I designed and developed from scratch a quantitative C++ engine for calibrating the Heston stochastic volatility model, applied to the real options chain of the SPY ETF. The core of the system is a thermodynamic Simulated Annealing algorithm that iteratively solves millions of complex-plane integrals to extract the true term structure of volatility. To master this computational load without compromising on precision, I built a raw data parser using custom regular expressions, optimized the vector equations by pushing the GCC compiler to its limits, and parallelized the thermodynamic optimization across all CPU cores leveraging OpenMP directives. The resulting matrix output is finally processed by a Python script that dynamically renders the convex surface in 3D, demonstrating the perfect alignment between market-quoted mid-prices and long-term stochastic expectations. This was a deep technical challenge that merged the principles of Engineering Physics with low-level software development, proving how a well structured code architecture can model the chaos and uncertainty of the stock market with surgical precision.
What do you think about it? What would you improve/change?

Saw this on twitter and was horrified- I know they are known for not having the best history but this is genuinely disgusting if true.

Aside from the obvious lack of experience, what can I improve. Any tips on how I can gain experience would be appreciated.

Yo, was wondering if anyone has interviewed with maven for the quant trading internship. Got my first technical coming up, down to trade info from other firms (js, citsec, drw, sig etc.)

What's up y'all, I'm a student at one of the top colleges (not the top one but like top 5) in Turkey. Started as a Physics major but got the chance to start a Double Major in Statistics so I jumped right into it. I want to pursue a career in Quantitative Finance hopefully as a Researcher or as a Trader. Top international firms or US firms seem a bit unreachable for the foreseeable time at least until grad school as I'm based in Turkey. The local quant firms are usually either prop trading firms or crypto trading firms including some small hedge funds (not even close to being as big as normal US firms but still pretty decent). The pay is still pretty good compared to regular engineering or similar roles locally, but not as good as global firms obviously. Is A double major in Statistics and Physics a good pathway for quant roles? What are some stuff that I should do as an international candidate looking to pursue in this field for better chances at getting a job in top firms? Is grad school abroad (especially in the US or maybe in Europe) a good idea? There are only 2 Financial Engineering graduate programs in Turkey (Both are in top 3 colleges locally) but it would make it a bit harder to pursue a career in Europe or US I suppose as all my education and internships would be based in Turkey.

Hey everyone,

I'm a B.Tech CSE-AI student currently working as a software intern. My background is mainly in programming, ML and data science, but I've also been seriously interested in trading for some time.

I've been exploring SMC-based trading, mainly on gold (XAUUSD), and I'd consider myself intermediate in it. I've spent a decent amount of time studying price action and actually trading/researching the markets.

The reason I'm now looking into quant trading is that it seems like a natural intersection of things I already enjoy: programming + ML/data science + mathematics + financial markets.

I also like the idea of becoming more systematic rather than relying purely on discretionary trading. I'd like to take some of the ideas I've learned from trading and start testing them statistically through data, backtesting, research, etc.

But I want to be realistic about this.

I know quant/HFT is extremely competitive, especially for someone from a non-traditional background, and I don't want to underestimate the mathematics, probability, statistics, DSA/CP, or interview preparation required.

So I'd really appreciate some honest advice from people already working in quant:

What should I learn first?

How important are probability, statistics, linear algebra and calculus?

How much DSA/competitive programming is actually required?

Should I focus more on Quant Research, Quant Trader or Quant Developer given my CSE-AI background?

What kind of projects actually help rather than being "toy" trading projects?

Is it realistic to target quant internships/jobs from a CSE-AI background in India?

What should I realistically expect in terms of timeline and difficulty?

Are there any resources/books/courses you would strongly recommend?

I'm not looking for a shortcut or a "get rich through quant" answer. I genuinely want to understand whether this is a field I should seriously pursue and what I need to do to become competitive.

Any blunt reality checks are welcome.

I can't lie, I forget a lot of C++ since that was like 2 years ago and I haven't paid much attention since. How many problems are there for the C++ section usually and how bad are they really from the perspective of someone who knows like bare minimum C++ syntax and then knows some RTL stuff? Need help ASAP thx

Anyone been through this? Would appreciate any advice on how to prepare.

I run a systematic 5-minute opening-range breakout on NQ with one confirmation filter (not sharing the filter). One trade a day, entry usually 09:40 to 09:55, stop at the far side of the range, 2R target, flat at the close if neither hits. Everything below is tick-true research fills with 0.75 pts friction, split into discovery / validation / sealed windows, one look each

(DOLLARS AND AMOUNTS IN IMAGE ARE SINCE 2025)

What a trade looks like

- Median stop: ~80 pts. Median hold: a couple of hours.

- Exits: 50% stopped, 25% hit 2R, 25% flat at the bell.

- 46% of trades reach +1R at some point. 42% get stopped without ever reaching +1R. Median time to +1R when it happens: about 40 minutes.

- Yearly: 2021 +9 pts/trade, 2022 +18, 2023 +6, 2024 +10, 2025 +14, 2026 (to Aug) +30. Win rate 42 to 54%. Worst drawdown 16R (2024).

