Performance for each of the last four years, since I started trying to follow the rules/principles in Sauls’ Knowledge Base and his chosen posts in the Right Side Panel, here.
2021 > +46.8% 2020 > +203% 2019 > +32.9% 2018 > +38.9%
2021>. Month. YTD March >. (-)13%. (-)11% April >. +13.56% +1.37% May >. +5.35%. +6.8% June >. +15.2%. +23% July >. +5%. +29% August >. +24.3%. +60.5% Sept> +2.9% +65.22% Oct> . +16%. +91.7% Nov>. (-)14%. +54.38%(given in error). Actual YTD 64.8% Dec> (-)11%MTD. +46.8%YTD
2022>. Month YTD January: (-)22.3% (-)22.3% February: 6.4%. (-)17.3%
Feb 28 Jan 31 Dec 31 Nov 30 Oct 31. Sept 30. Aug 31. July 31. June 30. May 31 Upstart 14.025%10.47% 11.28% 11.73%. 25.27% 27.52%. 22.47%. 14.76%. 13.85%. 11.39% Datadog. 14.53% 17.54% 16.60% 16.28%. 11.91% 16.39%. 16.43%. 16.42%. 16.21%. 16.63%. 16.83% Cloudflare. 18.38%.15.22% 13.48% 14.06%. 13.23%. 9.33%. 14.45% 17.60%. 16.48%. 18.92%. 25.12% Monday. 13.44%.15.08% 14.39% 17.92%. 10.37%. 8.72%. 0%. 0%. 0%. 0%. 0% Lightspeed. 0% .0%. 0%. 0%. 9.75%. 8.78%. 4.40%. 0%. 0%. 0%. 0% Zscaler. 10.79%. 9.26% 8.99%. 8.64%. 7.06%. 6.51%. 0%. 2.75%. 0%. 0%. 0% Snowflake 11.98% 13.25% 12.69% 11.35%. 8.84%. 7.51%. 10.32%. 12.67%. 12.10%. 12.20%. 15.68% ZoomInfo. 9.87% 12.69% 11.11%. 9.22%. 6.72%. 7.09%. 7.75%. 7.98%. 8.12%. 10.50%. 6.32% Crowdstrike. 6.6% 6.51% 11.45%.10.81%. 6.84%. 8.14%. 19.12% 21.50%. 22.36%. 24.19%. 24.05% Docusign. 0%. 0% 0%. 0%. 0%. 0%. 0%. 6.32%. 10.88% 6.46%. 7.75% Watch List: MongoDB
The following has become increasingly important to me in my investing decisions (Since I have no formal training in Investing into the stock market, I surmise all the following after reading a smattering of classic investing texts, the Knowledgebase and following this board for four years. This is for me more than for you, perhaps.):
I see every company with a different size flywheel. Focusing on the size of each companies flywheel has important distinguishing characteristics compared to Growth durability or many other characteristics that I find useful when determining, for me, how I evaluate each company.
To my understanding, ‘the flywheel’ consists of: level of market need for product (level of disruption of product offering), amount of friction in sales motion, rate of expansion in company offerings, and holding all this together is stickiness of product fit. I believe another useful way of looking at this is one Muji introduced when he drew a picture of the fly wheel as a swirling hurricane during a FinTwit Summit a year or so ago. He described Hhhypergrowth as being hyper-growth in four areas:
Scaling customers, Scaling Operations, Scaling Platforms, Expanding Markets. . Notice Muji does not address stickiness of product fit here.
The size of the flywheel, or Hurricane, matters because the inertia inherent in size effects any course corrections. When management decisions lead toward more or less efficient taking of market share, the larger the flywheel the more time it will take to amend any decision effecting this efficiency.
IMO, Snowflake is an example of having a relatively large flywheel. They have a slow onboarding of new customers and, IMO, a proportionate increase in stickiness to their platform. One indication of Snowflake ‘having a larger flywheel’ is that the momentum in their sales motion is hindered by the relative increased need to educate the buyers in how to best use their disruptive technology (taking greater effort in getting things to spin up and hum along). The stickiness of the market fit, as in Snowflakes case is seen in their Strong Network Effect . This means when the flywheel does get humming the momentum of Snowlflakes’ business performance will be great. I believe Palantir has perhaps an even larger flywheel than Snowflake (I just took a tiny starter position in Palantir, so small as to not even be considered a rounding error in my returns).
