TRUESHARES

The Winner-Take-All Theory of Tech Investing

It’s a winner-take-all world and we’re just living in it — and oftentimes benefitting from it. In the tech world, IBM has dominated computer mainframes since the 1960s. Microsoft and Intel have dominated PCs since the 1980s. Since the 1990s, Google has dominated internet searching while Amazon has dominated e-commerce. Facebook has dominated social media for decades, allowing it to systematically buy up smaller social media platforms, like Instagram and WhatsApp, as they come on the scene. 

These and several other household names in the modern technology market epitomize the winner-take-all system1. It’s a type of market dominated by a small number of powerful companies with a stranglehold on most of the market share. This is also known as an oligopoly. Because the stock market is seen as a zero-sum game1 whereby the winners advance themselves at the expense of others, tech investing largely becomes a winner-take-all system. Here’s why.

Like many other industries, tech products and services have economies of scale2, meaning the cost to enter the market is high. In the era of AI, many of the winning tech companies are benefiting from “economies of learning”3 whereby the technology itself gets better the more it is used. The same is true for the massive amounts of data these companies are able to collect and analyze in order to continually improve their products and services.

Social media and cloud-computing resources benefit from what was once called the direct network externality3, which refers to the disproportionate increase in value of something as more people use it. Similarly, “platform” or “multi-sided” markets3, like Uber, see their value increase as more users from different markets (ie. drivers and passengers) use the service. The ability of a company to gain dominance in one market, let alone two or more markets requires scale and money. Tech is particularly poised to do just that.

As they grow and gain dominance through various benefits of scale, these top companies reinvest their resources in nascent technology to remain relevant and innovative in the market even as startups come on the scene. Once they have gained a significant share of the market, top companies also invest in strategies to maintain their dominance by incurring switching costs that make it costly or inconvenient for a user to jump ship to a competitor.

Now, there is a limit to how much a company can thwart its competition and take control of an entire market. That’s what antitrust laws are for. In early 2023, the U.S. Federal Trade Commission sued Google4 for monopolizing digital advertising through various tactics that, the suit argues, reduces search result quality and stifles competition. The jury is still out (literally) as to whether or not Google will be found guilty.

Investing in the tech industry can be daunting, which is why many investors choose broad index funds. However, we believe the winner-take-all theory implies that there’s a well-known path for technology category killers that makes a concentrated portfolio the best chance for outsized returns. TrueShares’ Technology, AI, and Deep Learning ETF (LRNZ) is one such concentrated portfolio designed to provide thematic exposure through tech companies that possess a competitive advantage. These thoughtfully selected companies range from hardware, SaaS, and cybersecurity to data, cloud computing, and biotech.

If your goal is to understand AI investing, it helps to stay informed. View our Investor’s Guide to Artificial Intelligence for more industry insights.

  1. https://www.investopedia.com/terms/w/winner-takes-all-market.asp 
  2. https://www.investopedia.com/terms/e/economiesofscale.asp 
  3. https://www.london.edu/think/nine-reasons-why-tech-markets-are-winner-take-all
  4. https://apnews.com/article/google-antitrust-trial-search-engine-justice-department-2cfb06271455c7e12c4927959061e832 

For the fund’s current holdings, please visit www.true-shares.com/lrnz.

The TrueMark AI & Deep Learning ETF (LRNZ) is subject to the following risks: Artificial Intelligence, Machine Learning and Deep Learning Investment Risk – the extent of such technologies’ versatility has not yet been fully explored. There is no guarantee that these products or services will be successful and the securities of such companies, especially smaller, start-up companies, are typically more volatile than those of companies that do not rely heavily on technology. Foreign Securities Risk -The Fund invests in foreign securities which involves certain risks such as currency volatility, political and social instability and reduced market liquidity. Growth Investing Risk – The risk of investing in growth stocks that may be more volatile than other stocks because they are more sensitive to investor perceptions of the issuing company’s growth potential. IPO Risk – The Fund may invest in companies that have recently completed an initial public offering that are unseasoned equities lacking a trading history, a track record of reporting to investors, and widely available research coverage. IPOs are thus often subject to extreme price volatility and speculative trading. New Issuer Risk – Investments in shares of new issuers involve greater risks than investments in shares of companies that have traded publicly on an exchange for extended periods of time. Non-Diversification Risk – The Fund is non-diversified which means it may be invested in a limited number of issuers and susceptible to any economic, political and regulatory events than a more diversified fund.