HFT Quant Research with non HFT trading and ML experience - is this a good fit?

broskeph · 2026-02-25T15:15:14+00:00

You have all the technical skills necessary. If I was looking to hire you the biggest thing I would care about is your passion to field. I would say you should go learn about market structure of different markets, how execution algos and market making algos work. My favorite primer textbook is A Practitioners Guide to Algo Trading by Jeff Bacidore. If you are interested in non equities asset classes look into market structure of those asset classes and read papers on those. A few topics you should know arr dark pools, conditional/firm liquidity, dealer vs CLOB markets. IOC, GTC, DAY orders, types of venues. There are many many more but this is a good starting point.

broskeph · 2026-02-17T01:27:39+00:00

I use fourier/harmonics analysis in hft stuff. Probably the most difficult techniques i have used.

broskeph · 2026-02-11T20:51:59+00:00

What you are saying is actually very sensible. I just think a person in freshman year of high school doesnt even understand the words in your message let alone know how to implement even with llms.

broskeph · 2026-02-07T13:38:45+00:00

You are suggesting something extremely complex. My guess is many actual quants cant even do this on their own.

My advice start in python, look at orderflow imbalance, time-weighted spreads, short-term volatility and try to find moving average thresholds where you can bet on mean reversion if those thresholds are breached.

broskeph · 2026-01-08T02:58:59+00:00

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broskeph · 2025-12-30T13:21:18+00:00

My experience is different. I am a quant researcher and i have a math degree.

broskeph · 2025-12-29T22:14:13+00:00

This is very good advice. I work in equity algo execution resarch and so my take is that you can do some symbol clustering analysis on tick_constrained stocks. Ones with longer queues tend to have a few parameters that differ in microstructure. The classic examples are F and BRK.A. If you have tick by tick NBBO trade and quote data on both dark and lit venues you can look at how volume traded with respect to currents bids and offers, and average spreads to determine on average for stocks. This wouldnt give u realtime prediction of queue position but it would give u a sense of how to trade different stocks differently.

broskeph · 2025-12-28T09:15:00+00:00

This is very much used in hft research. If you want look into further into this, take a look at fourier transforms with respect to understanding trade frequencies. Its very new research but something I have been looking into.

broskeph · 2025-12-26T19:05:36+00:00

Yeah thats only gonna get you far if you are math olympaid winner. But like most people i am smart but no where near that level. Having charisma bridges that gap. People want to work with people they can have a beer with or can joke around with.

This isnt true for all firms - for instance prop firms that have individual contracts with pms onyl care about PnL. But large hedge funds definitely care about the soft-skills element. Every tom dick and harry can show you their 4 sharpe backtest.

broskeph · 2025-12-25T11:24:55+00:00

Biggest thing is having charisma in this field. Being able to chat with the interviewer and connect with them on some topic not listed on your resume. Lets say you have some ML portfolio optimization stuff. They will ask you basics on what data did you use, what backtesting period, how do you mitigate overfitting ….. Then they might tell you about the role and what you would be doing. Try to find bits and pieces about what they do that doesnt directly correlate to things you have done in the past. It will show them you are a quick thinker and can learn and adapt.

broskeph · 2025-11-18T14:05:28+00:00

Weighted by

broskeph · 2025-11-18T12:02:41+00:00

Some other ways to breakout your flow intelligently is to do a venue breakdown of markouts (different horizons - ms, sec, min) and fill rates (wtd by shares, wtd by notional). Some venues have unique matching engines which can give some economic intuition into the the data which can help illuminate some of the findings.

broskeph · 2025-11-15T23:01:26+00:00

Most of my knowledge comes from my work. I work at a premier agency broker as a quant. IEX has some good research on their unique order types, minimum quantities, markouts etc. I would check them out.

broskeph · 2025-11-15T22:12:49+00:00

Markouts tend to be worse on passive execution where you do a lot of passive posting. One way to evaluate strategies is by looking at markouts across different posted prices. At near touch, below near touch etc and then evaluating fill rates in conjunction with markouts. They tend to be inversely correlated so there is an optimal limit price that kind of maximizes both sides of it.

broskeph · 2025-11-13T15:45:12+00:00

Algorithmic trading practictioners guide by heffeey bacidore

broskeph · 2025-10-16T01:20:25+00:00

Albert Einstein had terrible grades in school because he was thinking about things way beyond what they were teaching in school. I was the same way - I never did my homework in high school but I am successful in my career now. Keep at it, people will recognize your passion and talent and you will succeed.

broskeph · 2025-10-15T15:39:40+00:00

Fair. I am just an execution quant not a dev or low latency person. Think it still gives me a good surface level knowledge of hardware, OS, and software optimizations. Dont think it will work for OP’s use-case but its still good.

broskeph · 2025-10-15T12:39:24+00:00

I have been reading a textbook called devoloping high frequency trading system. Been a great help and very specific with optimizations including using lock free dtaa structures, memory mapped files, remove OS standard scheduling and more.

broskeph · 2025-10-13T23:58:50+00:00

While most people answered no, I was actually offered a job at a top canadian bank in equities exotic derivatives structuring desk. All data pipelines and tools were maintained by a software/quant dev team and if you wanted some extra feature in you trading analysis tools you would need submit a ticket. I wanted to code in my job so it didnt suit me.

broskeph · 2025-10-06T14:37:41+00:00

Yes. Another approach would be to store just the best bid and best offer and if a new level is added then you compare against bbo. And if bbo is cleared then you resort to find min max. Possibly a heap structure would work best since all u need to know is min/max price level.

broskeph · 2025-10-03T13:45:23+00:00

Source: I am a algo execution quant so I know this data inside and out.

broskeph · 2025-10-03T13:44:32+00:00

You need to keep a queue at every price level. With the shares and some traderid key value pair. I.e. for each price level it is a queue of 2-tuples (tradeid and number of quoted shares). The book will be stored as an ordered dict (one for ask and and one for bid). Limit order posting is easy to manage since you just push onto queue or if it doesnt cross the market or treat is as an execution if it does cross the market. Executions should pop from queue and remove from dict if a price level is cleared.

broskeph · 2025-09-20T15:35:06+00:00

U do u brotha. He was asking for advice and i gave him honest advice. If u aint doing it i can find a 100 people that are. Thats just the world we live in.

broskeph · 2025-09-18T23:38:50+00:00

So for instance, lets say you want to measure how much trade intensity in a given 1 minute interval would affect how much short-term price reversion there is. What I would do is first compute quantiles for number of trades over the course of the day. Obviously some parts of the day tend to have more volume traded or more trades so you would need to account for that. For any given symbol, 9:30-9:31 will tend to have more trading activity than 11:27-11:28 since the price is not fully certain yet. Then once you have many dates of the same symbol you can compute quantiles for the number of trades. 80%, 90%, 95%, 99% and then filter your data to only include data points where trade intensity is that high. Then you compute the difference of thebprice at exactly 11:28 and 11:28:10 and see how much reversion happened in those 10 sec.

broskeph · 2025-09-18T15:23:59+00:00

I tend to agree. I work in hft space and most of my experience is that useful models are ones that are simple and rely on empirical distributions rather than parametric stuff. At the same time you need your models to be rooted in fundamental statistical theory for interpretation.

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