r/quantindia

Hey everyone, I'm trying to get into quant and I feel like I'm missing the bridge between learning and actually building things.

I like math a lot, and I already know Python and C++, but I don't come from a finance background. Whenever I look for beginner quant projects, people say things like "build a backtester," "implement Black-Scholes," or "make a limit order book." My problem is that I have no idea where those ideas even come from. I don't know what they are, why they're useful, or what I should learn before trying to build them.

Even if I learn the finance concepts, I still don't think I'd naturally know what to build or how to turn those concepts into actual projects. It feels like there's a huge gap between understanding the theory and saying, "Okay, now go implement this." I can code if I know what I'm building, but I don't know how people go from learning about markets or options to deciding, "I'm going to build this model," or "I'm going to calculate that metric." Is there some roadmap that teaches both the finance and the engineering side together, where you learn a concept and then build something meaningful with it?

I'd really appreciate hearing what and how u guys started, because right now it feels like I'm missing an entire step that everyone else somehow already knows.

Any one having some interview exp with them say here or dm me if u wanna share.

I don't see many roles in their website except python dev

some of you might've seen my build-to-kill post from a few days back. in the 4 days since, the system got "finished". multi sleeve, everything wired, and the final backtest spat out: ₹25L becomes ~2.7Cr median over 15 years, worst drawdown −31%. i'm not gonna lie, i stared at that number for a while and started mentally spending money.

problem is it's family capital. my dad's money, one shot, no refill. so before touching anything i decided to spend a day being the meanest reviewer my system could face. not "double checking". actively trying to prove my own work is garbage. wrote down everything that died, posting it here because honestly some of these hurt and i'd rather you find them in your systems before your first bad week does.

1. my hedge could not physically exist. the tail protection was shorting a basket of ~41 stock futures, and at my capital that whole basket got about ₹4-5L of notional. one stock futures lot is ₹5-15L. so the backtest had been "holding" a hedge for years that my account literally cannot hold even one leg of. every drawdown number i was proud of assumed protection that doesn't exist at my size. i genuinely sat there for a minute after this one.

2. found a 2.4x sizing mismatch between my model and my live code. the projections sized the options sleeve as a fraction of capital. the execution code sized it as a margin budget. two different conventions, both looked reasonable, nobody ever compared them. reconciling constant by constant showed live would've run 2.4x the short-vol risk that every single tail number assumed. no error message. every report looked normal. this would've only announced itself in a crash, at 2.4x the size i "planned" for.

3. one of my sleeves is literally illegal. currency futures leg, decent sharpe, backtested clean. turns out RBI barred retail from exchange traded currency derivatives without underlying exposure back in 2024. no data feed tells you this. your parquet files don't care what the rulebook says. felt like an idiot googling it after weeks of "research".

4. look-ahead was hiding in my liquidity filter of all places. i filtered tradeable stocks by fill rate computed over the full history, which means the filter knew in 2015 which names would still be liquid in 2024. that alone was +1.6pp/yr of completely fake alpha. everyone checks their signals for look-ahead. nobody checks the boring plumbing. it's always in the plumbing.

5. my crash kill-switch was validated on a proxy that flattered it 2x. tested on an index proxy: cuts max dd from −25%, looked great. rebuilt on the actual portfolio daily: real drawdown is −44% and the kill-switch cuts way less of it, at double the cost. if you validated something on a proxy you validated nothing.

6. and the part that actually humbled me, the errors ran the other way too. my slippage haircut, which i thought was the responsible conservative choice, turned out ~15x too harsh once i actually measured effective spreads from 23M rows of 1-min options data instead of assuming. and my tax model charged flat 30% on f&o... at my actual income slab the real rate is basically 0 (87A rebate, if you trade f&o small and don't know this, go look it up today). so i wasn't being conservative. i just didn't know, in both directions.

where it landed: honest numbers are roughly half the wealth and nearly double the drawdown of the pretty version. then measurement gave some back legitimately. it now runs at lower leverage than the optimizer wanted, on paper only, and it has to earn its way to real money.

the thing i actually kept from all this is a stupid boring document where every input is tagged: measured / estimated / assumed / no-way-to-know, with how much the answer moves if it's wrong. before the audit i had ~40 inputs and could honestly account for maybe 15. the scary column isn't what's wrong. it's what's unmeasured.

running count since i started: ~50 ideas tested, ~45 dead. the survivors are boring and staying that way.

happy to go deep on any of these in comments. can also paste the audit checklist i now run on everything if anyone wants it, fair warning it's deeply unpleasant to use on your own work. pretty sure that's the point.

Yo!!Does anyone know the pay for the iRage Quant Analyst Intern position?

Hello Everyone,

I'm a 28-year-old beginner in the quantitative strategies field.

I recently started working in FX Strategy, covering G10, LATAM, and EM currencies. While I'm enjoying the role, I know I'm only scratching the surface. My long-term goal is to develop a deep understanding of quantitative research, systematic trading, financial markets, and the mathematical and programming foundations behind them.

