Ask HN: How To Become Quantitative Analyst And Achieve Greatness?
So when my grandfather became paralyzed (3 months ago) I saw it everything more clearly. I want to help people and do my best.
I'm 20 years old. I decided to change my life 3 months ago. I like computers and finance world since my childhood. So 3 months ago I started to learn Python and Math. And I love it! I am so passionate about it now. I applied for CS degree at the most prestigious university in my country and I got the opportunity to study there.
I am very interested in machine learning and finance world. I would like to do quantitative research and beat that mean sharks at Wall Street. I have no bad intentions and I don't see any value in buying expensive things. My dream is to donate research from my earnings.
I have got the passion. I just need the direction. There is so much things to learn. What is the most important thing in this field? Should I focus to mathematics first and then start to learn programming?
What market should I choose? I am familiar with Futures and Forex. Forex seems to be very dangerous but more accesible for students (funding requirements).
Do I need to know more then this for start?
http://measuringmeasures.com/blog/2010/3/12/learning-about-machine-learning-2nd-ed.html
http://pindancing.blogspot.com/2010/01/learning-about-machine-learniing.html
http://quantivity.wordpress.com/2010/01/10/how-to-learn-algorithmic-trading/
You may have noticed that English is not my native language. I apologize for grammar. Thank you for your answers. I really appreciate it!
24 comments
[ 3.0 ms ] story [ 55.0 ms ] threadWhy not make money the way Larry & Sergey or Jobs & Woz did, by creating wealth?
These people are rare exceptions. I am just not sure if I can invent something so great as they did.
I am also interested in computer security. I would love to create OpenBSD-like user-friendly system and sell only hardware like Apple. But it is so improbable. Masses are not interested in secure system. They want a pretty and easy to use system. So it is really hard to work on things in which you have passion, interest and make big money as well.
My main tendency is to donate research. There are smart people who are short on money. I could pay for their education etc. Creating another Google is hard task, but make money for honest poor student is not so hard. It is quite difficult to make a decision now.
If your smart, can do some programming and are able to think on your feet this is a multi billion dollar industry right in front of you :)
Sadly, I can't disagree with the assessment about studying to become a quant. Odds would be higher if you simply picked up the books and tried to trade yourself. Otherwise you'll likely be sucked up into a big firm and get lost in that mess.
That said, I don't know what the relative odds are vs founding Google or Apple. It seems kind of like wondering which state's lotto to put your money in.
1) Read an overview of how the products and exchanges work like Hull or Wilmott.
2) Read every single post on elitetrader and nuclearphynance, and note links that may be interesting. This'll be confusing, boring, and frustrating because you'll be digging through nearly 100% crap. That's the point: almost all trading concepts and ideas touted are crap. Reading through this stuff will give you a feel for that, maybe give you some ideas, and serve as a helpful guide for your further learning.
3) Go follow-up on the links that still seem interesting.
4) If you make it to this point.. screw it. Email me. If you're good at programming, system administration, or statistical analysis, I'll probably give you a job. Otherwise I'll help you take the next step or get your foot in the door somewhere else.
Why not make money the way David Shaw or Jim Simon or Paul Wilmott did, by adding liquidity to global markets that have modernized economies and provided stable living conditions for communities that came from nothing.
Or you could make fun tech toys for the most privileged 1% of the world.
Of course neither side is that simple, but please don't mistake PG's preaching for the truth.
As far as practical links :
http://academicearth.org/courses/machine-learning
http://en.wikipedia.org/wiki/Support_vector_machine
http://en.wikipedia.org/wiki/Computational_finance
http://tepper.cmu.edu/master-in-computational-finance/index....
I'm also 20 with very similar interests as yours. You don't have an email listed, but I'm hoping you could email me at loganfrederick@gmail.com to talk to you more about quantitative analysis and computational finance!
Check out the forums on wilmott.com for suggestions on books and the like as that's where a lot of quants hang-out.
I have worked in algorithmic trading, hedge funds, and investment banking. I have degrees in CS and Mathematics.
There are a rare few people who have walked these footsteps - see Jim Simon of Renaissance or Doyne Farmer of Prediction Company. And of course there are more you never hear of because they don't have enough money or interest to garner media attention. This community is not an open community because unlike the open source world, it is not beneficial to share knowledge. Governments have to force them to.
One question I wonder if you've considered: do you feel comfortable working within boundaries that governments have the power to change? It's an aspect of the job I find interesting, but I feel many members here would find frustrating.
Mathematics is far more important than C.S. at crafting algorithmic trading strategies, but developers are in far more demand. Quant shops only really need one genius, and maybe a few in training in case the first gets hit by a bus.
In terms of what mathematics: you're going to need stochastic calculus, but don't worry about that yet. Unless you are blessed you're going to need a PhD in math or physics. The importance isn't the thesis, but the topical knowledge along the way regarding which relationships break down under what conditions. Most entry-level quants go for the PhD and pick up stochastic calc while job searching. Machine learning is no panacea: regression (a form of machine learning) is the oldest trick in the book.
So I'd suggest forgetting about finance altogether until you absolutely have to. If you're absolutely serious: ride the academic train for as long as you can. It's not easy riches, but neither is quant finance. Easy riches is swapping MBO's to your buddies on comission.
This seems to happen even in academia: research in CDS's seemed slim before the financial crisis, I imagine partly because the major U.S. data provider has enjoyed monopoly pricing.
I am aware of this. Now after reading your comment I need also a self-confidence and optimism to all that. I am just not sure if I can handle all this. I mean I am smart but not genius for sure. Is it worth it to persist in this field even if I have no talent in mathematics?
Don't sell yourself short on mathematics before undergraduate - the nature of mathematical talent changes the deeper you get into a particular topic. But yes: if your goal is to become a quant, do not think it will be easy to get into the industry without a PhD.