Had some difficulty topping our original GLP-1 primer’s title, “Upgrading from Overweight”, but that didn’t stop me from writing the sequel -

GLP-1s: A Second Serving

citriniresearch.com/p/glp-1s-the-s… Most of our calls from the original GLP-1 primer played out - for a time, almost too well. This lead us to taking off our GLP-1 long/short basket in November, but we’re ready to get back in.

Still, this time it’s a bit more nuanced.

This is the best thing CitriniResearch has ever done.

On Friday at 6:52AM, we published a note to our chat detailing our take on the implications of deepseek for the AI trade. Our conclusion was to go long Phase 2 (software/agentic AI enablers) and short SMH.

We spent the day going through our AI basket with a fine tooth comb. What could stay in if funded by short SMH, what needed to be added, what absolutely had to go.

Four minutes before the market closed on Friday, at 3:56pm, we published our finalized updated AI basket.

Our changes were drastic.

Our new additions: the AI basket was now ~50% short $SMH and long a collection of those Phase 2 software names - most of which closed green today.

Additionally, we expanded our deletions of data center buildout names despite already having deleted NVDA a month ago.

Without our community, we might have felt pressured to wait until we had an in depth piece filled with our analysis to pair with these changes, but we gave our subscribers a heads up and they gave us the all clear. Unlike previous updates, we felt enough urgency to release our trades first before the market closed and then release our analysis over the weekend.

Myself, @rennyzucker and @nicholastreece worked through the weekend to prepare that analysis in a way that accurately communicated a nuanced take while not slighting our high conviction.

On Sunday, we released our analysis. The conclusion: the intricacies aside, the market would take deepseek as extremely bearish for Phase 1 and generally bullish for Phase 2.

Within 12 hours, it was the most viewed article in our entire archive.

Today, the CitriniResearch AI basket was down 14bps.

if we had not made these changes, it would have been down more than 7%.

A huge thanks to everyone involved in this, I have never been more proud of our work, our team and our collective dedication to keeping our readers informed as to actionable and timely insights. 🥂


Also, I really do feel a debt of gratitude to the @SubstackInc platform for the way in which we were able to handle this. Through the chat we were able to keep constant contact with our readers and update them in real time, rather than have them kept in the dark while we wrote.

The first thesis I ever posted was my MSTR short thesis in November 2021, which I kept updated as a trade journal in real time for the whole trade.

It outlines my short, the decision to cover and the decision to go long the converts in late 22/early 23.

citriniresearch.com/p/microstrateg… The cool thing about the trade journal format of the thesis - it’s easy when you have a winner to just say “yes I was right about everything”.

No, I was clear that I was not expecting “BTC rips to 100K by 24”. The only risk I had a view on was Saylor wouldn’t get a margin call.

I have a new addition to my library, a facsimilie of “Confusions de Confusiones”.

This was the first book ever written about the stock market. Jose de la Vega, a Spanish trader & moral philosopher during the South Sea Bubble in Amsterdam’s exchange published it in 1688.

It describes options, buying on margin, market manipulation and, most interestingly, market psychology.

Despite being the first book to explain a stock exchange, it was relatively unknown until an essay was published about it in the late 19th century.

While a first edition from 1688 sold at auction for $300,000, if you’re lucky you can find facsimile copies from the late 19th/early 20th century - limited runs that likely were owned for the same reason you will - a trader thought it was cool.

This copy is from the 1920s. The first translation of the book into English was not until 1957.

If any of you are doubting that there is nothing new under the sun when it comes to markets, let me show you a few of the passages…

🧵
The most well known portion of the book is the discussion of de la Vega’s “four principles”. Paraphrased, these are…

1) Never give advice to buy or sell shares - the most benevolent of advice can turn out badly.

2) Take every gain without showing remorse about missed profits, an eel may escape sooner than you think.

3) Profits on the exchange are the treasures of goblins. At one time they may be carbuncles, then coals, then diamonds, then flintstones, then morning dew, then tears.

4) Whoever wishes to win in this game must have an excess of both patience and capital.

Even more interesting than these rules are discussions of his thought processes during trading (framed as a discussion between the “shareholder”, ostensibly de la Vega, and the “philosopher”).

I am incredibly proud of the job we did with this basket.

The performance of our L/S election basket (published March 5th) meant express market trump odds bottomed & rebounded strongly on August 2nd.

That is ten days before Predictit and two full weeks before Polymarket.

https://twitter.com/citrini7/status/1824606279173579053

Some people love formulating a comprehensive thesis on single name equities, I love constructing baskets.

Combining/neutralizing various exposures to isolate as much as possible the markets view on a very specific theme - whether that be AI, GLP-1s or US politics.

Some highlights from our China chartbook published this morning…

Had some fun and ran with “The Wall” concept, gotta keep it interesting!

