| As a CS student, I'd really make sure your stats knowledge is solid. Perhaps take a class that covers stochastic finance (Black-Scholes, etc.) if available. I learned the hard way that it is quite difficult to break into finance as a non-student, so do everything you can now to land that first gig. Good luck! Some starting resources: -Ernie Chan's books and blog (https://epchan.blogspot.com/) -QuantStart has great starter material and a new book, although I haven't read it (https://www.quantstart.com/) -"Inside the Black Box" (Narang) I've seen referenced a good bit but felt as though it leaned toward order execution and rather boring -"Dark Pools" (Scott Patterson) a great story about the rise of algorithmic trading -"Flash Boys' (Michael Lewis) offers a nice follow up (HFT), but considered a bit sensationalist EDIT: If you're planning on using Python (a solid bet)... -Python for Data Analysis (Wes McKinney) - Great, quick book for Pandas by former AQR (and now Two Sigma?) guy. -Yves Hilpisch books: "Python for Finance" is introductory while "Derivative Analytics in Python" is quite math heavy. |