John Rotonti Jr retweeted
OK, this is a legit bullish development: Trump in last hour going full bore on getting the permitting bill passed. (imo this is a truly bi-partisan thing that is truly good for all).
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John Rotonti Jr retweeted
Point72 started hiring more discretionary old school types in 2023.
Doesn’t this imply that the edge today is in buying cheap companies with strong tailwinds, accepting volatility, and holding for 2-5 years…??
If they’ve over-optimized everything, I wanna go ‘old school’ and focus on investing…
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John Rotonti Jr retweeted
The actual GOAT says it plainly:
Stop over-analyzing.
Stop over-analyzing.
Stan Druckenmiller: Knowing When to Stop Analyzing Is the Biggest Mistake We Make
I think it's the biggest mistake in our business. At some point, the analysis becomes counterproductive. That's one thing I've learned, and it's greatly to my advantage. Speed matters now. With AI g else, if you sit around and analyze a company for four months and you're not willing to operate with 15% or 20% of information, you'll often miss just a big move and then you're afraid to buy it because it has moved.
That to me is a core belief. Sometimes when the opportunity is so big and you just kind of know it, you've just got to plunge in without the proper information, do the work, and if it doesn't work out, it doesn't matter whether you're a profit or loss.
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John Rotonti Jr retweeted
Dr. Judd Biasiotto studied MLB pitchers’ biorhythms and found they couldn’t reliably predict performance.
Don’t let an algorithm of questionable value put a ceiling on your life.
A prediction isn’t a verdict. Show up, do the work, and make the damn thing wrong!
Don’t let an algorithm of questionable value put a ceiling on your life.
A prediction isn’t a verdict. Show up, do the work, and make the damn thing wrong!
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“We see the AI backlash as a speed bump, not a roadblock, at home and abroad.” - Dr. Ed @yardeni Nov 8, 2026
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John Rotonti Jr retweeted
$AMZN has the most permitted and power committed capacity to add going forward.
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John Rotonti Jr retweeted
$GEV GE Vernova CEO: Electrification backlog has expanded dramatically since 2022
"Today, we have a $46 billion backlog, which, again, to remind everyone, was $7 billion at the start of '22."
"Today, we have a $46 billion backlog, which, again, to remind everyone, was $7 billion at the start of '22."
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John Rotonti Jr retweeted
BREAKING: Anthropic has agreed to pay $3.4 billion for gas-fired generators for data centers, the FT reported, in what it described as the largest known single purchase of power-generation equipment by an AI lab
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John Rotonti Jr retweeted
$CAT Caterpillar CEO: Data-center power demand is extending Caterpillar's equipment order book into 2029 and 2030.
"As I mentioned, backlog continues to grow due to strong order rates, and we're now taking some large reciprocating orders as far out as 2029 and turbine orders into 2030."
"As I mentioned, backlog continues to grow due to strong order rates, and we're now taking some large reciprocating orders as far out as 2029 and turbine orders into 2030."
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John Rotonti Jr retweeted
Rob Gronkowski tells a story from his days at Arizona:
"Speaking of Arizona, I wish I could pull up the video somewhere, somehow. I can't find it, but I was asked as a sophomore, after a couple touchdown games - of course, a couple touchdown game that is - Who would be my if I could choose? And of course, I said Brady."
"Speaking of Arizona, I wish I could pull up the video somewhere, somehow. I can't find it, but I was asked as a sophomore, after a couple touchdown games - of course, a couple touchdown game that is - Who would be my if I could choose? And of course, I said Brady."
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John Rotonti Jr retweeted
The gap between investors who’ve embraced ai (especially in research + admin) and those who haven’t is staggering
One of the best I know said 90%+ of firms work is now Ai / automated
Another sole practitioner has a whole firm run by grok bots
Era of agentic investing is here
One of the best I know said 90%+ of firms work is now Ai / automated
Another sole practitioner has a whole firm run by grok bots
Era of agentic investing is here
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John Rotonti Jr retweeted
JPMORGAN:
“.. equity multiples have de-rated by ~4x since the January highs—one of the most extreme compressions in modern history outside of a recession ..” 👀
“.. equity multiples have de-rated by ~4x since the January highs—one of the most extreme compressions in modern history outside of a recession ..” 👀
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“Certain teams have struck me as deploying the proper mix of both (Gabe and the Melvin team in particular are the archetypal example of this for me...they knew their names at Tiger Cub Depth, and traded them with multi-manager market sense.) With variable cost structures and infinite incremental return on invested capital, the hedge fund business model will clearly fall in the Jevons Paradox camp of AI adoption. (I am making this bet with my career by working to build the exoskeleton to help funds do this). As always, adapt or die.”