Thread…

1/🧵 Typically the cadence in China has been:

policy impulse bottoms -> prices (assets & otherwise) bottom -> economy bottoms

But it’s not unheard of for prices to bottom first. In the aftermath of the Asian Financial Crisis, that’s what happened.

🗳️Election Thread (Way too Long)🗳️

I’m viewing the election as two separate trades.

The first is happening right now and has been happening for nearly 5 months. It’s the story aspect. The fear & hope associated with expectations of a specific candidate’s increased or decreased odds.

That trade has worked best if you were buying what people *think* Trump will do and fading what they *think* Bidenomics has benefitted.

The second will come about after the election is decided and has to do more specifically with what Trump or Biden will *actually* do. Outside of election years “who the president is” has relatively narrow impact on the performance of single name equities - it’s important to be selective.

As the election draws near, one should rotate out of exposures capturing the first aspect (focusing on common campaign rhetoric like immigration, law enforcement spending, renewables & carbon capture, M&A/deregulation etc) and index more on the latter.

Our basket for that is made up of exposures concerning only Tax Policy and Trade Policy.

Trade is more uncertain than Tax.

We have a lot of transparency into what both candidate’s tax plans would look like. The TCJA (aka the “Trump Tax Plan) is extremely likely to immediately be extended and renewed if Trump wins.

However, tax policy can be difficult to capture thematically - most names don’t trade on their after tax earnings but on EBITDA. TCJA concerns the T and D in EBITDA, so one has to attempt to find the names most affected by selecting for beneficiaries that have high ROI opportunities for the capital they preserve after tax & for negative impact in names that may have issue with debt repayment or competition if their tax burden goes up (or fails to go down on extension of TCJA, in the case of trump winning).

I believe we have accomplished this allocation and I am already thinking about this next phase of the trade, being that we were positioned for the “Trump trade ramping up” with our election odds basket back in March.

Now that the chyron on BNN & CNBC is “Trump Trade Ramps Up” we have to find ways to avoid getting too close to the consensus with our exposure.

The first image below shows how our “Long TCJA beneficiaries Short TCJA victims” basket *outperformed* the S&P500 following the discussion & passing (denoted by a dashed line) of the TCJA during Trump’s first term and *underperformed* following Biden winning the presidency in 2020.

YTD in 2024, TCJA beneficiaries have definitively outperformed both the S&P500 & TCJA victims, with performance rising as Trump odds were more positively viewed by the market.

Most trends & narratives driving markets do not come with a predetermined date, but the election does. While it’s understandable to miss some market trends, imo it is irresponsible to be unprepared for an obvious catalyst. It drives very significant opportunities to generate cross asset returns.

For example, the 2s10s yield curve is almost 25bps steeper following the debate. All you needed was a plan for how markets would react to very predictable potential developments during the campaign to generate serious alpha there.

Read my plan, published on 3/5/24. It includes both baskets I mention above & also discusses the potential impact of election results on broad assets & single names alike.

Traders - being caught offsides due to a predictable catalyst is unacceptable.

citriniresearch.com/p/election-202…

My 4 favorite articles to write this year (they’re not all the best performing, in fact one didn’t even have any trades, this is just about how much I enjoyed writing them):

#1) Signals, Noise & Bond Market Predictions

January 27th

citriniresearch.com/p/signals-nois… #2) Market Memo: Enter the Titan Stapler

August 8th

citriniresearch.com/p/market-memo-…

If we are being perfectly frank, it’s a lonely position to take to defend the idea that a long will continue to outperform the market once it has already done so in a significant manner for an extended period of time.

It’s much more sexy and fun to be controversial and contrarian. And I love that stuff in macro & occasionally in individual equities. Shorting MSTR in 2021 produced some great debates and insights and generally was a really exciting play.

But the thing you begin to recognize after long enough in equities is that over the past 2 decades, 40% of shareholder returns have been generated by 1% of companies.

The simple fact is companies that do well often continue to do well. It’s just like a person. We aren’t going to find out tomorrow that Soros, Druck or Buffett suddenly have lost the essence of what makes them good at what they do.

I forget where I first heard it, but someone once said on here “being able to pass on an investment and then get in after it’s gone up 100% is a superpower”.

What do you think the difference is between the guy who bought AAPL at 6 (split adjusted) in 2010 and the one who got in at 12 in 2011? The former is obviously going to have better returns, but the latter is probably going to have better overall performance because they were humble enough to recognize the obvious dominance and genuinely superior aspects of the company despite what I am sure was overwhelming feedback that they were simply being a mindless follower.

We never quite know exactly what the market is thinking in aggregate, so successful contrarianism is often times less about going counter trend to price and more about going counter trend to what the loudest voices tell you is common sense.

