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Quant Finance Study ThreadPosted by Doc Fenton on 1/5/13 at 4:06 pm

10

This might be a little overambitious, but with the eagerness that comes with the new year, I thought that perhaps I would start a quant study thread on this board, as this is a topic where I've recently gained a lot of interest.

I'm just going to lay out an outline for now, and then try to fill it in better over coming weeks, and perhaps bump it when things are more polished.

We'll see how it goes...

**PROSPECTIVE OUTLINE**

I. General Internet Resources: Quant Message Boards, Grad Programs, etc.

II. Necessary Math Background: Stochastic Calculus; etc.

III. History of Financial Engineering (since the 1970s, more or less)

IV. Interesting Factoids about Algorithmic Trading and the New Regulatory Environment (Basel III, etc.)

V. Notable Recent Happenings at Trading Desks & Hedge Funds

I'm just going to lay out an outline for now, and then try to fill it in better over coming weeks, and perhaps bump it when things are more polished.

We'll see how it goes...

I. General Internet Resources: Quant Message Boards, Grad Programs, etc.

II. Necessary Math Background: Stochastic Calculus; etc.

III. History of Financial Engineering (since the 1970s, more or less)

IV. Interesting Factoids about Algorithmic Trading and the New Regulatory Environment (Basel III, etc.)

V. Notable Recent Happenings at Trading Desks & Hedge Funds

re: Quant Finance Study ThreadPosted by Doc Fenton on 1/5/13 at 4:06 pm to Doc Fenton

Wilmott

QuantNet

QuantStackExchange

etc.

QuantNet's 2011-2012 rankings (released on Sept. 19, 2011) --> LINK

QuantNet's 2012-2013 int'l guide to programs (released in Oct. 2012) --> LINK

This post was edited on 1/5 at 4:28 pm

re: Quant Finance Study ThreadPosted by Bayou Tiger on 1/5/13 at 4:08 pm to Doc Fenton

I'm in.

ETA: ...for the study. Just showing interest, not "in" like "hey I'm on the first page."

ETA: ...for the study. Just showing interest, not "in" like "hey I'm on the first page."

This post was edited on 1/5 at 4:19 pm

re: Quant Finance Study ThreadPosted by Doc Fenton on 1/5/13 at 4:11 pm to Bayou Tiger

Congratulations.

EDIT: Congrats either way.

EDIT: Congrats either way.

This post was edited on 1/5 at 4:27 pm

re: Quant Finance Study ThreadPosted by GetBackToWork on 1/5/13 at 4:49 pm to Doc Fenton

Something I might throw in as you go about this. Any modeling exercise is always improved by having a sufficient understanding and knowledge of the environment or subject in question.

Pure quants may enjoy consistent moderate success but will often make egregious outlier failures when they skimp on the underlying economics.

Pure quants may enjoy consistent moderate success but will often make egregious outlier failures when they skimp on the underlying economics.

This post was edited on 1/5 at 4:50 pm

re: Quant Finance Study ThreadPosted by blowmeauburn on 1/5/13 at 5:34 pm to GetBackToWork

Count me as interested.

re: Quant Finance Study ThreadPosted by jso0003 on 1/6/13 at 4:21 pm to blowmeauburn

In and bookmarked, I'm looking to go through some of this stuff as I I'm working right now and getting ready to prep for the gmat ill be checking back

re: Quant Finance Study ThreadPosted by TheSurge on 1/6/13 at 9:04 pm to Doc Fenton

Count me in.

*PSA: Don't drink and model*

re: Quant Finance Study ThreadPosted by Doc Fenton on 2/23/13 at 11:21 pm to TheSurge

You know, quant school is kicking my arse right now, and I don't have time for much of anything these days, but just to prepare you for how to prepare for grad school in a math-related field, you might want to read an interesting blog post from "Ethan" about his steps for surviving grad school in physics: LINK.

There were some recent letters to grad students in chemistry (June 2010) and physics (October 2012) that went viral in the past couple of years, and that were really scary.

Quant finance or financial engineering is a whole different ballgame, chiefly because there are no laboratory research assistantships or anything like that. But the classes themselves are just as brutal, if not more so.

I'm not sure if recommending classic text books is a good idea, because it's pretty damn impossible to crack them until you actually take a class on them, but in general you need to have some acquaintance with Wiener processes, Ito's lemma, and formal probability theory, including all the really abstract stuff about sigma algebras, Borel sets/algebras, and Lebesgue measures.

