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New Quantnet members say hi

Hi all, I'm Jared, a new quantnet member. I may be an MFE candidate in the future, but I'm currently an undeclared sophomore studying computer science, math, and stats at Columbia. Just wanted to say thank you to all of you for the wealth of information that I've gotten lurking on this forum for years and that I'm excited to now be a part of the community. Best.
 
Hiya guys/gals!

I'm an undergraduate senior mathematics major with a minor in computer science (traditional) from Western Illinois University - I'll graduate in May of 2015 with a Bachelor of Science in Mathematics. I'm focused in algebra and applied mathematics. Courses I've taken include, in some type of order:

From mathematics:
Intermediate Algebra
College Algebra
Trigonometry
Pre-Calculus
Calculus I, II, III (I actually took the proficiency test for Calculus III to graduate on time)
Mathematica lab
Linear Algebra
Introduction to Mathematical Logic and Set Theory
Advanced Linear Algebra
Mathematical Modeling
Introduction to Mathematical Statistics I
Ordinary Differential Equations
ODE Lab (final project will be looking into applications of Wiener process and Ito process for retirement models using Mathematica, I'll be happy to post it once its complete if anyone's interested)
Abstract Algebra
Theory of Partial Differential Equations (a graduate level class I am taking for undergraduate credit)

From computer science:
Principles of Object-oriented Programming I, II
Data Structures
Computer Architecture and Organization
Automata and Computability Theory

From finance/economics:
Risk Management and Insurance
Investments
Principles of Microeconomics
Principles of Macroeconomics

I was originally a psychology major, started from the very bottom rung of the ladder (starting with the "remedial" course Intermediate Algebra), then after sorting through some medical problems, I discovered I was very capable of performing and understanding mathematics and switched to a Mathematics major. To give some background, I failed College Algebra THREE times due to medical reasons. I did OK in Trigonometry and Pre-Calculus and barely received a passing grade for Calculus I. Once my health situation remedied, I aced Calculus II with the highest grade in the class, taught myself the concepts and theories from Calculus III to test out of the course, and have been excelling at the rest of my courses. Looking back, I think it was important I didn't immediately jump into the calculus sequence (as is the typical route most mathematics majors go) - I was able to develop an in-depth understanding of topics previously learned in high school. Moral of the story: Hard work and perseverance can achieve almost anything. Also, transferring universities (in some cases) resets your GPA.

I find mathematics fascinating but wasn't thrilled by physics as much as I was by financing - I almost refused to believe that a blind-folded monkey throwing darts at the financial section of a newspaper could pick better market performers than most actively managed funds. The movie "Margin Call" also sparked my interest, as did learning about James Simons from Renaissance Technologies, and the 2008-2009 recession. So, I decided to pursue financial mathematics to both understand why our primate cousins can outsmart some of the more intelligent minds the world has to offer and because I'm attracted to the challenge the field offers - long hours and mentally straneous work in an environment where you are competing (in a sense) against other "players" or "teams" to see who can get the "highest score". It almost sounds like a fantasy.

I plan on applying to UIUC's MFE program as well as the Financial Mathematics program at University of Chicago. I have yet to take the GRE or Mathematics subject test. If I am not accepted, I will probably enter the industry as some kind of code monkey or analyst and continue to re-apply.

If you have any questions, I'm always happy to answer or help in any way that I can. I look forward to going over all the information available on QuantNet - I'm currently having one hell of a great time trying to solve some of the practice interview questions, keep the puzzles coming!

Best of luck to you all!
-mathemagician

PS: I'm also looking for networking and employment opportunities, so feel free to start a conversation with me about stuff pertaining to mathematical finance, or mathematics in general. I'm always open to making friends/acquaintances even if they are over the internet!
 
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Hey everyone!

I'm Siyu and I've been a software developer for a little over one and half a year. I did my undergrad at Univ. of Washington and graduated with the degree of Electrical Engineering, though my focus was heavily towards the Computer Engineering.

I always have the interests in the math modeling, software programming and finance, even though I don't know as much in finance as I do in math modeling and software programming. I was researching on a career path that could allow me to combine my three areas of interests, and then I came across various MFE programs. I noticed the online C++ course for FE provided by quantnet is really a good first step for me to step into the world of FE. I would like to know more about FE and if I would like to become a quant one day.

Thanks for providing the quant platform!
 
Hello everyone,

My name is Isaac. I am fifth year undergrad student at U of T. My programs of studies are Statistics (Quantitative Finance Specialist) and Economics (Major). Currently studying Bloomberg machine and VBA. Looking for first time summer internship.

Cheers
 
Hi,

My name is Bowen. I am fourth-year civil engineering student at U of T. I have a minor in economics. I love meeting new faces.

Thank you.

Bowen Wu
 
Hi. I'm a mechatronics graduate that ended up getting part time work at a hedgefund. Now at a career crossroad, between staying full time as an analyst, or moving to an IT company to build up my programming (especially scripting and SQL stuff). Thank you.
 
Hi everyone! My name is Fernando. I am a civil engineer from Peru, and I am looking forward to apply for a MFE program. This forum has been very helpful and informative for me for so long, and I thought it would be a good idea to be more active. Thanks!
 