Two: duration is still critical from an investment research lens. But the winners in this new market paradigm will just simply have to move their feet more aggressively. A tactical risk-reward lens can feel like you're leaving money off the table. But the firms I know and the PMs I know who are navigating this market structure shift most elegantly are not those who lean hard into a concentrated theme. But have a strong view of the thematic cycle and try to come off of consensus trades in the sixth or seventh inning. Which is obviously easier said than done. It can lead to major FOMO as the trade keeps working. Obviously, as informational edge further compresses, psychological edge becomes more critical.
Three: very obviously, AI will be a Red Queen race in the hedge fund world. In the past, investment styles were more discreet, i.e. I'm either a tiger cub or a multi-manager. I'm either trading quarters or I'm making three-year bets. I don't think that's a successful paradigm in the new market structure, personally. I believe the best PMs will, out of necessity, have to adopt both. Which is incredibly difficult, and before the advent of AI tools, almost an impossible task. Certain teams have struck me as deploying the proper mix of both (Gabe and the Melvin team in particular are the archetypal example of this for me...they knew their names at Tiger Cub Depth, and traded them with multi-manager market sense.) With variable cost structures and infinite incremental return on invested capital, the hedge fund business model will clearly fall in the Jevons Paradox camp of AI adoption. (I am making this bet with my career by working to build the exoskeleton to help funds do this)
As always, adapt or die.
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“For so many years, you could buy Google at a low teens multiple, growing 30, and shorting Sears into the dirt. And the times when Google did pull back from 13 times to 10 times, those were phenomenal buying opportunities.”
“But mostly just the success of the long winners, short losers trade invited more competition. Rising competition creates more crowding. It's almost definitionally a negative to Sharpe.”
“But mostly just the success of the long winners, short losers trade invited more competition. Rising competition creates more crowding. It's almost definitionally a negative to Sharpe.”
I think it's even more fundamental than this.
For many decades in markets, long-short hedge funds could construct portfolios where their longs *on their numbers* were cheaper than their shorts *on their numbers*. And so you could buy, say, a portfolio of high-quality longs growing 15% for 15x earnings and short a group of lower-quality businesses growing 3% at 20x earnings. Investment research and market expectations were a less efficient place, and so you could truly have a differentiated view relative to both Street and market-implied.
Even better, pre-GFC when you went through challenging macro periods, those high-quality longs tended to hold up better in down markets vs the lower-quality shorts (imagine that!!!). Positioning wasn't yet deterministic. As a result, it was quite common for high-performing hedge funds to put up mid-teens long-short spreads at attractive Sharps ratios. Spread PLUS downmarket protection!!
When you construct a portfolio wedge in that manner, definitionally, duration is an advantage. Really, all you have to do is be right and wait. This is how the Tiger Cub model became ascendant.
The archetypal ideas that come to mind in this wedge box are long Google and short Sears. For so many years, you could buy Google at a low teens multiple, growing 30, and shorting Sears into the dirt. And the times when Google did pull back from 13 times to 10 times, those were phenomenal buying opportunities.
If you look at the Cao, Chen hedge fund crowded position research and the research on underperformance of crowded shorts, just owning effectively the consensus hedge fund long-short book gave you roughly eight points of spread over three decades. The top tiger funds did materially better than this.
Over the last 18 years, things have slowly changed. This started in the GFC when crowded names like Apple underperformed highly crowded, low-quality businesses with high short interest (exacerbated by poorly constructed short-selling bans). The short side in particular has become much more crowded, and the GME-AMC saga further highlighted the market microstructure challenges on the short side.
But mostly just the success of the long winners, short losers trade invited more competition. Rising competition creates more crowding. It's almost definitionally a negative to Sharpe.
So this long-running deterioration in the spread opportunity more recently has met a much more narrow leadership in public equity markets. And that leadership on the long side tends to be dominated by companies that have a very wide fan of potential intrinsic value outcomes. Either the NeoClouds or even companies like NVDA, where the current level of profitability is so far out of historical norms. These are just very clearly much harder businesses to value than Google growing 30, trading at 13.
AI in general as a theme starts to touch the terminal value perception of nearly every company in markets. If you deconstruct the net present value of nearly any stock, the majority of value today lies in the terminus or the 10 to 50+ year out collective market view of those cash flows. As an economy that's in accelerating transformation, how does the crowd know what any business looks like in thirty years? The market obviously won't. And so very clearly, the public markets will just be structurally higher vol than they ever have been before. (I think probably the consensus view on X is that AI will make markets more efficient and boring, i.e. lowering equity vol, by making investment research more accessible. I believe the exact opposite is happening and will only accelerate due to structural terminal value distrust)
What does this mean for the future of long-short equity? I don't know, but I have a couple strong opinions.
One: The “buy good companies, short weak companies”, portfolio wedge approach is probably structurally impaired. Particularly if you are trying to express it in a 250-plus GMV wrapper.
(Continued in replies)
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