Image: http://upload.wikimedia.org/math/f/6/5/f658de4b607351d3bfda98dc68e9b263.png

Image: http://upload.wikimedia.org/math/4/7/4/4741446c77941ac175e0266fef2ce99c.png

Image: http://upload.wikimedia.org/math/f/8/2/f822e8939551cac1788de9a03fe094e3.png

To get an idea of why in the world anyone would need to learn abstract measure theory before understanding more sophisticated concepts in probability, you can watch this mini-lecture on YouTube by a young math teacher at the University of Missouri: " Mini Lecture #1 - Why use measure theory for probability?."

Additionally, probably the most famous young mathematical genius in the world at the current time, Terence Tao of UCLA, has a free pdf text giving students an introduction to measure theory: " An Introduction to Measure Theory" (2011).

The idea should probably be to work up to Jacod & Protter's "Probability Essentials," which is a very short & concise book giving in compact form everything an incoming quant student would need to know about the abstract concepts behind probability measure theory...

Image: http://bks0.books.google.ch/books?id=OK_d-w18EVgC&printsec=frontcover&img=1&zoom=1&edge=curl&imgtk=AFLRE70SHhwg9mno4Flty39T7R5DjfDSe6GdMf2rh_1PA8YOpVbfgw7GIXgpiQ6oRx6ZidPD5I6kfAZPU1rgov-1kG94Qr1FJbbmtaE0_7JVVOWCQFXrDqCEsnM7R5-qtYW0mg8RSpBw

There are other great texts that bear mentioning, but which might be best left untackled until you arrive at school:

"Stochastic Calculus for Finance I & II" (Shreve)

"Stochastic Finance: An Introduction in Discrete Time" (Föllmer & Schied)

"Limit Theorems for Stochastic Processes" (Jacod & Shiryaev)

"The Mathematics of Arbitrage" (Delbaen & Schachermayer)

"Stochastic Integration and Differential Equations" (Protter)

"Introduction to Stochastic Calculus Applied to Finance" (Lamberton & Lapeyre)

"Stochastic Differential Equations and Diffusion Processes" (Ikeda & Watanabe)

"Brownian Motion and Stochastic Calculus" (Karatzas & Shreve)

"Financial Modeling with Jump Processes" (Cont & Tankov)

"Derivatives in Financial Markets with Stochastic Volatility" (Fouque, Papanicolaou, & Sircar)

"Levy Processes" (Bertoin)

"Finite Elements" (Braess)

"Computational Methods for Quantitative Finance: Finite Element Methods for Derivative Pricing" (Hilber, Reichmann, Schwab, & Winter)

*... and from the more practical side, with books that might be useful references for derivatives traders and practitioners...*

"Hull-White on Derivatives" (Hull)

"The Mathematics of Financial Derivatives: A Student Introduction" (Wilmott, Howison, & Dewynne)

"Dynamic Hedging: Managing Vanilla and Exotic Options" (Taleb)

"Quantitative Methods in Finance" (vols. 1-5) (Alexander)

quote:

But practically, about a third of all students that enter physics graduate schools are gone — having either flunked out or given up — by the end of their second year. And I was worried I was going to be one of them if I didn’t work hard enough. The material was harder than anything I’d encountered before, and I knew that my old study habits weren’t going to cut it.Especiallybecause I wanted to do theory.

So I did something that wound up working for me, and that I suppose I would recommend to any student that was serious about succeeding during their first year in graduate school in physics.

For each class, my study habits actually became outstanding, although they required more time than I’d ever put in before. I would:

* Skim over the sections in the textbook that we were going to be covering in lecture that day.

* I’d go to class, write down everything the instructor wrote down, take the best notes I could, and ask whatever questions I could to make sure I understood the material. And then...

*I’d go through the relevant section in the book, that we just covered in lecture, along with my lecture notes. This time, unlike before class, I’d actually be able to work through it and figure out what the author was talking about. Andthisstep was immensely helpful to me.

* Because when it came time to do the homework, unlike when I was an undergrad, I had an idea of what we were talking about. I knew where to look in the book and my notes for guidance, and I was actuallypreparedfor the next class.

It was really amazing to see that every student thatput that kind of work indid just fine in those courses, and every student that failed those classesdidn’t put that kind of work in.

It isn’t, of course, the only way to do it, but it was tremendously useful for me, and it helped me turn myself from a student that came in with adeficientbackground in the upper division undergrad courses, who’d been away from academics for a year, to one ready to take on the most difficult theory courses — general relativity and quantum field theory — with great success in the next year.

So if you’re headed to graduate school in physics, that’s my advice for your first year. Put the work into those core courses, because whatever you want to do after that, that’s work that will pay off. I realize this doesn’t apply to many of you, but I’d also imagine that something very much like this would help inmostfields of academic study. Thoughts?

There were some recent letters to grad students in chemistry (June 2010) and physics (October 2012) that went viral in the past couple of years, and that were really scary.