That’s all I have to say about it but it’s something that has benefitted the things I’ve done with a long term mindset. @capitalatrisk23 i.e. if you take the entire increase in total market cap of all US stocks from 2000 to 2023 and do an attribution analysis, the contribution of just 1% of the names is responsible for 40% of the increase

“Wall Street has ruined me, and Wall Street will pay.”

Jim Fisk’s confederate bond short is one of the greats, with much more pizzazz than Rothschild’s informational edge on the gilt market after the outcome of Waterloo, but not many are aware of the story.

https://twitter.com/thestalwart/status/1670469739242463236

Fisk arrived in NY with dreams of fortune, but Wall Street devastated him. He lost money in the bear market, with Civil War events affecting stocks & gold prices unpredictably. Despite the losses, Fisk had a plan.

A lot of joking about how AI is going to save us from a recession but just wanted to point out that recessions are, to some degree, a self fulfilling prophecy (unless they are caused by a massive exogenous shock to the financial system: see 1929 or 2008). How does a recession start and, more importantly, perpetuate?

There is a key component in the fear of both businesses and individuals. If individuals won’t spend, businesses won’t earn. If businesses won’t earn, businesses won’t spend on opex (and equally important, capex).

We should have never broken up Standard Oil Imagine how good the world would be if people like @WTIBull and @RaisingTheBAR47 didn’t have to talk about whether oil and gas stocks were shitcos or not because there’s only one oil and gas stock.

Some thoughts on the Chinese econ data I - think & have expressed that Wall Street’s expectations for the reopening remain too optimistic. China was already in a debt crisis when lockdowns worsened, just reopening the economy does not fix that - it’s literally the bare minimum. It’s a recurring theme that the sell side expects immediate stimulus, higher GDP growth targets, a US style economic boom accompanying the reopening - and it is consistently disappointed. It is worth pointing out that analysts capitulating on their optimistic views has been a..

This is an example of game theory called “guess 2/3 of the average” or “Keynesian Beauty Contest”.
It shows there is a distribution of those acting from rational expectations and also those acting on expectations of the what the common knowledge of that rationality is.

https://twitter.com/citrini7/status/1656504013859192835

How does it relate to the market?

If the market operated on solely rational expectations, all traders acted in their most rational and best interest with all public knowledge, then it would be efficient and prices would always reflect fundamentals.

“fading consensus”: there is a certain spectrum, far end of this would likely be a purely market driven environment, but the economy is more than just market driven. If everyone thinks x about the economy, that doesn’t necessitate any force that causes the opposite to happen. While in a purely market driven scenario, everyone thinking x will go down and it going up is impossible makes at least the payoff of it going up more favorable and potentially leads to it going up, this isn’t the case with the economy.

Just read the short thesis on $MCB.

I am thoroughly unconvinced. It touches on some so-so strings and loose connections, but never really delivers the killing blow. A few points: SVB failed for a few reasons, banking crypto clients was almost purely ancillary as one of them, the main reason was and extremely undiversified deposit base in combination with engaging in the practice of giving out sweetheart loans at…

Someone asked me so I figured I’d share my favorite writings on macroeconomics. Reading all of these won’t give you a firm grasp, or even the basics, but they do give you an idea of how to approach those things in practice, as events unfold. Recognizing How it Happens:

Macroeconomic Patterns and Stories by Edward Leamer

Generally a good framework in markets is to be able to recognize patterns and explain them with words. This book is straightforward and avoids too much jargon.

This was a week that deserves a thread, especially on the macro side. I’ve already spoken enough about the bank stuff, here’s how my macro book did better than any other strategy I have this week.

Mega thread incoming: Overall, the outperformance was due to:

1) Risk Management
2) Flexibility & Adaptability
3) Asymmetric Risk/Reward Opportunities
4) Creative Implementations
5) Insomnia

The parabolic increase in M2 Money Supply following the 1994 Greenspan soft landing was accompanied by a steep rise in private sector productivity & was not inflationary as it was not “excess money growth”: the dot com/computing boom caused economic growth that absorbed it. WARNING: UNHINGED MACRO THESIS

Can Artificial Intelligence save us from inflation?

1 2 3 4 5 6 7 8 9

It’s the ten bankrun commandments:

Rule nominee uno: never let no one know how much dough you hold cause you know, that cheddar breed jealousy specially if that man’s fucked up get yo ass stuck up. Number 2, never let ‘em know your next move. Don’t you know bad boys move in silence and violence?

I am using some new capital ratios. Are they worth anything? Maybe, maybe not. Make your own. Factor in recent developments. Yesterday’s ratio doesn’t work for today’s situation necessarily. I’m considering first:

Duration Wtd non-Government Obligations as %RWA (higher = worse) I propose developing your own risk weighting in response to recent developments. Govvies and agency MBS should be ranked highest, regardless of duration. Then non-Agency CMBS, CRE and very illiquid securities lowest (this includes ABS).