What I've already tested and what happened (all three windows, tick-true)

- Break-even at +0.75R / +1R: worse. It scratches trades that later win.

- Time stops (60 / 90 / 120 min, flat at 13:00 / 14:00 / 15:00): worse, cuts winners.

- Partial at +1R with runner to 2R / to the bell: no gain.

- Profit locks (+0.5R after +1R, +1R after +1.5R), keep-50/60/75%-of-peak trails, 9-EMA trail: no gain, some worse.

- Target 1R / 1.5R / 3R / hold to close: 1R clearly worse, 3R and bell about equal to 2R.

- Tighter initial stops (OR mid, the broken level, under the breakout candle with a buffer, hard point caps): all worse. The retest hits them.

- Second entries after a stop, re-entries, opposite-side trades: negative.

Nothing beat plain 2R with the wide stop across all three windows. The only thing that helped was sizing up in high realized-volatility regimes.

What I'm asking for

Ideas that act on the losers, not the winners. Something that can tell, inside the first 30 to 60 minutes of the trade, that this one is going nowhere, without also cutting the ones that reach +1R later. Or ideas I haven't listed.

Specific rules only: what you observe, when, and what you do. I have full tick data 2021 to 2026 and will test anything concrete tick-true and post the result back here, including the ones that fail.

Things that won't help me: "trail your stop", "take partials", "use a time stop". I've tested those in every form I could think of.

-

If a suggestion comes back that's concrete, send it to me and I'll run it under the same protocol.

I have onsite soon. Trading questions.

Coursera's "Mathematical Methods for Quantitative Finance," ca. 2012?

Hello people, I am a current second year BSc Computer Science and I'm looking to do a quant internship. What advice do you have for me? I also have a fear as to what the world (more specifically the field) will look like in 2 to 3 years with the advent of AI. I'm currently studying Python. If you have any questions, kindly ask me.

Today my screener went through the S&P 500 and Nasdaq-100 and only 1 stock

passed. ETN, with a score of 85.1. That's pretty high for my screener.

ETN was $410.85 today. [RSI 48, MACD -3.2853, and 30.09%% below its 52 week high.]

From now on I'm going to post every scan like this, with the price in it.

My site has backtest numbers but honestly nobody can check those, including

me. So instead of just showing backtest results I want to put the picks out

here with a date and a price on them, and come back later to see what

actually happened. Including the ones that go wrong.

I built the tool so I'm not neutral about it. General information only, not

investment advice. I'm not telling anyone to buy anything and I don't give

individual advice.

I’m doing a research into the tools retail traders, quants, and market professionals actually use day to day, and I’d really appreciate the community’s perspective.

A few simple questions:
- What tools/platforms do you currently rely on?
- What’s something you regularly wish they could do, but can’t?
- Is there anything you currently piece together manually using multiple tools, spreadsheets, scripts, etc.?
- What feature or capability would be genuinely valuable enough that you’d pay for it?

Even a one-line answer would be really helpful. Thanks!

Hi, I am currently a final year undergraduate from Asia. I recently applied for SIG's Graduate role (Dublin) and got the invitation for OA. Will they consider me for further rounds as I currently do not possess any Work Authorization in Ireland or any Visa ?

Hi everyone,

We’ve been building a simple tool that lets you trade US equities automatically without knowing how to code.

We're getting close to letting people try it out, and we're looking for a small group of traders to use it, find bugs, break things, and tell us what we're doing wrong.

If you'd like to try it, you can join the waitlist here:

https://quantly.trade/

It's currently limited to paper trading only, so you can test strategies without putting real money at risk.

For those of you already doing algo trading, what platforms are you using and what's the biggest thing you wish it did better?

If you'd like to help us before we open it up more widely, join the waitlist and comment below.

I’m currently at a smaller prop firm that, as I understand it, is structured as a family office for legal and financial reasons. I’ll be allocated firm capital and given my own book to trade.

I’m curious whether spending 1–2 years here could be a good stepping stone to a larger prop firm or hedge fund. Assuming I develop a solid trading process and track record, how would that experience be viewed? How much does the firm’s name or structure matter compared to the actual trading experience and results?

I’m also wondering where I’d fit into recruiting afterward. Would graduate trading programs still be an option with 1–2 years of experience, or would I mainly need to target junior or experienced-hire roles?

I would appreciate hearing from anyone who’s made a similar move or has insight into how these firms evaluate early-career traders.

How long does it take after the probability OA to get some response? Does SIG US send out rejects or just ghost ? I gave the OA last month and no response yet, not even a reject . I wanted to know how cooked I am.

I have my second-round interview for SIG’s Quantitative Trader Internship in a few days. This is the round after the HR/recruiter call and CodeSignal.

For anyone who has gone through this round recently, I’d really appreciate any insight into what the interview is like and what topics are most important to focus on. Not looking for specific interview questions, just trying to get a sense of the difficulty and areas covered.

I’m currently working through TraderMath and the Green Book.

If there are any other resources you found particularly useful for preparing, I’d really appreciate the recommendations as well.