Quant finance or financial engineering is a whole different ballgame, chiefly because there are no laboratory research assistantships or anything like that. But the classes themselves are just as brutal, if not more so.

I'm not sure if recommending classic text books is a good idea, because it's pretty damn impossible to crack them until you actually take a class on them, but in general you need to have some acquaintance with Wiener processes, Ito's lemma, and formal probability theory, including all the really abstract stuff about sigma algebras, Borel sets/algebras, and Lebesgue measures.

Image: http://upload.wikimedia.org/math/f/6/5/f658de4b607351d3bfda98dc68e9b263.png

Image: http://upload.wikimedia.org/math/4/7/4/4741446c77941ac175e0266fef2ce99c.png

Image: http://upload.wikimedia.org/math/f/8/2/f822e8939551cac1788de9a03fe094e3.png

To get an idea of why in the world anyone would need to learn abstract measure theory before understanding more sophisticated concepts in probability, you can watch this mini-lecture on YouTube by a young math teacher at the University of Missouri: " Mini Lecture #1 - Why use measure theory for probability?."

Additionally, probably the most famous young mathematical genius in the world at the current time, Terence Tao of UCLA, has a free pdf text giving students an introduction to measure theory: " An Introduction to Measure Theory" (2011).

The idea should probably be to work up to Jacod & Protter's "Probability Essentials," which is a very short & concise book giving in compact form everything an incoming quant student would need to know about the abstract concepts behind probability measure theory...

Image: http://bks0.books.google.ch/books?id=OK_d-w18EVgC&printsec=frontcover&img=1&zoom=1&edge=curl&imgtk=AFLRE70SHhwg9mno4Flty39T7R5DjfDSe6GdMf2rh_1PA8YOpVbfgw7GIXgpiQ6oRx6ZidPD5I6kfAZPU1rgov-1kG94Qr1FJbbmtaE0_7JVVOWCQFXrDqCEsnM7R5-qtYW0mg8RSpBw

There are other great texts that bear mentioning, but which might be best left untackled until you arrive at school:

"Stochastic Calculus for Finance I & II" (Shreve)

"Stochastic Finance: An Introduction in Discrete Time" (Föllmer & Schied)

"Limit Theorems for Stochastic Processes" (Jacod & Shiryaev)

"The Mathematics of Arbitrage" (Delbaen & Schachermayer)

"Stochastic Integration and Differential Equations" (Protter)

"Introduction to Stochastic Calculus Applied to Finance" (Lamberton & Lapeyre)

"Stochastic Differential Equations and Diffusion Processes" (Ikeda & Watanabe)

"Brownian Motion and Stochastic Calculus" (Karatzas & Shreve)

"Financial Modeling with Jump Processes" (Cont & Tankov)

"Derivatives in Financial Markets with Stochastic Volatility" (Fouque, Papanicolaou, & Sircar)

"Levy Processes" (Bertoin)

"Finite Elements" (Braess)

"Computational Methods for Quantitative Finance: Finite Element Methods for Derivative Pricing" (Hilber, Reichmann, Schwab, & Winter)

"Hull-White on Derivatives" (Hull)

"The Mathematics of Financial Derivatives: A Student Introduction" (Wilmott, Howison, & Dewynne)

"Dynamic Hedging: Managing Vanilla and Exotic Options" (Taleb)

"Quantitative Methods in Finance" (vols. 1-5) (Alexander)

This post was edited on 2/23 at 11:27 pm

re: Quant Finance Study ThreadPosted by acgeaux129 on 2/24/13 at 11:38 am to Doc Fenton

What are your career goals?

re: Quant Finance Study ThreadPosted by Doc Fenton on 2/24/13 at 12:01 pm to acgeaux129

I'm still flexible at this point.

If I can get a job in some structured product group hedging derivatives for traders, then great.

If I can get a job using quant methods to optimize portfolios for hedge fund managers, even better.

If I need to fall back on a career in regulatory compliance, using knowledge of financial law along with statistical methods to ensure a firm stays within certain specified risk tolerance levels, then that'll be okay too.

If I can get a job in some structured product group hedging derivatives for traders, then great.

If I can get a job using quant methods to optimize portfolios for hedge fund managers, even better.

If I need to fall back on a career in regulatory compliance, using knowledge of financial law along with statistical methods to ensure a firm stays within certain specified risk tolerance levels, then that'll be okay too.

re: Quant Finance Study ThreadPosted by acgeaux129 on 2/24/13 at 12:35 pm to Doc Fenton

That's pretty cool, quant side isn't for me but I still find it interesting. Highest calc I took was 1435 which is a joke and offers little practical utility, so out of personal pride, I would like to try to get a better grasp of the subject at some point. Bookmarking this thread because I would like to look over the resources you provided when I have more time.

re: Quant Finance Study ThreadPosted by Doc Fenton on 2/24/13 at 12:39 pm to acgeaux129

The plan is to try to write a little something in a general way about 4 or 5 different core subjects within the field, but I'm just not ready to do it yet. It's still a confusing mess to me right now.

