 to 2016, its revenue fell from US$12.2 billion to US$7.2 billion and its net income collapsed from US$1.7 billion to a loss of US$2.4 billion. This experience taught me to be wary of companies whose business results have strong links to commodity prices, since I had no ability to foretell their movements. 

Fast forward to the launch of the investment fund that Jeremy and I run in July 2020, and I was clear that I still had no ability to divine oil prices – and neither did Jeremy. Said another way, we were fully aware that companies related to the oil & gas industry were beyond our circle of competence. Then 2022 rolled around and during the month of August, we came across a US-listed oil & gas company named Unit Corporation. 

At the time, Unit had three segments that spanned the oil & gas industry’s value chain: Oil and Natural Gas; Mid-Stream, and Contract Drilling. In the Oil and Natural Gas segment, Unit owned oil and natural gas fields in the USA – most of which were in the Anadarko Basin in the Oklahoma region – and was producing these natural resources. The Mid-Stream segment consisted of Unit’s 50% ownership of Superior Pipeline Company, which gathers, processes, and treats natural gas, and owns more than 3,800 miles of gas pipelines (a private equity firm, Partners Group, controlled the other 50% stake). The last segment, Contract Drilling, is where Unit owned 21 available-for-use rigs for the drilling of oil and gas.

When we first heard of Unit in August 2022, it had a stock price of around US$60, a market capitalisation of just over US$560 million, and an enterprise value (market capitalisation minus net-cash) of around US$470 million (Unit’s net-cash was US$88 million back then). But the company’s intrinsic value could be a lot higher. 

In January 2022, Unit launched a sales process for its entire Oil and Natural Gas segment, pegging the segment’s proven, developed, and producing reserves at a value of US$765 million. This US$765 million value came from the estimated future cash flows of the segment – based on oil prices we believe were around US$80 per barrel – discounted back to the present at 10% per year. Unit ended the sales process for the Oil and Natural Gas segment in June 2022 after selling only a small portion of its assets for US$45 million. Nonetheless, when we first knew Unit, the Oil and Natural Gas segment probably still had a value that was in the neighbourhood of the company’s estimation during the sales process, since oil prices were over US$80 per barrel in August 2022. Meanwhile, we also saw some estimates in the same month that it would cost at least US$400 million for someone to build the entire fleet of rigs that were in the Contract Drilling segment. As for the Mid-Stream segment, due to Superior Pipeline’s ownership structure and the cash flows it was producing, the value that accrued to Unit was not significant*.

So here’s what we saw in Unit in August 2022 after putting everything together: The value of the company’s Oil and Natural Gas and Contract-Drilling segments (around US$765 million and US$400 million, respectively) dwarfed its enterprise value of US$470 million.

But there was a catch. The estimated intrinsic values of Unit’s two important segments – Oil and Natural Gas, and Contract Drilling – were based on oil prices in the months leading up to August 2022. This led Jeremy and I to attempt to expand our circle of competence: We wanted to better understand the drivers for oil prices. There were other motivations. First, Warren Buffett was investing tens of billions of dollars in the shares of oil & gas companies such as Occidental Petroleum and Chevron in the first half of 2022. Second, we also came across articles and podcasts from oil & gas investors discussing the supply-and-demand dynamics in the oil market that could lead to sustained high prices for the energy commodity. So, we started digging into the history of oil prices and what influences it.

Here’s a brief history on major declines in the price of WTI Crude over the past four decades:

• 1980 – 1986: From around US$30 to US$10
• 1990 – 1994: From around US$40 to less than US$14
• 2008 – 2009: From around US$140 to around US$40
• 2014 – 2016: From around US$110 to less than US$33
• 2020: From around US$60 to -US$37 

Since oil is a commodity, it would be logical to think that differences in the level of oil’s supply-and-demand would heavily affect its price movement – when demand is lower than supply, prices would crash, and vice versa. The UK-headquartered BP, one of the largest oil-producing companies in the world, has a dataset on historical oil production and consumption going back to 1965. BP’s data is plotted in Figure 1 below and it shows that from 1981 onwards, the demand for oil (consumption) was higher than the supply of oil (production) in every year. What this means is the price of oil has surprisingly experienced at least five major crashes over the past four decades despite its demand being higher than supply over the entire period. 

