The VIX longer term chart below is in neutral, but the short-term signal thinks volatility is higher early next week, which isn’t surprising given it tends to go higher after a long weekend (I sha…

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The robotics story is shifting from programmable automation to physical AI. The old robot was a repeatable arm bolted behind a safety cage. The next generation is mobile, sensor-rich, trained in simulation, updated with real-world data, and increasingly able to make decisions in environments that were never perfectly mapped in advance. That change expands robotics from a factory-equipment category into a computing platform that can reach manufacturing, logistics, transportation, health care, security, construction, agriculture and eventually the home.

The starting point is already meaningful. Roughly 542,000 industrial robots were installed globally in 2024, bringing the operating base to about 4.66 million. Professional service robots sold nearly 200,000 units, led by transportation and logistics, while consumer service robots were already measured in the tens of millions. The critical difference in the next cycle is that AI can make this installed hardware more flexible. Instead of designing a dedicated machine for one motion, developers can increasingly train a general platform to recognize objects, interpret instructions, plan a sequence of actions and recover when something changes.

The 2030s: robots move from pilots to fleets

The 2030s should be the decade when robotics stops being defined mainly by installed factory arms and begins to look like a broad fleet of autonomous machines. A high-growth scenario puts annual robot hardware sales at roughly 93 million units and $540 billion of revenue by 2030, across autonomous vehicles, home robots, drones, humanoids, industrial robots and professional service robots. By 2040, the same framework reaches about 605 million annual units and $8.8 trillion of hardware revenue - a 20.6% unit CAGR and roughly 32.2% revenue CAGR through the decade. The installed base rises from about 343 million machines in 2030 to more than 2.1 billion in 2040.

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Are my index signals better than a related RSI? Here’s what ChatGPT says:

“Your signals are about 40% more accurate than a comparable RSI, measured relatively. Another, arguably clearer way to state it is that they produce about an 18.3 percentage-point improvement in directional accuracy: roughly 64% correct versus 46% for RSI.”

*I used standard Wilder RSI with RSI periods matched to the forecast horizon.

Last weekend I expected this week to be higher, and the S&P 500 increased a whopping 0.8%. Warsh’s speech Friday was a nothingburger to equities as the VIX declined and the S&P 500 was only down 0.2%, but not to the bond market. Bonds took notice as expectations for a rate hike increased.

Here’s what’s in today’s update:

>Forecast update and SPX/SPY, QQQ, and VIX trading plan leveraging my full option and macro data set with key price levels to watch

>Proprietary buy/sell signals for SPY -0.60%↓, QQQ 0.65%↑, VIX, META -0.93%↓, TSLA 2.23%↑, NVDA -1.57%↓, MSFT 0.11%↑, GOOGL 0.90%↑, IWM 0.15%↑, AAPL 0.39%↑, MSTR 3.82%↑, MU -2.20%↓

>Most interesting large trades from Friday

If there’s one update you read from me each week, this is the one.

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S&P 500 models in the table below are not concerned, but the VIX model is flagging a risk that volatility could go higher because it’s not seeing traders shor…

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Nvidia has a history of disappointing after earnings releases and it’s 100% due to retail falling in love with the stock. Since the summer of 2024, it’s been a stock retail buys the most of almost every week, pretty incredible. Of course, recently and have stolen the spotlight, but it’s still a top stock for single stock flows.

I gave AI all of my dat…

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I wanted to share some thoughts on the market beyond this week. While the data points to this week ending higher, I’m concerned about markets post-Labor Day.

This week’s range is likely:

760 - 780

If 765 holds, 772 is up next. A positive NVIDIA/Jackson Hole combination could then push SPY toward 780–785. 765 is a huge positioning level going into NVIDIA. …

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Are my index signals better than a related RSI? Here’s what ChatGPT says:

“Your signals are about 40% more accurate than a comparable RSI, measured relatively. Another, arguably clearer way to state it is that they produce about an 18.3 percentage-point improvement in directional accuracy: roughly 64% correct versus 46% for RSI.”

*I used standard Wilder RSI with RSI periods matched to the forecast horizon.

