Why You Shouldn't Be a Quant (Unfiltered)

So, you want to be a quant, or at least you think you want to be one. Well, I'm going to give you the unfiltered reality of the situation. Who the hell am I and how am I qualified to comment? Well, who the [ __ ] is qualified for anything? I worked in the industry as a quant researcher under the guy who came after Black and Scholes. And they say he's not a real quant. So, you know what? Nobody is a real quant. If you want the unfiltered reality, stick around. Otherwise, feel free to click away. First up, the money. You're not going to be rich. I promise. I promise you're not going to be rich. And that free time you think you're going to have to go to the gym, hang out with friends, and spend all that money, which you're going to adjust to in exactly one pay cycle, a fallacy. You are spending all of your time at the firm. Math, probability, statistics, finance, low latency engineering, you better love it cuz that's where all of your time is going to go. Your colleagues, you better get used to them. You better get used to them quick cuz you're going to be spending a tremendous amount of time with all of them. You're not going to be rich. And And the worst of it is, you are going to be you're going to think, right, that you're on this this track, this elite track, and you know, you're going to have the potential for this massive payoff down the line. And compared to most of the population, right, in the cross-section on average, you're doing pretty darn good. But you're going to see very quickly, if you were able to make it to this table, right, absolute idiots. Idiots that don't know a fraction of what you know making exorbitant amounts of wealth relative to you. They're going to be working less, making tremendously more, and it's all because they're in a position where they can exercise their soft skills. You don't need to be smart to exercise your soft skills, but you're not exercising them. You're doing math, probability, statistics, finance, low-latency engineering. That's your job. Remember, if you're getting paid what people think is a lot of money, somebody upstream is significantly smarter than you because they're employing you to be smart and do that work, and they're taking a massive payday for everything that you produce. Now, if you love the role, then that's awesome. That's why I went into the industry. I loved math, probability, statistics, finance. I wanted to do it all of the time, right? If you go into it for the money, you're going to be miserable, and you're not going to be rich. I promise. All right? Now, how much do you actually have to love this stuff? What does the role actually look like on a day-to-day basis? Yeah, it depends if you're in development, research, trading, whatever, but roughly, right? 80% of your time is going to be spent on tasks that you don't want to do. In the context of quant research, cleaning data, preprocessing it, trying to prepare it for some sort of backtest, right? I swam in this giant pond of crazy alt data strategies for quite some time. And we're talking about hundreds of millions of observations per day, trying to clean all of this [ __ ] just to cram it into some backtest, and even with randomized numerical linear algebra and all of this, you know, cutting edge capacity to to try to increase or improve the efficiency of the process, it still took an insane amount of time. Sometimes these pipelines would take days to run. Absolutely outrageous. With with institutional grade infrastructure. So tremendously boring. So tremendously boring. Not everything is just backtesting and taking a look at performance metrics, right? It would be really nice if that was most of the rule, but 80% of the time, 78% of the time, you're going to be doing stuff that you don't want to do. And to make you know, I guess the cherry on top, right? The cherry on top here is 95% of the work that you produce is is going to be thrown out. It's it's not going to actually lead to anything at all. Now, yeah, is it worthless? No, absolutely not, right? It's experience. I like to think of research and and work product in general as stepping on stones on a misty lake. You know the goal is out there somewhere, but you don't know where to go. You only see a few stones in front of you, so you're going to hop hop hop and you start hopping down that road and well, jeez, it's a dead end. Now we got to turn back, right? But you wasted all that time going to No, you really didn't waste anything, right? That's experience. You learned what doesn't work and maybe you'll have to come back there eventually when you go down the line again, but that's the reality of the situation is most of the time you're working on stuff you don't want to do and most of the time your work product amounts to nothing. Which is why you have to cling to that as experience, right? Otherwise it's just wow, it's it can be it can be quite frustrating. Quite frustrating, especially from a research perspective, right? All right, so that's not too bad. Roman, that's not too bad. You're not rich, but you're doing pretty well. Okay, I can you know, manage the