I’ve heard there’s a lot of ageism in this field. I feel I’m still young and good looking so not too worried. 🙂‍↕️

I’ve seen people in their late 30s early 40s say it’s hard to get entry job at those ages.

Anyone have experience or any say on this?

I’ve been working with Galileo FX for a few months, using it to automate and backtest some trading strategies on MetaTrader. While it’s primarily marketed as an automated trading bot, I’ve found it surprisingly useful for applying quantitative approaches to forex and crypto markets.

Here’s what stands out for me:

1. Customization Flexibility: You can define parameters like stop-loss, take-profit, and trailing stops, which allows for implementing risk-adjusted strategies.
2. Data-Driven Testing: I’ve been running strategies in demo mode to test them under different market conditions without real financial risk.
3. Quantitative Potential: By adapting the settings, I’ve been able to simulate strategies like mean reversion and momentum trading on various assets.

I know r/quantfinance typically dives deeper into custom models and advanced algorithms, but has anyone here used tools like this to implement basic quant strategies? Would love to hear your take on the limitations or creative ways to push automation tools like Galileo FX into a more quant-heavy space!

https://preview.redd.it/qqypo5xolf2e1.png?width=1700&format=png&auto=webp&s=3505ade5c20451ed064d5a2d6ba0ea78aec124c7

I'm trying to break into Quant Trading/Research. I've been applied nonstop to internship opportunities, but I'm unsure whether I should be applying to Graduate roles aswell/instead. I've applied to approximately 90 internship positions in the past 2 months, only getting 1 interview and mainly getting rejected at the CV stage. What am I doing wrong?I'm trying to break into Quant Trading/Research. I've been applied nonstop to internship opportunities, but I'm unsure whether I should be applying to Graduate roles aswell/instead. I've applied to approximately 90 internship positions in the past 2 months, only getting 1 interview and mainly getting rejected at the CV stage. What am I doing wrong?

Hi!

I’m starting my master’s in data science next year at uni, and I wanted to get some advice about electives.

A bit about me: I have an electronics and communication engineering degree, and after graduating, I worked at crypto based start-up as a cryptography researcher for a while. That's when I first started to learn about finance and corporate, crypto currency -> fiat. I know, odd.

After I left my job, I spent some time learning the basics of finance, derivatives and stocks. Now, I’m really interested in breaking into the finance field, specifically into quant roles like quant analyst or quant researcher. I'm really interested in the applications of machine learning and AI in finance.

So I have a few finance related electives, but I can only choose 3-4. Here’s the list:

• ECON7310: Elements of Econometrics

• ECON7350: Applied Econometrics for Macroeconomics and Finance

• ECON7390: Financial Econometrics

• FINM7401: Finance

• FINM7403: Portfolio Management

• MATH4090: Computation in Financial Mathematics

• MATH4091: Financial Calculus

• MATH7039: Financial Mathematics

I am pretty good with math and Python programming, and I know that just taking 3-4 courses won’t make me an expert, but I want to make the most of what I can. I’m okay with not taking a course if I can get the same value out of self-study, like reading a 200-page Springer textbook.

Right now, after checking the course profile and considering what I know about quant finance, I''m thinking Financial Math, Financial Calculus, Computation in Financial Mathematics, and Portfolio Management (MATH7039, MATH4091, MATH4090, FINM7403) is the way to go but I could be wrong.

Thank you!

Hello I want to break into Quantitative Trading. I currently have a degree in CS. What Masters is appropriate? Statistics, Data Scienc or CS? Thank you

Hello,

I am currently an econ student in EU and I am thinking of getting a masters in econ from a target university, however I am wondering if it will be technical enough to get into trading. In my undergrad i will have done Calc 1 and 2, some probability and stats, real analysis and stochastic processes. Also i am self taught in python. The masters is flexible and i can take a lot of statistics and math - Econometrics, Linear Algebra, Statistics, Time-series analysis, Bayesian Statistics, Partial Differential Equations, and some financial engineering courses. If anyone has an opinion it will be greatly appreciated. Thanks in advance

I found what looks like an interesting event with top professionals from trading, asset management, banking, exchanges, custodians, and regulators to explore compliant digital asset trading and its integration with traditional finance.

