- Diversification VS Concentration
- Innovation
- Commonalities of successful companies
Diversification VS Concentration
Conventional wisdom often tells you to not put all of your eggs within one basket. Commonly, this is deemed as being far too risky. Instead, you are told to diversify and to hedge against the uncertain future.
Often, investors who do concentrate their portfolios are deemed as gamblers. At first glance, this more concentrated approach can look like an attempt to win big at the lottery. However, this could not be further from the truth.
The issue with diversification is that often this approach is a matter of spray-and-pray, in hope that you will pick a winner. Commonly, when one diversifies their portfolio to a large scale, this leads to very mediocre results. Via mass diversification, investors have no knowledge of the companies that they hold. It is frankly impossible to invest within 20 companies, and know these companies inside out. Diversification leads to no conviction. No conviction is a matter of poor research and knowledge. The underlying philosophy behind the approach of diversification is centred upon the fallacy that the future is randomised, and that nothing can be predicted. This, once again, could not be further from the truth.
Within the past few decades, there has been a severe level of indefinite optimism encapsulating the West. In other words, the West has remained optimistic for the future, however nobody has actually acted to make the future better. Thus, stagnation occurs. Nobody builds or shapes the future, and the future remains the same as present date. If we, as a society, do not shape or act to build the future, this positive future will never occur.
Diversification is a matter of indefinite optimism.
In addition, never have I met anyone who can maintain a diversified portfolio of equities, and understand these equities in detail. This level of blatant arrogance when investing will lead to a passive bubble eventually.
How in the world can you invest within 20-30 equities, and understand these all in detail? You can’t.
When it comes to concentration, this is a far more logical approach to investing. Conventional wisdom explains concentration as a matter of buying a lottery ticket: in hopes that one of the equities chosen will 10X. This is paradoxically untrue.
In fact, concentration actually lowers risk. This is because, concentration stems from conviction. And, good conviction stems from research and knowledge. And yes, whilst there is a danger associated with poor knowledge and research, good investors will have processes in place to ensure that their research and knowledge it spot on.
There seems to be a level of subconscious fear associated with concentration. In fact, the schooling system teaches one to be average at a range of domains. Many other institutions of our day force the narrative of diversification in an attempt to hedge against an uncertain future.
The DOTCOM era likely played a role within this subconscious desire to hedge against the future via mass diversification.
Concentration philosophically is a way of being deterministic about the future. Once again, you are not a lottery ticket. The future is not solely luck. The future can be shaped, predicted and identified. And, the future is coming.
One thing I have learnt about markets is always to question. Always to ponder over conventional wisdom. The market is the ultimate contrarian. And, nothing is ever obvious.
Innovation:
Regardless of company size, if a company fails to innovate, that company will fail. And, perhaps rightly so. Innovation is the core principle behind all successful companies.
The accelerated law of returns states that within the next 100 years, there will not be 100 years of innovation. In fact, there will be 100,000s of years of innovation compressed within the next 100 years. This is what I call a flywheel of innovation.
After speaking with Jim Harris on a recent podcast, Jim explained how during the 2 year COVID period, the equivalent of 10 years of innovation has occurred within this short window. This is a staggering phenomenon. Innovation solves issues, and when society is within a period of crisis, innovation steps up and performs.
People often forget how much society has changed over the past 100 years. In fact, elderly individuals are often overwhelmed by the levels of technological advancement that now dominates everyday life. I believe that this change is only going to accelerate further with the advent of real world AI, and other related technological breakthroughs.
Real world AI, also referred to as foundation models, is AI that can be applied to any industry, domain or task. This is currently being seen within companies such as Tesla, who are aiming to solve full self-driving, and then adapt this general AI to other domains – such as a manufacturing. The current AI today is known as narrow AI. This is because, this modern AI can only work within one setting – for example solving complex mathematical equations. However, this same AI can not be applied to other domains or tasks. In the future however, general AI will take over. This is one example of a technological breakthrough that is going to rapidly increases productivity and innovation as a whole within the following years.
