DotCom Bubble VS Current Date:
Macro-Predictions VS Micro-Predictions.
Importance of indirect and direct network effects for innovative investing.
DotCom Bubble VS Current Date:
Within a recent exclusive interview with Manny Berabe, the CEO of BigPlasmaAI, Christian speculated and questioned the relevance of the DotCom bubble in comparison to current date innovative companies.
Manny mentioned how, upon reflection, without the DotCom bubble, Amazon or NetScape wouldn’t have existed. This is because, Amazon, NetScape and other truly innovative companies were a function of the DotCom era.
When considering past bubbles, one must understand that these bubbles often have excess, however there is a lot of underlying investments that happen that will be good longer term for economies. Manny pointed towards the original bubbles during the first Industrial Revolution – namely the use of railroads. There was a lot of excess around telecoms – often the hot players ended up flopping. However, the investments made through the bubble, end up creating huge utility. From an investors perspective, the challenge at hand is to identify which companies will succeed within these bubbles.
Whilst many individuals often make the argument that there are evident similarities between current date innovative companies, and the DotCom bubble, in reality this seems unrealistic. This is because, during the DotCom era, many organisations were not producing profit or revenues at all. To explain, often companies such as Pets.com had no solid profits, but were majorly blown-up due to speculation over globalisation and the internet.
Within current date, whilst some companies are overvalued, in reality these companies are producing a solid stream of revenue, and have a viable business model.
We believe that these face-value comparisons to the DotCom bubble are far fetched, and lack in detail.
It’s all fun and games until stocks reach absurd valuations at the peak of the business cycle. pic.twitter.com/jWnHDjinnZ
— Otavio (Tavi) Costa (@TaviCosta) April 22, 2022
Macro-Predictions VS Micro-Predictions.
Often, within public markets there is logical evidence to indicate towards a clear macro-market prediction. The macro often refers to a holistic picture of a market or economy. This is in comparison to the micro prediction, that look specifically at a more individualistic products or a specific company.
Some evident examples of the macro-predictions in which seem fairly logical includes:
- Blockchain utility
- NFT verifiability for real world outcomes
- Data trend increasing exponentially
However, as an investor, the challenge is to successfully predict which companies will best capitalise on the trend uptake. Often, investors are drawn towards the hype surrounding certain macro-waves, and therefore fail to successfully identify the company in which will benefit from this trend.
A common consensus surrounding innovative investing, posits forwards approaching innovative investing within a similar manner as venture capital. If you are investing within technology companies, one should approach this area as a venture capitalist. If you look at a venture capitalist, these individuals invest within 100s of different equities, however often only 1-2 succeed.
Importance of indirect and direct network effects for innovative investing.
There are other investment techniques, namely value investing, in which the whole focus is to avoid these hyped stocks. It is often very challenging to pick out the companies that will become the winners. As noted within a recent report, we believe that there is a solid methodological approach available for analysis of innovative companies. This includes the use of an 8 pillar investment strategy that can identify if a company has the potential to become truly disruptive and innovative.
One of the most fundamental principles Manny mentioned included the use of network effects. Below we distinguish and define indirect and direct network effects, and therefore indicate how vital these are for long term competitiveness.
Indirect network effects occur when the value of a network increases as a result of one type of node benefitting another type of node directly, but not directly benefitting the other nodes of its same type. Within the context of eBay, the addition of a new seller does not directly benefit other sellers. In fact, another seller just means more competition for all the other eBay sellers. However, due to the expanded inventory of goods, this makes the marketplace as a whole more attractive to buyers. Additional sellers end up indirectly benefitting other sellers because of the total increase in potential customers.
OS platform like Microsoft Windows is a good example. New Windows developers do not directly benefit each other, however with an increased library of Windows programs, the number of Windows users will grow. Thereby, a greater number of windows users are beneficial for all developers because it increases the pool of potential customers for their program.
Direct network effects is when the value of the service simply rises in value when the number of users increase. Within the context of a social media platform, this is revealed most clearly. As more members join the platform within your community, this results in more connectivity and interlinking, thereby resulting in more utility of that set platform.
These competitive moats often are majorly useful for identification of an innovative investment.
The use of network effects can explain why social media platforms recently have been very hard to replicate or displace. Whilst the underlying code behind these social platforms is easy to replicate, the utility provided by these social platforms creates an element of stickiness.
