Why Size Matters More for Tech Stocks
Table of contents
Our end-of-the-year portfolio review meeting ran into a brick wall almost immediately when one of our MBAs sparked up some Slurricane creeper that could have killed Elvis. Nonetheless, we powered our way through that hurdle, and started down the path of thinking more like portfolio managers and less like stoned MBAs. As risk-averse investors, we’re always interested in better understanding what risks we’re taking and further refining our tech investing methodology.
A common way to analyze risk for any given portfolio is by grouping the constituents into similar buckets. Some common factors to evaluate include value vs. growth, size (big caps, medium caps, small caps), and industry. Tech investing, by definition, is all about growth. That’s why our simple valuation ratio focuses on how fast revenues are growing. As for industry and size, these are two factors we haven’t evaluated for our own portfolio. First, let’s look at size.
Big vs. Mid vs. Small
Many index providers like MSCI (MSCI) define size as a target that moves along with the overall universe. Their size buckets adjust to the ebb and flow of the markets. For our own purposes, fixed-size buckets will work just fine. ARK Invest analysts put together a breakdown for the ARK Innovation ETF (ARKK) that we’re going to leverage for our own purposes as any good MBA would do. Here are their five categories of stock sizes.
Since we don’t invest in stocks with a market cap of less than $1 billion, we can redefine the “small” segment to ($1B – $2B) and remove the “micro” segment. Here’s how our portfolio is broken down into each of these categories by weighting with cash and ETFs included.
| Size | Weighting |
| Mega | 19.68% |
| Large | 26.09% |
| Med | 22.63% |
| Small | 7.23% |
| ETFs | 5.75% |
| Cash | 18.62% |
Investing in an ETF is what you do if you’re unable to pick any quality stocks. We’ve been slowly removing ETFs from our portfolio and replacing them with stocks which we’ll continue to do. So, let’s remove ETFs and cash so that we can see a true picture of size weightings across the tech stocks we’re holding.
| Size | Actual Weighting |
| Mega | 26% |
| Large | 34% |
| Med | 30% |
| Small | 10% |
As risk-averse investors, we want to lean towards having more exposure to big stocks than small stocks because that lowers our overall portfolio risk. Perhaps a more ideal size distribution would look like this:
| Size | Optimal Weighting |
| Mega | 20% |
| Large | 55% |
| Med | 20% |
| Small | 5% |
Based on our current size weightings, we’re overweight medium/small stocks and underweight large stocks, something that we can consciously try to change as time goes on.
When evaluating our portfolio of positions, rarely do we think about them in terms of size. We’ll be adopting this mindset going forward and moving towards shifting actual size weightings towards optimal size weightings.
Size is particularly relevant for tech stocks because they’re exceptionally volatile. Uncertainty, disruption, innovate or die, all these adjectives used to describe the tech industry have a “hero or zero” commonality. We can therefore expect size to change very quickly, and that’s where the responsiveness of our simple valuation ratio comes in handy. The more a stock price falls, the more attractive it becomes, and vice versa. For risk-averse tech investors, monitoring size risk helps to minimize overall portfolio risk for an asset class that’s already risky enough as it is.
The Nanalyze Growth Funnel
We can view size as a funnel with small stocks being the most risky. That’s the category most SPACs fall into. Of the 75 SPACs we’ve covered, 72 fall into medium or small with an average market cap of $2.448 billion.
The growth with the best Sharpe Ratio (risk vs. reward) is happening in “large” stocks (from $10 billion to $100 billion), the sweet spot for growth if you will. We don’t have any evidence to prove that, but we have MBAs, so we can just will that fact into existence. It also makes sense intuitively. Most of our holdings should be in “large” because by the time a company reaches a $100 billion market cap (mega), consistent double-digit growth becomes more difficult. The bigger a stock becomes, the more likely it is to see interest from private equity sharks who provide some form of stock price support (Blue Prism was a good example of this).
Generally speaking, the bigger a company becomes, the less risky it becomes (companies like Rivian and QuantumScape being obvious exceptions to this rule). It’s why large companies growing very quickly are so highly valued, Snowflake being a good example of that.
