hfsl_course
 Fall On Campus
 Spring On Campus
According to their site http://www.rproject.org/ :
"R is a language and environment for statistical computing and graphics."
"R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, timeseries analysis, classification, clustering, ...) and graphical techniques, and is highly extensible."
"One of R's strengths is the ease with which welldesigned publicationquality plots can be produced, including mathematical symbols and formulae where needed."
This course is designed for both graduate and undergraduate students. It covers some fundamental topics in the statistical programming language R, as well as some basic applications in finance. Upon completion the students will gain an understanding of the programming syntax and should be able to use R in any future courses.
Lecture Notes and Code.
The art of R programming: a tour of statistical software design. Norman Matloff, First Edition, 2011. ISBN10: 1593273843, ISBN13: 9781593273842
An Introduction to Analysis of Financial Data with R. Ruey Tsay, First Edition, 2012. ISBN10: 0470890819, ISBN13: 9780470890813
CRAN: http://www.wikibooks.org
Rhelp Info: https://stat.ethz.ch/mailman/listinfo/rhelp
Rhelp Archive: http://r.789695.n4.nabble.com
Quick R: http://www.statmethods.net
The plan is to schedule 5 to 6 assignments for this semester. The assignments should be done exactly before the next class. All LATE SUBMISSION will be punished unless you send me an email BEFORE DUE and get approved. If your submission passes the due for less than 24 hours, your highest score will be 67%; between 24 and 48 hours, your highest score will be 33%; after 48 hours this assignment is worth nothing. However, for each student, the lowest grade will be dropped when I calculating the final grade.
Starting from this semester we will have midterm and final exam. Both exam will be arranged outside class time due to the limited time for each section. Estimate both exam will be 2 hour length and you are allowed to use any material to help finish it but NOT including use all kinds of tool to discuss with anyone, such as email, skype, text message and so on.
You are encouraged to have discussions but NOT including homework questions. All code and reports must be written by yourself. Copying solutions from sources other than your brain is strictly forbidden. This kind of behavior will be considered as academic dishonesty/misconduct and will be dealt with according to the Stevens honor board policy.
Assignments 50%
Midterm 20%
Final 30%
Bonus Questions TBD
Date 
Topics 
Assignments 
08/29 L1 
R basics & Data structures & Loops 

09/05 L2 
R basics & Functions, “apply" functions 
A1 
09/12 L3 
R basics & Generating random variables & Simulations 

09/26 L4 
Date and Time Objects 
A2 
09/26 L5 
Download data through R: Thomson Reuters API (TRTH), Yahoo API (Quantmod) 

10/03 L6 
Return, Autocorrelation & Asset Volatility 
A3 
10/10 
Monday schedule, No class 

10/17 L7 
Simple linear regression, Gradient Descent 

10/21 
Midterm 

10/24 
No class 

10/31 L8 
Newton's Method 
A4 
11/07 L9 
GBM, volatility 

11/14 L10 
Plot and GGplot 
A5 
11/21 L11 
Rmarkdown, R Sweave, R html & R presentation 

11/28 L12 
Advanced Topic: TBD 

12/05 L13 
Advanced Topic: TBD 

12/09 
Final 