POSITIONS REPORT (2/27/23)

Posted on February 28, 2023June 30, 2026 by io-fund

For reference to terminology used, please look at technical analysis under our resources section here. Regarding the charts below, the vertical tan shades represent time factors. These are inflection points where we have high odds of something significant happening. More times than not, (3/4 of the time), they mark a turning point in the trend. So, what matters is the direction we are trending into these periods. Regarding the vertical lines, black lines represent strong support/resistance, while dark red lines mark very strong support/resistance.here. Regarding the charts below, the vertical tan shades represent time factors. These are inflection points where we have high odds of something significant happening. More times than not, (3/4 of the time), they mark a turning point in the trend. So, what matters is the direction we are trending into these periods. Regarding the vertical lines, black lines represent strong support/resistance, while dark red lines mark very strong support/resistance.

Elliott Wave count are meant to provide context. There is a pattern unfolding in real-time, one of which will play out. By monitoring price levels that are held/broken, it will help us figure out which one is in play

Broad Market

The major US markets continue to trace the complex corrective pattern we outlined weeks ago. What this pattern calls for is a final 5 wave drop to new lows. For SPX, the downward targets are 3295, 3150, 2940. If we get confirmation of this pattern playing out, we will look to remove our hedges and commence buying around these key price targets.

From an Elliott wave perspective, the structure of the bounce from the October 13th low warrants caution. Anytime we see a 3 wave bounce, the odds favor this pattern being a correction within the larger trend, which is down. The above chart is clearly 3 waves up.

This is backed up by various supporting markets that are important. In short, for a major bull market reversal to be underway, we need the below markets to participate. Instead, they seem to be confirming the bearish setup.

Financials (XLF)

The Banks have been very strong since the October low. However, the structure of XLF off the low is also an overlapping 3 wave structure. Note how this 3 wave bounce has retraced the majority of the 2022 drop. Also, note the weakening momentum as price moves higher. This pattern may have one more high in it, but it is clearly a B wave until proven otherwise.

Transports

The Transportation sector is also flashing similar warnings.

Canada

The Canadian TSX is an important market to track for US equities. More times than not, it leads the US. When these markets diverge, it is a big warning of an imminent trend change. This is not what we are seeing. Note the bear pennant forming. This triangle pattern is common with B waves, which the TSX appears to be tracing.

If we zoom in on the bounce off the October lows, the S&P 500 appears to have an incomplete uptrend. The 3 wave bounce is marked by an A wave up, B wave down, and C wave up, which completes the 3 wave pattern. The C wave always plays out in a 5 wave pattern, and it appears that we only have 4 waves in place. This suggests that we see a final run towards a double top, or 4225 SPX in the coming weeks, but this is not guaranteed.

The above blue count has been my primary analysis for several weeks. In fact, we removed some of our hedge and have gone net long (25%) in an attempt to capture some of this potential move. This move needs to manifest this week, or it is in danger of not playing out.

My alternative count (red), which is quickly becoming my primary. This suggests that we already topped and are almost done with the 1stwave down in the final move towards the 3000 SPX level. If we push towards 3920 before breaking out over 4040, then this will become my primary, as we look to fully hedge on the 2nd wave retrace. In both cases, we should see a larger bounce before the wheels fall off.

Futures

It may seem odd that a tech service covers futures; however, I am always looking for clues in many markets so that we can properly position. Futures are very important right now because they track commodity prices, which is the underlying pressure within inflation. The most important to monitor is food and energy, both of which are suggesting higher prices into the near future.

Wheat

Wheat prices look to be completing the 5th wave in this large correction. It is trending down into major support with a cluster of cycles coming into play between Feb 28-Mar 3. Once we see a bottom, a large degree bounce should follow. This means food prices are likely going up.

Energy

Gasoline looks very similar to oil prices below. This very much looks like a consolidation before the next move higher. The next major cycle is in late April (this is a very big time frame to monitor). I doubt that we consolidate above the 1×2 line for that long. Look for energy prices to move higher in 2023, which will only put pressure on inflation.

Macro Analysis

Recent data growth has opened the door to the prospect of a “soft landing” or “no landing.” We discussed what a soft landing looks like last week – manufacturing contracts while services does not contract too much more. This last happened in 2014-2016, and most famously in the mid-90s. The idea of no landing means that we just continue to expand from here, avoiding a recession all together.

We would be onboard with this rosy outlook if it wasn’t for one key data point – inflation. All prior soft landings going back to the 80s had one factor in common – a supportive liquidity cycle. With inflation under control, the FED was able to allow the continuation of a supportive liquidity cycle (2014-2016), or start up a new liquidity (mid-1990s).

With talking heads focusing on stronger than expected growth metrics in the economy, they fail to acknowledge what this means for inflation. In short, inflation may have peaked, but the real battle will be getting it from 6.4% to 2%.

If you pay attention to what the FED is saying, they are now tracking something they are calling “Super Core” Inflation. This metric excludes food and energy, like regular core inflation, but goes one step further to exclude all other goods as well as shelter. Because the US GDP is ~85% tied to services, this gives the FED a look into how their policies are affecting the largest segment of the US economy.

In January, the Super Core prices rose at a 7.4% annualized rate. This is the fastest increase for any month since 2021. These prices are up 4.6%, which is just off its peak at 5%.

It is alarming how little effect the current aggressive rate campaign by the FED is having on services. While manufacturing remains in an on-going contraction, services continues to expand, proving that the economy is much more resilient than expected. This also means the FED will likely have to hike higher and for longer than the equity markets are pricing in.

So, the only questions an investor needs to ask – is it more likely or less likely that the FED will start up a new liquidity cycle soon, based on the overly resilient services segment of the economy? Will starting a new liquidity cycle hurt or help their primary goal to get inflation back to 2%?

Counter Analysis/Bail Out Levels

My current outlook for 2023 has evolved (or devolved) since the start of the year. I have grown more bearish as time has progressed, and would rather remain cautious until we get evidence that the above analysis is being shrugged off. The levels I need to see reverse, which would have me reverse my analysis is below.

Dow Jones Industrial Index (DJI)

The consolidation pattern in DJI broke to the downside, as it suggests a continuation of selling before a low takes hold. I’ve stated before, and will repeat, as long as the DJI holds its October low, no matter what else happens, it will set up a great buying opportunity. This still holds. However, for me to reverse course, the Dow needs to reclaim its December high.

Financials (XLF)

I’m adding XLF to the mix. Like the Dow, it needs to reclaim its February high.

Caterpillar (CAT)

I’m also adding CAT to the mix. CAT is a key stock to track for early signals. It put in a major top according to Gann – multiple time clusters coming together at the 1×1 line off the 2016 low. If it can reclaim its February high, then I will start looking to buy.

Bonds

I’ll also want to see TLT take out its December high.

It may seem like I’m adding more criteria to my reversal pivot; however, if we are entering new bull markets, all of these markets will confirm it in unison.

Hedge Signal

Our signal nailed this swing in both directions. We remain in the basement, and a long way from turning back to a buy.

Time Analysis

These are the dates to monitor for a trend reversal/big break put. The most important aspect of these dates is how the market is trending into them. These dates will be inflection points that can help determine swings.

Small Cycles in March: 6-7, 15-17
Medium/large Cycles: February 27 – Mar 3. Note how we are trending down into these dates. It should mark a low in red 1 or blue 4.
Notable Events: March 22-23 is the next FOMC meeting.
Late April will be one of the biggest time factors of the year.

I/O Fund Portfolio

Though it may seem that we are heavily concentrated, as of now, our biggest position is really cash, which nearly double the percentage of NVDA.

NVDA (17%)

NVDA tagged the 100% extension (this is where the length of the C wave is identical to the length of the A wave). This is the most common spot that a 3 wave bounce terminates. It is now struggling to break above this level, while momentum continues to fade at these heights. This is not where you buy a stock. After this 3 wave pattern is complete, we should see a drop back towards our target region. We plan to make NVDA a larger position, so expect buys in the coming months.

NFLX (14%)

I’m starting to question the below bullish count. I’m looking for a big drop in equities, while NFLX is close to the lower trend line. Another 16% drop towards $270 is as far as I would give NFLX. If we do see a more bullish outcome in the markets (my red count, where SPX tags 4225), then NFLX can complete the large degree diagonal for wave 1. That would make more sense, but that’s a big ask. Long-term, I believe NFLX has put in a major low, but we could see a deeper pullback in the coming months than previously expected.

AMD (13%)

The top is in for AMD. One more low and we have 5 waves down from the high. There should be a larger bounce that follows, for anyone looking to hedge/unload. We will plan to buy more at lower levels.

TSM (9%)

A crash scenario for TSM would likely be due to geo-political tensions. This would create a great buying opportunity, as this company is likely not going anywhere. Like all semis, it has completed a 3 wave bounce up, and now we get to see how deep the pullback takes us.

AEHR (9%)

Look for us to take more gains in AEHR on the next bounce. My confidence in the chart is fading.

ENPH (9%)

Without question the most interesting chart we track is Enphase. It continues to trade like an energy commodity. In other words, it appears to be bottoming while NDX/SPX appear to be topping. If correct, we could see a repeat of 2022.

MSFT (8%)

Regarding the FAANGs, first Google topped, then AMZN, NFLX, MSFT, and AAPL is now hanging on by a thread. MSFT is the key, right now. It looks like it has a 4th wave then one more drop to complete the larger 1st wave of the larger C down. We should see a corrective 2ndwave bounce before the wheels fall off.

TSLA (5%)

The 1st buy zone will be between $160-$140. My primary is that we visit $92, but we will begin layering in based on the red count. When technicals are calling for a drop that appears to be dramatic, especially when it runs counter to a recent positive earnings report, I prefer to set up buying plans based on both scenarios playing out.

MGNI (2%)

The top is likely in for MGNI. We need to get back over $14.30 to change my mind.

Crypto (14%)

One more swing high is possible from here, but that should be it. Then we have a very full pattern, which should lead to a deep retrace that holds the lows, at minimum. The next deep pullback should set up the buying opportunity we have been waiting for. Late March and late April will be the time cycles to monitor for Bitcoin.

Nvidia Q4 Earnings: A Tough Company to Bet Against

Posted on February 27, 2023June 30, 2026 by io-fund

Note: We’ve written a lot about Nvidia this month for our Essentials Members. One thing that differentiates the I/O Fund from other services is that we are an actively managed portfolio that is audited and traded in real-time. This means, we will gladly discuss a stock many times in one month if it means we will make money.we will gladly discuss a stock many times in one month if it means we will make money.

Other services need to fill a meaningless, content pipeline. This means they will cover four, eight or even more stocks per month! This does not lead to making good money, it’s distracting and noisy, at best. Instead, we provide a strong, fundamental picture alongside thorough technicals. After a setup plays out, we will gladly tell you a stock we think is quite strong fundamentally may need to take a breather. This work is not quick, it’s not easy, and very sites are good at it. I wanted to illustrate for our Essentials Members in the Month of February how our site operates differently. We are here to make money; we are investors – not marketers. We look forward to providing more strong calls like we did with Nvidia prior to earnings. Notably, we may trim this position now. So, stay tuned next week of 2/26 for a Positions Update including a broad market stock tip from Knox. Click here for more information on our Advanced Plan. This work is not quick, it’s not easy, and very sites are good at it. I wanted to illustrate for our Essentials Members in the Month of February how our site operates differently. We are here to make money; we are investors – not marketers. We look forward to providing more strong calls like we did with Nvidia prior to earnings. Notably, we may trim this position now. So, stay tuned next week of 2/26 for a Positions Update including a broad market stock tip from Knox. Click here for more information on our Advanced Plan.Click here for more information on our Advanced Plan.

