Best products from r/quant
We found 25 comments on r/quant discussing the most recommended products. We ran sentiment analysis on each of these comments to determine how redditors feel about different products. We found 32 products and ranked them based on the amount of positive reactions they received. Here are the top 20.
2. Financial Calculus: An Introduction to Derivative Pricing
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3. Heard on the Street: Quantitative Questions from Wall Street Job Interviews
4. 150 Most Frequently Asked Questions on Quant Interviews (Pocket Book Guides for Quant Interviews)
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5. Stigum's Money Market, 4E
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8. The Misbehavior of Markets: A Fractal View of Financial Turbulence
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10. The Handbook of Fixed Income Securities, Eighth Edition
- McGraw-Hill
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11. Quantitative Equity Portfolio Management: An Active Approach to Portfolio Construction and Management (McGraw-Hill Library of Investment and Finance)
12. Active Portfolio Management: A Quantitative Approach for Producing Superior Returns and Controlling Risk
15. Algorithmic Trading and DMA: An introduction to direct access trading strategies
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16. Quantitative Finance for Physicists: An Introduction (Academic Press Advanced Finance)
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disclaimer: Not a quant, never went to school for it nor worked in finance. I just like reading. This list is more than enough for the summer, but let me know if you want material focused on anything in particular. (Structured products, history, etc.)
I have a similar academic background as you (math / econ) and am a largely self-taught quant. For books, I recommend Active Portfolio Management and Quantitative Equity Portfolio Management. I also recommend academic papers to get a feel for the empirical side in addition to theory that you will read in the books. Great papers to start with are Fama / French (1992) and Avellaneda / Lee (2008). As mentioned, Quantopian is also great for the user forum and pre-baked back-testing engine. You would also find a lot of value in building your own simple back-testing engine in python or matlab or whatever. I wrote mine in python.
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Don't feel intimidated. When I first picked up academic papers, I understood 10% of it on first read. Now, I'm able to breeze through many of them, depending on how esoteric the math / symbology is. Feel free to message me any specific questions you need and I can try to point you in the right direction.
The programming languages really depend a lot. If you're looking to work in low-latency, more than likely, you'll want to have pretty much expert knowledge in C++. Many other firms use Java, Python, or Matlab to develop their strategies.
What I've found is knowing either Python or R is really useful as well for those really quick calculations/ideas.
As for math, knowing linear algebra and probability (extends to stochastic calculus) is a must in any case at all. Having a reasonable knowledge in Calculus is also really helpful. Most of the intense math lie in the derivative markets. If you're working with pure equities, you can usually get away with a lesser knowledge of math in favor of better technical skills (i.e. market microstructure).
There's a lot you can read, but to start off, I would say Dan Stephanica's financial engineering book is a must if you're going into derivatives:
http://www.amazon.com/Mathematics-Financial-Engineering-Advanced-Background
If you're looking into DMA, I highly recommend Algorithmic Trading and DMA:
http://www.amazon.com/Algorithmic-Trading-DMA-introduction-strategies/dp/0956399207
What you'll notice going into the field is that you can't be just an expert in one thing: you need to be well-rounded and an expert in several topics.
A book from 2005:
Quantitative Finance for Physicists: An Introduction. Anatoly B. Schmidt. ISBN 0-12-088464
I don't know anything about the book or author but the title stuck in my mind and it seems like it might be appropriate for you. Good luck!
"Y'all"? Ha you remind me of my friend from da South.
Anyway, getting fixated on a specific journal will not be effective, especially when you are not familiar with the fundamentals. I suggest reading some introductory texts (Hull, Baxter). Then maybe you can move on to Wilmott magazine (school library might have it). Then perhaps you will know enough to search for relevant papers on http://www.ssrn.com/en/.
Hope that helps.
Hey man, I interviewed a couple of months ago at a trading firm in Chicago for an Analyst/Quant role. Aside from the one the other user mentioned, this one was super helpful for me too!
Heard on the Street. The classic.
https://www.amazon.co.uk/Heard-Street-Quantitative-Questions-Interviews/dp/0994103867
Very good luck.
What kinda strategies?
There is Fama-French and a few hundreds of other factors, some of which probably work if done right (though maybe not quite in this market).
There is all the microstructure literature like e.g. https://scholar.google.com/citations?user=-ggKCCAAAAAJ&hl=en&oi=ao about LOB and order flow imbalances predicting short-term price moves.
There is the new fashionable ML stuff
https://www.amazon.com/Advances-Financial-Machine-Learning-Marcos-ebook/dp/B079KLDW21
There are all sorts of standard books on various topics, like this list
https://www.quantstart.com/articles/Quantitative-Finance-Reading-List
And some of them might even be somewhat relevant to the actual quant work.
But ultimately, as with a lot of data science, it's about data not the models. If you read a decent time series and a decent ML book it should be more than enough to start interviewing at quant funds (or to start working and developing models).
There are tonnes of 'Inverview Questions' books out there. This one is probably the best known.
https://www.amazon.com/gp/aw/d/0979757649/ref=mp_s_a_1_10?ie=UTF8&qid=1474590120&sr=8-10&pi=AC_SX236_SY340_FMwebp_QL65&keywords=quant
This one is good IMO
Here's a list of resources I've been collecting. Note that quantitative finance is a broad term, so different people will be doing very different things, and have different opinions about them. The work can range anywhere from high frequency trading strategies to macro global trends.
Quantitative Trading Summaries:
A summary of quantative trading
Max Dama - On Automated Trading
Cliff Asness - A Brief and Biased Survey of Quantitative Investing
Mark Joshi - On Becoming a quant
Becoming a quant for a programmer
Interview Prep:
Jane Street - Probability and Markets
Heard On The Street
Brainteaser section of On Automated Trading
Sites:
Wilmott
Nuclear Phynance
Blogs:
Math Investor
Investment Idiocy - Systematic Trading
Meanderful - HFT stuff
Jane Street Blog
Jane Street Youtube
Papers From funds:
AQR
Two Sigma