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Apparently this is the key to unlocking vast riches through a career as a derivatives quant. I'm told it's a requirement even though you don't really use it on

Apparently this is the key to unlocking vast riches through a career as a derivatives quant. I'm told it's a requirement even though you don't really use it on the job. A bit like how you need to rebalance a binary tree to be a web developer. Anyway now it's the key to unlocking vast riches through a career as an AI researcher too, seems like a good skill to have.

vcdimension 1y ago
Yes, you need a good tutor to help you navigate through such a complex topic.
werdnapk 1y ago
Most web developers don't even know what a binary tree is, nevermind rebalancing one.
mamonster 1y ago
It's not extremely difficult(I mean for the most important results like Yamada-Watanabe, Girsanov, etc) if you have a good grasp on measure theory. That said, without that grasp this topic is very hellish. The main problem for people is understanding intuitively what "quadratic variation" actually is and how that factors into the difference between a normal Riemann integral and a stochastic integral.
- almostgotcaught 1y ago
  > not extremely difficult... if you have a good grasp on measure theory If this were Reddit I would paste the "You got into Harvard Law? - Elle Woods" meme. Ok it's not that hard - I did an independent study of Oksendahl in my junior year before my first measure theory class and understood most of it ok. But then again I didn't have to take exams on the material lol.
mikrl 1y ago
Not a quant, but I have physics training and I’m very curious about stochastic calculus and finance. Isn’t it implicit in a lot of the work? If you’re modelling volatility you’ll need the rigorous mathematics in the back of your mind while you do so to keep you on track. Similarly, a webdev isn’t going to use fancy tree algorithms often… but they need to understand the DOM and its structure.
- v4nn4 1y ago
  The comment above is probably from a bot. You do need an extensive understanding of stochastic calculus to maintain quant models code, let alone explain what it does to regulators.
  - ogogmad 1y ago
    > The comment above is probably from a bot. Wtf Is this happening?
    - bee_rider 1y ago
      People accusing comments they don’t agree with of being bots? Yes it has been happening for decades. Lots of folks are bad at arguing, so they make random accusations to distract from that fact.
      - deleted 1y ago
        [deleted]
    - mdp2021 1y ago
      Yes, it happens that some people create bots and have them post in these pages. They (some?) do not pass the "naïve Turing Test" though: there is one that tries to speak like an "inspiring lifecoach" and has zero juice squared. Check the shadowed posts around... And on the other side, I have been accused a few times - writing outside expected canon (of form and content) can be sufficient. So, bragging I will say, accusations hit both tails of the juice curve ;) .
  - AnimalMuppet 1y ago
    The parent comment definitely violates the site guidelines.
  - kelseyfrog 1y ago
    How can you tell? They're missing the telltale sign — the em dash.
EGreg 1y ago
Uh bruh. I took this class when I was 22 at NYU. Quadratic variation, brownian motion, and of course black-scholes etc. A lot of the work is based on a Japanese guy named Ito, who pioneered Ito integrals. And yes you need to know basic measure theory or probability as a prerequisite (take Math Analysis at least) The closest I ever got to being a quant is doing an internship at a hedge fund called Concordia. They were just using Excel and VBA for credit default swaps back in the day. I then ended up at Bloomberg building their front end in C++ which st that time was a huge compiled binary. I quickly exited that world and realized I enjoy building web applications. Had been doing that ever since. Guess turning $220 billion into $223 billion wasnt my idea of fun. What you need as the key is Python, ML, SciKit, etc.
- bormaj 1y ago
  Adding to this, stochastic calculus matters more for modeling volatility/interest rates/derivatives. As you mention, Python/ML are more than suitable for many other areas within quant finance like optimization, algo development, signal research, etc.
- Agingcoder 1y ago
  It depends on where you are - many large banks have their derivatives pricing libraries written in c++ or c#.
mdp2021 1y ago
> now it's the key ... as an AI researcher ...For the moment. We will have to return to controlled processes at some stage - pure stochastic (using stochastic processes alone) is not adequate for precise questions requiring correct answers. Only very little ago an LLM stated General Zhukov as German (probably because he had been the scourge of the German army - enough of a relation to make of something its substantive opposite in a weak mind). Imagine if we had that "method" applied to serous things.
whatup480 1y ago
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vcdimension 1y ago

