HN user
ah yes, a nice discussion of the central bank toolkit when policy rates are at their effective lower bound
wait, what's this? Bitcoin and ethereum tickers at the top of the page? A section titled 'Helicopter Money on Blockchain'? hold on a minute...
In fairness, the article did avoid a few of the 'not even wrong' pitfalls you might expect to see written about QE and other sovereign currency monetary operations
Quant is a pretty broad term. Some would say it’s often working on nonlinear desks to implement/calibrate volatility surfaces and things like that or working more on the risk management side. There’s also the whole HFT world (Jane St, Virtu, Jump etc) many would call ’quant’ but really is a different game than the HF space.
On the machine learning side, in my experience it’s often simple, linear models that work best in the messy world of financial data. I’m sure there are shops out there breaking out the GPU clusters and training NNs with 6 trillion parameters but in no way will your super deep NN guarantee alpha whatsoever.
Is an HFT arms race necessarily a bad thing? Doesn’t the market in general benefit from these firms viciously competing to grind out spreads+inefficiencies?
I know very little about HFT, but it seems like we’ve gone past “peak HFT margins”. With the Virtu+KCG merger, firms like Jump doing microwave stuff, it seems like return on assets for these firms could have already peaked.
A famous anecdote along these lines are the whatsapp founders.
I haven’t done so personally yet but it’s starting to look like I might consider this route.
Several years ago, I would have leaned toward a SaaS business targeting some super niche vertical, not to make 1000x VC style rocket-ship returns of course, but as a way to bootstrap into a nice business. I get the sense most verticals with a TAM worth going after are now very competitive.
Interested to see if people see opportunities in non-tech routes.
It seems like Tesla is at a pivotal moment.
On one hand there are hyper-bulls who claim Tesla is a $4000 stock and the future of transportation. On the other, hyper-bears claim the equity should trade around $0-$10. There seems to be no middle ground.
It seems like they are almost betting the company on FSD. I don’t think FSD is really even close to a possibility over the next 5-10yrs. I hope I’m wrong, but if I’m right, I don’t see how Tesla keeps going on like this.
Isn’t it just one big misunderstanding between them?
Taleb thinks 538’s probabilities represent a binary option price on the event, in which case, yes, the probabilities should stay very close to 50% because the vol is so high. Whereas Silver’s models are actually saying “Based on current polls, if the election were held tomorrow, then the probability candidate X wins is Y%” and are thus allowed to swing more wildly. Aren’t both just fundamentally different things or am I missing something in Taleb’s argument?
I don’t work at FAANG, but the general sense I get is that while there is no doubt top DL talent that should command mid six to seven figure salaries, it seems that with AI programs stuffed at both the undergrad and grad levels that things should cool off eventually.
More broadly, does success in academia usually translate to delivering business value? Are these companies betting on these researchers to come up with the next great DL architecture?
Looking at that odds chart got me in a betting mood. I think those Yang odds in the article could be steep given the exuberance of some in his online following, however there could be interesting arb plays with an outsider like Yang like going long presidency+short nomination paired with going short presidency+long nomination with someone more establishment like Biden.
If prediction markets had more depth, I’m sure we would see politics hedge funds emerge.
You’re right. Like a lot of other engineers, I once thought “ML+High level team info=$$$$” but quickly learned that you really can’t get an edge unless you’re digging into that more granular data and even then it’s really tough. It can be very hard to improve on simple linear models.
The odds coming out of Vegas are usually priced correctly. Sports markets are very efficient—although perhaps not as ruthlessy efficient as public equity markets. I would imagine there are still syndicates out there that are the “RenTec of sports betting” and just printing alpha.
I just heard about this on Patrick O’Shaughnessy podcast. As a coffee-fiend, I really should look into becoming a customer, and am also interested to see what offerings come next.
Reminds me of a Whitehead quote that I like that can also serve as a heuristic to evaluate business ideas:
“Civilization advances by extending the number of important operations which we can perform without thinking about them”
I love that literally everything is abstracted away from the customer. Stuff just appears like magic.