Here’s what’s in today’s update:

>Forecast update and SPX/SPY and QQQ trading plan leveraging my full option and macro data set with key price levels to watch

>Proprietary buy/sell signals for SPY -0.60%↓, QQQ 0.65%↑, VIX, META -0.93%↓, TSLA 2.23%↑, NVDA -1.57%↓, MSFT 0.11%↑, GOOGL 0.90%↑, IWM 0.15%↑, AAPL 0.39%↑, MSTR 3.82%↑, MU -2.20%↓

>Most interesting large trades from Friday

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The S&P 500 chart below came into the week in the bearish zone, but after today we’ve moved firmly into the bullish zone.

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A Win for “F*ck Cancer”

Back in May, I wrote about and how they can be used to power personalized cancer vaccines in the future (you can read the article here). I provided an update on the stock here on 8/5, then on 8/8 I shared a portfolio update writing:

Portfolio Themes That Matter Most

Precision oncology, genomics & molecular data. CAI, NTRA, GH, ILMN, WGS, DGX, LH. CAI and GH are the clearest data-platform expressions: testing generates proprietary molecular/clinical datasets that can be used for treatment selection, AI models, clinical research and biopharma partnerships. NTRA, ILMN and WGS extend the theme into MRD, sequencing and genome-scale diagnosis…

Today things got real.

The success of Moderna and Merck’s personalized mRNA cancer vaccine announced today could represent a major inflection point not only for cancer treatment, but for Caris Life Sciences ($CAI). The treatment works by sequencing an individual patient’s tumor, identifying mutations unique to that cancer, and creating a personalized vaccine that teaches the immune system to recognize those molecular targets. Combined with Keytruda, this approach has now produced successful late-stage results in melanoma and is being investigated across additional cancers.

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The QQQ signal is dipping into bullish land once again after tapping the red zone last week.

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Are my index signals better than a related RSI? Here’s what ChatGPT says:

“Your signals are about 40% more accurate than a comparable RSI, measured relatively. Another, arguably clearer way to state it is that they produce about an 18.3 percentage-point improvement in directional accuracy: roughly 64% correct versus 46% for RSI.”

*I used standard Wilder R…

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Flows today showed selling of $785 SPY calls to finance $780 SPY calls for next Friday. Aligned with my view of selling strength.

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If core CPI is clearly hotter than the expected ~0…

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Payrolls disappointed on Friday and the indexes cheered it as it reduced the odds of future rate hikes. Financial conditions (above) have been loosening (downtrend = loosening), but rate hikes would reverse this trend and that would be a negative for asset prices, as late 2021 and 2022 show (S&P topped in late 2021 and declined substantially in 2022).

Since May I’ve been pounding the table on after writing about it here. This week in increased 42% and I provided an update here. It’s a long-term investment (not a trade) with a long runway ahead of it, but it’s probably closer to the lowest fair value estimates after the run (the valuation I performed in the May writeup said it was worth $21 when it was trading in the $15s, BofA’s target price is $28). I think the company has a ton of potential so unless it becomes materially overvalued, my plan is to be an owner for years.

Last weekend the models were neutral/bullish and I said the “first few days of August tend to be bullish, and the AI forecast below agrees.” After the sharp rally, mid-week I said expect digestion with a slight bearish lean, we then drifted lower. Thursday, I said Friday leaned slightly bullish and it turned out the large bearish SPX traders were wrong as markets rallied to ATHs on Friday. As I mentioned before, for whatever reason, historically the most accurate forecasts I produce are off of market data from Thursdays and Fridays. So, let’s get into it!

Here’s what’s in today’s update:

>Portfolio deep dive: what stocks and themes are most interesting?

>Forecast update and SPX/QQQ trading plan leveraging my full option and macro data set

>Key index price levels to watch

>Puts sold relative to calls; what is this metric saying about returns?

>Proprietary buy/sell signals for SPY -0.60%↓, QQQ 0.65%↑, VIX, META -0.93%↓, TSLA 2.23%↑, NVDA -1.57%↓, MSFT 0.11%↑, GOOGL 0.90%↑, IWM 0.15%↑, AAPL 0.39%↑, MSTR 3.82%↑, MU -2.20%↓

>Most interesting large trades from Friday

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The model above is tuned for 5 TDs, the one below is tuned for 15 TDs, the one below is more bearish than the one above (i.e., it will be hard to sustain these prices).

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Leveraged ETF flows: When the Nasdaq popped ~1.5% Monday, retail poured into TQQQ (3x long) and fled SQQQ (3x short), the kind of "dumb money chasing green candles" setup that usually gets a knowing eye-roll. But the data doesn't support the reflexive fade. Going back through sixteen years of flows, retail piling into leveraged longs on an up day has be…

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