idiots making more money than me. I don't care about that. I love the role. Yeah, it's frustrating sometimes, but I really like the math, probability, statistics, finance, and you know, that's why I'm there, right? All right. Well, there's an entire social layer that comes with all of this or maybe anti-social layer depending on the firm that you work at. What a vile industry for gatekeeping prestige and titles. [ __ ] vile. Who's a quant? Who's technically allowed to use the title as a quant? What is What does that even mean? Or you're conducting buy-side research. Now you're allowed to be a quant, but you're not actively managing risk. It's absolutely insane. The inter- inter-party politics, if you will. For what constitutes being a quant? Are you on the sell-side or the buy-side? If you're a sell-side quant, you're not a real quant. If you're middle middle office, you're not a real quant. If you're back office, you're not a real quant. Okay, well, relative to what? What's the What's the bench What's the benchmark? Who cares, right? But it is violent in this space. Absolutely violent. I've been at seminars. It's just a giant pissing contest, right? Oh, he works for whatever whatever. He's a real It's like absolutely absolutely outrageous. The pedigree and the gatekeeping for the role is just the role, the title, whatever is is insane. Let alone like the pedigree of like the academic background that you have, who you studied under, what institution you went to. Did you go to an Ivy League university? Did you study under, you know, a a renowned researcher? All of this stuff, right? Starts to play into some absolutely outrageous, ridiculous inter- inter-party politics. You know, most of what you see online, I think, is, you know, people that love to speculate and people that love to just pigeonhole others based on, you know, whatever particular sector they're working in. So, it's like, a quant developer, right? Isn't that really not a quant at all? It's not not really a quant at all. They're really just a glorified software engineer, right? That's what I would say. And it's like, "Okay, well, Roman, you're not really a quant, right? Because you were just a quantitative researcher, right? Conducting conducting pricing research, buy-side alpha research, right? You're You're not actively managing managing risk, right?" So, that This is the game that you end up being a part of and it's just a giant [ __ ] and I honestly want no part of the industry and no part of that. So, be prepared for the entire social component of it, right? Not to mention that uh a lot of the colleagues that you're going to end up working with, if you're anything like me, if you're anything who, you know, anyone who is is a very social animal and isn't just necessarily going into the math, probability, statistics, finance to grind away behind a computer talking to nobody for, you know, 16 hours a day, >> [snorts] >> prepare yourself for what that looks like because you're surrounding yourself with people that are prepared to do that. So, you know, that's going to look exactly, by the way, how you think it's going to look. All right. Lastly, I'll just wrap up with this thought. It takes an insane amount of time to get a seat at this table. We're not talking about a year or two here, guys. We're talking about a very long time. If you have prior work experience, relevant work experience, that's not what I'm talking about. I'm talking about from the ground up, right? An insane amount of time. You need to really love this [ __ ] to do it for how long it takes to get a seat at the table, right? And then, you know, that entire social component of is it really a seat at the table? Are you really a quant? It's just absolute [ __ ] but at the end of the day here, right? You're going to need to spend years studying math, probability, statistics, finance, latency engineering, coding, whatever for even a shot at a seat at a table. So, after hearing all of that, if you're still stoked to be a quant, get after it. Go master your quantitative skills. Check out quantkill.com if you want to roll as a trader, a market maker, or a quant. It's exactly why I built the platform. Over 100 hours of lecture content, everything that I've learned in the industry and academia, no fluff, cutting out all of the nonsense, getting you from A to Z, from academic to practitioner as quickly as possible. There's a ton of stuff there and an adaptive practice engine, over 90 lessons in math, probability, finance. The list goes on. So, if none of this deterred you from your goal, then check out quantkill.com to master your quantitative skills. That's really going to do it for this one today. This is just the unfiltered reality of the situation. The unfiltered reality of the situation is that all of the opportunity nowadays, right? is in applying some form of AI or LLMs and acquiring attention. So, keep that in mind as you go about making your optimal decisions under uncertainty, right? Optimizing that policy function of yours to make informed decisions and other than that, I'm going to thank you so much for watching and I'll see you in the next video.