Nvidia Q4 Earnings:

Nvidia stock has reacted positively to an adjusted EPS Q4FY23 beat of $0.88 vs $0.80 and a Q1FY24 revenue guide of $6.5B vs $6.32 consensus. The most important on the call was the statement: “We expect sequential growth to be driven by each of our 4 major market platforms led by strong growth in data center and gaming”We expect sequential growth to be driven by each of our 4 major market platforms led by strong growth in data center and gaming” as it supports the H2 rebound.

Nvidia’s current quarter weakness is already priced in, yet the anticipation is high that Nvidia nails the turnaround come the October quarter. This quarter — especially with the comment on sequential growth comment across all four quarters — makes this outcome a bit more likely.

We had recently written about Big Tech’s prioritization of AI related infrastructure and how Nvidia was well positioned to benefit from this secular trend here. We listened for further evidence of this from the conference call. Big Tech capex can’t be overestimated in terms of how Nvidia will perform, and the comments about re-allocating for AI investments was further reflected in Nvidia’s report.

Financials

$6.05B revenue came in line with prior guidance and consensus estimates, up 2% sequentially and down 21% year-over-year. For the full year, total revenues came in at $26.9B, flat year over year.

Next quarter’s revenue guide was $6.5B, better than consensus of $6.32B.

Adjusted eps came in $0.88 which beat consensus of $0.80.

Within the main business segments, Data centers came in at $3.6B, down 7% sequentially, and up 11% year-over-year. Gaming revenue was $1.8B, up 16% sequentially and down 46% YoY. Importantly, gaming’s sequential improvement showed further evidence that it had bottomed. We wrote about this in November here.

Gross and adjusted gross margins came in at 63.3% and 66.1%, in-line with guidance. Operating and adjusted operating margins came in at 20.7% and 36.8%, in-line with guidance.

Both gross and operating margins showed sequential improvement as China related inventory write-downs and higher compensation related expenses were limited to Q3.

Net income improved to $1.4B vs $0.7B in the previous quarter for a net income margin of 23.3% vs 11.5%. Adjusted net income improved to $2.2B vs. $1.5B in the previous quarter for an adjusted net margin of 35.9% vs 24.5%

For the full year, total revenues came in at $26.9B, flat year over year. Within full year sales Data center sales were up 41% and gaming sales was down 27% y/y. Gross margins were 56.9% vs 64.9% the prior year while adjusted gross margins were 59.2% vs 66.8% prior. Operating margins were 15.7% vs 37.3% prior while adjusted operating margins were 33.5% vs 47.2% prior.

Regarding Gaming, Nvidia added the following. “The year-on-year decline reflects the impact of channel inventory correction, which is largely behind us.” This is important because it is exposed to the consumer and was facing cyclical headwinds last year that impacted group earnings. Rather than a detractor, it should be a contributor to group earnings going forward. Management provided a Q1 outlook compared to Q4 for all business segments. ,

“Let me look to the outlook for the first quarter of fiscal '24. We expect sequential growth to be driven by each of our 4 major market platforms led by strong growth in data center and gaming.”“Let me look to the outlook for the first quarter of fiscal '24. We expect sequential growth to be driven by each of our 4 major market platforms led by strong growth in data center and gaming.”

Looking at the balance sheet. Cash, cash equivalents and marketable securities were $13.30B. Inventory increased, primarily to support the ramp of new products in Data Center and Gaming. Meanwhile, free cash flow was $1.74B compared to $2.74B a year ago and negative $156 million a quarter ago. Fiscal-year free cash flow was $3.76B, down from $8B a year ago.

Earnings Call:

The main write-up on Nvidia’s product side will come following GTC at the end of March. However, on the call, Nvidia’s AI-as-a-service was mentioned, so I want to provide that quote for you, as it was one of the most important parts of the earnings call.

I’ve discussed in the past that the H100 is an important leap forward for enterprise AI when stating: “the A100 GPU is what led the company’s gains since Q2 2020 (detailed here) and the Hopper H100 GPU is what will lead the company’s gains for the next two years (detailed here).

The company has stated the following in regards to H100 sales:

“Adoption of our new flagship H100 center GPU is strong. In just the second quarter of its ramp, H100 revenue was already much higher than that of A100, which declined sequentially.”

I feel like I’ve talked quite a bit about the H100 and its importance, so we won’t rehash that right now.

However, per our July write-up here, there is an important point to what was discussed on the call and what Nvidia investors can expect to hear about in the coming quarters in regards to software monetization. I’m repeating here what we wrote in July before I elaborate on what I think was the most important part of the earnings call:

“According to Nvidia, the H100 delivers 9X more throughput in AI training, and 16X to 30X more inference performance. The company also states in HPC application-specific workloads, the H100 is 7X faster. The goal of the H100 was not only to add more transistors and make the H100 faster, but to also offer function-specific optimizations. This is achieved through the transformer engine.

The architecture aims to answer one of the bigger challenges facing superfast compute, which is that moving data into traditional servers overloads the CPU and system memory and becomes bottlenecked by PCI-Express.

By improving the bandwidth issue, Nvidia’s goal is to create more demand for their DGX Pod and SuperPod Systems, which in turn, will create more demand for their software.”

The comments in the earnings call that pertain to the H100 and DGX Pods and SuperPods is this – it’s important because it can mark the beginning of Nvidia’s software revenue. So, I’m including this as a bigger quote from the earnings report:

“Generative AI's versatility and capability has triggered a sense of urgency at enterprises around the world to develop and deploy AI strategies. Yet, the AI supercomputer infrastructure, model algorithms, data processing and training techniques remain an insurmountable obstacle for most […]

We are partnering with major service — cloud service providers to offer NVIDIA AI cloud services, offered directly by NVIDIA and through our network of go-to-market partners, and hosted within the world's largest clouds. NVIDIA AI as a service offers enterprises easy access to the world's most advanced AI platform, while remaining close to the storage, networking, security and cloud services offered by the world's most advanced clouds […]

AI supercomputers are hard and time-consuming to build. Today, we are announcing the NVIDIA DGX Cloud, the fastest and easiest way to have your own DGX AI supercomputer, just open your browser […]

With our new business model, customers can engage NVIDIA's full scale of AI computing across their private to any public cloud. We will share more details about NVIDIA AI cloud services at our upcoming GTC so be sure to tune in.”

The takeaway is that not only will Nvidia begin to monetize through software on the DGX systems but accessibility will improve through CSPs, or cloud service providers. This is an attempt to democratize AI development while driving software sales.

In the call, management stated the following about CSPs, or cloud service providers:

“With cloud adoption continuing to grow, we are serving an expanding list of fast-growing cloud service providers, including Oracle and GPU specialized CSPs. Revenue growth from CSP customers last year significantly outpaced that of Data Center as a whole as more enterprise customers moved to a cloud-first approach. On a trailing 4-quarter basis, CSP customers drove about 40% of our Data Center revenue.”

This is important as it links back to the comment about Nvidia’s AI as-a-service and cloud service providers helping to move DGX Cloud. It also helps to illustrate how DGX Cloud can be successful, given the strong CSP partnerships and revenue growth in the data center segment.

Here is another quote in regard to DGX Cloud and why it’ll be important for a lower barrier to entry for AI development:

“The accumulation of technology breakthroughs has brought AI to an inflection point. Generative AI's versatility and capability has triggered a sense of urgency at enterprises around the world to develop and deploy AI strategies. Yet, the AI supercomputer infrastructure, model algorithms, data processing and training techniques remain an insurmountable obstacle for most. Today, I want to share with you the next level of our business model to help put AI within reach of every enterprise customer.

Moving along, this was the Q&A piece that is most important to Nvidia investors long-term:

“Timothy Arcuri

Jensen, I had a question about what this all does to your TAM. Most of the focus right now is on text, but obviously, there are companies doing a lot of training on video and music. They're working on models there. And it seems like somebody who's training these big models has maybe, on the high end, at least 10,000 GPUs in the cloud that they've contracted and maybe tens of thousands of more to inference a widely deployed model. So it seems like the incremental TAM is easily in the several hundred thousands of GPUs and easily in the tens of billions of dollars. But I'm kind of wondering what this does to the TAM numbers you gave last year. I think you said $300 billion hardware TAM and $300 billion software TAM. So how do you kind of think about what the new TAM would be?

Jensen Huang

I think those numbers are really good anchor still. The difference is because of the, if you will, incredible capabilities and versatility of generative AI and all of the converging breakthroughs that happened towards the middle and the end of last year, we're probably going to arrive at that TAM sooner than later.”

Today, Nvidia trades at less than 1X that TAM at $515 million compared to what this analyst believes will be an easily-achieved TAM of $600 billion. This would suggest the stock price does not yet fully reflect the future market opportunity.

Conclusion:

There are some upset investors today on social media who shorted Nvidia going into the print. This was based on Nvidia’s current weak financial profile coupled with its valuation. As pointed out in our Q1 webinar, we are entirely focused on the H2 rebound, which can arguably be easier to predict with semiconductors due to the longer-term supply chain visibility this industry has. At least for today, Nvidia proved it’s on track for the H2 rebound.

As you know, we track Nvidia very closely due to its leading allocation in our portfolio. We saw evidence of a gaming bottom in November, which we published about here. We also felt Nvidia had masterfully timed it’s RTX40 Series with the Ada Lovelace architecture plus the H100 release to drop exactly when the crypto mining selloff would be most felt. We discussed this here in September. These points were entirely overlooked by Nvidia critics.

Yes, that revenue miss in the Fall was crazy – but what was lying beneath the surface for chances of a quick recovery?

Basically, the devil is in the details and not a lot of investors or analysts care to look into Nvidia’s complex hardware products. Jim Cramer got 1M views on his tweet here that admitted it was tough to listen to this particular company’s earnings calls. It works in our favor that talking heads prefer to discuss consumer tech, and that the masses are collected around those who have not taken the time to get to know his company.

We know Nvidia is not pushing a buzzword to move stock, as we’ve been covering Nvidia’s AI angle for going on five years. It’s the headlines that changed; not Nvidia.

To remain balanced here, we agree that Nvidia is likely due for a pullback. The shorts were probably right in that regard. That is Knox’s territory. He had written here that $230 has a lot of resistance and also on the forum. He plans to update everyone on Nvidia in his webinar this afternoon.

Your bigger product update will come post-GTC as we begin to lay a strong foundation for 2024 and onward for this exciting company.

Nvidia Q4 Earnings: A Tough Company to Bet Against

Posted on February 23, 2023June 30, 2026 by io-fund

Nvidia stock has reacted positively to an adjusted EPS Q4FY23 beat of $0.88 vs $0.80 and a Q1FY24 revenue guide of $6.5B vs $6.32 consensus. The most important statement on the call was: “We expect sequential growth to be driven by each of our 4 major market platforms led by strong growth in data center and gaming”We expect sequential growth to be driven by each of our 4 major market platforms led by strong growth in data center and gaming” as it supports the H2 rebound.

We had recently written about Big Tech’s prioritization of AI related infrastructure and how Nvidia was well positioned to benefit from this secular trend here and here. We listened for further evidence of this from the conference call. Big Tech capex can’t be overestimated in terms of how Nvidia will perform, and the comments about re-allocating for AI investments was further reflected in Nvidia’s report.

Financials:

$6.05B revenue came in line with prior guidance and consensus estimates, up 2% sequentially and down 21% year-over-year. For the full year, total revenues came in at $26.9B, flat year over year.

Next quarter’s revenue guide was $6.5B, better than consensus of $6.32B.

Adjusted eps came in $0.88 which beat consensus of $0.80.

Gross and adjusted gross margins came in at 63.3% and 66.1%, in-line with guidance. Operating and adjusted operating margins came in at 20.7% and 36.8%, in-line with guidance.

Both gross and operating margins showed sequential improvement as China related inventory write-downs and higher compensation related expenses were limited to Q3.