Figure 1; Source: BP

We shared our unexpected findings with our network of investor friends, which included Vision Capital’s Eugene Ng. He was intrigued and noticed that the U.S. Energy Information Administration (EIA) maintained its own database for long-term global oil consumption and production. After obtaining similar results from EIA’s data compared to what we got from BP, Eugene asked the EIA how it was possible for oil consumption to outweigh production for decades. The EIA responded and Eugene kindly shared the answers with us. It turns out that there could be errors within EIA’s data. The possible sources of errors come from incomplete accounting of Transfers and Backflows in oil balances: 

• Transfers include the direct and indirect conversion of coal and natural gas to petroleum.
• Backflows refer to double-counting of oil-streams in consumption. Backflows can happen if the data collection process does not properly account for recycled streams.

The EIA also gave an example of how a backflow could happen with the fuel additive, MTBE, or methyl tert-butyl ether (quote is lightly edited for clarity):

“The fuel additive MTBE is an useful example of both, as its most common feedstocks are methanol (usually from a non-petroleum fossil source) and Iso-Butylene whose feedstock likely comes from feed that has already been accounted for as butane (or iso-butane) consumption. MTBE adds a further complexity in that it is often exported as a chemical and thus not tracked in the petroleum trade balance.”

Thanks to the EIA, we realised that BP’s historical data on the demand and supply of oil might contain errors and how they could have happened. But despite knowing this, Jeremy and I still could not tell what the actual demand-and-supply dynamics of oil were during the five major price crashes that happened from the 1980s to today**. We tried expanding our circle of competence to creep into the oil & gas industry, but were stopped in our tracks. As a result, we decided to pass on investing in Unit. 

I hope that my sharing of how Jeremy and I attempted to enlarge our circle of competence would provide any of you reading this ideas on how you can improve your own investing process. 

*In April 2018, Unit sold a 50% stake in Superior Pipeline to entities controlled by Partners Group – that’s how Partners Group’s aforementioned 50% control came about. When we first studied Unit in August 2022, either Unit or Partners Group could initiate a process after April 2023 to liquidate Superior Pipeline or sell it to a third-party. If a liquidation or sale of Superior Pipeline were to happen, Partners Group would be entitled to an annualised return of 7% on its initial investment of US$300 million before Unit could receive any proceeds; as of 30 June 2022, a sum of US$354 million was required for Partners Group to achieve its return-goal. In the first half of 2022, the cash flow generated by Superior Pipeline was US$24 million, which meant that Unit’s Mid-stream segment was on track to generate around US$50 million in cash flow for the whole of 2022. We figured that a sale of Superior Pipeline in April 2023, with around US$50 million in 2022 cash flow, would probably fetch a total amount that was in the neighbourhood of the US$354 million mentioned earlier that Partners Group was entitled to. So if Superior Pipeline was sold, there would not be much proceeds left for Unit after Partners Group has its piece. 

**If you’re reading this and happen to have insight on the actual historical levels of production and consumption of oil during the past crashes, we would deeply appreciate it if you could get in touch with us. Thanks in advance!

---

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.  I currently have no vested interest in any company mentioned. Holdings are subject to change at any time.

JPMorgan Chase (NYSE: JPM) is currently the largest bank in the USA by total assets. Because of this status, JPMorgan is naturally able to feel the pulse of the country’s economy. The bank’s latest earnings conference call – for the fourth quarter of 2023 – was held two weeks ago and contained useful insights on the state of American consumers and businesses. The bottom-line is this: The US economy remains resilient, but there are significant risks that are causing JPMorgan’s management team to be cautious.  

What’s shown between the two horizontal lines below are quotes from JPMorgan’s management team that I picked up from the call.

---

1. The US economy and consumer remains resilient, and management’s base case is that consumer credit remains strong, although loan losses (a.k.a net charge-off rate) for credit cards is expected to be “<3.5%” in 2024 compared to around 2.5% for 2023

The U.S. economy continues to be resilient, with consumers still spending, and markets currently expect a soft landing…

…We continue to expect the 2024 card net charge-off rate to be below 3.5%, consistent with Investor Day guidance…

…In terms of consumer resilience, I made some comments about this on the press call. The way we see it, the consumers find all of the relevant metrics are now effectively normalized. And the question really in light of the fact that cash buffers are now also normal, but that, that means that consumers have been spending more than they’re taking in is how that spending behavior adjusts as we go into the new year, in a world where cash buffers are less comfortable than they were. So one can speculate about different trajectories that, that could take, but I do think it’s important to take a step back and remind ourselves that consistent with that soft landing view, just in the central case modeling, obviously, we always worry about the tail scenarios is a very strong labor market. And a very strong labor market means, all else equal, strong consumer credit. So that’s how we see the world.

2.  Management thinks that inflation and interest rates may be higher than markets expect…

It is important to note that the economy is being fueled by large amounts of government deficit spending and past stimulus. There is also an ongoing need for increased spending due to the green economy, the restructuring of global supply chains, higher military spending and rising healthcare costs. This may lead inflation to be stickier and rates to be higher than markets expect.