Yes, you need a good tutor to help you navigate through such a complex topic.

werdnapk 1y ago

Most web developers don't even know what a binary tree is, nevermind rebalancing one.

mamonster 1y ago

It's not extremely difficult(I mean for the most important results like Yamada-Watanabe, Girsanov, etc) if you have a good grasp on measure theory. That said, without that grasp this topic is very hellish. The main problem for people is understanding intuitively what "quadratic variation" actually is and how that factors into the difference between a normal Riemann integral and a stochastic integral.

almostgotcaught 1y ago
> not extremely difficult... if you have a good grasp on measure theory If this were Reddit I would paste the "You got into Harvard Law? - Elle Woods" meme. Ok it's not that hard - I did an independent study of Oksendahl in my junior year before my first measure theory class and understood most of it ok. But then again I didn't have to take exams on the material lol.

mikrl 1y ago

Not a quant, but I have physics training and I’m very curious about stochastic calculus and finance. Isn’t it implicit in a lot of the work? If you’re modelling volatility you’ll need the rigorous mathematics in the back of your mind while you do so to keep you on track. Similarly, a webdev isn’t going to use fancy tree algorithms often… but they need to understand the DOM and its structure.

v4nn4 1y ago
The comment above is probably from a bot. You do need an extensive understanding of stochastic calculus to maintain quant models code, let alone explain what it does to regulators.
- ogogmad 1y ago
  > The comment above is probably from a bot. Wtf Is this happening?
  - bee_rider 1y ago
    People accusing comments they don’t agree with of being bots? Yes it has been happening for decades. Lots of folks are bad at arguing, so they make random accusations to distract from that fact.
    - deleted 1y ago
      [deleted]
  - mdp2021 1y ago
    Yes, it happens that some people create bots and have them post in these pages. They (some?) do not pass the "naïve Turing Test" though: there is one that tries to speak like an "inspiring lifecoach" and has zero juice squared. Check the shadowed posts around... And on the other side, I have been accused a few times - writing outside expected canon (of form and content) can be sufficient. So, bragging I will say, accusations hit both tails of the juice curve ;) .
- AnimalMuppet 1y ago
  The parent comment definitely violates the site guidelines.
- kelseyfrog 1y ago
  How can you tell? They're missing the telltale sign — the em dash.

EGreg 1y ago

Uh bruh. I took this class when I was 22 at NYU. Quadratic variation, brownian motion, and of course black-scholes etc. A lot of the work is based on a Japanese guy named Ito, who pioneered Ito integrals. And yes you need to know basic measure theory or probability as a prerequisite (take Math Analysis at least) The closest I ever got to being a quant is doing an internship at a hedge fund called Concordia. They were just using Excel and VBA for credit default swaps back in the day. I then ended up at Bloomberg building their front end in C++ which st that time was a huge compiled binary. I quickly exited that world and realized I enjoy building web applications. Had been doing that ever since. Guess turning $220 billion into $223 billion wasnt my idea of fun. What you need as the key is Python, ML, SciKit, etc.

bormaj 1y ago
Adding to this, stochastic calculus matters more for modeling volatility/interest rates/derivatives. As you mention, Python/ML are more than suitable for many other areas within quant finance like optimization, algo development, signal research, etc.
Agingcoder 1y ago
It depends on where you are - many large banks have their derivatives pricing libraries written in c++ or c#.

mdp2021 1y ago

> now it's the key ... as an AI researcher ...For the moment. We will have to return to controlled processes at some stage - pure stochastic (using stochastic processes alone) is not adequate for precise questions requiring correct answers. Only very little ago an LLM stated General Zhukov as German (probably because he had been the scourge of the German army - enough of a relation to make of something its substantive opposite in a weak mind). Imagine if we had that "method" applied to serous things.

whatup480 1y ago

[dead]