IIRC posts and answers used to be short , or at least, not as long as a postmortem email

Recently I saw a few super long ones. I can't help wondering if people have ChatGPT-ed this sub

Especially trading right? If you are capable of bringing big returns to a firm, then surely you become valuable?

Got a kid who is crazy about pure math and is interested maybe about being a quant. He picked his first college for engineering but over the summer before he started decided he really wanted math as his first focus - but it isn’t the right school for it (math is just in service to engineering). So he’s assembling schools to transfer to. Just helping him suss out programs folks really liked for math undergrad so he can find a community of peers who love it like he does.

I think I have some understanding of this, but I want to clean it up because it's a bit messy and fragmented.

Let's hone in on one specific example and one market. Let's say I'm the fastest options market maker in ES options. My tick to order is something like 500 nanos, and everyone else is slower, it could be by 100 nanos, it could be by 10 micros. And let's just say I'm running all the strategies necessary to get exchange updates as fast as possible (e.g. priority quoting and reacting on private fills, reacting to NQ or other correlated products as well). Let's say on any given day, there's a few hundred big paythrough events that occur in the ES underlying, which cause the underlying to gap up or down by several ticks, and which guarantee that there will be orders in cross in the options market (from the slower MMs). For these events, how is everyone else not just a sitting duck compared to me? Once I get that trade event, my order is going into the matching engine faster than anyone else can send a bulk delete, every time.

I understand that there is exchange variance. But this just means that there's a distribution surrounding my positive EV when these opportunities arise, it doesn't change the fact that everyone else's EV is still negative.

I also recognize that everyone will have slightly different valuation for the underlying, and slightly different valuation for the vol curve, which will explain a lot of the different trade selection by each firm. But I purposefully specified the big paythrough part in my example to remove this noise and focus in on my deterministic advantage.

Is it because of my own positional tolerance and positional retreat? (i.e. might already be long when there's a big buy paythrough, and so I don't try to lift anyone else)

Or is it because if I have 10 orders to that I see to be in cross it's conceivable that only the first order will be the fastest? It's not possible for the FPGA to send off all 10 orders before the others can bulk delete? (I don't know that much about the hardware side of things)

Or is it just that, yes, everyone else is a sitting duck - they are forced to quote wider and just tune their system to a level where despite these guaranteed negative EV trades, they can still churn out a profit with the other trades they can capture. And as a result, I dominate the market share while also taking money from all the other MMs, so my profit will be massively higher than the next fastest HFT, like if I'm making 250M then #2 is making 25M. We would NOT expect to see the second fastest MM making 150M and the third one making 100M etc. - the distribution of pnl (strictly in this market, for HFT), has to observe a power law.

Please feel free to throw in more accurate numbers if they're pertinent. It would be great if someone could bring this out of abstract space into something more concrete (like quantifying the actual exchange variance compared to the actual tick to order times, maybe talking about the what actually happens in the bursty periods, talking about how this might be a thing for OMM but just for D1 correlation trading there's too much diversity in pricing for this to be the main issue).

Thanks in advance, I'm sure this is a question that other lurkers must have thought about as well!

I've studied on books but I don't have market experience.

From my understanding, futures are cleared by clearing houses and pay every day (you actually give/receive the money every day, right?). The contract is always at fair value 0, and at maturity you just exchange the underlying for its price.

With forwards, however, at maturity the underlying is exchanged for the agreed price.

Can forwards be collateralized? Assuming only cash can be posted for collateral, would n't make it exactly like a future?

Hi, Is there any good / industry standard source for long histories of downsampled snapshot/bar continuous futures data?

Sampling cadence of 1s or 1min or something like that

History of many years (more is better, but flexible)?

Multiple contracts needed for futures that have more than one active liquid c1 contract (e.g. NG)?

This feels like it would be a pretty commoditized offering by now, possibly even freely available, so just wanted to see if true.

Thanks!