For the full year, total revenues came in at $26.9B, flat year over year. Within full year sales Data center sales were up 41% and gaming sales was down 27% YoY. Gross margins were 56.9% vs 64.9% the prior year while adjusted gross margins were 59.2% vs 66.8% prior. Operating margins were 15.7% vs 37.3% prior while adjusted operating margins were 33.5% vs 47.2% prior.

Earnings Call:

The company has stated the following in regards to H100 sales:

“Adoption of our new flagship H100 center GPU is strong. In just the second quarter of its ramp, H100 revenue was already much higher than that of A100, which declined sequentially.”

I feel like I’ve talked quite a bit about the H100 and its importance, so we won’t rehash that right now.

By improving the bandwidth issue, Nvidia’s goal is to create more demand for their DGX Pod and SuperPod Systems, which in turn, will create more demand for their software.”

In the call, management stated the following about CSPs, or cloud service providers:

Here is another quote in regard to DGX Cloud and why it’ll be important for a lower barrier to entry for AI development:

Moving along, this was the Q&A piece that is most important to Nvidia investors long-term:

“Timothy Arcuri

Jensen Huang

Conclusion:

Yes, that revenue miss in the Fall was crazy – but what was lying beneath the surface for chances of a quick recovery?

Most importantly, we discussed Nvidia’s entry into AI software here, which we stated was the important analysis we have ever written on Nvidia. I think “most important analysis” will be rivaled when I write about Nvidia’s automotive segment.

We know Nvidia is not pushing a buzzword to move the stock, as we’ve been covering Nvidia’s AI angle for going on five years. It’s the headlines that changed; not Nvidia.

Your bigger product update will come post-GTC as we begin to lay a strong foundation for 2024 and onward for this exciting company.

Magnite Q4: Ad Budgets Weigh on Growth, Bottom Line Miss

Posted on February 23, 2023June 30, 2026 by io-fund

Magnite beat on revenue in the current quarter and raised top line guidance for Q1. The expectation was that Magnite would report GAAP profitability this quarter. However, the company reported GAAP EPS of ($0.27) compared to GAAP EPS estimates of $0.02. The adjusted EPS also missed at $0.24 versus $0.32 expected.

The bottom-line miss is due to the CTV ad platform that launched in February, which created “a $35 million accelerated amortization related to the CTV ad platform consolidation.”

In the prepared comments, management also stated: “Total operating expenses, which includes cost of revenue for the fourth quarter, increased 29% to $204 million compared to $158 million in the same period a year ago. Adjusted EBITDA operating expense was $92 million, up 11% sequentially from Q3 and up from $75 million from the fourth quarter last year and slightly above our guidance range. The increases were driven by higher cloud and personnel expenses, T&E and higher engineering team expenses, partially due to lower internally developed capitalized software due to the completion of our new CTV platform.”

Financials:

Note: numbers below are reported as ex-TAC unless otherwise stated. This stands for “excluding traffic acquisition costs” for a better representation of actual revenue minus any payments to online partners or affiliates.

Magnite reported revenue of $156.6 million, for growth of 10%. This beat estimates of $153.7 million. This led to a beat on FY2022 revenue of $514.6M compared to $511.7M expected.

For Q1, Magnite is guiding for $109 million to $113 million, which implies a raise at the midpoint compared to consensus of $109.7 million for Q1.

For Full Year 2023, Magnite provided a vague guide to “expect FY2023 revenue to grow from 2022.” Analysts have 7.5% growth for consensus of $550.3 million in revenue.

GAAP EPS of ($0.27) missed estimates of $0.02 for the reasons stated above. Adjusted EPS of $0.24 missed estimates of $0.32.

Q4 CTV Ad Revenue grew 19.6% for revenue of $64.6 million. The Q1 guide for CTV revenue is $42.5 million to $44.5 million, compared to $42.3 million in the year ago quarter. One of the bigger issues in this report is that CTV ad revenue is expected to be flat YoY to up to 3% growth for Q1. (See below for the earnings call discussion.)

Mobile revenue of $61 million, was up 18% YoY. Desktop also grew 18% YoY for revenue of $30.8 million.

The United States and International mix remained the same at 78% of revenue and 22% of revenue, respectively.

Margins:

The adjusted EBITDA in Q4 was 41% which was lower than the Q4 EBITDA margin from a year ago at 48%. Management stated adjusted EBITDA would remain the same in 2023 as 2022, which was $178.8 million. Given the guide nodded toward nominal growth in 2023, this makes sense that EBITDA would be similar.

· Gross Margin of 37% is lower than usual with a FY2022 gross margin of 47%

· Operating Profit Margin of (16%) compares to +2% OPM in the year ago quarter

· Net Margin of (21%) compares to a flat net margin in the year ago quarter

· Adjusted net income was slightly down at $34.7 million compared to $37.5 million in the year ago quarter.

Cash:

Cash flow was the strongest line item in Magnite’s report.

The company reported operating cash flow margin of 32% compared to 37% last year for operating cash of $56.9 million.

Free cash flow of 28% compared to 34% in the year ago quarter. This remained Magnite’s strongest quarter in 2022. Total free cash flow was $48.91 million. All things considered; this is a good report on cash.

The free cash flow guide for next year is $100 million, which means Magnite intends to not lose ground here as FY2022 cash flow was $106 million.

The company lowered its net leverage to 2.2X down from 3.3X in the year ago quarter. The company has $326.3 million in cash on the balance sheet with $726.4 million in debt for net debt of $400.1 million.

Earnings Call:

On the earnings call, the main discussion points were ad budgets and how macro affecting is affecting ad budgets this year. Magnite management sees the industry at a potential bottom but admits they don’t have a crystal ball. Also, within this topic, analysts wondered why Magnite’s CTV ad revenue would be flat to 3%, per guidance.

On the positive side, Magnite pointed toward the upfront season as a potential turning point for the CTV ad tech segment. We’ve covered as a potential catalyst for our Netflix position, since this will be Netflix’s upfront season. By the time the next earnings season starts to roll-in, we will likely hear quite a bit about the upfront, committed ad spend each publisher or ad network is able to secure. Additionally, the Disney partnership is extended another year for Magnite’s ad server.

Macro/Ad Budgets

Below are two discussions that directly relate to what Magnite saw in Q4, which was a deceleration that seemed to be unexpected. I believe our analysis here on Ad Budgets Set to Slow Even More is in sync with this discussion. The deceleration we are seeing in ad-tech revenue growth across the board from Q1 2022 to Q1 2023E reflects this flat to minimal YoY annual budget growth.

Shyam Patil

Nice job on the execution. I had a couple of questions. First question, for 1Q, as you guys talked about it, it seems like things have started off a bit slow for the industry in terms of ad spend growth. I was just wondering if you've seen any improvement or changes in the growth rates as we've kind of gone from early January to late February?

Michael Barrett

Yes, sure. I'll start off and allow David to chime in or Nick. As far as improvements are concerned, I think what has us cautiously optimistic is there hasn't been further decline. So I think what we — and especially talking with our big buyers, agencies, marketers, the consensus seems to be that we've seen the worst, and that it should get better from here and out. That's not to say we're starting to see it, it get better overnight, but it is to say that I think that the notion that late Q4 into Q1 probably is we're bouncing along the bottom and hoping that things have freshen as we get into the Q2 and the upfront period of time.

Jason Kreyer

Michael, I just wanted to ask about visibility. I mean it sounds like things kind of decelerated pretty quickly in Q4, have stabilized since. But just wanted some color on if the visibility has changed? Or how much visibility you have now into marketers may be pulling back on budget or reaccelerating budget or just things like that?

Michael Barrett

Yes. And you're right, Jason. I mean no sooner do we finish our call, [indiscernible] around for the Q3 earnings. And it's universal across talking to every publisher sometime right around mid-December, Q4 stopped behaving like Q4, right? And it kind of limped across the finish line in December, and that kind of headwinds followed into Q1.

Our visibility, generally speaking, comes more from the insight of our buyers from agencies. We do, as you know, have the demand facilitation team, and that's a little bit of a features market. Insertion orders tend to be more of a I'm willing to spend x amount over the next couple of months. And those bookings are quite strong.

And so it leads us to believe, and I think this is kind of the industry rhetoric, that we're bouncing along the bottom with the hope that the recovery begins sooner than what some folks are hoping, which is second half of the year. But again, our crystal ball is no greater than anyone else's in that respect.

CTV Ad Budgets Weak in Q1

Outside of the bottom line miss, what was most surprising is the deceleration in growth on CTV ads. Magnite has consistently been growing this segment around 40% YoY and is now guiding for 0% to 3% growth YoY next quarter.

In the opening comments, management stated “this slowing of growth is attributable to an industry-wide slow start to Q1.”

When an analyst questioned the team about it, the following was stated:

“CTV is 100% macro, and there's no question that CTV will be the fastest-growing segment as we exit 2023. It's just budgets that were more branding-oriented, that were TV-oriented are always the first to get paused as opposed to more performance-related advertising, which is typically the domain of the DV+ world.”

Upfront Season

That brings us to the potential time frame when CTV ad revenue could turn back up, and start growing again. Per our previous Netflix coverage:

“I foresee Netflix doing quite well during next year’s upfront season, which is when prepaid inventory is contracted between high-paying brand advertisers and media companies. Assuming there are no changes, we fully expect to hold our position well into this time frame (Q2 2023). This is primarily because Netflix has very high-quality content and because Pay TV advertisers are in some pain right now with the need to find strong content to place ads.”

Magnite is asserting they will also do well in the upfront season, which takes place in May. Notably, we wrote about Netflix and the upfront seasons prior to getting information on the flat 2023 budgets. Netflix being a new entry could take market share, however, as has been pointed out on the forum, this is speculative as the ad tier will not have had much time to accumulate many users. Ultimately, weaker 2023 budgets complicates things and Magnite’s report reminded us of this, in no uncertain terms. Technically, every ad-tech investor is speculating as the data (today) doesn’t support a strong 2023. This can change if budgets get revised.

What management is saying below is that Buyers are in control for the 2023 Upfront season and auctions will be more n demand this year than presold inventory at a set price. He is hopeful that Buyers will be encouraged by the favorable conditions for a successful Upfront season.

Michael Barrett

Yes, great question. These trends are hard to like kind of draw generalizations just given the needed nature of the marketplace. But I think that you're going to find going into the upfront a kind of record, which is a little embellished to talk about a record when there's been very little biddable inventory in the premium CTV categories of the plus services, the broadcasters, et cetera.

But I think you're going to find a record amount as dictated by the buyers. The buyers — every dollar is going to go a lot further in this marketplace, and they have demanded, for quite some time now, the opportunity to be able to bring data to the foray and bid openly on it. And so I think this concept of the invite-only auction that who has done so incredibly well with, just no question that you're going to see the spread of that, just given the cloud that the buyer has coming into it.

We're also seeing quite a bit of biddable inventory at CPMs that are quite different than perhaps CPMs were in Q3 in the fast service market and in the OEM market. So yes, a biddable is coming. It's probably coming faster because of this tough ad economy. And it does bode well for take rates for sure because of the amount of value that we contribute to conducting an auction versus just being the technology partner to process presold deals by the publisher.

Disney Partnership

In the opening remarks, Magnite stated the partnership had been renewed:

“First, I'd like to highlight the news in late January that we expanded and renewed our agreement as Disney's global programmatic SSP partner. As you may recall, our relationship with them started with Hulu. We have since grown the relationship to include the full portfolio of Disney properties […] We are thrilled to be a partner with Disney in support of their audience and targeting capabilities, which leverage the Disney Select first-party data platform with more than 100 million U.S. household level ideas.”

Here is a question from an analyst on the call. The answer pertains to the value Magnite adds, and why Disney prefers to outsource this, and Magnite’s expectation that others will follow suit in using them for biddable/auction side.

“Michael Barrett

Sure, Ian. So as it relates to Disney, I think we've been pretty clear that — we are working with them primarily as a technology partner that helps facilitate programmatic buys that are sold by Disney. The belief is that it moves to a more biddable environment. With us running the auction piece of it, the economics increased in terms of take rates. And so I think that, that plays itself out over time.

