I use markitdown[0] religiously. You’ll lose fidelity for anything complex (math equations, images), but it does a great job 95% of the time in my experience.

I’m assuming the attack surface is reduced. I invoke it through a docker container. But this might be a misplaced sense of safety.

[0] https://github.com/microsoft/markitdown

Dropbox is rendering that pdf as html, so using that link should be safer than downloading the pdf.

Open it with Firefox. The Firefox PDF renderer is implemented in Javascript and sandbox-restricted like any unknown web site.

Sumatra PDF if you are on Windows.

A one-way link (data diode) transmits it to a box with simplified hardware (eg RISC architecture). The box has a dedicated monitor and keyboard. Once you're finished, you sell the box on Craiglist. Then, buy a new, sealed replacement from Best Buy.

Pay per view was an expensive, business model for cable. For PDF's, it's even more expensive.

Note: It's more convenient than full, per-app, physical security.

Gappy is very good but occupies a slightly odd role in that he's sort of a jobbing philosopher for hedge funds at this point

The “fancy math” associated with quant usually refers to pricing derivatives like options.

The thing is that there isn’t really strong institutional demand for exotic derivatives, people are happy using existing methods and just applying those to current markets.

The other type of fancy math has to do with deriving alpha, which is also not that complex, from a statistics perspective you’re mostly using linear regression or other basic forms of regression.

The hard part of quant is implementation, making sure your data is right, hunting through poorly understood markets, and managing risks carefully and understanding them.

There’s also ML but that’s equally complex in quant as it is anywhere else.

In finance, if you have a better understanding of how to price a certain asset then you can make better trades than your competitors and thus make money.

Some assets are very easy to price, like bonds. Others are esoteric, like Exotics which are options or other securities with uncommon pricing structures. This is where the "fancy math" kicks in. But as time goes on, more and more firms figure out how to better price all the various assets that they trade, which erodes the competitive edge between market participants.

The assertion is that today, most firms have most things mostly figured out as far as how to value them. There's little to no competitive advantage to be mined from esoteric stochastic calculus. In contrast, it's rumoured that one of the most successful firms of all time, Renaissance, owes a large part of their success to their absolutely pristine data which comes from a massive data ingestion and cleaning pipeline, allowing them to get a clearer statistical picture of what the current market forces at play are, and how they're going to manifest.

The days of doing some calculus, having a moment of brilliant insight, and writing down a pricing formula then getting paid millions probably only ever existed in people's imagination.

Fancy math definitely is part of derivatives pricing. However financial world has become too complicated for simple models. Adding things like the risk of counterparty default to your pricing equation quickly leads you into the world of equations without closed form solutions. The common approach these days is some kind of huge multi factor Monte Carlo model. These are still solving pricing equations but the challenge is more about numerical methods than brilliant algebraic gymnastics.

There’s a great quote from Nick Patterson of RenTech who says that the most sophisticated technique they generally used was linear regression, and the main thing was avoiding stupid mistakes:

“I joined a hedged fund, Renaissance Technologies, I'll make a comment about that. It's funny that I think the most important thing to do on data analysis is to do the simple things right. So, here's a kind of non-secret about what we did at renaissance: in my opinion, our most important statistical tool was simple regression with one target and one independent variable. It's the simplest statistical model you can imagine. Any reasonably smart high school student could do it. Now we have some of the smartest people around, working in our hedge fund, we have string theorists we recruited from Harvard, and they're doing simple regression. Is this stupid and pointless? Should we be hiring stupider people and paying them less? And the answer is no. And the reason is nobody tells you what the variables you should be regressing [are]. What's the target. Should you do a nonlinear transform before you regress? What's the source? Should you clean your data? Do you notice when your results are obviously rubbish? And so on. And the smarter you are the less likely you are to make a stupid mistake. And that's why I think you often need smart people who appear to be doing something technically very easy, but actually usually not so easy.”

http://www.thetalkingmachines.com/episodes/ai-safety-and-leg...

What is being meant by exotics in this discussion?

The salesman can't tell you how to hedge the product. If you can't hedge you will lose that 5% upfront pretty fast.

You need quants and sales and trading. Which is why all banks have all three.

This matches my experiences as a non-quant, but havin done support work for quite a few of them. You can feel the novelty slough off of them as they get burned down into realizing they're just fitting curves.

Several things : immediately after 2008 less demand for exotics because clients were afraid of them, cutting costs rather than increasing revenue ( that’s industrialization with IT and standardization ) and more importantly, industry reaching some kind of maturity, with large quant libraries which are pretty stable these days.

if you are doing equity statarb, its all low touch strategies, so yes the quants 'trade' in that they can write the strategies. The traders in that environment are more like support, usually.

The series of a shuffle of a 6-deck shoe is not "incomplete information"?

Sam Bankman-Fried. And I think he’s a bit of a special case, others do not need to be worried they’ll succumb to multi billion dollar fraud schemes if they try to earn-to-give.

Freudian slip?

there are a lot of quants who aren't at T1 firms or in the hottest seats. plenty make less than this. obviously if you are top of class and getting headhunted by XTX, your offers will be much bigger than $500k ... but it's kind of obnoxious to claim that QRs making less than this aren't even players

Feel free to do more accurate math! I don't think you'd be doing $500k right out of college either, so it was intended to be a rough average. The person I know I'm finance is doing well over $1,000,000/yr, but I have no idea how average that is.

> aren't just keeping people's money in vaults. They literally take your checking, savings, retirement accounts, etc. and make money off of them while they "sit". <

depending on jurisdiction and TOS, this maybe legal, but it needs to be announced somehow to the customer; a capital management firm of an ETF needs to buy the included shares, e.g; those have no money "sitting around"?

It can both be true they provide a necessary service and that unfair financialization exists.

We are not in disagreement.

But it is ignorance to say the system would work better without any involvement of HFTs.

I ended up rewatching that movie more than ten times a few months ago after I got stuck with a capped internet connection and not much to do online. It's one of those films where there isn't a single fucking scene wasted: everything plays out a little over a day, and the character dynamics and dialogue feel genuinely tight. Lots of great characters overall, but Jeremy Irons's John Tuld is just stellar in terms of presence and delivery.