Hi everyone, I work since almost two years in a small European Hedge Fund (my first job in the quant world). For the first time, my research has started to show good results for a new systematic strategy I've been developing since. I wanted to ask you how variable compensation usually works in case it gets implemented. Should I ask for a share of the strategy's P&L or what is common practice? How much % of the P&L would be sensible to get? Is this variable comp usually capped?

I made a website for practicing multiplication. Its designed as a game. You can set the ranges for the multiplications, then you set a number of problems, then you set a time (in milliseconds). It will begin throwing questions at you, once every x milliseconds. If 6 of them build up, you lose the game. If you manage to answer all the questions with only 5 "in the queue" at a time, you win.

I think its pretty fun, and I use it a lot myself.

https://hmys-b.github.io/

Does anyone know where I can find white papers or research articles on quantum strategies/math models or where to even begin to look? Is this more in the math journals or more in the finance journals?

I’ve worked in junior quant (trader) roles at a couple of mid-tier prop firms. First role was all coding/project based with practically no trading, second role was a good mix of coding and trading. Both roles were equity focused.

I then moved to a crypto market maker under the premise that there would be good opportunities to undertake more quantitative work with some trading as well, however it’s just not been the case. The company as a whole is not overly quantitative in nature as you would perhaps expect from a crypto firm; positions are put on based on ‘feel’ and drawing lines on charts - I’m not saying that it’s not possible to make money from these approaches (they do), I’m just saying that it’s not really for me.

So now I want to get back into TradFi, perhaps in a desk quant or quant dev kind of role. How should I go about this? I’m under the impression (perhaps wrongly) that firms will see my most recent experience in crypto and immediately throw my CV in the bin. Has anyone else done the yo-yo between TradFi and DeFi? If so, how did you find it?

I have been working as a quant for the past few months after doing a PhD in Finance. I mostly studied empirical asset pricing. Now, I am working for an asset manager and do pretty basic modeling of equity/bond related stuff. I would say my tasks are very „operational“, definitely no complicated derivatives pricing or anything related.

My question is: What are my options after doing this for a few years? I feel like I am doing too little math related stuff to qualify for more sophisticated quant positions. In general, the job market seems to be horrible. Anyone here that got into other investment-related positions after being a quant for some time? Is going the portfolio management route realistic?

Thanks in advance. Happy to provide more details if this is not enough information.

Hello r/quant. I'm a new grad that got into a pretty well doing quant hedge fund ($900M-$1B AUM) but they have a very small headcount. Less than 10. I wanted to know what are some things I should expect, should watch out for, and things I should focus on as I navigate into this space.

For the inevitable question of How I got here, I got into this position because I created a start-up with a product but failed because the competitors were more well-staffed and had full legal teams and funding. Fortunately, building the product opened a few doors which landed me this role.

If people need additional information I'll continually editing this post. I wish to remain somewhat anonymous though so I may not answer all the questions.

I got an internship offer for a portfolio support role at pension fund. The guy told me I’d be a front office quant as needed for different PMs teams.

The job sounds really good, my end career goal is to be quant PM so this looks like a great way to get my foot in the door for portfolio management.

My only concern is that an internship at a pension fund would hurt future opportunities after the program. Can anyone give any advice? is working at a pension fund career suicide?

Degree apprentice at a BB here, thinking of doing a stats masters after my program.

Heard some jokingly - or not - say masters degrees or phd’s can be a negative signal when assessing a candidate lol. Curious on people’s thoughts…

Hope I'm not breaking any rules with this post. I'm looking for a physicist who can share his professional view on the question of the existence and (hypothetical) structure of parallel universes. I've read a couple of books concerning the theme, so I want to check whether a) I understand correctly what I've read since I lack proper education in physics and b) whether my own ideas on the issue are not alogical (I'm a beginner author, though I doubt any of my novels would ever be published, so I can hardly promise even mentioning in the acknowledgements).

In your opinion, what’s the most complete quant book that you ever read? And better yet, what was the one that had the better information adjusted by difficulty? Meaning lots of info but extremely complicated vs less info in general but much more practical?

For me, it ranges from 50 to 70 hours a week. Working on the sell side. Rarely work on the weekends.