Furthermore, this is not just a wishful fallacy. Just in the past few months there has been major break thoughts within the scene of real world AI. One major breakthrough is showcased via OpenAIs GPT.
This interlinks with the future of AI in which refers to AI being flexible, reusable models in which can be applied to just about any domain or industry task.
IBM mention how, “the next wave of AI looks to replace the task-specific models that have dominated the AI landscape to date”. The future is models that are trained on a broad set of unlabelled data that can be used for different tasks, with minimal fine-tuning.
Foundation models however are not trivial, and results within the real world have already been seen. For example, the first glimmers of foundation models have been shown within GPT-3, BERT or DALL-E 2.
One can input a short prompt, and the system then generates an entire essay, or complex picture based on set parameters – even if it was not trained on how to execute that image or task explicitly.
The model is used to create articles, poetry, stories, news reports and dialogue using just a small amount of input text that can be used to produce large amounts of quality copy. GPT-3 has over 175B parameters and can generate any text including guitar tabs, or computer code.
“Others have found that GPT-3 can generate any kind of text, including guitar tabs or computer code. For example, by tweaking GPT-3 so that it produced HTML rather than natural language, web developer Sharif Shameem showed that he could make it create web-page layouts”.
Therefore, this shows that AI can be used within any domain, industry or task – despite not being trained to do so. And, this is just within infancy stages.
The phenomenon of AI is bound to lead to increased levels of productivity and innovation because, AI has a zero marginal cost associated with replication. In other words, one can scale code, and AI across the internet, to millions of vehicles, manufacturing plants, or planes with a zero cost associated with the replication of that AI.
When creating a tangible good, to scale this to a high level, there are mass overheads associated with this scale. One must purchase the materials, manufacture, design, and then sell the product. This process of manufacturing a tangible good does not experience the luxury of zero marginal replication costs.
However, software and code does. One can scale full self-driving AI to millions of cars within seconds, and with a zero marginal cost associated with replication. This is the power of AI and code.
Fundamentally, it is likely that innovation within the next 10, 15, 20 years is going to rapidly accelerate.
I believe that there is a case to be made in which, similarly to emerging markets back in the 1980s, capital allocation towards the domain of innovation will rapidly increase over the next few decades. Initially, many investors resisted exposure to developing markets based on the volatility associated with geopolitical uncertainties, corporate governance, and liquidity. With time, however, they observed low correlations between and among the stock returns of the various developing nations, as well as growth rates that far surpassed those in the developed world. Investors concluded that broad-based exposure to developing markets offered enough higher risk-adjusted return.
In other words, similarly to emerging markets within the 1980s, the same will occur with innovation. Investors initially resisted exposure to innovation, but as time passes and innovation provides higher growth rates, exposure to innovation will become far more common for investors.
Bret Winton, at ARK Invest says:
“We believe a strategic allocation to innovation probably will evolve into a sub-asset class, as did the “niche” strategy of the 1980s—emerging markets. In the late 1980s and early 1990s, investors had little, if any, exposure to what has evolved into 13% of the global equity market capitalization and 60% of global gross domestic product (GDP) on a purchasing power parity basis.”
The bottom line remains, we are at a historic time for innovative growth. Innovation within the near future is going to provide tremendous societal improvements and changes. Full self-driving cars, flying taxi networks, and psychedelics to solve mental health issues, will all become a common practice within everyday life shortly.
Investing within innovation today can be deemed as inertly dangerous and too risky. Instead, the majority of investors want to purchase conventional companies such as Coca-Cola, or Walmart. But, if these companies do not innovate, eventually they will fail.
A great example is seen within the automotive sector. Currently there are legacy companies such as Ford and GM that have clearly failed their transition towards the new function of a vehicle: renewable, autonomous, productivity and leisure zones.
This transition is by no means an easy feat to overcome. In fact, there is a case to be made that these legacy companies will fail to successful pivot in time, and thus will crumble under the new wave of disruptive EV companies.