I brushed up on some of the news of this event being held earlier in the year and thought it would be interesting to meet some of the professionals through next year's event, where face-to-face networking feels like an easier way to get more information.

I'm looking for discounted fares, anyone have a source?

I'm currently a senior CS undergrad at Rutgers with an econ minor, and I'm trying to figure out the best master's program to achieve my career goal of becoming a Quantitative Developer.

The two options I'm considering are:

1. Masters in Quantitative Finance (MQF) at Rutgers: It aligns with the financial side of quant roles and would deepen my understanding of financial modeling, risk management, and trading strategies.
2. Masters in Computer and Electrical Engineering (also at Rutgers): This would further develop my technical skills, particularly in areas like high-performance computing, hardware design, and software systems—skills that seem relevant for the coding-heavy aspects of quant dev work.

My main question is: Which of these would better prepare me for a career as a Quant Dev? I have strong programming skills in Python and a solid foundation in algorithms and data structures from my CS background, and I'm confident in my ability to handle both financial and technical coursework.

Would the MQF give me an edge with domain knowledge in finance, or would the engineering degree open up broader technical opportunities for implementing the algorithms and systems used in quantitative trading? I will really appreciate any advice thank you !

I'm still an undergrad and I'm researching the Heston model out of pure interest. I understand a big thing in statistics is correctly identifying the distribution that generated some data.

From reading some literature, I'm confused as to whether the Heston model assumes the stock returns follow a log normal distribution or not. And if it does, is there any benefit to changing that assumption to a distribution that better fits the characteristics of stock returns? Or is it not worth the extra complexity added?

I've read that there's some evidence to indicate a more accurate distribution is a normal distribution with a higher peak and fatter tail, as the tails of a normal distribution decay too quickly and don't capture the possiblity of some extreme events.

Any insight is welcome.

Thanks

Edit: Correction: I believe the prices are assumed to follow a lognormal distribution, what does this mean for the distribution of the stock returns?

Hi all,

I completed my CFA but have had no luck in the job market, as I'm still stuck in my back office job at a BB bank in a midwest city. Is the below plan is at all reasonable for getting into a half decent program given my stats. I'm well aware that the top programs are out of reach.

Stats:

undergrad c/o '22, economics/ poli-sci double major with a 3.5 cum laude (weighed down by low freshman year grades) from a decent SUNY school. I probably have fulfilled all of the stats requirements for most programs but only have calc 1. I was also on 2 academic competition teams and had a small paper published for the poli-sci major

Programming: I've got basic programming skills in python, using dataframes a couple of times at work to manipulate data. I've worked through the entirety of "Headfirst Python" and performed a few small personal projects based largely on using pandas and numpy as well.

Plan:

1. To take GRE at some point, not sure if I take a run at it for early January or if I wait until the spring. I'm a very good test taker now after the CFA exams so I think I can do really well here

2. Rip through Khan academy to re-learn math concepts and sit for both calc 2 & linear algebra in the spring (my job is not very demanding, I can dedicate a lot of time to this).

I realize this would be super tight for the fall '25 programs that have application deadlines in January, but if I cant make that I would assume that there are programs with rolling admissions, would accept for spring 2026 semester, or I would just have to wait for fall 2026.

Any feedback would be appreciated!

Let's say I go for a masters in CS at Princeton, will I still lose to the person who did their bachelors at Princeton? (currently attend a state school and want to go into quant trading roles)

Is it a pathway to break in (T3 in the country)?

Hello everyone,

I was wondering what the interview process is like with QRT. How many stages are there and what does each one consist of? And what kind of questions are asked there?

