This is your periodic reminder that Medallion has underperformed the S&P since inception, on account of it paying out profits as dividends rather than allowing reinvestment. Don't cry for its investors- they've realized 3x the Sharpe with no drawdowns- but it isn't magic.

https://twitter.com/Alkibiades_/status/1873808551128555986

if you divided VIRT's trading revenue by the securities HFS on their balance sheet you'd get a very similar chart to the Medallion one above, but a quick look at the stock suggests investors aren't compounding at that rate!

A zero employee single manager fund runs somewhere between $500k and $1mm per year in expenses like audit, admin, legal/formation costs nowadays, so $50mm is the minimum for *you* to draw a paycheck, let alone employ a team, without eating performance fees for ~all of comp.

https://twitter.com/alz_zyd_/status/1867055506713456772

Once you have launched, institution interest evaporates because giving money to a nonexistent fund is way easier than a fund w/ a 4 month track, so you need to tough out 3 years minimum to get calls, and then they’ll bitch about scalability because you were managing HNWI money

Not to pick on this guy in particular, but there is a great deal of misinformation floating around re: DWAC. Fortunately for you all, I spent today reading the S-1, and as a SPAC expert I can confidently answer the question of “can Trump sell Monday” with a firm “idk, maybe?”

https://twitter.com/kellyscaletta/status/1771331942320939377

Here is their lock-up agreement, I’ve attached a screenshot of the relevant sections. Formal disclaimer that everything that follows is neither legal nor financial advice, I may have positions in securities mentioned, do your own research, etc. sec.gov/Archives/edgar…

I just attended a talk on the mathematics of diffusion image generation models and it blew me away. Takeaways:
1. The math is very “simple”
2. In fact, it’s so simple that this method *shouldn’t really work*
3. The fact it does says something very fundamental about the universe The basic idea is you define a stochastic process X_t, where dX_t = a(t,X)dt + b(t,X)dW_t. Let X_0 be random noise and X_1 be, eg, vector of RGB values for an image. Interpolate and add noise to generate a sample X_t, do this for many images, and then you can “learn” a() and b()

Since it's Sunday and I'm bored, I figured I would finally, definitively answer the question of "why do people think the economic is bad (and is that the case?)". This is because it is easy to answer, and the answer is funny and will make many people mad.

https://twitter.com/whstancil/status/1687867023353958400

First of all, we will ignore everyone on Twitter and look at objective data, in this case the University of Michigan's consumer survey asking what people think economic conditions are. Spoiler: People think the economy is very bad, worse than any time other than 1980 and 2008!

Junior data scientist interview question: Assume you generate points X = N(0,1); Y = N(0,0.1). Rotate the (x,y) dataset 45 degrees, so they look something like pic below (line is y = x). If you were to calculate the OLS regression y = b1*x + b0, what is E[b1] as n->infinity? (this question and the answer were previously buried in my replies, don't cheat or i will bully you for it)

As I strive to provide #content for my followers, I typed up my ratings from this weekend. Of the 200+ wines I tasted, ~150 were producer samples of guaranteed quality, and ~100 of those were reds (I don't drink enough white burg to have an opinion). Editorializing to follow: The scoring method was just A+ to F, since it needed to be simple enough to be robust to me getting smashed over the course of the tastings, since I didn't spit. The older wines were Friday, all the 2020s were Saturday.

Doesn’t take a genius to read behind the lines here and conclude that the agencies most likely to have actual relevant data from China think it’s natural, whereas the one who would have the least (the FBI, a *domestic* agency) has the highest confidence it is a leak (“moderate”).

https://twitter.com/JChengWSJ/status/1629821329510916101

The current agency distribution is 4-2-2 natural-leak-undecided, and curiously despite the breathless reporting on the FBI+DOE the identities and arguments of the 4 is are unremarked upon, despite their evidence being persuasive enough that an interagency panel sided with them.