Curious to know what schedule you guys do.

there are a lot of very small shops, one i recently came across is amdirac (.com). I cannot see any information about them online and the only person i see is X @ nope_its_lily

How do people get recruited/join these ultra niche shops? especially out of uni?

I am currently working on recreating the results from the paper Deep Learning Statistical Arbitrage by Jorge Guijarro-Ordonez, Markus Pelger, Greg Zanotti.

Since this paper was first published in 2019 i am wondering what other quants consider the state of the art in this field.

Edit: Ok i u get that the best strategies are not published, let me rephrase my question then, what are some interesting new paper in this field?

Can anyone recommend a broker with CBOE access and a FIX API offering sub-millisecond latency into the matcher? This would all be done colo / cross connected. I’m aware of IB, but their internal latency is 100-300ms+. I also know about LIME (which routes options trading to DASH) and, of course, DASH itself. Are there any other brokers that might be good alternatives? Thanks!

Looking for advice. Currently in this “quant researcher” position for less than a year at a rather well known and large fund.

I had strat and alpha research experience in prior internships and there has been a handful of discussions like that in the team. But as it turns out 95% of the job is to monitor and debug. Currently the team just doesnt do much real research (im often told its just a transitionary period). The hours are ridiculously long (spanning 16-18 hours each weekday) as we monitor many markets in different timezones, and there are many end of day tasks after close (also to report to people in other time zones).

Im often expected to debug code that I am seeing for the first time and understand very little of. A lot of these seem to be neglected for a long time, and now we are expected to solve them. I do not have a cs background (was in science) and Im unsure if this is normal or am i just not good at this. Im just struggling a lot with these tasks, and asking seniors and other teams only sometimes helped.

I have talked to some recruiters but not yet told anyone my desire to switch. All have told me normally I should stay at least one year before switching, and I should try to note down my main contributions etc. My concern is that i am really struggling to do this job and im quite sure I wont have much solid research/pnl results to show for it in the future. This job just feels very deadend to me.

or is it something that would work with quants?

Question is in the title for the most part. I am providing some context below.

I am currently researching market making strategies in spot and perpetual futures markets, assets/derivatives that are delta one (have no greeks), and how it affects taker clearance. I am trying to simulate order generation from market makers to simulate an exchange and clearance. I plan on creating MM strategies using a liquidity curve, using a couple oracles, specifically current price and realized vol over different intervals. I want to make these strategies as realistic as possible and have justification that the simulations are valid.

Do market makers in these markets, use polynomials in practice, to generate their orders of price and volume? If so could someone provide some context on this, how they change them over time through risk parameters, and point me in the direction of materials that could give me more context into this?

I’m curious to know what kind of side projects quants are involved in, especially those related to trading or finance. Given the unique skill set in engineering, mathematics, and statistics that quants have, what interesting or innovative side projects are you working on? Would love to hear about any tools, models, or other projects that apply these quantitative skill ?

What are the best cities to live in (worldwide) as a quant. Taking into account salary obviously but not as the main measure, also the level of job security, the level of job availability, the overall quality of life in the area, the level of adventure (like Switzerland might be a bit boring), good food in the area, good weather. ETC etc.

Money isn't the main factor I'm considering anyway, but its important. I'd hate to live in NYC for example just cause the city life isn't for me, too corporate.

Anywhere in Asia worth going to?

As the title says i got a offer as a trader in a quant firm in india i have always wanted to join one but there are actually many things that are bothering me

1. There is a 4 year of bond

2. They are paying less than what i am getting right now( its a different line of work)

3. My expectations were different back then and now i got the reality check that the incentives are not that much now in india because continuous change in rules and regulations and taxes.

What should i do guys?

Hi everyone! I completed my Ph.D in Physics (a few years ago) and I'm looking to transition into quantitative finance. Does anyone know of any specific communities (or threads) focused on Quantitative Finance/Trading in South America (LATAM)? I'm particularly interested in learning more about opportunities and challenges in this field across the region, especially for someone with my background. Any information about local quant communities, resources, or insights would be greatly appreciated. Thanks!"