For example, when it comes to Tesla & their FSD, this is a process that experiences major exponential trends within growth. This is also referred to as a network effect. Specifically, for Tesla, the network effects within the FSD network are continually growing. This means that, as more people purchase a Tesla, the overall FSD network improves for the company.
Within each Tesla, FSD is continually picking up data, and feeding this back into the FSD network holistically. Thus, as more people drive a Tesla, the smarter the FSD network becomes. This obviously leads to major exponential trends in utility of the FSD network.
For a company like Ford, or GM – it seems implausible to assume that they can compete with Tesla on FSD in consideration of the huge competitive, first mover advantage Tesla has in this domain. The same theory is true across all of vectors of the vehicle manufacturing process.
Relating this back to the concept of being a contrarian investor, whilst previously Tesla was viewed as a highly speculative and risky play, in reality this company has been a disruptive force in the EV sector. Ford, and GM paradoxically were viewed as safe investments based on their reputable name and brand, little risk and seemingly conventional business model. However, when innovation comes into action, it can be clear to see how these so-called safe investments actually can be more of a value trap than previously anticipated.
Innovation causes disruption, and innovation will continue to disrupt legacy domains. If conventional companies do not innovate, they will eventually fail.
The contrarian approach when investing is to identify controversial, misunderstood, and innovative companies that will produce value in the future. This is where real value remains, in comparison to legacy, stagnant and conventional equities.
Commonalities of successful companies
Upon reflection, whilst I agree that business is unformulaic, there are some commonalities between successful companies.
- Start small, & monopolise:
- Propriety technology:
- Network effects:
- Branding:
Starting small and monopolising a niche is a common trait between highly successful companies. It is far better for entrepreneurs to hold 100% market share of a small base, in comparison to holding 1% market share of a large pie.
Furthermore, fundamental to my philosophy when investing is the idea that technology does not sell itself. The best technology does not always win. However, the combination of superior technology, good strategy and sales can create dominance. Monopolisation of a niche can give direction for the company when starting out, and can specifically aid the adoption of early usage within a platform. Once again, this is because there is far less friction associated with infiltration of a small, untouched market.
When it comes to starting small and monopolising, this can be seen within the case of Facebook and PayPal.
Specifically for Facebook, the company monopolised the social media scene within all major universities and colleges. As time went on, Facebook increased the level of distribution of the platform across more campuses. And eventually the company released their platform to the nation, and then on a global scale.
However, if Facebook didn’t market and specifically target their product for college campuses, it is likely that initial adoption of the platform would have never been achieved, and therefore the platform would have failed.
Moving on, marginal improvements are not sufficient. Within an increasingly crowded world, the necessity for undisputable 10X improvements within technologies is needed.
The reason being is because 10X better technologies are very hard to duplicate, or replicate.
Looking at Google, the company has managed to garner a phenomenal competitive lead over Bing, or Yahoo. In fact, Yahoo and Bing are actually incomparable to Google’s products.
Google clearly has a 10X better lead, and as a consumer, this is most definitely felt. With Google, their autocorrect, search, speed, and precision are just a few of the factors that contribute to the competitive lead of the company.
The only way to ease friction associated with adoption is via undisputable improvements within the technological features of the product. New technologies can be very invasive, and frighting for some early adopters. Thus, there is a major incentive to stay on existing networks and conventional platforms if the new product is only marginally better than incumbent players.
With new technologies, the incentives associated with adoption are against you. Therefore, the necessity to have undisputable 10X improvements in every regards is paramount.
Network effects can create incredibly powerful companies. In fact, the largest companies to date, all experience network effects within their products and services. Network effects can be defined as an increase within utility of the network, as more nodes join that specific network.
When looking at Google, every search and click contributes to improvements within the whole network. As more people use Google, the improvements in precision and accuracy increase. This leads to an unstoppable flywheel effect.
Similarly, network effects can be powerful as a matter of incentives. On social media platforms, as friends and family become members of a certain platform, the perceived disconnectedness, and feeling of isolation for individuals who have not joined the network is not trivial. Thus, the incentives are aligned to encourage outsiders to join platforms via network effects.