Absolutely fascinating to read the memoirs of the founder of Huawei's trip to America in 1994 (translation by @ZichenWanghere) today pekingnology.com/p/ren-zhengfei… Ren is impressed with the natural environment and beauty of the US, and is amazed that in New York ("the largest and most prosperous city in the United States, but also the dirtiest one with the worst social order", New Yorkers btfo) has a space like Central Park

This is the greatest article I have ever read. Every part of it is so perfect it is beyond any parody wsj.com/articles/glori…

Militaries are built to accomplish specific goals, which dictates their cost- for instance, France's is "fuck around in Africa", China's is "take over Taiwan", Pakistan's is "fight India", etc. The US's is "win a war against anyone anytime anywhere in the world in under a month".

https://twitter.com/BeijingPalmer/status/1557038053742583808

The US can deploy an 800-man Ranger battalion anywhere in the world within 12 hours, a 4,000 man rapid response brigade within 24, an armored Stryker brigade within 96, and an entire armored division within 5 days.

Quick analysis: Musk pledged 69mm (sigh) shares in 2020 at an average VWAP of $257 + 18mm shares in prior years when the stock was ~60. Assuming a 25% initial LTV, his existing borrowings are likely ~$6bn. Whether this gets refinanced is critical to if the TWTR deal gets done.

https://twitter.com/WallStCynic/status/1520122678421696512

If you assume that, for whatever reason, he is stuck in those loans and cannot free up the shares, he only has 75mm unencumbered shares left, so the minimum price Tesla can have for him to get a $12.5bn loan is $12.5bn/20%/75mm = $837.44, which was breached yesterday. Not good!

Student loan debt in America: the angle is proportional to the number of people with debt in that range, the area is proportional to the total value of debt in that range. The top 10% of borrowers have half the debt, a Gini coefficient of 62%. Everyone complaining about this visualization:

Starting off light tonight, with a mere one * amuse bouche at Nakazawa before we move into the real heavy hitters A selection of the greatest hits- smoked mackerel (a revelation), toro, ikura, wagyu. The real meal, however, begins later.

I have struck deep into enemy territory for dinner tonight- no longer ensconced in hip hop Spotify playlist small plate (((coastal elite))) restaurants, I am in a massive “steak-house” with antler chandeliers and antique guns on the wall. The menu is just a list of cuts of beef. Men named “Chip” and “Buddy” mill around me, wearing golf shirts and drinking old fashioneds that look like someone mashed up an orange and poured five shots of bourbon over it. They are doubtless congratulating each other on another record quarter at their used BMW dealership.

Spaces desperately needs an audience chat feature like Twitch does so I can call Cohodes a delusional muppet who thinks RH getting a $3bn LOC from Citadel to meet DTCC margin calls was ever on the table "You know, I'm gonna speculate.
'cause I don't want any hassles, I'll speculate.
That it wouldn't surprise me that Citadel just takes the other side of some of [Robinhood customer's trades]."

Finally, the product I've been looking for: what if instead of Robinhood, there was a slick app that dropped confetti on you whenever you allocated into a shitty private equity fund-of-funds and underperformed? notboring.co/p/is-that-a-fa… Ah yes, I'm sure your fund of funds will in fact have a Sharpe ratio of [checks notes] 4, just like in the backtest. God I want the client list for this app so badly, they're all accredited investors too.

Dear reader, I have just completed as near to a true kaiseki dining experience as is possible outside Japan. Every single plate was handmade by the chef, who would be gravely insulted were his food to be served on another’s pottery. For the final sake pairing, we selected our own glass, which unbeknownst to us would be wrapped and presented as a gift after dinner.

Here's a fun "conditional probability" example: Both vaccination rates and hospitalization/deaths are very left skewed, while the US population is right skewed. What effect does this have look at vaccine efficacy, but normalize by current hospitalizations, because you're a hack? Let's assume for simplicity the weighted average of vaccines is 90% effective, and also flat across age groups. Conditioned *only on dath/hospitalization*, 35% of all deaths will still be fully vaccinated individual, and 24% of hospitalizations will be vaccinated. Not great!

Alright losers, it’s Krugposting time. I have had nothing but coffee and cigarettes all day in preparation for this meal. Starting off with a sea bass sando w/ green tea, then a grilled maitaake chawanmushi, and then a tuna inari pocket. A DIY wagyu taco in pickled daikon, plus an action shot; octopus with hijiki seaweed salad, and butter poached white asparagus

There is a 100.0% chance that is a Roman spear design, I don’t even need to look it up to know

https://twitter.com/genepark/status/1401980214910107648

Roughly 2 meters in length, wood shaft, topped by an iron tip about 20% of the total length- it’s a fucking hasta