Hi Andy and others,
I`m from Russia and we are going to visit New-York in the beginning of December. Is there any special place (bar) that quants usually go to? I heard about such bar but I don`t remember its name. We are looking for high-frequency trading quants. Also I need a guy to be in contact with. I really-really need your help, pleeeeeease. Thanks in advance))))
 
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Hi all,
My name is Zak, I'm the creator of DMSolution which is a solution to manage derivatives products from the start to the expiry. I'm pleased to be one of the members of quantnet :)
 
Hello everyone! I'm new here and don't know a lot of people here yet. It would be cool to know where are you guys from :)
Personally, I'm from Finland. I'm interested in quantitative finance and would love to learn about it a bit more deeply.
 
Welcome to Quantnet.
BTW do you like metal: Finntroll,. Wintersun, Lordi(?)
 
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Hi all,

I'm a software engineer with an interest on quantitative analysis and specifically the machine learning applications of it.
 
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Hi all,

I'm a senior researcher working for government in Canada. I've been doing quantitative trading at home for the last four years and I would like to connect with professionals and know more about the field. I really enjoyed the reading I found on Quantnet so far so please keep posting :)! And don't hesitate to contact me!
 
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Hi Everyone,

My name is Matt I am new to the working world, I have spent 8 months as a risk analyst for an extremely well-known firm in London, I have a BSc in Mathematics and MSc in Mathematical Finance. I am currently doing my CFA for that injection of corporate finance! At the moment I am extremely interested in Monte Carlo simulations with respect to different risk metrics, so most of my posts will be regarding that!
 
Hi Everyone,

My name is Matt I am new to the working world, I have spent 8 months as a risk analyst for an extremely well-known firm in London, I have a BSc in Mathematics and MSc in Mathematical Finance. I am currently doing my CFA for that injection of corporate finance! At the moment I am extremely interested in Monte Carlo simulations with respect to different risk metrics, so most of my posts will be regarding that!
Welcome to Quantnet, Matt!
I have taken the liberty to place a link to your MSc thesis here :)

 
Hey Daniel, fancy seeing you here! Thanks for that!
Matt, I have known the friendly people of QN and Baruch for almost 15 years now and I am the originator of the 2 C++ online courses here.
So, I like to have a look to see how everyone is doin', say hello and hopefully be useful :)
 
Hello World,

My name is Mike Lawrence, I am a sophomore at Baylor University. Until last semester I as mostly focused on the humanities but planning to go into Finance (mostly because I needed to pay bills and humanities jobs don't typically pan out terribly well). I was a quadruple major in Business Fellows, Finance, Mathematics, and Great Texts; now I am a triple in Business Fellows, Finance, and Mathematics with a minor in Stats (Baylor refuses to give anyone majors in both Mathematics and Statistics, so I get a minor).

I come from a humanities family (both parents graduated from Seminary), and my childhood was spent reading and walking around in nature. I didn't find Math/Stats terribly interesting until last semester when I took Math Stat I and Linear Regression, giving me some insight on where the computational formulas I was using before came from and how this stuff can be used in the real world. Now I'm beginning to dive deeper into math, stats, and coding/computational methods as I am able. It is difficult shift in some ways. I am used to taking in large amounts of information through the written word and then occasionally distilling it into an essay or journal entry. The fermentation period on knowledge in the humanities is much longer (though I think this difference disappears at the highest levels). Long walks (I preferred runs), thinking about the current book and ideas from other books, were practically homework. Now I am acclimating myself to a quicker turnaround, gaining familiarity with finding a topic I didn't know about and thinking about transferring it to code or to something else. I haven't done much of this, but I'm starting to search for methods. It is a different beast. More time spent crunching numbers and writing code than walking and thinking.

I am at the beginning of this process but excited to start. I decided to make the switch last semester around finals when I realized I would rather work through some more Functions of Random Variables problems than finish my essay. I have two years until I finish undergrad. I'm hoping to make it to a top Fin.Eng. Program. Ideally Baruch, Berkely, or UChicago. I will be happy with many others, but from scrounging their websites I prefer these programs course setups and some of the other 'top' colleges have some random really negative feedback. Tandon has terrible reviews on this site that have been buried by recent positivity. I can't determine how much of the turnaround was good marketing by (or due to) Peter Carr and how much was earned. I'll figure more about that later. Right now I have to prepare myself to get into the base programs, later I can try to get into the top ones.

If anyone has any good books with code to work with I'd love recommendations. I'm currently going through Hastie et. al.'s Elements of Statistical Learning, much of which I've covered in linear regression and more of which I'll probably cover soon in Time Series; but I can't find any accompanying code. I wanted to experiment with k-nearest neighbor methods (solely because I had worked with most of the other topics in that chapter) but don't know where to start.

To Lkarna: I was mostly raised in Oklahoma, in the United States.
 
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Hello World,
*Edit: I found a link near the front of the ESL book that takes me to a site with much of the data used in the book up for free.

Elements of Statistical Learning: data mining, inference, and prediction. 2nd Edition.

So if you want a good start for Machine/Statistical learning, from basic concepts through advanced, and you want to work alongside an author, then buy this. No code is given, but a couple R libraries are linked. I think I'll be lazy and just find a library in R for nearest neighbor methods and whatever else I find interesting until I take the quantnet C++ course. Then I might try and redo some of it in more detail. Good luck to whoever reads this.
 
I'd like to welcome everyone who recently joined QuantNet. We have a huge spike of members and it is our tradition to do a little introduction and get to know other members who potentially become our future classmates or colleagues.
I started this in 2006 so I've been around here for a while but it's very exciting to see many new members.
 
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