This obviously doesn’t mean that a larger flywheel is better. Each of the aspects, of the flywheel may be entirely different for each company and usually are. However, generally speaking my keeping the size of each companies flywheel in mind does effect how much weight I give fluctuations in metrics each quarter. This is not the same as momentum trading as I undstand that, which I do not wish to understand well.
You won’t see me write that Crowdstrike’s decline in Revenue growth was small. It was quite large. What I’m trying to explain is that IMO Crowdstrike has a small and spectacularly efficient flywheel for their business model, which is selling into a massive market. That’s what I mean by, Crowdstrike has a better than a Zscalers chance to reaccelerating revenue growth.
I look at the numbers given at each quarterly Conference Call as describing the efficiency with which the company has been able to take advantage of the market adoption for what their selling. This is much needed periodic confirmation to the past narrative, as I understood it. However, I’m trying not to draw trend lines for revenue growth out into the future based on the past quarters’ numbers. Similarly, it’s difficult not to consider guidance. If I do consider historical patterns in quarterly numbers or guide/beat ratios, I’m looking for when the company might surprise based on what appears to be unrelenting demand for what their selling. Again for example, I see all the above as playing out well for Crowdstrike.
I’ve heard some say Crowdstrike is going up against the Law of Large Numbers. Doesn’t the law of large numbers only apply when the company is either having difficulty ramping new products to move the revenue growth needle and/or running out of customers? My understanding is that Crowdstrikes’ Serviceable Addressable Market remains enormous and growing. Assuming they are hitting the ceiling of their TAM or Competition is taking share, for the sake of this argument I’ve laid out, if the law of large numbers were applying to Crowdstrike, given the size of their flywheel, I suspect they are easily spinning up the fixes, further enabling their existing and new customers and leading Crowdstrike to re-accelerating revenue Hypergrowth. Am I carrying this analogy to far? Or is this making sense?
If you’ve read this far, thanks and I’d love some reply’s to these questions.
When reading the following keep in mind that this portfolio remains ~85% of what we will live on in retirement. This portfolio is what is in our non-taxable Roth and Rollover IRAs only. We have not added any money to these accounts for many years. To buy something I’ve sold something else. I don’t trade options or use any leverage. I stay fully invested at all times and keep less than 1% in cash.
4 investing decisions this month:
(About half of this has been posted already)
What I did:
Sold 17% of my ~10% position in Zscaler to add to what was a 15% position in Cloudflare making it now a 17% position at $104/share.
Why I did it:
After reviewing what I’d written in my last months portfolio decisions, where I wrote The reason I’ve been holding less Zscaler thus far has been due to their lessor advantages in being able to provide a programmable network, when compared to Cloudflare for example. Security alone is a cost without direct ROI*… and after Cloudflare checked all my boxes during their Quarterly Conference Call I’d rather be overweight early than late here.*
In this recent Quarterly Conference Call, Cloudflare broke out their early successes with many of their newer products. Specifically, CEO/Founder Mathew Prince spoke about Cloudflare Workers product milestones leading to gaining relevance. As I’ve recently stated, Cloudflare and Zscaler go head to head reguarding Zero-Trust. This third act of which I speak, Cloudflare capturing the astronomical TAM of the programmable Edge-Cloud with the Cloudflare Workers product. Their movement toward this third hockey stick, when Cloudflare’s Workers becomes the fourth Cloud is the promise land, IMO. How soon? Well In the Q4 CC, CEO/Founder Mathew Prince said, they’ll be adding their ‘1 Millionth developer to Workers this year. What’s the tipping point to when they’ve sufficiently built out their network and will produce an avalanche of increasing revenue growth ? Dunno, I’m not waiting anymore for the financial numbers to improve before making Cloudflare my #1, when we all know the Market on average is thinking six months ahead. I believe Workers will be every bit as large a revenue growth contributor for Cloudflare as Data Sharing will be for Snowflake. The Strong Network Effect moat will likely be much smaller for Cloudflare than what Snowflake has created just due to the different enterprise culture I see at each company. Nonethelessless the creation of Workers, Cloudflares’ third flywheel of Hyypergrowth, was a massive undertaking and will get spinning sooner rather than later🧐.