...

**EDIT for Sunday, April 7, 2013:**

So the other day I was perusing some Wikipedia articles on quantitative investing and quantitative analyst, and I came across a lot of hedge funds / asset management firms that were specifically listed by name as being known to participate in quant-related investment strategies.

Firms listed included:

AQR Capital Management (Greenwich, CT)

Barclays Wealth & Investment Managment (12 U.S. locations)

PIMCO Portfolio Management (Newport Beach, CA + NYC location + 11 int'l locations)

BlackRock Investment Management (HQ on 52nd Street in Manhattan)

Citadel Group (Chicago)

Renaissance Technologies (Long Island & NYC)*(see Medallion Fund)*

Winton Capital (London)

D.E. Shaw & Company (on 6th Ave. in Manhattan by 46th Street)

GMO (Boston & San Francisco locations in U.S.)*(founded in Boston in 1977 by Grantham, Mayo, & Otterloo)*

First Quadrant (Pasadena HQ + Wellesley, MA location)

LGT Group (Vaduz, Liechtenstein)

Robeco (Rotterdam, The Netherlands + U.S. offices in NYC, Chicago, & Boston)

...

So the other day I was perusing some Wikipedia articles on quantitative investing and quantitative analyst, and I came across a lot of hedge funds / asset management firms that were specifically listed by name as being known to participate in quant-related investment strategies.

Firms listed included:

AQR Capital Management (Greenwich, CT)

Barclays Wealth & Investment Managment (12 U.S. locations)

PIMCO Portfolio Management (Newport Beach, CA + NYC location + 11 int'l locations)

BlackRock Investment Management (HQ on 52nd Street in Manhattan)

Citadel Group (Chicago)

Renaissance Technologies (Long Island & NYC)

Winton Capital (London)

D.E. Shaw & Company (on 6th Ave. in Manhattan by 46th Street)

GMO (Boston & San Francisco locations in U.S.)

First Quadrant (Pasadena HQ + Wellesley, MA location)

LGT Group (Vaduz, Liechtenstein)

Robeco (Rotterdam, The Netherlands + U.S. offices in NYC, Chicago, & Boston)

This post was edited on 4/7 at 12:23 pm

re: Quant Finance Study ThreadPosted by Bayou Tiger on 2/24/13 at 2:46 pm to Doc Fenton

quote:

"Brownian Motionand Stochastic Calculus" (Karatzas & Shreve)

Concepts like Brownian Motion are part of the reason that I lost interest in quantum mechanics. My mind works better when I can visualize the math.

That being said, I am pretty well versed in a lot of the basic probability mathematics and discounted cash flow analysis. I am still looking forward to the thread but am starting to realize that I may be in way over my head!

re: Quant Finance Study ThreadPosted by Doc Fenton on 9/22/13 at 3:13 pm to Doc Fenton

Man, I think I am still nowhere near being able to put this thread together like I thought I would. Give me another year and maybe I'll be ready.

In the meantime, there is a Coursera MOOC now being offered by Professor Kjell Konis of the University of Washington, Mathematical Methods for Quantitative Finance.

In the meantime, there is a Coursera MOOC now being offered by Professor Kjell Konis of the University of Washington, Mathematical Methods for Quantitative Finance.

quote:

Course goal:

Upon completion of the course students will know the fundamental mathematical concepts needed to effectively study quantitative finance areas such as fixed income, options and derivatives, portfolio optimization, and quantitative risk management.

Course Objectives:

Upon completion of the course students will:

Understand the concept of a limit, differentiation, and integration;

Be able to compute partial derivatives and multiple integrals;

Understand the utility of matrix decompositions;

Be able to use Lagrange multipliers to solve constrained optimization problems; and

Apply the above methods to problems arising in finance.

Recommended Background

Students should have completed entry-level college calculus courses that include an introduction to multivariable differential calculus; additional introductory mathematics and statistics coursework is desirable.

Suggested Readings

Stefanica, D. (2011). A primer for the mathematics of financial engineering. (2nd ed.). New York, NY: Financial Engineering Press. Retrieved from http://www.fepress.org/primer-second-ed/

Course Format

The class will consist of lecture videos, which are between 8 and 12 minutes in length and there is a short quiz at the end of each video. Additionally, there is a homework assignment accompanying each set of 8-10 videos.

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