3. …and they’re also cautious given the multitude of risks they see on the horizon

On top of this, there are a number of downside risks to watch. Quantitative tightening is draining over $900 billion of liquidity from the system annually, and we have never seen a full cycle of tightening. And the ongoing wars in Ukraine and the Middle East have the potential to disrupt energy and food markets, migration, and military and economic relationships, in addition to their dreadful human cost. These significant and somewhat unprecedented forces cause us to remain cautious.

4. Management is seeing a deterioration in the value of commercial real estate

The net reserve build was primarily driven by loan growth in card and the deterioration in the outlook related to commercial real estate valuations in the commercial bank.

5. Auto loan growth was strong

And in auto, originations were $9.9 billion, up 32% as we gained market share, while retaining strong margins.

6. Overall capital markets activity is picking up, but merger & acquisition (M&A) activity still remains weak…

We are starting the year with a healthy pipeline, and we are encouraged by the level of capital markets activity, but announced M&A remains a headwind and the extent as well as the timing of capital markets normalization remains uncertain…

…Gross Investment Banking and Markets revenue of $924 million was up 32% year-on-year primarily reflecting increased capital markets and M&A activity…

…So as you know, all else equal, this more dovish rate environment is, of course, supportive for capital markets. So if you go into the details a little bit, if you start with ECM [Equity Capital Markets], that helps higher — and the recent rally in the equity markets helps. I think there have been some modest challenges with the 2023 IPO vintage in terms of post-launch performance or whatever. So that’s a little bit of a headwind at the margin in terms of converting the pipeline, but I’m not too concerned about that in general. So I would expect to see rebound there. In DCM [Debt Capital Markets], again all else equal, lower rates are clearly supportive. One of the nuances there is the distinction between the absolute level of rates and the rate of change. So sometimes you see corporates seeing and expecting lower rates and, therefore, waiting to refinance in the hope of even lower rates. So that can go both ways. And then M&A, it’s a slightly different dynamic. I think there’s a couple of nuances there. One, as you obviously know, announced volume was lower this year. So that will be a headwind in reported revenues in 2024, all else equal. And of course, we are in an environment of M&A regulatory headwinds, as has been heavily discussed. But having said that, I think we’re seeing a bit of pickup in deal flow, and I would expect the environment to be a bit more supportive. 

7. …and appetite for loans among businesses is muted

C&I loans were down 2%, reflecting lower revolver utilization and muted demand for new loans as clients remain cautious…

…We expect strong loan growth in card to continue but not at the same pace as 2023. Still, this should help offset some of the impact of lower rates. Outside of card, loan growth will likely remain muted. 

8. Management is not seeing any changes to their macro outlook for the US economy

So the weighted average unemployment rate and the number is still 5.5%. We didn’t have any really big revisions in the macro outlook driving the numbers, and our skew remains as it has been, a little bit skewed to the downside. 

9. Management’s outlook for 2024 includes six rate-cuts by the Fed, but that outlook comes from financial market data, and not from management’s insights

[Question] Coming back to your outlook and forecast for net interest income for the upcoming year with the 6 Fed fund rate cuts that you guys are assuming. Can you give us a little insight why you’re assuming 6 cuts? 

[Answer] I wish the answer were more interesting, but it’s just our practice. We just always use the forward curve for our outlook, and that’s what’s in there.

---

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. I don’t have a vested interest in any company mentioned. Holdings are subject to change at any time.

How much should you pay for a stock to get a 10% return? In this article I explore a valuation method that helps me find just that.

The dividend discount model

First, we need to understand that the core concept of investing is that we are investing to earn a stream of future cash flows. Ideally, the amount we receive in the future should exceed the amount we invest today.

In this exercise, I’ll make one assumption: We are long term “buy and never sell investors” who make our money through the cash a company returns to shareholders as dividends.

Using this assumption, we should use the dividend discount model to value a stock. A dividend discount model discounts all future dividend income back to the present. It also assumes that you can reinvest the dividend at a rate similar to the discount rate.

Achieving a 10% return

So how do you get a 10% return? Let’s start with a simple example. Suppose a company will pay $1 per share in dividends for 10 years. At the end of the 10 years, it closes down with no liquidation value.

In total, you will receive $10 per share in dividends.

Using a dividend discount model, and discounting all the dividends to the present day at a 10% discount rate, we can calculate that the price to pay for the stock is $6.14. You can find the calculation in this spreadsheet.

Just looking at the price alone, it may seem strange that the dividend yield that you are getting is more than 10%.