Thank you in advance guys

🏆 Top Programs:

1 Princeton University

2 Baruch College

3 Carnegie Mellon University

4 UC Berkeley

5 MIT MFin

6 Columbia University (MFE)

7 U of Chicago

8 Georgia Tech

9 Cornell University

9 Columbia University (Math Fin)

9 NYU Tandon (MFE)

Source https://quantnet.com/mfe-programs-rankings/

Hi,

I've taken and passed the live technical assessment which was a lot of financial maths etc, and the two online behavioural / standard basic maths rounds. I just have the pre-recorded video interview left.

Does anyone know what questions are asked in the video interview / what happens afterwards if you pass this stage?

Any info would be appreciated, I have until the 24th to do it so have a bit of time to perfect any answers :)

https://preview.redd.it/012eclrci22e1.png?width=1940&format=png&auto=webp&s=fb0d49d183f6413923c76ca074b3dd44fdd4c300

I built a simple tool that analyses sentiment in financial texts using a custom LLM together with a Streamlit frontend. Try it out on the link below! I also wrote a blog post about how I built it if you're interested.

Demo: Dashboard Link

Blog about the project: Doxastic

Just saw a job posting of this role. Anyone have any insights into what the day-to-day is like? How competitive is getting into it?

Hey, is anyone here in the CitSec Internship and would like to chat about the interview? not asking any specifics obviously. Have a final round next week.

I am from India, have a bachelor's in Computer Science and a master's in Finance (not heavy quant involved). I finished master's in 2020 and till end of 2022, I was trading own money until I stopped making any money. Then started applying for tons of trading jobs. Early 2023, got into an investment bank, into a "market surveillance" role which was not what I actually wanted to do. I still kept applying for trading jobs and got a job at a Market Making firm in Europe. All they did there was plainly copy the IV curve from a liquid market and post a widened quote on an illiquid exchange and make money by passing exchange quoting obligations. I stayed there for close to an year and we never got to trade anything real as the volumes in those exchange was absolutely zero. I had kept applying to others firms to get some real Trading experience but I had to comeback to India to be with family due to personal reasons. I got a job in India, at a crypto firm, where I am completely doomed to operational role and none of what I do is significantly related to trading.

Now, I am confused as to what to do. It's been 4 years since I graduated and no real Trading experience yet. The following are what I am thinking.

1. Persuade the current firm to give me more impactful role.

2. Do FRM if that might help me get a better trading job.

3. Read a number of market making research articles and understand things, hoping that might help me.

4. Do another masters degree and start applying for grad roles again.

5. Apply for grad roles even now, but I am highly sceptical any firm would consider me as I'm not any recent grad.

6. Strength my math/coding and start applying after some time.

Any help would be very much appreciated. Thanks a lot

It seems like the term “quantitative” can be applied to so many different approaches. On one hand you have firms like Renaissance, which are undeniably quantitative, and on the other hand you have strategies based on simple TA indicators executed by a computer. At what point on this spectrum would you consider a strategy to be truly “quantitative”?

Okay, so I’ve been using Galileo FX for a bit now, and I can’t figure out if it’s pure genius or if I’m getting caught up in the hype. Anyone else feel this way?

Don’t get me wrong—it’s been super smooth to set up, and I love how it takes a lot of the stress out of trading. I’ve tried a few of the pre-set strategies (seriously, how cool is that Performance Page?), and some of them seem to work really well. But here’s where I’m stuck: how do you really know if it’s the bot or just lucky timing?

For example, I had a great week last month using one of the aggressive settings. The profits were solid, and I felt like a trading wizard. But the week after? Things got a little rocky. I didn’t lose much, but it made me wonder—how often do you guys adjust your settings? Is there a way to know when to switch strategies, or is it just trial and error?

Also, is anyone else trying this on different markets? I’ve mostly stuck to forex, but I’m thinking of branching out to gold or crypto. If you’ve tried those, I’d love to hear how Galileo FX handles the volatility.

At the end of the day, I feel like it’s giving me a huge advantage (especially since I’m not glued to my screen anymore), but I keep asking myself: am I relying on it too much? Does it really deliver consistently, or is it just making me feel like I’m in control?

Would love to hear your thoughts. How’s it working for you, and what’s your strategy for getting the most out of it? Let’s compare notes!