And there's no question that I think Hulu has shown the efficacy of having biddable inventory going up against what traditionally is upfront inventory guaranteed pricing. And I think that, that's the model that Disney is going to emulate. And I don't think they're an outlier by any stretch. They're just more advanced. They have more inventory, right? They're global, and they have Hulu. And they also had the learnings of Hulu being at this for 8, 9, 10 years doing programmatic.”

Conclusion:

Given Magnite remained strong on cash and has a fairly direct reason for missing on the bottom line, some of the price weakness is likely due to valuation and investors taking gains. We discussed the valuation concerns leading into earnings on the forum.

This is one of the strongest stocks off the bottom in October in the tech universe and certainly in the ad-tech universe.

· For example, Magnite has been much stronger than TTD since October, at +80% versus +6.3%.

· It’s also been stronger than TTD since Jan 1st, 2022 at (22%) versus (38%).

· If you go back to Nov 1st, 2021 blowoff top, then TTD has been stronger at (51%) MGNI versus (26%) TTD.

The point is that even a perfect earnings report (if we agree TTD had a perfect earnings report) may have been sold off due to the strong price action Magnite has seen recently as Magnite has been beating the ad-tech favorite (TTD) for going on 14 months in price action. Eventually, the market is going to take a breather. The strong price action is based on the stock often hovering in a 1 to 2 forward price-to-sales with a strong bottom line, unlike most small caps right now. Magnite didn’t lose any major ground on its bottom line.

Most importantly, weak ad budgets in 2023 are a gale rather than simply a headwind. This is a powerful force that we are seeing across every single ad-tech name right now in terms of YoY deceleration (Q4 is always strongest quarter for ad-tech so the YoY is the important comp).

Magnite is correct in that the bottom for budgets is likely to be hit when you least expect it, hence the comment we could be at the bottom right now. Most investors may not care to time a bottom with their ad-tech stocks. We are going to attempt to time the bottom, and so it’s likely you see us exit Magnite, and then rely on technicals for when to re-enter.

Nvidia Throwback: An Example of Why Conviction Matters for Stocks

Posted on February 23, 2023June 30, 2026 by io-fund

The video below was originally recorded on August 8th 2022. You can view the full clip here.view the full clip here.

Last August, Nvidia had a $2.5 billion revenue miss due to gaming and crypto mining related weakness. This caused the stock to selloff (8%) in one day. Many pundits were questioning if Nvidia could overcome the gaming segment weakness given Ethereum’s Merge to Proof of Stake would permanently reduce demand for gaming GPUs.

Charles Payne of Fox Business News asks Beth Kindig of I/O Fund if she still plans to hold the stock given the crypto mining surprise.

Her answer is fairly simple: “It’s a tough day for Nvidia investors but in the long run it’s not going to matter. We hold the stock for its lead in artificial intelligence. Anything outside of that thesis is not important to us. To be contrarian, data center is going to be up 61%, so for AI investors such as myself, we are right on track.”

Below is the I/O Fund trading history on Nvidia which shows why it’s important to have conviction in tech stocks. Due to having this conviction, the I/O Fund bought Nvidia at the low in October at exactly $108 with a real-time trade alert sent to their research customers.

You can view follow-up analysis on Nvidia here:

Get Free Weekly Webinars Delivered to Your Inbox! Subscribe for Free Weekly Stock Analysis from Top-performing Analysts with 403% gains here:

https://bit.ly/3QqzEVF

Read More about I/O Fund’s Portfolio Returns:

https://bit.ly/3zXFp7M

Google Stock: Search Is On The Precipice Of Multi-Decade Disruption

Posted on February 23, 2023June 30, 2026 by io-fund

This article was originally published on Forbes on Feb 17, 2023,01:18am ESTForbes on Feb 17, 2023,01:18am EST

Earlier this month, Google’s stock (Alphabet) tumbled 7% when chatbot Bard was unable to complete a search with 100% accuracy. During a demonstration, Bard returned incorrect information about which telescope was the first to take pictures of a planet outside the Earth’s solar system. This was a minor mistake given how far large language models and generative AI has come, rather it was the timing that was a bit flawed as OpenAI’s ChatGPT, the chatbot powering competitor Microsoft Bing, had been dominating headlines since its November 30th launch.

Microsoft, being an opportunist, took it a step further and announced Bing would now be powered by a faster and more accurate version of GPT-3.5 one day after Bard’s failed demonstration: “We’re excited to announce the new Bing is running on a new, next-generation OpenAI large language model that is more powerful than ChatGPT and customized specifically for search. It takes key learnings and advancements from ChatGPT and GPT-3.5 – and it is even faster, more accurate and more capable.”

Both companies have been preparing for this moment for many years. Microsoft invested $1 billion into OpenAI a few years ago with a new $10 billion round announced last month. Meanwhile, Google acquired DeepMind in 2014. Google also previously developed conversational neural language models such as LaMDA, which is used by Google’s Bard for its conversational AI technology.

As much fun as the media has had lately poking fun of Bard, there have been similar, compelling reports of ChatGPT-powered Bing also having accuracy issues.

Point being, both are in the early stages and mistakes are being blown out of proportion. Which brings up more important questions for investors – given that technology can require many iterations, what’s the right timing for generative AI and chatbots to drive real advertising revenue?

Investors can get burned by being too early. For example, autonomous vehicles (AVs) were promised in 2019, and the Metaverse has not driven any real gains despite a large media push in early 2021. How does AI compare in terms of time to market?

Secondly, Alphabet has a lot of turf to defend. It won’t only be Bing, but also browsers like Opera that will incorporate ChatGPT into its sidebar. From there, it’s easy to imagine other competitors may crop up over time, some replacing search engines entirely with conversational AI applications powered by speech recognition, which are otherwise unimaginable today.

We look at these key points below for a 360-degree view on Google’s stock given search is on the precipice of its first major shift in over two decades.

Background on AI-Powered Search

“AI is the most profound technology we are working on today. Our talented researchers, infrastructure and technology make us extremely well positioned, as AI reaches an inflection point.” -Sundar Pichai, Alphabet’s Q4 earnings call.Q4 earnings call.

Despite the mishap with Bard, it would be a human-generated mistake to think Alphabet does not command a place of leadership right now in generative AI. Alphabet was one of the first tech companies to focus and invest on AI and natural language processing (NLP). We pointed out to our premium research members in July of 2022 that ChatGPT is based on transformer architecture that Google initially introduced in 2017 when we saidpremium research members in July of 2022 that ChatGPT is based on transformer architecture that Google initially introduced in 2017 when we said:

“Transformers are becoming one of the most popular neural-network models by applying self-attention to detect how data elements in a series influence and depend on one another.

Sequential text, images and video data are used for self-supervised learning and pattern recognition, which results in more data being used to create better models. Prior to transformer models, labeled datasets had to be used to train neural networks.

Transformer models eliminate this need by finding patterns between elements mathematically, which substantially opens up what datasets can be used and how quickly.

Google first introduced transformer models in 2017 and transformers are used in Google and Bing Search. Transformers also led to BERT models, which stands for Bidirectional Encoder Representations from Transformers, and is commonly used for text sequences. Transformers are also used in GPT-3 (it’s the T in GPT) which improved from 1.5 billion parameters to 175 billion parameters. GPT-3 has the ability to report on queries it has not been specifically trained on.”

Earlier this month, Google’s CEO, Sundar Pichai, gently reminded the AI community of how cutting edge Google’s research is when he stated, “Transformer research project and our field-defining paper in 2017, as well as our important advances in diffusion models, are now the basis of many of the generative AI applications you're starting to see today.”

BERT was designed to help Google better understand search intent, as despite billions of searches every day, about 15% of those searches are for brand new terms. This prompted Google engineers to develop a model that could self-learn.

The result is that searches results are more accurate by taking into consideration the nuances of language.

Sign up for I/O Fund's free newsletter with gains of up to 221% -Click hereSign up for I/O Fund's free newsletter with gains of up to 221% -Click hereClick here

Multitask Unified Models (MUMs) are 1,000X More Powerful than BERT

Multitask Unified Models (MUM) were introduced in 2021 to further address conversational nuances and is 1,000 times more powerful than BERT. MUMs will have a large impact for search users as it decreases the amount of effort put into seeking the desired information. It’s not only addressing the 15% of search based on new terms, rather it’s a powerful iteration that returns search results that more closely resemble how humans interact.

According to Google, it takes an average of eight queries to answer a complex question. With MUM, this is reduced to one query. You can theoretically ask “should I travel to Hawaii or California this Fall?” and MUM will be able to compare travel rates and weather patterns to answer this question with more depth. Similar to if you ask your friend this question, they might answer “Hawaii is more expensive to travel to but California is prone to wildfires in the Fall, so I would go to Hawaii.” To search for this answer would take many queries, but with MUM, succinct, human-like responses are provided in only one interaction.

Large language models have been helping to improve search results for many years. Therein, Google presents its moat; which is not only a deeply engrained behaviour pattern where search users automatically turn to the multi-decade leader out of pure habit, but that Google search truly presents the highest quality search results today.

Google’s commanding lead on search is not a legacy metric, by any means, rather it symbolizes the lead Google has on data for training large language models.

Bard’s demonstration may have been problematic compared to Chat-GPTs more favorable reviews, however, it’s nothing more than that for now —- which is a mix of bad reviews and good reviews by a limited number of beta users.

TPUs:

This brings us to Google’s TPUs, which are essentially ASICs (application specific integrated circuit) on the efficiency/flexibility spectrum. I first covered the differences between TPUs and GPUs nearly four years ago in 2019 for our premium members when I said:first covered the differences between TPUs and GPUs nearly four years ago in 2019 for our premium members when I said:

“TensorFlow is rising in popularity as a machine learning framework and TPUs primarily run TensorFlow models. This is one of Google’s more successful experiments. They are cheaper and use less power than GPUs and are specifically focused on machine learning.

TPUs train and run machine learning models and power Google Translate, Photos, Search, Assistant and Gmail – i.e., image recognition, language translation, speech recognition and image generation.”

Although there are ongoing debates between TPUs and GPUs, the primary difference is that TPUs are application specific and have been optimized for Google’s AI tools. Meanwhile, Nvidia was the first to break ground in deep learning due to the ease of programming GPUs and the relative speed in which parallel computing can train networks. Nvidia also offers its customers an aggressive product road map.

An example of this is the H100 DGX SuperPods, which we covered for our premium members in July when we said:

“Nvidia and Microsoft recently worked on a Mega transformer model with 530 billion parameters and the future for AI engineers is trillion-parameter transformers and applications. The H100 is already prepping for this. According to Nvidia, the training needs for transformer models will increase 275-fold every two years compared to 8-fold for other models. The H100 GPU with its Transformer Engine supports the FP8 format to speed up training to support trillion-parameter models. This leads to transformer models that go from taking 5 days to train to becoming 6X faster to only taking 19 hours to train.”

As of today, TPUs do not necessarily provide Google an advantage over Microsoft’s partnership with Nvidia. When TPUs were first launched, it was expected that it would provide Google an important lead in launches such as Bard. However, Nvidia has proven to be a more difficult competitor than originally expected, and I imagine Microsoft will not stray from this partnership as the company will instead focus on other areas, such as taking more market share with Bing.

Introduction of Bard powered by LaMDA

LaMDA is a conversational language model that powers Bard. Two years ago, Google launched LaMDA to better mimic open-ended conversations by training the language model on dialogue. The result was a more human-like chatbot that personally knows you well enough to recommend movies or books, is sensitive enough to change an uncomfortable conversation, can discuss its own “death” by being turned off, —- and also has machine vision to where it can look at a picture and discuss the picture intelligibly.

