Our funds ended the month slightly under benchmark. The full 2022 year was the first year in the last 7, that they underperformed. This is unsurprising given the mix of calamitous factors converging in ‘22 and the spike in outsized returns occurring from a small handful of industries, that our way of investing deliberately avoids.
We continue however to meet our stated objective of beating the benchmark after fees, over rolling 5-year periods.
Our analysis of the portfolio’s 2022 performance showed that it was impacted almost entirely by markets reducing valuation multiples from the record highs of 2021. Positive 7-8% increases in earnings per share on a weighted-average basis across our holdings were not enough to combat this initial market response.
This leads us to today where the valuation of the portfolio has become much more attractive. Over the long term, there is a clear correlation between a company’s stock price and its earnings growth. We invest in companies with growing sustainable earnings. As investors begin re-focusing on fundamentals, this relationship will start to dominate future stock price returns again. This sets up our portfolio for strong performance in the years ahead.
The events of 2022 do not present sufficient evidence of having entered a “new era” of investing, despite media headlines. Today’s 10-year US Treasury yield of 3.5% is similar to the levels achieved in October 2018. Interest rates were rising back in 2018 too. What was different, was the 2020/21 period when rates hit historical lows and the market’s inevitable initial response to their longer-term normalisation that commenced in ’22.
Obtaining a discount on quality: The important attribute about investing in profitable businesses propelled by global megatrends is that they typically grow at multiples well above prevailing GDP, even with rate increases and in recessions. During this present decline in the stock prices of this small and select group of businesses, their earnings continue to sustainably grow. This provides investors with an opportunity to buy at much lower and attractive valuations than usual. How compelling are these multiples? Looking at the price to cashflow (P/CF) multiple of the portfolio, it is presently trading on similar multiples to the entire benchmark of companies. Yet, with Insync, you are getting 2.5x the market average in terms of quality/profitability (ROIC).
Tuning out of hearing about AI
It certainly is a very broad and increasingly overused term, but one that will continue to grab headlines. Why is it at the centre of so much deliberation about our shared future and why is it capturing the attention of most companies and industries?
The mix of attention-getting events of 2022 has had investors so focused on the macro environment that many lost sight of both fundamentals and the tectonic developments that are already quickly changing how we live and work.
Artificial intelligence (AI) is a prime driver of these tectonic shifts. Understanding the impact of artificial intelligence is critical to ensuring that investors avoid being in the wrong companies & industries, as much as identifying the ones that will most benefit.
AI is actually a constellation of different technologies working together to enable machines to sense, comprehend, act, and learn with human-like levels of intelligence.
AI is reaching a critical tipping point: As a term it has been around for nearly 60 years. But it is only recently that AI is reaching the brink of revolutionising industries as diverse as health care, law, journalism, and manufacturing. It has the potential to profoundly affect how people live, work, and play. Importantly this won’t evolve at a nice easy pace either; it will move devastatingly fast. Many companies will fail to both identify its impact and act fast enough to combat or exploit it.
A current example is the explosion onto the scene of the search and composition work of chatGPT.
Let’s use this very newsletter to appreciate what it can do. Insync focuses on providing ‘insight’ in writing these updates. This is unlike most of our peers who tend to produce the easier ‘commentary’ about events. Whilst we believe insight is much more valuable, it is also much harder to do. ChatGPT proves this. It can now not only write songs, pass the US Bar Exam and write a thesis in an instant, within in its first few months of existence, it can also produce investment commentary! Copy writers and some managers will be facing a career change.
Observe the statement below made by Accenture (who serve more than 9,000 clients - including more than 3/4 of the Fortune Global 500).
A number of forces have been converging to bring AI into its own.
1. Increased processing power. This makes it possible for computers to execute complex tasks at speeds once unimaginable—and at a cost that has fallen rapidly.
NVIDIA dominates the new GPU chip suites (we wrote about this game changing technology in our September 2020 issue). It is worth noting that a decade into the GPU-for-AI era, the speed with which they continue to make massive strides continues. A near 7-fold performance improvement in only 2.5 years! Functions unimaginable in machinery, processes or services 5 years ago, can now be achieved.