My votes are for:
-the use of fire
-the number 0. (Although we can debate if this was invented or discovered)
Wouldn’t large banks and other institutions be in favor of more regulations to deepen their moats?
I could see why they’d want to get rid of Volckler though, so the big I-banks can return to the serious pre-crisis trading revenues they were printing.
Just looking quickly at Goldman’s 2006 10K shows they had over $25B in trading revenue, compared to $5.6B from their traditional investment banking sleeve. I had no idea it was at that level, wow.
I’ve been interested in learning about topological data analysis, haven’t dug in too deep yet, but it definitely looks like an interesting direction to zig in while the field at large zags with ever larger deep learning architectures.
UMAP has already demonstrated its efficacy as a tool in any data scientist’s belt. Ayasdi and Gunnar Carlson’s work is certainly interesting, but unsure how much business value it can actually unlock. Seems like there is also opportunity to draw inspiration from the applied category theory crew (Spivak, Fong etc) to use some CT tools to approach data science from a fresh perspective.
Some of the research coming out is interesting, but as a practitioner I’m more interested in seeing how TDA can add differentiated value in a business context. Interested to hear where people see the field moving next.
With the rise of lambda+managed services, I think we’ll start seeing finance and development start to blend and merge.
Besides giving businesses more legibility into what specific parts of their business logic cost to operate vs. the value they generate, you can start building higher-order financial systems based on flows of capital+information within businesses. From there you can implement all sorts of financial engineering like insurance and options+derivatives that could allow businesses to do things like dial up leverage against these flows. Certainly half-baked ideas, but fun to think about the possibilities.
I think it is possible for that culture to exist on teams if it’s instilled by the coach. I have been on teams with more disciplined, formal coaches and people certainly weren’t as open about it. It would probably be frowned upon if brought up.
But I’ve also been on teams with more free-wheeling coaches and that attitude—ahem—trickled down to the rest of the team. And people would openly talk about it and just straight up do it.
When you’re in the water that much, I think you just end up getting desensitized to it.
I’ve seen things you people wouldn’t believe. Teammates going to a corner and openly declaring “don’t come over here I’m peeing.” Coaches literally encouraging it, saying it’s not worth it to get out and miss a set when you can stay in the water: “your urine is just a tiny, minuscule fraction of the total volume anyways”
When you spend that much time in the water with your teammates, it’s no longer an “open secret” that eveyone is doing it. It’s simply open.
As a longtime swimmer and water polo player, my eyes have been absolutely wrecked by harsh pools many, many times.
However, I don’t think it’s pee. First off, every swimmer pees in the pool.
I have been a part of tens of thousands of man-hours in the pool and seen people get out to pee maybe three times.
I have been in the first games of the day at water polo tournaments and have seen them chlorine shock the water followed by everyone’s eyes getting decimated. To me, the devil is unbalanced chlorine coupled with the thick, thick film of sunscreen that develops in the water after a scorching day with hundreds of people jumping in and out.
You get desperate when your eyes get that destroyed. The classic trick is to fill a pair of goggles with milk and just put ‘em on for a few minutes.
This is a good point. There is some sentiment in this thread, and among the public in general, that Hollywood has lost its touch and is unoriginal with the deluge of remakes and superhero movies. I don’t work in the industry, but I think Hollywood knows precisely what they’re doing.
A primary concern is how you differentiate your product in the age of Netflix. If you want to make an original and complex character driven work, you’re better suited with a Netflix series. Movie studios therefore gravitate to producing works uniquely suited to highlight the things that can’t be done on the small screen and simply must be experienced at a theater. Thus, they continue to churn out special-effects laden blockbusters based on familiar IP because it makes sense for their business.
Yes, from the looks of it, they are well behind in self-driving tech. If it’s inevitable that self-driving will bankrupt them, why would anyone invest in them at all?
The two scenarios I can see are
1). That their ride-matching platform will still play a role in a self-driving world. However, I think a worst case for Uber is Waymo gets there first and then Google can almost trivially replace Uber with their own matching platform.