Bard was released this month for beta testers and will be available to the public “in the coming weeks.” As mentioned in the introduction, Bard answers questions with real-time data whereas ChatGPT is trained on data from 2021 or earlier (note: the new Bing version is rumoured to use real-time data, see below).

Bard is also free, and given Google’s search revenue, the company may have incentives to undercut competitors that charge paid plans for conversational AI.

Other ChatGPT alternatives

Anthropic is building a 52-billion-parameter pretrained model called Claude, which is a potential rival to ChatGPT. Google invested $300 million into Anthropic last year, with a similar arrangement as Microsoft and OpenAI, which includes a stake in the R&D of the startup. Anthropic was founded by former employees of OpenAI. Whether Claude can actually exceed Google’s own language systems is yet to be determined, or perhaps Google is simply spreading its bets and wanting access to its competitors’ former talent. Despite being in closed beta, there’s an excellent write-up here about the differences between ChatGPT and Claude.

DeepMind is also not to be underestimated. Google’s sister company is behind many of Google’s AI product integrations to-date. In September of 2022, DeepMind introduced Sparrow which is trained with human feedback, similar to ChatGPT, but will use up-to-date information from a Google-powered internet. DeepMind’s previous release, Chinchilla, was competitive with ChatGPT 3.0 before the more advanced ChatGPT 3.5 was released.

There are many other large language models, such as Google’s PaLM and Microsoft’s Megatron, in the 530 to 540 billion parameters size and also based on Transformer architecture.

Notably, this is not meant to be a comprehensive list rather a sample of the level of innovation occuring in this space.

The I/O Fund has launched a new $99/year Premium Newsletter called "Essentials" — this newsletter delivers premium samples for our readers who want more actionable analysis for their tech portfolios. This month, we released a stock pick that we believe will be a leader in 2023 plus a video with the buy plan.$99/year Premium Newsletter$99/year Premium Newsletter called "Essentials" — this newsletter delivers premium samples for our readers who want more actionable analysis for their tech portfolios. This month, we released a stock pick that we believe will be a leader in 2023 plus a video with the buy planbuy plan.

AI to Drive Advertising Revenues

The strength in Search highlights the advantage that having first-party data provides. The company had global desktop market share of 84% in online Search at the end of December 2022, according to data from Statista. Desktop share dropped slightly from 88% at the end of December 2015 to 84% at the end of December 2022. Meanwhile, Microsoft’s Bing share increased from 5% to 9% during this period.

Source: Statista

According to data from Statista, YouTube has 2.5 billion monthly active users. It ranks second behind Facebook which has 2.96 billion monthly active users.

Source: Statista

According to the data from Nielsen, the company also has a leadership position in streaming in the U.S. For the month of December 2022, YouTube (including YouTube TV) accounted for 8.7% of TV usage, followed by Netflix with 7.5% and Hulu with 3.4%. With AI, the company is helping advertisers address pain points like frequency and measurement.

Source: Nielsen

Android has a dominant market share in Mobile Operating Systems. As per the datafrom Statcounter, Android accounted for 71.8% share compared to 27.6% for Apple iOS at the end of Q4 2022. The share for Android has come down marginally from 74.5% in Q1 2018.

Source: STATCOUNTER

This vast amount of first-party data from Chrome and Android can be efficiently used to train complex AI models. A few years ago, I accurately predicted Apple’s IDFA changes would cause problems for advertising companies in an editorial for Forbes:

This is a problem for the ad industry because it goes well beyond personal sentiments and niceties around privacy and slow-moving government regulations and pits tech giant against tech giant in the black box world of ad software, user tracking and engineered loop holes. There is little question who will win as Apple goes up against Google, Facebook and many others. After all, it’s Apple’s device, Apple’s operating system and Apple’s app store. The only question is why this hasn’t happened sooner.

Similarly, Google is a large real estate owner with arguably more data than any other tech company in the world. This advantage cannot be overstated when it comes to training large language models (LLMs). In addition to having a strategic advantage for future development of LLMs with data, Google can offer advertisers instant ROI.

Philipp Schindler, Senior Vice President and Chief Business Officer said in the earnings call, “Going forward, we are focused on growing revenues on top of this higher base through AI-driven innovation.”

This will be accomplished with AI campaigns, such as Performance Max and Smart Bidding. Smart Bidding uses machine learning tools to optimize the bid of the advertisers. ML tools can analyze millions of data signals and can better predict future ad conversions. The further advancement in AI helped to improve the bidding performance in 2022.

Performance Max will replace Smart Shopping Campaigns. Performance Max allows advertisers to access all Google ad channels from a single campaign and uses Smart Bidding to optimize performance by efficiently matching the conversion goals of the advertisers. Advertisers saw a 12% increase in conversion value with Performance Max when compared to Smart Shopping Campaigns. This is a drop in the bucket in terms of what’s likely to follow over the next few years in terms of better ad tools.

Financials

Alphabet’s current revenue growth is one of the lowest in its public history. Last quarter, revenue grew by 1% to $76.05 billion and on constant currency basis grew by 7%. Next quarter, analysts expect revenue to grow 1.1% to $68.78 billion in Q1 2023. From there, the revenue growth is expected to gradually increase.

Google Search revenue was negative (1.6%) YoY to $42.6 billion and YouTube ads revenue was negative (7.8%) YoY on the back of the tough macro environment. Per the earnings call, “In YouTube, we are prioritizing continued growth in Shorts engagement and monetization, while also working on other initiatives across our ad-supported products.”

The number of YouTube creators is at an all-time high. This can create a flywheel opportunity as content increases with more creators, which leads to an increase in viewership, which in turn is expected to drive more revenues. In order to reward creators, the company has started revenue sharing with YouTube Shorts, which now averages 50 billion daily views. This is up from 30 billion daily views in Q1 2022.

Google Cloud revenues was up 32% YoY to $7.3 billion. The company is seeing strong momentum from enterprises and governments for digital transformation. Management mentioned in the earnings call, “Google Cloud is making our technological leadership in AI available to customers via our Cloud AI platform, including infrastructure and tools for developers and data scientists like Vertex AI.”

Source: Company IR

In light of the soft revenue, net income declined to $13.6 billion compared to $20.6 billion in the same period last year. EPS was $1.05 and missed estimates by 11.9%. The company also recently announced a reduction of about 12,000 employees to improve long-term profitability

Risks to consider

Microsoft’s investment in OpenAI is an obvious risk with quite a bit of awareness. Google has not faced a similar threat for many decades. Microsoft also recently announced a new version of Bing which is yet to be available to the public. A student named Owen Yin previewed the new Bing before it was shut down. The new version is expected to replace the search bar with a chatbox.

However, you can also search the traditional way by toggling between chat and search in the toolbar. The new Bing is also expected to have access to the real-time data, unlike ChatGPT, which is trained on the data collected through 2021. The new version is expected to provide detailed answers rather than just links to websites. Similarly, the users will be able to chat with the bot regarding their queries and develop a conversation. It is also expected to perform more creative tasks, such as writing an email or a poem.

Opera also plans to integrate ChatGPT with a Shorten button feature, which will provide summaries in the side bar.

Conclusion:

I would not be surprised if we exit 2023 with a reimagined way to use Search Engines. The iteration cycle here is likely to move quickly compared to AVs or the Metaverse, as there are real-world applications where AI can be applied without safety issues (AVs) or friction in terms of user adoption (Metaverse/VR headsets). Instead, the scale has already been built with Search being a viral, daily activity used by nearly every human on earth. AI advancements will simply improve what is already in place.

Cutting-edge chatbots can be quickly deployed on the search engines that already exist, and this is a substantial difference from other overhyped, early-stage technologies. Their accuracy may still need time, but they're probably not too far off from being deemed “reliable enough.”

Investors should expect that AI will become a winner(s)-take-all market. In time, the difference in how search and other applications operate in terms of user experience plus ROI for advertisers will help carve a larger lead.

Secondly, investors should not forget the best innovation comes from the private markets, and even if stock-driven media focuses on Google Versus Microsoft, there will be a few David-versus-Goliaths where the smaller team comes seemingly out of nowhere to win the hearts and minds of consumers with a viral entry on the market. However, back to point number one, look for the Goliaths to court the smaller teams and bring them into the fold rather than compete head-on.

It may be clear that there are some puts and takes with Alphabet, such as search being on the precipice of a multi-decade shift, yet the reality is that ad revenue for the company is flat to declining. Our firm uses a blend of broad market analysis, technicals and fundamentals to time entries, such as when we bought Nvidia at its lowest trading point in October 13th for $108 with a real-time trade alert provided to our Members. Our process helps to reduce risk around stocks and find strong entries. Nvidia is up 100% from that recent entry. Our firm will do something similar with Alphabet, as we believe there is a further drawdown in its future. We hold weekly webinars on Thursdays at market close to go over the exact levels we plan to enter stocks. You can learn more here.

Royston Roche, Equity Analyst at the I/O Fund, contributed to this article.

Please note: The I/O Fund conducts research and draws conclusions for the Fund’s positions. We then share that information with our readers. This is not a guarantee of a stock’s performance. Please consult your personal financial advisor before buying any stock in the companies mentioned in this analysis.

POSITIONS REPORT – 2/21/23

Posted on February 22, 2023June 30, 2026 by io-fund

Broad MarketBroad Market

I am updating the current counts to fit the most likely interpretation of the price action of the 2022 bear market. The blue count is the same, and I consider to be a low probability, while the red count is favored for several reasons. For those that have not seen my most recent webinar, I encourage you to listen, as I go into detail why the macro and technical information that we have supports this thesis. You can listen here for I/O Premium, and here for Seeking Alpha.

The NASDAQ-100 (NDX) offers the most pronounced version of this structure in red below. In fact, it was the only structure that accounts for the price data, while the blue count feels forced.

Red – The reason I’m moving away from the standard A,B,C structure is because the current 3 wave bounce would have to be the B wave. B waves tend to retrace the majority of the first leg down. This would mean that we make a run to new highs well above 4400 SPX. This is simply not true in this case. The B wave is making a lower high in price, while extending longer in time than prior attempts at a bounce.

The only structure that accounts for this type of behavior is a complex corrective pattern called a W,X,Y pattern. This is characterized by downward trending 3 wave patterns in all directions (sound familiar?), where the structure gets more extended towards the end. If true, we should drop in a 5 wave pattern into the 9000 NDX region to complete the bear market. This level would be around 3000 SPX.

Blue – this scenario has us bottoming in a rather exotic structure. The C wave plays out as a very extended diagonal pattern, while the A and B waves are rather short. It fits, but is more rare to see a correction unfold with such disproportionate waves than a W,X,Y pattern. To make this scenario more improbable, the fact that we only have a 3 wave bounce off the October low means that if this is a new bull market, it would have to unfold as a diagonal pattern. More times than not, 3 waves tends to be a correction than the start of a new trend.

Daily Chart SPX

Shifting back to SPX, which has the same W,X,Y pattern unfolding, if we analyze the 3 wave bounce off the October low, it appear to be incomplete. C waves are always 5 wave patterns, and this one only appears to have 4 waves in place. This would imply a run to new highs in the coming weeks, which will target 4225 – 4275.

15 Minute Chart15 Minute Chart

If we zoom in on the ongoing 4th wave of the larger C wave, it also appears to be incomplete. I suspect we will see early weakness into this week, which would be a buyable low for anyone trying to play the ~200 point bounce that the coming 5th wave implies.

The lower support region is 4025 SPX and must hold 3985. We will likely remove half of our hedge and go net long to play this move. The R/R levels are quite attractive – stop below 3985 with a target of 4225. However, please keep in mind, the odds favor that we will be picking up quarters in front of a steamroller, so being nimble is crucial. For this reason, if we break back below 3985 and sustain below this region, any hedge that we log a gain on, will be put back on.

