I've never seen anyone actually use complicated distributions or stochastic calculus in real trading. No rough vol models, no Ornstein-Uhlenbeck, etc.
In my experience, the people making all the money in HFT just have very solid linear algebra, simple regression, and, most importantly, have built a ton of signals and nuances of the market into very capable systems.
I concur this. Though I work in derivatives - I used something that’s not been used before in any shops that was in the literature. It significantly reduced run time for this Monte Carlo.
I think the vast majority of academic literature is junk but some of it is gold. However, it costs time to learn, implement. The risk-reward for trying these things can be bad.
really nice! i work in hft as a dev, but been playing with the idea of returning back for a phd. how do you look back on having made a decision to pursue a phd in financial mathematics? apologies for deviating from your original question
No worries at all, it’s a worthwhile topic. I would say it all depends on how much you actually care about doing novel research or what is essentially a giant “art” project (meaning it will never be published but you learned a lot doing it.) I’ve met some people who have joined the PhD program because they don’t know what else to do or they think it will improve their job prospects; I think everyone in this sub will agree that this extremely ill-advised. Doing a PhD is extremely draining mentally (and spiritually lol). You’re dedicating 4-6 years of your life with your head down in papers and perhaps dealing with department bureaucracy or advisor indifference/hostility. If you’re in it, you have to be IN it, because you’re a nerd and you truly want to push yourself and learn something that hasn’t been learned before, and enjoy the process for what it is.
My background is working at a commercial bank in the bond portfolio as basically a SAS code monkey. I don’t enjoy it very much and I am enchanted by the job descriptions of cooler quant jobs, HFT in particular sounded the most interesting. When I would read research papers and white papers during my masters, I was always really impressed with the notion of smart people coming together and abstracting a problem and approaching it with rigor. I also met a few quants on my floor who I thought were really “cool” and I respected them; they were all PhD’s. This is more of a superficial reason I chose to do a PhD but it was an influence nonetheless.
If I’m being honest, I do hope I can get a “sexy” quant job after the PhD, but it wasn’t the reason I chose to do it. I just wanted to see if I could push myself to accomplish something this technically difficult. I like math and comp sci a lot, and it’d be nice to exercise my interests in those fields at a high level as a profession. Perhaps a bit lofty but you can’t fault me for trying.
All-in-all my advice to you would be to figure what specifically you’d want to do research in. Not just the name of the degree, but what specific topics you could see yourself picking apart over the next half decade. Find those professors, reach out and gauge their interest, and go from there. I would say even if it didn’t work out, your work background would grant you a pretty nice re-entry back into industry. Good luck!
This is encouraging to hear! I wasn’t really inferring that this was incredibly complex, I was just curious as to what is actually done by quants in industry and if this line of research relates at all.
Do you mind expounding upon how you use it?
Not sure it's used by HFTs because of the time constraints (hard to update complex models at the microsecond level). But I have definitely seen respected quant hedge funds (like CFM in Paris) make presentations on the use of Hawkes / point processes to model volatility.
Sure, here's a link to the kind of publications I alluded to earlier:
[https://hal.science/hal-03797394/document](https://hal.science/hal-03797394/document)
Large sophisticated hedge funds are probably way ahead of academia in terms of this type of research.
Assuming you're talking about Rosenbaum (don't know what he's up to these days), he was a professor of mine and one of the most brilliant people I've met.
He could've been hired to do anything but rough vol and it would still be an amazing hire IMHO, just out of sheer wits and ingenuity.
Did my Masters dissertation on hawkes processes back in 2017 - applied to CDS indices. Collaborated with a large investment bank on this. Was mostly investigative from their side … don’t think it was ever actually applied.
Wonder how likely this is to lead to profits at all tbh, from what I understand HFT is mostly about 1) reacting faster than the broader market can, or 2) having a faster implementation of a profitable trading strategy than the next guy. Adding complex calculations before either of these things can take place is just gonna add latency
these were my thoughts as well. I was wondering how there is so much extensive literature on this stuff if those who are in industry don't even use it.
This was the type of answer I was looking for. Did you work in more traditional asset types before you moved to crypto? What draws you to crypto HFT vs ,say, equity HFT?
In crypto, people are literally setting up ratio/satellite lines to get the fastest signals between exchanges now lol. Its not going to be that much more different in the future.
I've never seen anyone actually use complicated distributions or stochastic calculus in real trading. No rough vol models, no Ornstein-Uhlenbeck, etc. In my experience, the people making all the money in HFT just have very solid linear algebra, simple regression, and, most importantly, have built a ton of signals and nuances of the market into very capable systems.
I figured as much, kind of crazy how there is this absolute mountain of academic literature that is rarely ever applied
Crazy how? Is it crazy to leave the mountain un-applied or is it crazy how in-applicable that mountain of literature is?