At $6.14 per share, you will be earning a dividend yield of 16.3% but your annual return is still 10%. This is because the company closes down after 10 years and your initial capital will not be returned to you. To make up for that, you need to generate more than 10% in your annual dividend yield just to make a 10% annualised return. 

More durable companies

In the above scenario, the company is not durable and is only able to pay you a dividend for 10 years. But for more durable companies, you can afford to pay more to achieve the same return.

For instance, there’s a more durable company that pays $1 per share in dividend for 20 years before closing down. In this scenario, you can pay $8.51 per share to earn a 10% return.

The more durable the company, the more you can pay. If a company can pay you $1 per share in dividend for eternity, you can pay $10 per share to earn a 10% yield and a 10% return.

Vicom – a no-growth company

An example of a steady but no-growth company is Vicom, which provides car inspection services in Singapore. It is a stable business as Singapore’s law requires vehicles to undergo regular inspections for road-worthiness. 

Vicom, with its longstanding history, is also trusted by Singapore’s authorities to provide these inspection services, making it difficult for competitors to encroach into the space. But there is limited opportunity for Vicom to grow as the authorities regulates the number of vehicles given entitlement to be owned and driven in Singapore, resulting in zero vehicle-growth in Singapore for many years. In addition, the inspection fees are also likely regulated by the government, ensuring that consumers are protected from price gouging.

As a result, Vicom’s annual net income has hovered around S$25 million for years. The company also pays out around 100% of its net profit to shareholders.

Given all of this, as well as assuming that Vicom’s business can sustain for a long period of time and we want a 10% annualised return from owning Vicom’s shares, Vicom’s value should be S$250 million, representing a dividend yield of around 10%. Vicom’s current market cap is around S$450 million, which means that shareholders will earn less than a 10% rate of return.

Amphenol – a growth stock

Amphenol Corporation, a company based in the USA, designs and manufactures electronic connectors and sensors. Unlike Vicom, Amphenol has a track record of growing revenue and earnings per share while paying a growing dividend.

Since 2011, Amphenol’s revenue and earnings per share has compounded at 10.5% and 13% per year, respectively. In addition, the company’s dividend per share has grown from US$0.02 per share in 2011 to US$0.83 per share in 2022, for an annulised growth rate of 40%. Amphenol’s business can likely continue to grow at a steady rate if the company continues to acquire other companies for growth.

How much will you pay for its stock? Let’s assume Amphenol will pay US$1 per share in dividend in 2023 and grow that dividend at 9% per year for a long period of time.

In this case, using a dividend discount model, we can calculate that to earn a 10% return on investment (assuming no dividend withholding tax), we will need to pay around US$109 per share. My calculation can be found here.

You may notice that the dividend yield based on the price we are willing to pay is only 0.9%. Yet, we can still make 10% a year because the dividend that we will collect in future years grows over time. 

Using the model 

This model can be applied to all companies as long as you can predict its dividend stream. However this model only works if you are going to be holding the company for the full duration of its lifespan. If you intend to sell the shares to someone else, the share price that you are able to sell the shares at depends on the buyer’s own required rate of return.

This can be influenced by a range of factors, such as the risk-free rate at the time of the sale, or the state of the economy. 

The model also assumes that you can predict with strong certainty the timing and amount of dividends. In practice, this may be hard to predict for companies without a history of dividend payments.

Nevertheless, this framework provides me with a clear way of thinking about valuation and gives me a sense of how I should approach valuing companies.

---

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. I currently do not have a vested interest in any companies mentioned. Holdings are subject to change at any time.

I published Thoughts on Artificial Intelligence on 19 July 2023. Since then, developments in AI have continued at a breath-taking speed. In here, I want to share new thoughts on AI that I have, as well as provide updates on some of the initial discussions.

Let’s start with the new thoughts, in no particular order (note that the caution from Thoughts on Artificial Intelligence that my thinking on AI is fragile still apply):