MacroMacro

The blue count would imply a soft landing is more than possible, as the FED maintains a terminal rate of around 5%. The February FOMC meeting had a tone that implied this was possible, and that after a few more hikes, we would hold ~5% Fed Funds rate into 2024. Though cautious, the market seemed to agree that peak inflation was behind us and that the actions taken by the FED are working. The problem with this narrative is that equities bought it and bonds did not. In fact, the February FOMC meeting marked the high in bonds, as the downtrend continues into this week.

What the bond market is likely picking up on is that the economy is quite durable, and declaring victory over inflation is not a probable outcome at this point. The recent CPI and PPI readings confirmed that inflation is re-accelerating, proving that the battle against inflation is not over. Peak inflation is likely behind us, but the real battle will be getting it back to the 2% target. Considering the extraordinary actions taken to quell inflation, it is concerning that we are starting to see inflation re-accelerate, even slightly.

This is further shown in the recent PMIs. Regarding the PMI readings, anything above 50 indicates an expansion, while below 50 indicates a contraction.

For one, manufacturing is currently at lower levels than just before the February high in 2020. This is a notable reading, as prices are much higher than in the 2019 downturn. Manufacturing is in a recession, and due to its sensitivity to interest rates, it is always a leading indicator of a slowing economy. However, if you look at services PMIs, which accounts for about 86% of the GDP in the U.S., it has re-accelerated into expansion territory.

This is ultimately what a soft landing looks like in the US, where manufacturing contracts while services stays resilient. We saw similar soft landings in the mid-80s, mid-90s and most recently in the 2014-2016 slowdown. So, it seems plausible that this could be playing out again, and all the recession talk is overblown.

The one common thread between all the prior soft landings was the liquidity cycle. The FED was either still in the expansion part of a liquidity cycle, or started up a new one, which diverted services from following manufacturing into a contraction. The current liquidity cycle is below in black and put up against the S&P 500 for reference.

There is a stark divergence between liquidity continuing to trend down and equities trying to recover. The bet that the bulls have to make, which would bolster the trend in equities (blue count), is that the FOMC is about to start a new liquidity cycle, or at the very least, stop QT and allow liquidity to stay flat to trending slightly up based on other metrics. So, the question one has to ask is – with the current new data in CPI and PPI, with pockets of strength in non-manufacturing and employment, is the FED more likely to start a new liquidity cycle, which would push asset prices higher, along with wealth and discretionary spending power? The bond market has answered with a resounding no. In fact, for the first time in this cycle, the bond market as well as institutional analysts are projecting a higher terminal rate than the FED, which is concerning.

Bail Out LevelsBail Out Levels

I have stated before, and will continue to state that my bearish outlook has an expiration. If TLT and the DOW can break back above their December highs, I will abandon our bearish thesis and flip back into the bull camp. I will also want to see DXY (the US Dollar) commence its downtrend. Short of this, I consider the current rally in equities to be running on fumes.

Hedge SignalHedge Signal

We will continue to lean into our hedge signal to tell us when to hedge/not hedge. Our cash raises are determined by our tech/macro outlook. As of now, the hedge signal is not close to flipping back into a risk-on mode. We are in bear market mode, which uses 3 data points to capture bear market bounces (compared to the normal signal that uses ~ 7 data points).

I/O Fund PositionsI/O Fund Positions

NVDA

NFLX

MSFT

MSFT is pennies away from closing the 3rd wave gap. Below $255.40 and it gets closed, as does the hopes of another 5th wave run higher. MSFT has clearly only given us 3 waves up off the low, and this wave, maybe, has one more high in it. As of now, NFLX, AMZN, GOOGL have likely topped. MSFT looks to be next.

TSLA

Here’s a big picture view of TSLA. Technically, it appears to have an incomplete correction. One more wave towards $92 would set up a phenomenal buying opportunity. However, if we get there, the fear surrounding that move would make one not want to buy. The coming pullback needs to hold $138 or this becomes the likely scenario. We will likely buy assuming both scenarios are playing out, and buy in layers.

AMD

My guess is that AMD has one more run to new highs in it. However, this drop needs to reverse soon. Below $75 and the odds start shifting towards the top being in.

TSM

Only 3 waves up, and right at the symmetrical price level (A=C). This type of pattern is usually bearish. The coming pullback needs to hold $70, or we could be in for new lows.

AEHR

MGNI

ENPH

I continue to signs of bottoming while NDX shows signs of topping. We’ll take a shot with some of our cash that the best ER of the year is holding its inverse correlation to NDX.

Crypto

Be open to this count. Bitcoin is completing 5 waves up off the low. How can it continue higher while risk assets push lower? Either the red count thesis is wrong above (we are very open to this), or Bitcoin is tracing a 4th wave. that would mean we are in a nasty, expanded flat correction with $13K on deck. Like with every position, the coming pullback will tell us everything.

Time AnalysisTime Analysis

We have many stocks and indexes showing a time factor coming up this week/next (Feb 20 – March 2). As always, depending on how we trend into it will be the most important piece of information. The NDX shows 2 cycles coming together in the chart below (20th-28th). If we see a sharp drop and reversal early in the week, it could signal the 4th wave low. If we see a move back towards 4200+ by next week, it will be a big warning.

Timeout for Tesla Stock: Where We Plan to Buy

Posted on February 22, 2023June 30, 2026 by io-fund

On 1/26/23, we sent out a trade alert notifying our readers that we purchased shares of TSLA after the release of its 1/25/23 Q422 earnings release. Based on the 2/17/23 closing price of $208.31, TSLA is up 31%. Since that Q4 report, we thought it be worthwhile to update our readers on our thoughts both fundamentally and technically on what we’re watching for in the upcoming weeks.

Right now, our technical analysis is at odds with our fundamental analysis, which is often good news, as it means we will be afforded a lower entry on a stock position we plan to build.

The technicals are telling us a lower entry is on the horizon. However, what will make or break Tesla stock in 2023 is the margins. As most Tesla investors are aware, the company has lowered its price on its vehicles. Coupled with the $7500 EV credit, Tesla's vehicles are more affordable in Q1 than ever before, with some price points below $50,000 for the Model Y SUV when combining the price cut with the EV Credit.

This has led to Model Y selling out in Q1, per a Reuters report on February 15th. Considering a Model Y is now priced at $52,990, down from $65,900, this means a 30% price reduction is possible with the additional $7500 EV credit with the total cost of $45,490.

With these incentives, most investors can see a path to Tesla meeting its delivery goal this year, however, the impending issue is if Tesla can do so while maintaining healthy margins.

The stakes are high for Tesla's stock because if the margins remain healthy, the stock will do quite well. However, if the margins contract, then the bears will be in control. This is a big moment for Tesla, as high average sales price has been a contentious issue for meeting its addressable market. Wall Street will want to see it's possible to do both — serve a wider total addressable market (TAM) with more affordable prices while maintaining a healthy bottom line.

Our in-depth analysis below discusses why the I/O Fund Analyst Team is forecasting that the margins will, indeed, overcome a lower average sales price to sustain operating leverage. Once we discuss the margins in-depth, which to reiterate, we believe is the most important piece to Tesla's 2023 story, we then go into how we plan to build this position while respecting the fact the broad market is in the driver's seat for growth stocks.

Tesla Stock: What to Look for in 2023

First, let’s take a quick look at Tesla through a few graphs. If you were presented with the following company, would you find this an attractive business?

A company with steadily increasing operating margins vastly superior to its competitors and greater that those in the S&P 500.

Source: Tesla Q422 investor presentation

With historical y/y revenue growth also exceeding its peers due to strong demand for its product.

Source: Tesla Q422 investor presentation

With a significant market share gain opportunity for its products

Source: Tesla Q422 investor presentation

It’s these attributes that have drawn us to Tesla as an attractive business. However, as investors in the equity, there are several key factors we are monitoring that may drive the stock.

Sign up for I/O Fund's free newsletter with gains of up to 221% -Click hereSign up for I/O Fund's free newsletter with gains of up to 221% -Click hereClick here

Profitability: Gross margins (GM) vs Operating profit margins (OPM)

Both are impacted by different variables. For GM, the main drivers are the ASPs Tesla charges for their cars and number of cars sold less costs of goods sold such as raw materials costs, particularly lithium used in batteries. For reference, here's the 5-yr price chart of lithium ($/kg). Tesla does not break out this cost but they did refer to lithium battery demand as "quasi-infinite" and a "significant cost." It won't impact their production targets but it continues to be an unpredictable cost headwind. It also explains while there has been renewed speculation that Tesla is interested in purchasing lithium mining assets.

Source: Dailymetalprice.com

For OPM, it’s mainly related to R&D and factory ramp-up costs. Here’s a snapshot (2017 – 2022) of Tesla’s ASPs in relation to its GAAP operating margins. It’s grown from negative 14% to almost positive 17%.

Source: Tesla Q422 investor presentation

The chart above demonstrates that while ASPs have come down about 40% from a little over $100k to $47k, OPM has expanded. A reflection of the immense impact manufacturing efficiency has on operating leverage from higher utilization as the number of cars produced and sold increased.

In the most recent Q4 call, Tesla discussed how their future focus would be on increasing operating margins over time. A sign of the evolution of its mindset from that of a technology company needing to invest and sacrifice short term profitability to one with a large industrials-like manufacturing footprint and supply chain focusing on costs and efficiencies. A focus that long-term investors should find appealing.

Perhaps a simple picture provides insight on how Tesla thinks about manufacturing efficiencies versus its peers. If you compare the Q422 investor presentation of Tesla to GM and Ford. There's not one picture of a human. Rather, you see high precision Kuka German robots. There's not a single robot in GM or Ford's presentation. Tesla's Q4 opm were 16% compared to GM at 8.8% (adj) and Ford at 5.8% (adj).

That said, at the moment, the investment community is understandably focusing on the automotive gross margins given the recent price reductions A positive takeaway from the call was that Tesla expects ASPs to stay above $47,000 and automotive gross margin to go above 20%. Indications that automotive gross margins have bottomed. This message contributed to the stock rally (emphasis added below).

“The next question from investors is, after recent price cuts, analyst released expectations that Tesla automotive gross margin, excluding leasing and credits, will drop below 20% and average selling price around $47,000 across all models. Where do you see average selling price and gross margins after the price cuts?Tesla automotive gross margin, excluding leasing and credits, will drop below 20% and average selling price around $47,000 across all models. Where do you see average selling price and gross margins after the price cuts?

Zachary Kirkhorn, CFO:Zachary Kirkhorn, CFO:

So there is certainly a lot of uncertainty about how the year will unfold, but I'll share what's in our current forecast for a moment. So based upon these metrics here, we believe that we'll be above both of the metrics that are stated in the question, so 20% automotive gross margin, excluding leases and rent credits and then $47,000 ASP across all models.we believe that we'll be above both of the metrics that are stated in the question, so 20% automotive gross margin, excluding leases and rent credits and then $47,000 ASP across all models.

An analyst pointed out that the avg COGS per car has gone from $36,000 in mid-2021, peaking at $42,000 back to almost $40,000 currently. Estimates that management did not refute. So a very simple back of the envelope calculation comes to about 18% auto gross margins currently ($(47,000-40,000)/($40,000)). The key takeaway is that pricing and costs efficiencies will both have an impact in getting margins above 20%. For example, using the prior calculation just a $1000 increase in ASPs or $1000 decrease in COGS alone will lead to 20% auto gross margin. If both happen at the same time, that's about a 23% auto gross margin.

There was a follow-up if COGS could go back down to $36,000. This exchange provided further insight.

Excellent. Zach, actually, I'd like to follow up on the data point you just gave on cost. If I look back at the COGS per car, you guys bottom close to $36,000 in the middle of 2021. And then the number went up as you had to face with inflation in input costs and the ramp of Berlin and Texas. And this quarter, I think we are close to $40,000 and we peaked maybe close to $42,000 at some point last year.