At the moment, I'm strengthening my Python and R skills while learning statistics, econometrics, and quantitative modeling. Over time, I'd like to build trading strategies, backtest ideas, and eventually contribute to meaningful quantitative research.

I'd love to connect with others who are on a similar journey whether you're just starting out or have more experience. It would be great to discuss research papers, exchange ideas, work on small projects, review code, stay accountable, and learn together.

If you're interested in quantitative strategies, systematic investing, algorithmic trading, or financial markets, feel free to leave a comment or send me a message. Building a small community of curious learners would make this journey far more enjoyable.

P.S. English isn't my first language, so I appreciate your understanding if there are any mistakes. Thank you!

Hi, so I am going to be starting college in a few weeks, I got <100 rank in JEE Advanced, (so CS in top IIT), I made it to last level of math and physics olympiads, but couldn't qualify it (yeah I made it just before the OCSC camp).

I just wanted to ask seniors what can I do as a fresher to make myself eligible for quant interviews, and if possible could you share what you guys did to accomplish the same.

I have browsed a bit about codeforces, leetcode, dsa, but i can't seem to understand many things as of now, so i sort of feel overwhelmed

Anyone here know much about hiring for entry level QR/QT roles in Hong Kong?

I'm from IIT Patna/Jodhpur/Mandi and have about 6 months of quant dev experience. Been thinking about trying to break into QR/QT roles in HK and honestly have no clue how realistic it is coming from India.

Would love to know:

Do firms in HK hire directly from India?

Are there any visa issues like US?

Any firms/recruiters I should be looking at?

Would really appreciate any advice from people who've been through this or know the HK quant scene.

i'm currently a bachelors student, prior to this i was a studying in canada, but i returned to india for a change. i've always loved mathematics and the sheer abstraction of it, but was always disappointed since not many career opportunities were available in the field. ever since i came across quant finance and stochastic processes, i've been obsessed and been working towards it- learning programming languages and reading finance literature. i want to commit to this field wholeheartedly, and i see that MStat is a promising degree that can help me pivot towards quant roles. any suggestions as to how i can leverage my current position for working in quant in the future. i'm also willing to do a PhD in math, stats or financial engineering. looking forward to your responses :)

So basically I am currently in t1 IIT Cse i want some advice and actually I was able to change my branch from a lower one to cse, my adv rank isnt good at all and my whole first year i dedicated to acads. Now I want to get into quant so wanted some guidance from the seniors

Where do I start from exactly and end up getting into quant

I am planning to pursue a PhD in Applied Maths/Stats from NTU or NUS. I am currently doing a master’s in Maths at NTU, and I have a B.Tech in EE from one of the top 5 IITs.

Like US quant firms, which prefer Maths, Stats, and Physics PhDs for quant researcher roles, do Indian quant firms also have a similar preference for PhDs? From what I have seen, most quant research roles in India are bagged by undergraduate students from top tier IITs.

Got into tier 1 mtech - IISC/IIT
Btech t3 - 8.36(2023 grad)
12th - 54%
Cf - almost CM
I have 3 years of gap. I have 1 year to prepare.
Should i prepare or will my resume will be rejected based on my background?

Iisc btech mnc 4y or iit bhu cse for quant sde/Big tech

I'm currently working in a product-based MNC (like Microsoft/Adobe/Oracle/Salesforce) with around 2 years of experience, and I have offers from two Indian HFT firms.
Profile: 8.5+ CGPA, Top 3 IIT Circuital

1. Bangalore based HFT for a C++ role (~40% compensation increase)

2. Gurgaon based HFT for an Applied AI Engineer role (~85% compensation increase)

From a long-term career perspective, which would you choose? How are the growth opportunities, learning in these two paths?

Would really appreciate advice from people working in HFT or who have made a similar decision.

what are the general career trajectories one can end up in after early career start in prop trading firms as a trader?

how possible is it to enter into QR and Low Latency environment?

Is masters from abroad a better option if you want to enter into HFTs and Hedge Funds?

Last year I quit my quant dev job to trade full-time. Things were going great initially, I made around 50% on a 4 crore portfolio last FY. But since the end of April, everything has changed.
I’m down about 70 lakh this FY (over 15%). Both my directional and gamma scalping strategies have been struggling, and higher slippage and STT aren’t helping either.
Are other quants still consistently profitable in the current market, or are you seeing the same thing? I’m honestly considering going back to a job.

Hi, I have a interview for FPGA role at Mathisys coming thursday.

Can anyone please help me how to prepare for this?

Thanks a lot.

Hello everyone, need your guidance! I have an interview with NK soon for the role of SDE python backend. Can someone guide me about what kind of rounds or topics I can expect there. If anyone else has gone through the process, can you share how many rounds there are and what are the difficulty levels.
PS: This is a fresher role, also I am not from IIT, NIT, IIIT.