• AI could be a long-term tailwind for the development of biotechnology drugs. AlphaFold is an AI-model from Alphabet’s subsidiary, Google Deepmind, that is capable of predicting the structure of nearly every protein discovered by scientists thus far – this amounts to more than 200 million structures. And Alphabet is providing this data for free. Proteins are molecules that direct all cellular function in a living organism, including of course, humans. A protein’s structure matters because it is what allows the protein to perform its job within an organism. In fact, diseases in humans can be caused by mis-structured proteins. Understanding the structure of a protein thus means knowing how it could affect the human body. Biotechnology drugs can be composed of proteins, and they tend to manipulate proteins, or the production of proteins, within the human body. According to an Economist article published in September this year, AlphaFold has been used by over 1.2 million researchers to-date. Elsewhere, researchers from biotechnology giant Amgen noted in a recent paper that with the help of AI, the company has reduced, by 60% compared to five years ago, the time it needs to develop a candidate drug up to the clinical-trial stage. But the researchers also shared that AI could do more to help biotechnology companies make the development process for protein-based drugs faster and cheaper. An issue confronting biotechnology companies today is a lack of sufficient in-house data to build reliable models to predict the effects of protein-based drugs. The researchers proposed methods for biotechnology companies to share data to build more powerful predictive AI models in a way that protects their intellectual properties. As AI technology improves over time, I’m excited to observe the advances in the protein-drug creation process that is likely to occur alongside.
• It now looks even more possible to us that generative AI will have a substantial positive impact on the productivity of technology companies. For example, during Oracle’s earnings conference call that was held in September, management shared that the company is using generative AI to produce the code needed to improve all the features in Cerner’s system (Oracle acquired Cerner, a healthcare technology company, in June 2022), instead of its usual way of writing code in the Java programming language. Oracle’s management also said that even if AI code generators make mistakes, “once you fix the mistake, you fix it everywhere.” In another instance, MongoDB announced in late-September this year that it’s introducing generative AI into its MongoDB Relational Migrator service, which helps reduce friction for companies that are migrating from SQL to NoSQL databases. When companies embark on such a migration, software code needs to be written. With generative AI, MongoDB is able to help users automatically generate the necessary code during the migration process.
• The use of AI requires massive amounts of data to be transferred within a data centre. There are currently two competing data switching technologies to do so, namely, Ethernet and Infiniband, and they each have their supporters. Arista Networks builds high-speed Ethernet data switches. During the company’s July 2023 earnings conference call, management shared their view that Ethernet is the right long-term technology for data centres where AI models are run. In the other camp, there’s Nvidia, which acquired Mellanox, a company that manufactures Infiniband data switches, in 2020. Nvidia’s leaders commented in the company’s latest earnings conference call (held in late-August this year) that “Infiniband delivers more than double the performance of traditional Ethernet for AI.” It’s also possible that better ways to move data around a data centre for AI workloads could be developed. In Arista Networks’ aforementioned earnings conference call, management also said that “neither technology… were perfectly designed for AI; Infiniband was more focused on HPC [high-performance computing] and Ethernet was more focused on general purpose networking.” We’re watching to see which technology (existing or new) would eventually have the edge here, as the market opportunity for AI-related data switches is likely to be huge. For perspective, Arista Networks estimates the total data centre Ethernet switch market to be over US$30 billion in 2027, up from around US$20 billion in 2022. 

Coming to the updates, in Thoughts on Artificial Intelligence, I discussed how AI software, especially generative AI, requires vector databases but that NoSQL databases will remain relevant. During MongoDB’s latest earnings conference call, held in August this year, management shared their view that the ability to perform vector searches (which is what vector databases do) will ultimately be just a feature that’s built into all databases. This is because standalone vector databases are point-products that still need to be used with other types of databases in order for developers to build applications. I am on the same side as MongoDB’s management because of two things they shared during the company’s aforementioned earnings conference call. Firstly, they see developers preferring to work with multi-functional databases compared to bolting on a separate vector solution onto other databases. Secondly, Atlas Vector Search – MongoDB’s vector search feature within its database service – is already being used by customers in production even though it’s currently just a preview-product; to us, this signifies high customer demand for MongoDB’s database services within the AI community. 

I also touched upon the phenomenon of emergence in AI in Thoughts on Artificial Intelligence. I am even more confident now that emergence is present in AI systems. Sam Altman, the CEO of OpenAI, the company behind ChatGPT, was recently interviewed by Salesforce co-founder and CEO Marc Benioff. During their conversation, Altman said (emphases are mine):

“I think the current GPT paradigm, we know how to keep improving and we can make some predictions about – we can predict with confidence it’s gonna get more capable. But exactly how is a little bit hard. Like when, you know, why a new capability emerges at this scale and not that one. We don’t yet understand that as scientifically as we do about saying it’s gonna perform like this on this benchmark.”

In other words, even OpenAI cannot predict what new capabilities would spring forth from the AI models it has developed as their number of parameters and the amount of data they are trained on increases. The unpredictable formation of sophisticated outcomes is an important feature of emergence. It is also why I continue to approach the future of AI with incredible excitement as well as some fear. As AI models train on an ever increasing corpus of data, they are highly likely to develop new abilities. But it’s unknown if these abilities will be a boon or bane for society. We’ll see!

---

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. I currently have a vested interest in Alphabet and MongoDB. Holdings are subject to change at any time.