And so my question from here is, how much time do you think it takes you to get back to this kind of $36,000, which would mean Berlin and Texas and those input costs, all that stuff is normalizing, is that like — and that would be like a kind of like a 10% decline in the COGS per car? Is that something we can hope to see this year or is that too optimistic?

Zachary Kirkhorn, CFOZachary Kirkhorn, CFO

The Austin and Berlin ramp inefficiencies in 4680 will make a substantial amount of progress on that over the course of the year, and that's within Tesla's control. We're doing a lot of work on cost reduction outside of that. And we talked about supply chain costs, expedite, logistics, attacking everything.

On the raw materials and inflation side, where lithium is the large driver there and this was a meaningful source of cost increase for us, we'll have to see where lithium prices go. And we're not fully exposed to lithium prices, but I think in general, is what we've seen from our forecast here, cost per car of lithium in 2023 will be higher than 2022. So that's a headwind that would have to be overcome to return back to those levels. So, I don't think we'll get there this year, but I think we'll make progress. And we'll continue to find ways to offset these raw material costs that we don't have control over. [Indiscernible] is there anything on that?

Furthermore, to the extent the Fed’s actions have lowered non-lithium prices, there will be a lag.

Roshan Thomas, VP of Supply Chain, added the following.

“.. on the non-cells raw material, we begin to capture benefits of indexes tapering out, but due to the length of various supply chains, it does take time before this is reflected in our financials. And while alumina is down like 20% year-over-year, steel is about 30% down year-over-year, the global non-cells raw materials market continues to be influenced by geopolitical situations in Europe, high production cost due to labor cost increases and energy spikes and disruptions due to natural disasters like typhoon in Korea four months ago, pandemic lockdowns.

So, we believe that meaningful price corrections will ultimately come, but it remains uncertain exactly when. In the meantime, we continue to redesign supply chain to make it more efficient and work with our supplier partners to find more efficiencies, streamline logistics and transportation to reduce costs.”

Below, is a simple sensitivity analysis of the impact that changes in asp and cogs per car have on automotive gross margin per car. It excludes leasing and credits. The numbers are estimates only and the primary purpose is to illustrate the magnitude these changes have on automotive gross margins. The yellow highlight is where they are estimated to be currently, blue is the minimum level Tesla has guided, green is potential upside depending on the change only in price or cogs and gray is if both change. At the moment, a change in price will likely be the main driver in automotive gross margin improvement. So, an increase in asp to 49k or 50k results in an automotive gross of 23% and 25%, respectively.

Gross Margins and Operating Margins for 2023

We outlined the variables that impact both. We will look for continued signs of stabilization in the Q123 report and further confirmation that we have seen the bottom in both.

In Q122, Tesla reported operating margins of 19.2% and ended Q422 with 16%. For 2022 it was 16.8% vs. 12.1% in 2021. If the operating margin stabilizes at a level similar to or greater than Q4, then a recovery in 2H23 is reasonable, if not sooner in Q2.

Tesla will have an investor's day on March 1st, this may provide further insight.

Long-term OPM Potential:

Tesla has not provided any medium to long-term OPM targets, but if they did, this would lead to a re-rating of the stock. The auto industry is still cyclical so that may be wishful thinking. At the moment, Tesla's OPM dwarfs its auto competition. Perhaps, we are getting closer to the point where the best comp will be other industrial companies with best in-class margins. A topic we will look at in the future.

This is what Musk had to say.

“As we mentioned many times before, we want to be the best manufacturer. But really, manufacturing technology will be our most important long-term strength. And we'll talk more about our upcoming plans at the March 1st Investor Day.”

For a point of reference, Mercedes Benz and BMW have about 13% group operating margins while Ferrari has 23%. Of course, they have different product mixes, price points and client bases but they are useful comparables to parameterize the margin potential.

In Q122, Tesla reported 19.2% operating margins. So, is a medium-term 20%+ operating margin realistic?

Another potential source of upside to margins is if Tesla acquires a lithium mining asset so that they will have better control over their lithium input costs.

Earnings Outlook

Fundamentally, analysts have reduced their adjusted 2023 EPS estimates to $3.97, compared to 2022 $4.07 EPS (actual) mainly due to a decrease in Q1 estimates. Reflecting management's guidance of operating margins similar to q422 due to recent pricing initiatives and raw materials costs but then stabilization and improvement over the course of the year. Upside to these estimates will likely come from higher ASP assumptions.

The Current Demand Outlook

One factor that contributed to the stock rally was management's comments that January orders were 2x that of production (emphasis added).

The most common question we've been getting from investors is about demand. Thus far — so I want to put that concern to rest. Thus far in January, we've seen the strongest orders year-to-date than ever in our history. We currently are seeing orders at almost twice the rate of production. So it’s hard to say that will continue twice the rate of production, but the orders are high. And we've actually raised the Model Y price a little bit in response to that.”Thus far in January, we've seen the strongest orders year-to-date than ever in our history. We currently are seeing orders at almost twice the rate of production. So it’s hard to say that will continue twice the rate of production, but the orders are high. And we've actually raised the Model Y price a little bit in response to that.”

There are signs that demand has remained strong and that the combination of Tesla price cuts and changes to incentives from the U.S. government have been positive for demand. According to Electrek, the Model Y is sold out for Q1. There are no more production slots for a Y order in Q1. Estimated delivery now is April to June. Model Y levels are estimated to be low.

Demand indicators that are supportive of higher pricing and moving automotive gross margin above 20%. Recall, that a $1000 asp increase alone will get to 20%.

Source: Tesla Inventory Charts

Cash flow

We had recently written that the decline in FCF, mainly due to an inventory build in Q4, was worth monitoring. From Q2 of last year to Q3 to Q4, it increased from 4 to 8 to 13 days of inventory. Although higher, these levels are much lower than peers. According to Statista, as of 2022 one of the highest was Dodge at 64 days. Ford had 41, GMC at 38, Hyundai at 37, BMW at 27, Toyota at 21 and Kia at 18.5 days. Here's a snapshot on how Tesla compares to its peers.

A glass half-full perspective would be that Tesla's lower inventory vs its peers is a product of their leading manufacturing capabilities. And that the recent inventory "build" (relative to its historic levels) was a reflection of their effective inventory management and anticipation of future demand in 2023.

Given the recent demand trends, we are less concerned and will check inventory levels at the end of Q1. These initial concerns were tempered by the large $20b cash balance that would allow Tesla to execute necessary investments if cash flow was tied up in inventory.

One factor that impacted Q4 cash flow that we are still looking into is the $4.4b spent on investments. Given the recent lithium asset acquisition speculation, could they be related?

More on FSD:

From a gross margin perspective, this is how Elon described (emphasis added) the impact of a customer paying for the FSD software.

Elon Musk

Yes. Something that I think some of these smart retail investors understand, but I think a lot of others maybe don't is that the — every time we sell a car, it has the ability, just from uploading software to have full self-driving enabled and full self-driving is obviously getting better very rapidly.

So that's actually a tremendous upside potential because all of those cars, with a few exceptions — I mean, only a small percentage of cars don't have Hardware 3. So that means that there's millions of cars were full self-driving can be sold at essentially 100% gross margin. And the value of it grows as the autonomous capability grows. And then when it becomes fully autonomous, that is a value increase in the fleet. That might be the biggest asset value increase of anything in history. Yeah. So that means that there's millions of cars were full self-driving can be sold at essentially 100% gross margin. And the value of it grows as the autonomous capability grows. And then when it becomes fully autonomous, that is a value increase in the fleet. That might be the biggest asset value increase of anything in history. Yeah

But it’s still a work in progress

There was recent headlines on 2/17/23 regarding concerns over the software. Tesla recalled about 300k cars and will update the software. The stock finished up over 3% for the day so the market does not seem to be concerned. But we will monitor it.

Conclusion

The recent data points have given us reasons to give more credence to Tesla’s Q4 constructive commentary around auto gross margins and company operating margins for 2023.

The next catalyst will be the March Investor Day.

Things we will be updating our premium members at I/O Fund on:

Further evidence of a stabilization in automotive gross margins and group operating margins
Demand vs. production trends through January and February
Pricing trends
Manufacturing initiatives to increase cost inefficiencies
Efforts to secure lithium assets
Recent FSD concerns

How to position now and going into Tesla’s Investor’s Day on March 1st

The 2022 bear market appears to be a large degree correction within an even larger uptrend. Like some FAANGs, this implies that when the current macro cycle ends, and a new growth cycles begins, it has a probable chance of making new all-time highs. This cannot be said about all tech.

The question the next few weeks will answer is: Has TSLA bottomed at $102, or Does TSLA have one more low around $92 before bottoming?

If we look at the structure of the 2022 decline, it appears to be incomplete. In other words, the final drop only has 4 waves in place, and implies a 5th wave drop is soon to follow. Considering that strength of Tesla's recent earnings report, this decline, if it were to unfold, would be the result of a continuation of macro forces. This cannot be ruled out.

The below chart has two scenarios to address, one of which outlines this possibility. The blue count implies that TSLA bottomed at $102 and will need to make a higher low in the coming weeks/months that holds $138 and turns back up. The red scenario breaks below $138, and continues to make a slight new low into the $92 region, which would complete the large degree drawdown off the 2022 high.

In the above chart, you can see how the weekly momentum indicator is making a higher high while price makes a lower high. This is typically bearish, and a warning to anyone looking to buy TSLA at these levels.

If we zoom-in on the bounce, we have a what appears to be a bullish structure. Note the gap in the middle of the uptrend on heavy volume. This gap stayed open, and price continued higher. These gaps tend to occur in the middle of the move, which has proven to play out. We are now in the final moves of this bounce as momentum and volume continues to fade at these price levels.

If our blue scenario is in play, the coming pullback needs to hold $138. If we break below $138, the odds start to shift that the scenario in red is in play. Regardless of what plays out, we believe Tesla, Inc. is about to set up a great buying opportunity for years to come.

We issue real-time trade alerts to our research members when we enter, exit, add or trim to a stock. Our portfolio is actively managed with allocations that correlate to a stock's current technical strength or weakness, as well as the underlying fundamentals.

What's next

This Thursday at 4:30 pm Eastern, I will be holding a webinar for premium I/O Fund members to discuss how I plan to navigate the broad market, as well as various tech entries including Tesla. We offer trade alerts plus an automated hedging signal. In addition, we are holding an annual webinar on March 14th that discusses "How to Build a Defensible Tech Portfolio" Follow me on Seeking Alpha for more details.

The I/O Fund Analyst Team contributed to this article

Datadog Q4 Earnings: A Candid, Conservative Management Style

Posted on February 16, 2023June 30, 2026 by io-fund

Tech growth is a certain style of investing; it’s a mix of grand slams but more strikeouts. Value investing is a mix of singles, doubles and even bunts, but with fewer strikeouts. Investing style and risk appetite runs a large spectrum from high risk/high reward to low risk/low reward.

Similarly, there are different management styles. Datadog falls firmly in the candid, conservative style of management. They are the best-of-breed team that is least likely to overpromise and under-deliver, hence the perfect record on beating on the top line and bottom line.

Both the CEO and CFO will tell investors exactly like it is, even it’s hard to hear. This is very different from other management teams that will take risks on guidance, with the hope of meeting the numbers somehow, and will smooth over anything negative so as not to raise alarm bells.

Datadog’s guide does not necessarily foreshadow lower growth than other cloud companies that have reported, especially as we can assign a high level of probability the actual report will come in higher than the guide. Rather, it was the tone on the call that was very different. Ultimately, as we covered in our Q1 Earnings Prep Webinar, there is a lot of built-up anticipation for a H2 rebound. The rebound may or may not happen; I imagine next earnings season will be a real line in the sand given it takes place four to five months into the year.