2. Data storage: the advent of Cloud computing. Essentially, it’s the highly efficient storage and its manipulation that this form of data storage can produce. Is has been a key driver in the necessary price collapse of storing data essential to AI. It has created untold uses for data and its analysis.
3. Advances in mobile broadband. This makes it possible for workers, customers and leaders to access applications and perform work from multiple locations at once even from remote locations.
4. Our ability to embed brain-like elements into computers is the last element. This is exemplified with such capabilities as voice and pattern recognition, natural language learning, and machine learning. There will be an exponential increase in the number of commercial AI-based applications taking on work that otherwise is too vast, expensive or lengthy for today’s processes.
Biotech provides a good example. AI has driven down the cost of genome sequencing and led to the development of more effective drugs to treat chronic diseases. Below depicts genome sequencing realities.
AI is already part of our lives. Take a look at the following common examples you’re bound to be familiar with:
Netflix uses AI to determine streaming suggestions based on your viewing history.
Facebook uses all the data you input on the platform, from the videos you watch to what you say in your status update, to determine which advertisements you might be interested in.
Universities use essay submission software to determine if work has been plagiarised.
Google Maps utilises ongoing satellite imagery to determine the best route for you to take on a given journey.
Let’s study the last example of maps, a little further. Over the past decade or so, we’ve shifted to AI to provide us with directions from one place to another.
Not only that, AI enables Map-Apps’ to take into account road closures, current traffic conditions, and the driver’s preferences for tolls and turnings, or the way a route is displayed, yet the act of driving doesn’t fundamentally change.
Uber and Lyft used these AI developed tools to create an entirely new system of ride-hailing that first upends and decimates the current service, then grows its use to far bigger than ever proportions.
This all happened in well under a decade. With reliable driving directions and ubiquitous mobile devices, they realised that anyone could provide ride services. The number of people who could match the skill of professional drivers became several times larger.
Five years ago, there were approximately 200,000 professional taxi & limo drivers in the U.S. Today, there are more than 10x that number of people who drive for Uber alone (approximately 3.5 million in just the U.S.)
To integrate this much larger workforce required further innovations in security, location tracking, pricing, dispatch, and a wide variety of other areas. The entire system needed to change.
Gojek and Grab are examples of companies further leveraging this transport service into scooters then food deliveries and so-on. This was not a viable or even imagined proposition in the previous taxi dominated mindset. The convergence of the four factors of the AI constellation makes all this possible.
Let’s take a further look at ChatGPT. Its name is short for "Chat Generative Pre-training Transformer". It is a natural language generation tool developed by OpenAI, released only late last month. It utilises the power of deep learning, specifically the GPT-3 (Generative Pre-training Transformer 3) model, to understand and respond to a wide range of queries in a human-like manner.
It's ability to understand the intent behind a user's query and generate responses that are both relevant and human-like has led to speculation that it could potentially revolutionise a number of industries including search engines, customer service, content creation, education and healthcare.
ChatGPT passed an MBA exam given by a Wharton professor. The bot’s performance on the test has “important implications for business school education," wrote Christian Terwiesch, a professor at the University of Pennsylvania’s Wharton School.
Education - The incredible part is not only did the bot pass the exam but it did so in only one second! The bot's score, Terwiesch wrote, shows its "remarkable ability to automate some of the skills of highly compensated knowledge workers in general and specifically the knowledge workers in the jobs held by MBA graduates including analysts, managers, and consultants."
Healthcare – Hospitals will have AI widely integrated into their systems, enabling practitioners to more accurately predict patient needs and overcome growing skilled staff shortages. Imagine its impact on hospital administration. For example, many patients are admitted before a diagnosis is made, meaning no-one knows for how long the beds will be occupied. This makes it very hard to assign resources and forecast demand. A systemic use of AI could involve predicting a newly admitted patient’s tenure. Predicting when particular patients can safely be discharged and then treated as outpatients, or when it's safest to keep a patient in for observation until doctors can better understand their condition is a coming reality.
