@shriidharkulkarni6648
I wish I had seen this kind of videos in my childhood and not at the age of 62. I too would have fallen in love with mathematics. Good video. Thanks for upload.
@johnnykleytonful
My major is also Economics and the sorcerer is really helping me with my math.
@AbselutlyNobody
A little more advanced but still very useful would be "Stochastic differential equations" by Bernt Øksendal. A lot of research in quantitative finance is based on stochastic calculus and stochastic/random processes. So anything related to that would be useful.
@redskytitan
Quant finance major here with 20+ yrs of experience in the industry - I would say that numerical analysis and methods is probably the most useful course you’ll ever take and you should focus on. Stochastic calculus and option pricing theory is fun but of little practical use, at least in my career, where I’ve focused on fixed income and structured products primarily. If you’re interested in algos and stuff like that, then maybe. Otherwise your 4 semesters of calculus will more than suffice. I’d say spend more time learning about the business, how markets work and how money is made on the trading desk. Then apply your math skills to solve these problems or optimize existing solutions. Best of luck!
@vvillegas01
youre literally one of the best people i know. thank you for making this video
@Pabloparsil
Hi, I just wanted to mention that for a rigorous option pricing book you might want to check out Shreve. The first volume pretty much doesn't require math background, it is short, extremely well written and simple (it's all about the binomial model, which is discrete and very intuitive). The second volume is the hardcore one, where he briefly starts with sigma algebras, filtrations, Lebesgue integral...
@americanhero8606
FYI Sheldon Ross has written two different books: (1) Intro to Probability and (2) Probability Models. The latter one is somewhat more advanced and assumes you already took a course on probability theory. Not sure how prepared you are on the finance knowledge side, but assuming you're not well versed on the topic I suggest you start with Bodie/Kane/Marcus's Investments. Fairly comprehensive, includes a lot of mathematical explanation of important theories in finance and investing. After you read that cover to cover (highly suggested), then move on to Hull's "Options Futures and Swaps" to learn the fundamentals of derivatives (the finance kind, not the calculus kind).
@blazel462
The Hull book, ‘Options, Futures and Other Derivatives’ is an industry standard. You will always find one on a quants desk.
@AndersBjornTH
Introductory books on stochastic calculus at various levels of rigor are extremely important. Also, options and futures related texts would be valuable as background for what comes next. Optimal control theory for corporate finance related topics would also be useful. Best of luck!
@Efesus67
I recommend Probability for the Enthusiastic Beginner by David Morin; he takes the time to explain things more than I've seen in other books. And his problems (with solutions) are not just plug and chug, they really help you develop your understanding. For mathematical maturity, i would recommend The Book of Proof. But I also like "Introductory mathematics: algebra and analysis" by Geoff Smith. He's very keen on foreseeing confusion with mathematical formalisms. Best of luck.
@ryanhermanson6121
Brownian Motion Calculus by Wiersema is the book I’m working through with my grad program for stochastic calculus. I’ve found it very approachable compared to some of the other books on the subject.
@benjamintreitz1647
Casella / Berger. Wilmott. Shreve 1 & 2.
@anthonybernardi4929
Great question! I am in a similar spot, preparing to enter Graduate School in Math. I had a class I took as a non-degree student in Probability, where we used Ross' Intro to Probability Models. Great book, but super dense at times. I used Ross' A First Course in Probability as a supplement and found that significantly easier to work through. I think using Ross' A First Course along with Wackerly and the other texts the Sorcerer mentioned should put you in a good position. Hope this helps!
@dareklewlaaaaaaa
Oh, this is very nice knowing, that I am not the only one pursuing the same educational path. I am after BSc in Financial Analysis (economics and finance), had a lot of statistics, forecasting, econometrics, maths for economics. In October I am starting my MSc in Financial Maths. I believe, I made the right choice!
@TQuantP
This is a very interesting take, I actually have exactly the opposite problem to be honest. I graduated in math, did a master's in algebraic topology (it was mostly cohomology theory but still) and I've decided that it's too dense of an area for me with too narrow exits on the private sector to continue, thus I turned to econometrics and quantitative finance for my PhD. I find beffudling that there is no clear avenue in doing something related to quantitative finance. In the end I decided to go to the high-frequency empirical data point of view, where the financial and economical literacy required is minimal (it's mainly statistics and data science). If anyone knows a way that I can follow, any books to read or any guidelines at all, please commend. (I have an unlimited supply of "take and forget" books from my university's library so at the moment I just borrow whatever I find interesting and relevant but it's too time consuming with bad results, since I'm basically picking at random)
@matteogirelli1023
Finance is more "statistical" and economics is more "mathematical" . I suggest you read the syllabus of some courses in the graduate program. Also simply write to the professors of the graduate program or simply the professor of your bachelor's. They will know. Anyway, you'll find math and stats but I think you should focus on getting the probability and proof writing skills since those are harder
@zeed54
You are a man of light
@matheusferesturcheti288
If you want a general book, maybe "A Primer for the Mathematics of Financial Engineering" from Dan Stefanica. If you need help with Analysis (which might begin at measure theory, not "formal calculus"), I'd check "Calculus" from Michael Spivak (since it's actually an intro to analysis) or the "Principles of Mathematical Analysis" from Rudin (not the "Real and Complex Analysis" one, which is measure theory).
@albertotrelles5748
Just saw in the background a book with the title "Origametry". Maybe we can have a review? Wonder what kind of exercises that book may have
@alphafound3459