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Comment by Agingcoder | Hacker News Reader

Im reasonably familiar with the exotics quant space.

It’s essentially IT/data work - the days of sophisticated maths are mostly gone. There always was a lot of code, but these days for most people there’s little to no new maths.

From what I’ve seen, post-2008 the job changed significantly, with more IT, less maths, more standardization - basically the job moved from bespoke everything to super industrialized. You’ll be able to have your model work for one underlying and one product, but what’s really useful is for lots of underlyings and many products - and that’s very hard.

That being said, and that’s important, you must understand the maths behind, otherwise you won’t be able to do anything useful.

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I started my career in derivatives. Mostly vanilla, but I did have a look in the exotics.

Intellectually, it's interesting when you start. There's all these weird payoffs that you are introduced to, and it feels like a game.

The thing is, there's a limit to how exotic things can get. People have already figured out how to price most of the things you can imagine, including all the things that customers normally ask for. Most of the day goes on looking after your hedges, basically implementing the model.

It's like a zoo. When you arrive there's a bunch of different, interesting animals. After a while, you've met them all. There's no new animals, just variations of existing ones.

However the thing that is really an issue is how the business works. Over time I came to the conclusion that the quants in the derivs space are really secondary to the salespeople. How important is the quant who can get the price right to within 1%, when the sales guy can talk the customer into overpaying by 5%? Sometimes it feels like the customer is not even shopping the structure around at all, he just feels comfortable with his sales guy and is willing to hand over a few million bucks of customer money with barely any thought.

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.

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.

> 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.

I don't think anybody said you can just run without one of those. But it seems the magic is in spotting the fish, not hauling it in.

Spotting fish who you can overcharge is not really a sustainable business model. You can do it once but your colleagues will find out, move to a competitor, and next time they'll rip them off a bit less than you did and you'll have to rip them off less than that.

There is, eventually, a shortage of dumb money. The sustainable way of making money involves competition, and this involves knowing the "right" price within a tight tolerance.

No, the feedback loop isn't closed. The fish customer just keeps handing his spread to his favourite sales guy.

I've witnesses this several times, some trader always uses the same relationship, irrespective of cost. I've seen this both in terms of friends from a long time ago helping each other, family, or backhanders.

And so the real winner is that sales guy. I've known people climb to the very top of well known institutions on the back of relationships with just one hedge fund.

What you're describing is a sort of ideal market from an economics textbook.

The situation you are describing definitely happens, people have their mates they like working with and a single relationship can make a whole career.

Normally though, such relationships do not involve the sales person charging significantly above market rates. The client usually has very strong incentives to reduce costs. While a single salesperson might build a career on a chummy relationship this isn't a sustainable approach for an entire firm to take because it is too unusual. The majority of the revenue is coming from client/sales relationships where the client is at least somewhat price sensitive and sufficiently savvy to get more than one quote.

> but these days for most people there’s little to no new maths.

You are right. For most people there's little to no new maths.

But not for all. There's still plenty of good quality math to be done in the exotics space. However, there's a bit of Catch 22 that prevents people from doing new math: all the big shops have had exotics libraries since before 2008, and because of the exotics hiatus between about 2008 and maybe 2013, the research momentum was lost. After that, most quants in the space were happy to find ways to use the old stuff, and apply small tweaks at the margins. Most small shops use vendor models (Numerix, Murex) or open source (QuantLib), and people who use vendor solutions or open source are not looking for cutting edge stuff.

But there's still good math left out there.

What is being meant by exotics in this discussion?

I assume exotic derivatives (binary, asian, barrier options...) and structured notes that predominantly use above said derivatives (autocallables, barrier reverse convertibles, accumulators etc.)

Thank you.

No matter how much I try to understand the financial system, there seems no end to the nomenclature.

Do you or others know of any good references that help navigate this?

Really depends how deep you want to go.

For a structured products introduction you may take a look at this one: https://sspa.ch/en/book/

It's a very simple book, very high level, but explains the most popular structured products in a very simple manner. If you can read a payoff diagram, then this is the simplest intro.

Looking at their website though, they seem to have some nice online material there also. For example this explains the 5 most popular products, and perhaps that's good enough for an introduction (really these 5 products cover 90% of the market anyway, though there's no limit to how exotic some bespoke structures can get): https://sspa.ch/en/lab/?underlying=CH0012221716&final_fixing...

In case you're interested in getting to get to learn about them on a deeper level I would recommend https://www.amazon.com/Exotic-Options-Hybrids-Structuring-Pr.... This book explains not only the products, but also the pricing dynamics and hedging too.

And just a small gem I found recently about volatility trading:https://www.ebay.co.uk/itm/306680584072?chn=ps&_ul=GB&_trkpa...

Despite its appalling Amazon reviews I consider this book to be a real gem when it comes to the introduction to vol trading (basically dynamic hedging of equity derivatives)

Patrick Boyle, early in his YouTube career, made some videos on exotic options. This is a lot more engaging and possibly more informative than reading Hull.

https://youtube.com/playlist?list=PLHC72UlhAthBEEAhoQwPdDaL_...

Options, Futures, and Other Derivatives by Hull, that's the classic.

Not sure how exotic he gets but likely the page that sells this book will have other options books.

I think there's one by Espen Hauge about exotics.

Relevant book by Nassim Taleb (before his big break) is Dynamic Hedging, which tells you what to do with your option risk once you have it.

There's definitely room for new math but , at least for banks, the process of getting your fancy model validated by internal model validation teams and regulators is so time and energy consuming that most people don't want to bother with using all the fancy math they could use and instead rely on simplifications and simple extensions.

What happened? Is this a case of the actual job changing, or just title inflation? I’d expect the quants to be the ones doing the math and implementing the kernels…

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.

theres math, its mostly about pulling in obscure data sources, rank and file in alot of hedge funds dont even get to see what actually makes money

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