The rebound comes from analyst estimates, so of course, analysts are keen to make sure their estimates are correct with the bulk of questions aimed at what 2023 will look like. Datadog told analysts on the call they do not see evidence of a rebound yet, and with what they know today, their guide assumes optimization will continue throughout the year. They do believe eventually optimizations will slowdown, and that cloud migration will again become a tailwind. They are unwilling to provide guidance on when this will happen.

Management specifically called out a bigger slowdown in December on usage than what they saw in October and November. So far, 2023 has more closely resembled December. They also specifically called out larger customers as the primary cohort optimizing and lowering usage and/or spend, while smaller customers are seeing little to no change. Large customers have more to gain from lowering costs, and face more uncertainty.

Datadog’s financials are similar to what we posted on the forum, which is a slowdown from this time last year (to be fair, all cloud has slowed on a YoY basis from Q1 2022 to Q1 2023E). RPO was flat but Billings were down QoQ. Datadog still has a top position for bottom line strength in best-of-breed, although notably, the bottom line has softened.

Financials:

Datadog beat estimates in the current revenue, yet guided below analyst consensus for Q1 and FY2023.

In the current quarter, revenue of $469.4 million represents growth of 44% year-over-year. This beat previous management guidance and analyst consensus of $449M, for a beat of +6% on the top line. This led to a beat on FY2022 revenue at 63% growth compared to 60.8% expected.

Guidance for Q1 is for $460 to $470 million, for growth of 28%. Due to being conservative, as discussed in the intro, the fiscal year guidance is lower than Q1 at 23.8% for $2.08 billion.

You can reasonably assume these estimates will be beaten with a 5% to 10% beat, if we rely on previous earnings surprises, but there’s no guarantees, of course.

Adjusted EPS of $0.26 comfortably beat estimates of $0.19. GAAP EPS came in at ($0.09).

Q1, Datadog management provided a guide in line at $0.22 to $0.24 compared to estimates of $0.24. For FY2023, there was a miss with guidance of $1.02 to $1.09 compared to analyst estimates of $1.13.

Cash flow was up sequentially due to seasonality yet was down on a year-over-year basis. Despite Datadog decelerating, it still ranks high on FCF margins for cloud best-of-breed. Operating cash flow margin was at 24.3% and free cash flow margin of 20.50% equaling $96.4 million in cash flow.

Let’s say we have a deeper recession than expected. Datadog is likely to survive this, but at what valuation is the question. There’s a solid chance cloud remains range bound at these valuations until there’s a return to growth, which means fluctuations up in price/down in price that ultimately provide little movement or gains. I don’t think Datadog is going to be the company that has an unpleasant surprise from an unexpected miss in their earnings report, which is my preference certainly for management style. Rather, they will take the hit up front, like we saw today.

The company has cash and marketable securities of $1.9 billion on the balance sheet with fairly high stock based compensation of $112 million.

Margins:

· Datadog has a high gross margin of 79.3%.

· GAAP operating margin beat at (7%) actual compared to (10%) guide. This is a deceleration from 3% in the year ago quarter.

· Adjusted operating margin was 18% compared to 22% in the year ago quarter.

· GAAP net margin of (6%) compares to 2% net margin

Key Metrics:

· Datadog reported RPO of 30% YoY which was flat from the previous quarter. Notably, the Q4 to Q1 quarter tends to be flat for Datadog with more variability in Q2.

· Billings softened to 31% growth YoY compared to 86% in the year ago quarter. This was a deceleration from Q3 with billings of 51%.

· Customers with ARR of > $100K grew 38% compared to 64% last year

· Customers with ARR > $1 million grew 46.7%. This is a newer metric for Datadog with no year-over-year comp available

· DBNRR is above 130 but management stated on the call they expect this to dip below 130.

Earnings Call:

In the opening remarks, the company stated the following about large customers in Q4:

“Now moving on to this quarter's business drivers. Overall, we observed slower usage growth with existing customers while continuing to scale our new logo acquisition and new product cross-sells. Starting with usage. Usage growth of existing customers in Q4 was overall slightly lower than what we observed in Q2 and Q3, which we attribute first to a continuation of cloud cost optimization by our larger spending customers; and second, to a seasonal annual slowdown in the second half of December that was more pronounced than in previous years.

As in Q2 and Q3, we continue to see more optimization from customers as a larger cloud footprint, while our smaller spending customers are exhibiting higher growth.”

The CFO later provided more color in his opening remarks:

“Next, similar to Q2 and Q3, we saw larger-spending customers grow slower than smaller spending customers. As with Q2 and Q3, we saw relatively more deceleration in the consumer discretionary vertical, particularly in e-commerce and food delivery. Geographically, we saw solid and relatively similar growth across all regions.”

And the CFO also stated this:

“We are incorporating an expectation for seasonally weaker growth in the first quarter due to the subdued growth in the month of December that creates a lower growth trajectory to start the first quarter. While our customers are continuing to expand with us, we are assuming in our guidance that cloud optimization continues to affect our expansion rate in 2023.”

In regards to Datadog’s specific business, they essentially believe they are the next in line on optimization following cloud hyperscalers. In other words, companies are optimizing with the hyperscalers now and working their way through the stack with Datadog second in line, in terms of what order makes the most sense:

“What we see, though, is that customers save money where it matters, which tends to be the very large line items, which for customers that are fairly far along into the cloud, is going to be, first, their cloud provider deals that are, again, one or two others are larger than their observability bills.

And then we're going to be affected by that and maybe with some optimization more specific to observability as well. So that's what we see there.”

Also, management clarified with analysts the slowdown (for Datadog) is not related to headcount, given the many layoffs announced, rather it’s more usage based and related to reducing budgets.

In regards to the larger trend of cloud migrations, Datadog said the following:

“So that's where we're going. I think you're right, though, that the underlying wave that is — has been a tailwind throughout the of the company was cloud migration and digital transformation. I think that we might be a bit more of a headwind over the next few quarters. But we strongly believe that it will become a tailwind again in the future.”

Conclusion:

Datadog is a company we will watch closely and return to in the future. Knowing that I can’t control macro, it feels like 2023 should be used as an opportunity to build tech generals in the belly of a recession rather than guess on companies that are reporting tapering growth (although formally were very high growth). Please note, many companies are reporting tapering growth despite the market rewarding the companies with earnings pops. This is entirely based on expectations for future growth which may or may not materialize.

It’s our preference to take advantage of the lower prices by focusing more on key tech generals for now while allowing time for smaller companies to prove their ability to withstand macro pressure. This strategy can be a win-win, because if we see a deeper recession than normal, the risk of picking the wrong company is much lower than if we bet on decelerating growth from less defensible companies. However, if we see a soft landing, then we are still positioned to participate in growth.

We will continue to identify outliers, such as AEHR, with a heavy focus on this in March and early April. Look forward to new coverage and deep dives coming soon as we wrap up the last of our portfolio’s earnings season next week.

Nvidia: How We Plan to Manage our I/O Fund Position

Posted on February 15, 2023June 30, 2026 by io-fund

From the October 13th low, one of the best performing sectors has been semiconductors. This is a theme that we introduced in the I/O Fund Essentials video “Semiconductor Stocks Continue to Outperform Value” where we stated:

“With a rotation into value names underway, it would be easy to discard all of tech and move towards the sectors that are working. However, as we discussed last week, one specific tech sector is currently outperforming most value names – semiconductors.

This week, we provide a brief video taken from our weekly webinar where we offer a more macro context around why we like semiconductors going forward. Some markets appear to be closer to new highs than lows, and we believe that semiconductor stocks are signaling that they are ready to resume their leadership role going into 2023.

Reference our analysis last week “The Next Bull Market’s Leaders are Being Decided Now” for more information in addition to the video below.”

Since releasing this for our Essentials Members at the end of December, semiconductors have continued to shine. The chart below shows semis are the number one performing sector in tech.

Once of the leading stocks within this sector is Nvidia, a stock that has been a top holding in our portfolio since 2018. Notably, focusing on building Nvidia and closely managing this allocation is as relevant as ever.

We covered this last week in our February stock tip when we stated:

“Simply put, as Big Tech continues to build out hyperscale scale data centers and AI based technology, they will require specialized semiconductor chips – AI accelerator chips – to provide the necessary computing power required. At the moment, the AI chip market is a duopoly with Nvidia and AMD. However, Nvidia’s position is much larger than AMD and a “better” GPU. So as Big Tech continues these AI related investments, Nvidia is the first place Big Tech will go to buy them – namely Nvidia’s H100 GPU chip.”

Nvidia: Technical Analysis

Unlike most tech names, NVDA has a probable path to new highs. The long-term technical path from the 2018 low is listed below in blue, with my alternative path in red.

The market is stretched and setting up for a pullback. This is evident with NVDA’s momentum indicator below the chart. Every time internal momentum reached these heights, and pullback soon followed. As long as the coming pullback holds the $140-$138 region, then the blue path remains valid. This path has the 2022 bear market as a pullback in a larger uptrend, targeting $355+ in the coming months. If we do break below the $140-$138 region, then the odds of this path to new highs becomes diminished, and it opens the door to the $90 region.

The pressing question is how much farther can NVDA run in this bounce off the October lows? The $230 region is strong resistance. There is a confluence of key angles in this region.

If we do see a breakout above the $230 region, this is not a breakout we would buy. If we zoom in on the bounce off the October lows, it is quite clear that the structure of the uptrend is only 3 waves.

A three wave move (in either direction) tends to be symmetrical, and leads to large corrective moves. In terms of symmetrical, what I mean is that the length of the 2nd move higher tends to be the length of the first move higher.

So, if NVDA does see one more high into the $241 region, this would be the exact symmetrical move where most 3 wave bounces tend to end. When you factor in that each move higher is happening with less momentum, the risk is quite elevated above $241.

Conclusion:

We see the odds of NVDA retracing back to the $170-$150 region as a high probability. We will likely look to slowly layer in around these levels. However, NVDA holding the $140-$138 region will be crucial. If this region breaks, it will open the door to the $90 region. This would coincide with the macro environment beginning to drive equities once again. As long-term investors, our plan is to keep NVDA as a high allocation in our portfolio. Our goal is to further accumulate on the coming drawdown, and we will slowly layer into this stock at key levels.

We favor buying in small layers of 1% or 2% at key levels, which we described above. This mitigates our risk if we do reach the $90 region. For example, we bought at the Nvidia low in October at $108. No matter how high our conviction may be in a specific name, macro is the primary force on stocks right now, which is why adding in small layers is even more important in 2023 than in previous years, such as 2020-2021.

Knox Ridley holds a premium webinar every Thursday where he reviews key positions, including NVDA. We cover macro charts as well as various stocks to get a clear understanding of where the market may be going and how to position for it. Learn more about Advanced Market Signals here.Advanced Market Signals here.

Broad Market

Futures

Macro Analysis

Counter Analysis/Bail Out Levels

Hedge Signal

Time Analysis

I/O Fund Portfolio

Financials:

Earnings Call:

Conclusion:

Financials:

Earnings Call:

Macro/Ad Budgets

CTV Ad Budgets Weak in Q1

Upfront Season

Disney Partnership

Conclusion:

Background on AI-Powered Search

Multitask Unified Models (MUMs) are 1,000X More Powerful than BERT

TPUs:

Introduction of Bard powered by LaMDA

Other ChatGPT alternatives

AI to Drive Advertising Revenues

Financials

Risks to consider

Conclusion:

Broad MarketBroad Market

I/O Fund PositionsI/O Fund Positions

Time AnalysisTime Analysis

Tesla Stock: What to Look for in 2023

Profitability: Gross margins (GM) vs Operating profit margins (OPM)

GM:

Tesla:

Ford:

Gross Margins and Operating Margins for 2023

Long-term OPM Potential:

Earnings Outlook

The Current Demand Outlook

Cash flow

More on FSD:

Conclusion

How to position now and going into Tesla’s Investor’s Day on March 1st

What's next

Financials:

Earnings Call:

Conclusion:

Nvidia: Technical Analysis

Conclusion: