B8306 Fall 2016
Professor Mamaysky
Due Date: Wed, Sep 28
Problem Set 1
PROBLEM SET INSTRUCTIONS
Use the Excel template entitled ps1_template.xlsx for your final answers. Type the names of all
group members at the top of the first worksheet and set the pri
Assignment 4
IEOR 4701  STOCHASTIC MODELS FOR FINANCIAL ENGINEERING (Fall 2016)
Instructor: Prof. Jose Blanchet
Due October 20, 2016  in class
1. Let cfw_X(t) : t 0be a continuous time Markov chain with the following transition rate
matrix
0
0 4
1
A= 2
IEOR E4525: Machine Learning for OR and FE (Spring 2016)
Syllabus and Course Logistics
Instructor: Martin Haugh
332 S.W. Mudd Building
Department of Industrial Engineering and Operations Research
Email: mh2078@columbia.edu
URL: www.columbia.edu/mh2078/
TA
IEOR E4602 Quantitative Risk Management: Spring 2016
Columbia University
Syllabus and Logistics
Instructor: Martin Haugh
332 S.W. Mudd Building
Department of Industrial Engineering and Operations Research
Email: martin.haugh@columbia.edu
URL: www.columbia
Solutions to Assignment 3
IEOR 4701  Stochastic Models for Financial Engineering
1. Gamblers ruin problem.
We have two gamblers, A and B. We toss a coin: if it comes up H, then A pays 1 dollar
to B; otherwise (i.e. if T comes up), B pays 1 dollar to A. T
Rsum Guidelines
What is a Rsum?
A rsum is a document which outlines your
experiences and the skills you have acquired as a
result. Preparing your rsum is like starring in your
own commercial. Often, the first impression an
employer has of you is based so
View the full edition of Spotlight at: https:/www.preqin.com/docs/newsletters/hf/PreqinHedgeFundSpotlightJune2014.pdf
Feature Article
Discretionary vs. Systematic: Two Contrasting Hedge Fund
Approaches
Download Data
Discretionary vs. Systematic: Two
ALEXANDER M. MATTHEWS
 (540) 9612469

alexmatthews@vt.edu
College address: 123 Turner St. N.E. #5, Blacksburg, VA 24060
Permanent address: 4097 Back Creek Rd., Bishopville, MD 21813
OBJECTIVE
Position in the design field, with emphasis on continuing de
Insights
CTA Trading Styles
Managed futures is an alternative asset
class in which Commodity Trading Advisors
(CTAs) seek to generate returns by trading
futures contracts on financial instruments and
physical commodities.
The potential
return opportunitie
INTERNSHIP PARTNERS 2014
Below are the reported companies who offered students internships during the summer of
2014 (MSFE students graduating in December 2014). Some companies hosted more than
one student. 80% reported having internships
Company
Location
Formatting a Resume
11 Tips & Tools for Creating a WellFormatted Resume
1. Manipulate margins to create a bigger page.
Changing margins to values slightly less than the default settings (i.e. .75 top, .5 bottom,
.9 left and right) will enlarge the presen
There is growing demand for professionals
with rigorous finance training who can also
master specialized technologies. This program
is a response to that demand.
J IANG WANG, M IZUH O F INANCIAL GROUP P ROF ES S OR,
P ROF ES S OR OF F INANCE
MIT SLOAN SC
Matlab Tutorials for IEORE 4701
Fan Zhang
Columbia University
IEOR Department
September 25, 2016
Fan Zhang (IEOR@Columbia)
Matlab Tutorials (IEORE 4701)
September 25, 2016
1 / 24
Overview
1
Linear System of Equations
2
Entries, Rows(Columns) and Submatric
How CTA strategies work: a
guide to managed futures
By Olivier BaumgartnerBezelgues 29 Sep, 2010
Managed futures or Commodity Trading Advisors (CTAs) are back in
fashion as some of the most famous names in the space become
available in the Ucits III form
MiniQuizzes
Lecture #2
Do Not Open!
(dont worry, this will not be graded)
Mathematics & Statistics for Financial Engineering
MiniQuiz #1
1) Express z as a linear combination of ln(x) and ln(y).
= ln (
)
5
2) Find the extrema (minimums and maximums) of
MiniQuizzes
Lecture #3
Do Not Open!
(dont worry, this will not be graded)
Mathematics & Statistics for Financial Engineering
MiniQuiz #1
1) Find the solution to the following differential equation.
1
= and (0) =
2
2) Find the solution to the following d
MiniQuizzes
Lecture #4
Do Not Open!
(dont worry, this will not be graded)
Mathematics & Statistics for Financial Engineering
MiniQuiz #1
1) Assume the weather and change in the S&P 500 are independent random variables. The probability of
rain tomorrow i
Mathematics and Statistics Review for
Financial Engineering
Michael B. Miller
mm5013@columbia.edu
2016 class schedule:
1.
2.
3.
4.
Wednesday, August 24, 4:006:30 pm
Thursday, August 25, 3:005:30 pm
Tuesday, August 30, 4:006:30 pm
Wednesday, August 31,
Why We Have Never Used the Black
ScholesMerton Option Pricing Formula
Espen Gaarder Haug
Nassim Nicholas Taleb
Abstract
Options traders use a pricing formula which they adapt by fudging and changing the
tails and skewness by varying one parameter, the sta
Richard Olsen
How to Trade
ISBN: 9783952370803
Introduction
High frequency finance, with the analysis of tickbytick market data, offers
new insights in how to trade. Before you continue reading, I want to caution you that over 80% of the traders in
John Liew, Cliff Asness, David Kabiller, and a team of highpowered Ph.Ds have
built AQR into a $141 billion investment giant that gets impressive returns in
good markets and bad.
(over p lease)
The Publisher s Sale Of This Reprint Does Not Constitute O
IEOR DEPARTMENT COURSE OFFERINGS
FALL 2016
SCHEDULED IS SUBJECT TO CHANGE; PLEASE CHECK DIRECTORY OF CLASSES FOR UP TO DATE INFORMATION.
SUB
DROM
DROM
DROM
DROM
DROM
DROM
DROM
IEME
IEOR
IEOR
IEOR
IEOR
IEOR
IEOR
IEOR
IEOR
IEOR
IEOR
IEOR
IEOR
IEOR
IEOR
IEOR
Big Data in Finance  Syllabus
The vast proliferation of data and increasing technological complexities continue to transform the way
industries operate and compete. Over the last two years, 90 percent of the data in the world has been
created as a result
On Thinning of Poisson Processes
Thinning
Jose Blanchet
Columbia University.
Department of Statistics,
Department of IEOR.
Blanchet (Columbia)
1/7
Thinning Property
N ( ) is a Poisson process with rate .
N (t )
N1 (t ) = m =1 Im ; Im s are i.i.d. Ber(p) r
Applied OR
School of
Operations
Research and
Information
Engineering
Master of
Engineering
Student Handbook
Data Analytics
Financial
Engineering
Information
Technology
Manufacturing
Strategic
Operations
Systems
Engineering
1
Revised August 2015
TABLE OF C