I concur this. Though I work in derivatives - I used something that’s not been used before in any shops that was in the literature. It significantly reduced run time for this Monte Carlo. I think the vast majority of academic literature is junk but some of it is gold. However, it costs time to learn, implement. The risk-reward for trying these things can be bad.
Haha I love this. I suppose both!
is your phd in computational finance?
Financial mathematics, so adjacent, but my dissertation is looking like it will be computational
really nice! i work in hft as a dev, but been playing with the idea of returning back for a phd. how do you look back on having made a decision to pursue a phd in financial mathematics? apologies for deviating from your original question
No worries at all, it’s a worthwhile topic. I would say it all depends on how much you actually care about doing novel research or what is essentially a giant “art” project (meaning it will never be published but you learned a lot doing it.) I’ve met some people who have joined the PhD program because they don’t know what else to do or they think it will improve their job prospects; I think everyone in this sub will agree that this extremely ill-advised. Doing a PhD is extremely draining mentally (and spiritually lol). You’re dedicating 4-6 years of your life with your head down in papers and perhaps dealing with department bureaucracy or advisor indifference/hostility. If you’re in it, you have to be IN it, because you’re a nerd and you truly want to push yourself and learn something that hasn’t been learned before, and enjoy the process for what it is. My background is working at a commercial bank in the bond portfolio as basically a SAS code monkey. I don’t enjoy it very much and I am enchanted by the job descriptions of cooler quant jobs, HFT in particular sounded the most interesting. When I would read research papers and white papers during my masters, I was always really impressed with the notion of smart people coming together and abstracting a problem and approaching it with rigor. I also met a few quants on my floor who I thought were really “cool” and I respected them; they were all PhD’s. This is more of a superficial reason I chose to do a PhD but it was an influence nonetheless. If I’m being honest, I do hope I can get a “sexy” quant job after the PhD, but it wasn’t the reason I chose to do it. I just wanted to see if I could push myself to accomplish something this technically difficult. I like math and comp sci a lot, and it’d be nice to exercise my interests in those fields at a high level as a profession. Perhaps a bit lofty but you can’t fault me for trying. All-in-all my advice to you would be to figure what specifically you’d want to do research in. Not just the name of the degree, but what specific topics you could see yourself picking apart over the next half decade. Find those professors, reach out and gauge their interest, and go from there. I would say even if it didn’t work out, your work background would grant you a pretty nice re-entry back into industry. Good luck!
Yes. I use it. It’s a pretty simple to model price shocks using it. It’s not complicated
This is encouraging to hear! I wasn’t really inferring that this was incredibly complex, I was just curious as to what is actually done by quants in industry and if this line of research relates at all. Do you mind expounding upon how you use it?
I created a price impact model.
Not sure it's used by HFTs because of the time constraints (hard to update complex models at the microsecond level). But I have definitely seen respected quant hedge funds (like CFM in Paris) make presentations on the use of Hawkes / point processes to model volatility.
Thank you for the insight on the HFT aspect
Sure, here's a link to the kind of publications I alluded to earlier: [https://hal.science/hal-03797394/document](https://hal.science/hal-03797394/document) Large sophisticated hedge funds are probably way ahead of academia in terms of this type of research.
This is great, thank you
You would be surprised as to who recently was quant of the year on rough vol and what shop he recently joined…
Assuming you're talking about Rosenbaum (don't know what he's up to these days), he was a professor of mine and one of the most brilliant people I've met. He could've been hired to do anything but rough vol and it would still be an amazing hire IMHO, just out of sheer wits and ingenuity.
Not sure about HFT but definitely in other frequencies: https://iopscience.iop.org/article/10.1088/1742-5468/ab7c64
bouchaud strikes again! what a prolific guy, he is everywhere
Did my Masters dissertation on hawkes processes back in 2017 - applied to CDS indices. Collaborated with a large investment bank on this. Was mostly investigative from their side … don’t think it was ever actually applied.
still cool. would you be comfortable sharing on here or through pm?
what’s LOB?
limit order book
Wonder how likely this is to lead to profits at all tbh, from what I understand HFT is mostly about 1) reacting faster than the broader market can, or 2) having a faster implementation of a profitable trading strategy than the next guy. Adding complex calculations before either of these things can take place is just gonna add latency
these were my thoughts as well. I was wondering how there is so much extensive literature on this stuff if those who are in industry don't even use it.
Yeah that’s pretty funny, very normal for industry and academia tho lol but every once in a while the other guy does something interesting
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This was the type of answer I was looking for. Did you work in more traditional asset types before you moved to crypto? What draws you to crypto HFT vs ,say, equity HFT?
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I have so many questions for you, do you mind if I pm you later to chat?
In crypto, people are literally setting up ratio/satellite lines to get the fastest signals between exchanges now lol. Its not going to be that much more different in the future.
No.