Zscaler has better numbers now; but, I’m here trying to pick companies bringing future surprises to Mr Market. I’m erring on the side of too soon rather than too late getting overweight in Cloudflare in part because I recognize my having difficulty keeping ahead of our companies, due to them using and selling exponential technologies.
What I did:
I sold 20% of my 19% DDOG position to add a 4% position in MongoDB.
Why I did it:
I held MongoDB for about a year, a while back. I got out due to their cloud based solution, Atlas, not replacing on-prem licensing fast enough (Innovators Dilemma), resulting in their growth rate slowing. In this last earnings, Mongo management explained that Atlas now accounted for more than 50% of sales and is growing in the 80% range. With this and the announcement of their Application Data Platform last June, I expect MongoDB to expand the number of data workloads that their platform addresses significantly. This will be due primarily to these two factors and what I see as a shift in sales motion toward larger customers, I believe Mongo will dramatically accelerating growth into their market, a market in which I want more exposure due to its size and one in which enterprises have shown a tendency to consolidate their usage onto one platform.
What I did:
I ended up selling 20% of my ~13% position in ZoomInfo in pre-hours, when Mondays’ share price dipped more than 35% since their report yesterday, to buy 25% more Monday shares.
Why I did it:
Despite a 27% drop in Monday share price yesterday, I had gone to bed last night not having done anything. I wanted to sell in order to buy more Monday. I understand Mondays’ Rev growth dropped to 15% sequentially; but, will other productivity tools quickly put together similar no/code work automation capabilities? IMHO, Software engineering is more complicated than just needing to add stuff (see why Jira is both loved and hated). I believe the moat Monday has has to do with their architecture. IMO, when Monday.com’s management is this efficient in selling into their market, a 2% decrease in this quarters’ rate of acceleration in Revenue growth isn’t gonna make this company worth any less in 1-3 years. Then this morning pre-hours, Monday was down another 5.5% and ZoomInfo flat. Efficient Market?, not so much IMO.
What I did:
I sold the 4% position in MongoDB I bought two days ago to buy 50% more Zs after hours following the CC.
Why I did it:
When I saw accelerating Revenue Growth 63% YoY while going up against a difficult compare Q2 last year…and then in answer to why Claculated Billings was only +59%, Romeo Cannesa, said, Federal was low single digit of our new and upsell business. Now why is that? It’s just the budget constraints basically. Billings is revenue + change in deferred revenue. So I figure Federal not having kicked in those big contracts yet, the change in deferred revenue is going to huge when it does. And to be honest, it was the disconnected market reaction to this report that got me to defiantly add so much. I mean, despite my having a 17% position in Cloudflare now- Zscalers’ direct competitor, I had to take advantage of this.
I’ll likely reverse this trade when I see another catalyst line up for MongoDB to further the recognition of their dominance in that market. I think the odds are in my favor that I’ll make a bit on Zscaler in the short term, allowing me to get more shares of MongoDB when I do. Managing a concentrated portfolio allows me to understand these companies well enough that I feel confident when I do step out of my usual more disciplined approach to investing. And if I don’t see an opportunity to get back into Mongo, I’m happy to own a 10% position in Zscaler for the next 1-3 years.
As a habit, when I make investing decisions I’m thinking out 1-3 years. When I do make a short term decision, it’s almost alway based on an obvious market disconnect between how the companies were performing and a share price over reaction based on something outside of what the companies were doing (see for example this last of the 4 decisions I made this month).
Heartfelt thanks to those following the rules of this great Board! I’m grateful to be one in a group of individuals who’ve come together with these rules as an agreed upon standard.
Special thanks to Saul and all the Board Managers for insisting on these now absolutely necessary standards of conduct. https://discussion.fool.com/monday-morning-rules-of-the-board-34…
2020 Portfolio Summaries here: https://discussion.fool.com/jason8217s-2020-port-review-34708368…
2021: Porfolio Summaries here: https://discussion.fool.com/jason8217s-december-portfolio-decisi…