2.) They acquire a startup that has a successful direct self-driving play.
Either way, the economics of their core offering changes drastically. I have a hard time believing investors in Uber aren’t pricing this in at least somewhat accurately.
I think it’s inevitable. Cloud providers will continue to move up the stack so other firms can focus more resources on their unique and differentiated offerings. It just seems like in the future most companies shouldn’t have any notion of servers/containers etc, they will only focus on their core business logic. We’ll just keep going upupupupup.
Another consideration is that FB would have to reorient their culture to sell to and service the enterprise customer. You could argue that Google is having that very problem with their cloud offering. Despite having superior engineering and product, it’s just not in their DNA to cater to the enterprise in the same way it is for Amazon and Microsoft. FB might have considered cloud a few years ago, but I think they wisely stayed out to focus on their core offerings.
Urban combat tactics are fascinating. I’m reminded of this post that explains how the IDF in the early 2000s would try to “walk through walls” in urban combat. It also discusses how the film ‘Die Hard’ is a study of architecture. [0] The underlying essay referenced in the post is brief and interesting as well, discussing how those urban tactics were influenced by postwar French thought, in particular the ideas of Deleuze & Guattari.
Always mind boggling to see those margins on that sort of volume. It’s no question FB is one of the greatest money-printing machines ever built.
Where does the growth come next though? Do they need to diversify their revenue streams away from advertising? Do they just start paying out dividends or can they really reinvest earnings at a sufficient return to satisfy shareholders?
In what sense did Facebook ‘happen’? People chose to join; they weren’t forced to. Facebook qua social network is a valuable tool for many people.
Now you can perhaps make the case that their effort to monetize was an unethical bait-and-switch. Get people on the service, then keep them engaged via promotion of provocative and unhealthy behaviors, which ultimately fuels an advertising money-printing machine the likes of which we’ve never seen before, save Google.
I think you’re specifically thinking of covered interest rate arbitrage, in which a trader borrows in one currency at a cheap rate, lends in another currency at a more expensive rate and uses a currency forward to hedge out the exchange rate risk, netting the rate differential in the process. It’s not truly ‘arbitrage’ in the formal sense;there are still some notable risks in such a trade.
I often wonder how much climate change is priced in. If climate change is a given, wouldn’t we see it reflected e.g. in the implied vols of super long-dated options or real estate in Miami? VCs would be placing bets like crazy on solutions. Markets just don’t seem to be assimilating this info to me. Wonder if there have been any formal studies on this.
In a straddle/strangle you have unlimited upside on both legs (up and down/call and put). It’s a matter of determining if the long gamma+long volatility position is worth the price you pay in option premium up front and decay thereafter (theta).
This idea forms the basis of a crackpot theory I have about business and economics which is that value accrues to firms that find new ways to “alter the constraints of the game. “
To steal an example from Ben Thompson, the internet enabled Netflix to change television in a highly nonlinear way. Instead of Starz offering their 11,000 title catalog in a linear fashion (whatever was on the channel at the time), Netflix offered their whole catalog at all times to all users. This is a shift in constraints that fundamentally changes the nature of personal entertainment which allows the sector to reach a higher state of ‘entropy’. The market subsequently ‘rewards’ Netflix for the change.
These nonlinear shifts are enabled via changes in technology, law, finance, and social norms. Of course this is all crackpottery, and there are probably tons of counter examples to be had, but these are fun ideas to play with nonetheless.
Yes, that’s one way of putting it. In general, by ‘deeper’, I mean it’s more abstracted away from the final customer, that it is ‘further away’ from them.
For example, if you sell toasters, you better hope that electricity has been commoditized in the value chain that you operate in.
Another corollary is that you should commoditize ‘deeper’ complements when you need to defend existing money-makers when they’re at risk of bottom-up disruption. Mobile could have seriously hurt Google’s ad business, so it was a smart defensive play to commoditize mobile os on their terms via Android. To see what happens otherwise, note that they pay Apple $12B annually to have google as safari’s search default.
I think the key is to commoditize the complement when the complement is embedded deeper in the value chain than your product.