Best Way To Start Learning Quant Finance?

Hi Monkeys,

I recently caught the quantitative finance bug so it’s been a few days since my last post. Since catching this bug I’ve been trying to read and learn as much as I can on ways to practice quant finance - and I found tons of material. In fact, it’s so much material that I was hoping to hear your thoughts on where to start or what to attack first.

Below are list of the resources I was able to dig up along with what I consider to be their key features...for anyone who is in the same boat as me at the moment, I hope you find these useful.

Datacamp.com
* Quantitative Analyst with R career track

Quantopian
* Access to multiple datasets which you can use immediately with Python along with a tutorial on how to get started

Coursera
* Library of courses taught by universities which may or may not be specific to finance

Sentdex
* Free videos that teach Python for finance covering topics like Monte Carlo Simulations or Machine Learning for Forex trading

Codecademy
* Intro course to learn the basics of Python

Codeschool
* Another intro course to Python

O’Reilly: Python for Finance
* Book that teaches Python specific to Finance.

From the research I’ve done so far it seems like I need to make two choices...Python or R. And after deciding on a programming language, I also need to decide on which resources to devote my time to.

So my question to you...

**Which language should I pick to learn and what resource do you recommend? Or do you recommend going a whole other route? **

For some context, I'm looking to eventually apply this via a trading algorithm that is based on fundamental factors. The term "quantamental" comes to mind...I think I read that somewhere. Not sure if it's a thing.

 
Best Response

IMO, trading algorithm =/= quant finance. There's a lot of literature/coursework on quantitative finance which surrounds the mathematics of it, not the coding of trading algorithms. Sounds like you've found mostly online material about how to code trading algorithms. If you're interested in the coding aspect those seem like fine resources, and I would recommend learning python for this purpose. If you're interested in the mathematics pick up Shreve's books or something.

 

Thank you @QF 2 IB" and halleb

I'll make sure to add Shreve's to my list of To-Dos. But I'm curious to know, have either of you given R a shot?

I was actually leaning to towards the Quantitative Analyst with R career track through Datacamp.com. Idk why, but this language seemed to be more focused on the mathematics aspect of Quant Finance, as opposed to Python which seemed to be more about the implementation.

 

I know a little bit of R. You are correct that Python is more appropriate for implementation, and R is more appropriate for statistical analysis. But Python has some powerful statistical powers too like Python pandas. Hence I recommend Python.

 

Depends on how do you define quant trading:

1) if you are talking about using statistical model or computer algorithm to identify new alpha and then trade, then no book or course can teach you that. Your best shot is to join a top fund and keep pitching ideas to senior ppl and get feedback (or better, running it with real money )such kinds of oppturnities are only avaliable in funds.

2) if you are talking about derivatives trading, in particular, exotic derivatives trading, then banks are good to start

3) if you are talking about quantative protfolio management. Well, this is the most controversial part, most of quant PMs are using quant model to conduct risk management, which is not that much different from bank’s risk team (usually middle or back office) of course, there are some people using “quant” as a marketing strategy... in reality, these fund managers are quite discretionary rather than systematic.

 

Quant Finance isn’t something you’re going to be able to just pick up from a book. If you’re really interested in going the quant trading route I’d recommend doing an MSF, and then seriously considering a PhD in Finance at a competitive school. The reason being, is that quant trading is highly mathematical and you need an advanced understanding of higher level mathematics and statistics/prob to make it. If you have some free time and want to prepare I’d pick up a linear algebra book, partial differentials book, and maybe a few books on time series and econometrics.

 

Buy Schaums outline for each respective subject. Schaums outline is by far the best fundamental book/guide you can buy for any subject honestly. Each should give you a strong base as a whole, you’ll probably want to pick up a Schaums outline of probability theory and stat theory as well, as all of the subjects end up converging into one at a high level.

 

basics of python and c could be pretty useful since they're used a lot, stochastics (you probably already have sufficient background) and strong maths skills are what came to my mind. I don't have a background in quantitative finance but know a guy from our uni who has done few internships and now works as a quant so that infos from his background.

so called hardcore quants don't really have any finance studies done, they have excellent mathematical and computer science backgrounds (some did study physics at advanced lvl) but they lack the knowledge of what their algorithms actually do or what is going in the markets/why does it affect your work as a quant.

 

I'm from commerce field(B.Com 2nd year) lately I got near to Quant Finance and I'm digging into it. I've pursued Data Science I'd say out of interest tho performed analyses using Monte Carlo and modelling but my stream is not initially focused towards it so its mostly self study of how I got here. I need some suggestion as to how to take myself into further advancements mainly because I've self studied as most of it wasn't there in my undergrad degree which is commerce based so I'm not sure what advancements I may be open to.

 

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