Stocks we decide to hold enter our growth funnel at various points. We would never purchase a “mega” stock because we should have identified it much earlier in the funnel. Its best years are behind it. When a stock becomes “mega sized,” it’s time for us to start taking some profits which we funnel into smaller companies – new shoots of growth for the future. Just remember, the earlier in the funnel we make a bet, the more risky it becomes.
Now, let’s look at our industry allocations.
Industry Allocations
Using traditional industry allocations becomes difficult when assessing our portfolio. If you’re using the Refinitive add-on for Excel like we do, then you can very easily pull this data point and see what your allocations look like according to traditional industry allocations.
| Software & IT Services | 19.11% |
| Healthcare Equipment & Supplies | 14.23% |
| Semiconductors & Semiconductor Equipment | 13.39% |
| Electrical Utilities & IPPs | 9.72% |
| Biotechnology & Medical Research | 8.07% |
| Machinery, Equipment & Components | 3.01% |
| Healthcare Providers & Services | 2.37% |
| Financial Technology (Fintech) & Infrastructure | 1.48% |
| Pharmaceuticals | 1.44% |
| Professional & Commercial Services | 1.39% |
| Food & Tobacco | 0.60% |
Software eats the world indeed. Our overallocation to Software & IT Services stems from our predilection towards software-as-a–service (SaaS) business models. Analyzing industry allocation at this level isn’t overly insightful because many of the platforms and technologies we invest in are industry agnostic. A better way to look at allocation is across the 12 categories we cover as seen below:
Above you can see in orange what an equally-weighted portfolio would look like. The blue lines show where we’re actually placing our biggest bets – in Life Sciences, AI, and GreenTech. We can then break our industry allocations down even further into themes.
| AI Chips | 10.0% |
| Genetic Sequencing | 9.9% |
| Renewable Energy | 9.7% |
| Gene Editing | 4.5% |
| Distributed Manufacturing | 3.6% |
| Genetics Testing | 3.6% |
| Robotic Process Automation | 3.5% |
| Industrial Robots | 3.4% |
| Robotics – General | 3.2% |
| Solar | 2.5% |
| Telemedicine | 2.4% |
| AR/VR Content | 1.9% |
| IoT Connectivity | 1.9% |
| Enterprise IoT | 1.8% |
| AI Drug Discovery | 1.8% |
| Long Read Sequencing | 1.6% |
| 3D Bioprinting | 1.5% |
| Consumer Payments | 1.5% |
| Business Payments | 1.4% |
| IoT General | 1.4% |
| LegalTech | 1.3% |
| Proteomics | 1.3% |
| Enterprise AI | 1.3% |
| Biometrics and Authentication | 1.3% |
| Smart Homes | 1.2% |
| Energy Storage | 1.1% |
| Geospatial Intelligence | 0.8% |
| Synthetic Biology | 0.7% |
| Multi-State Operators | 0.7% |
| Food Tech | 0.6% |
When looking at the granular allocations above, trying to equal weight everything makes little sense. It just helps us understand what sort of exposure we’re getting with our tech stock portfolio.
In our previous piece titled How Many Tech Stocks Should You Hold In Your Portfolio?, we decided to aim for holding three stocks in each of our 12 categories which would give us 36 stocks total (with a 10% buffer). Today, we’re holding 36 stocks. Getting rid of our ETFs frees up several slots. We can also consider balancing our categories a bit more. We’re overweight Life Sciences and AI because there are so many quality stocks in both categories. However, we may have some duplicate exposure in these buckets so we’ll look to evaluate that in the coming weeks. Some slots may free up as a result. Finally, we may look to do substitutions. If we’re already holding the market leader, no sense in holding those who play second fiddle.
If you track your own stock portfolio using a brokerage firm, consider also tracking it yourself using Excel and the Refinitiv data plugin as we’ve done above. Manually figuring these things out leads to a better understanding of how two important risk factors – size and industry – are impacting your own portfolio.
Conclusion
It’s a generally accepted rule in the finance industry that smaller stocks carry a great deal more risk than larger stocks. Risk-hungry investors may choose to overweight smaller stocks while risk-averse investors may overweight larger stocks. Based on our own portfolio weightings, we’re a bit overweight medium/small stocks, something that we will be consciously trying to change as time goes on. We’ll also be moving away from having any ETFs in our portfolio so that it becomes a true equity portfolio.
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