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Wild week in the market. Some of these earnings reactions are probably more about multiple contraction than poor reports/guidance. I wrote about my thoughts on various earnings reports as well as corresponding portfolio moves $ABNB, $PAYC, $DDOG, $ZI

Other quick thoughts on earnings:

$CFLT - good but not looking to add aggressively
$HUBS - great, will probably add more
$TWLO - good, may add more
$SHOP - not great, but also not looking to sell

Have a great weekend!

April 2022 Bloodbath - Names Down >30% Since April 1
April 2022 was one of the worst market months of all time. In fact, it was the worst since October 2008. Here are 100 stocks down >30% since April 1:

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Beaten-down 2021 IPOs
I love avoiding new initial public offerings for their first couple of earnings reports as a publicly-traded company -- but even more so, I love revisiting them after this 6-12 months.

Life as a newly public company is rough as expectations from analysts are wonky, and management is adjusting to a new lifestyle of increased scrutiny.

With this in mind, here's a list of 2021 IPOs I'm watching that have traded down since going public.

$RSKD Riskified -74% | $PATH UiPath -67% | $COOK Traeger -66% | $BIRD Allbirds -65% | $MQ Marqueta -64% | $CPNG Coupang -62% | $OLO Olo -56% | $COIN Coinbase -53% | $APP Applovin -51% | $EXFY Expensify -44% | $USER UserTesting -42% | $BMBL Bumble -42% | $WRBY Warby Parker -40% | $AFRM Affirm -39% | $WEBR Weber -37% | $NU Nu -31%| $RBLX Roblox -30% | $SEMR SEMrush -27% | $FIGS FIGS -27% | $MNDY Monday -13% | $DOCN DigitalOcean -11% | $CFLT Confluent -8% | $GLBE Global-e Online -6% |

Curious to hear what you all may like the most from these?

Out of this list, four are part of my Core 34 group of holdings that I aim to add to the most here in 2022.

Have a good weekend, friendly humans.
With of the four from my core 34 do you like the most?
10%Global-e Online
19 VotesPoll ended on: 05/02/22
Ryan Mahony's avatar
$17.4m follower assets
$CFLT is reporting earnings Feb. 10th. Last quarter they grew total revenue by 67% and cloud revenue by 245%.
Interesting, so Confluent mostly does integrating Kafka into enterprises?

Seems like a valuable service— to handle the complex parts integration so that in-house staff don't have to manage it. But $17B is a hefty market cap for that! Color me interested in this earnings call as well :)
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Ryan Mahony's avatar
$17.4m follower assets
After some really good learning years in the market I have begun to practice some better tactics. I started 6 new positions in Sept. and added to the 5 that performed well improving the overall gain. The one that was underperforming $DOCS I did not add to. There is no good adding to an under performing stock unless you really, really have a conviction, however this generally just leads to magnifying losses. Best returner was $CFLT

The MAD Landscape report: Machine Learning, AI and Data
FirstMark's 2021 MAD Landscape report is out. John and Matt from VC fund FirstMark do a great job synthesizing the current state of (or actually, convergence between) Machine Learning, AI, and Data. Let's dive in:

  1. The macro picture

Recent technological advances have unlocked a "symbiotic relationship between data infrastructure on the one hand, and machine learning and AI on the other," mainly driven by data warehouses and data lakes. The former contains structured and filtered data (Snowflake, Amazon Redshift), and the latter saves unstructured raw data (Databricks.)

This new infrastructure allows for real-time data in analytics and operations processes, which enables intelligent and automated operations.

A positive flywheel is emerging, where every company has the potential to become a data company → increases supply and demand of data → increases the need for data and AI tools and platforms to make sense of data → more innovation from data and ML infrastructure companies.

As infrastructure companies scale, consolidate, compete, and build a suite of products and analytics tools, users like asset managers gain access to cutting-edge technology without hiring top data and ML engineering talent. Meanwhile, data-driven investment processes benefit from an increasing data supply that may unlock better insights and drive alpha.

  1. Financings, IPOs, and M&A activity

It's no secret that investors regard these data and ML/AI companies as hot investments. For example, snowflake's IPO back in September 2020 was the biggest software IPO ever (currently valued at over $100B.) More recent IPOs include UiPath ($PATH, robotic and AI automation), Confluent ($CFLT, data infrastructure), and Couchbase ($BASE, no-SQL database.) (Disclosure: I am long $SNOW)

Even though some investors cry at their current sky-high valuations while bleeding cash, the authors claim that, as a group, data and ML/AI companies have outperformed the broader market.

On the private market's side, VCs have also happily poured billions of dollars into AI startups. Funds like Tiger Global, Coatue, Altimeter, Dragoneer, and D1 have identified this industry as a critical investing area.
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$AGC (Grab)

Portfolio 2:

Watchlist Companies:

I'm looking forward to engaging with everyone to discuss Technology, Analytics platforms, Cloud, Improving as an Investor, and more!
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