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Course Offerings

Course Evaluation Results

Course Details

Fall 2018-2019
ORF 405   Graded A-F, P/D/F, Audit

Regression and Applied Time Series

René A. Carmona

Regression: linear, nonlinear, and nonparametric (kernel and projection pursuit). Neural networks, convolution networks, deep learning: Tensor Flow and Keras. Time series: classical linear models (AR, MA, ARMA) univariate and multivariate.

Sample reading list:
Rene Carmona (2014), Statistical Analysis of Financial Data
Goodfellow/Bengio, Deep Learning
Chollet/Allaire, Deep Learning with R
Ruey Tsay (2013), An Introduction to Analysis of Financial Data with R

Reading/Writing assignments:
Homework: Approximately four hours/week

Requirements/Grading:
Mid Term Exam - 40%
Design Project - 40%
Problem set(s) - 20%

Other Requirements:
Not Open to Freshmen.

Prerequisites and Restrictions:
ORF 245 and ORF 309 or instructor's permission.

Other information:
There will be TWO in class midterm examinations

Schedule/Classroom assignment:

Class numberSectionTimeDaysRoomEnrollmentStatus
20458 L01 03:00:00 pm - 04:20:00 pm M W        Enrolled:48 Limit:48 Closed
20461 B01 08:30:00 pm - 09:20:00 pm M        Enrolled:24 Limit:24 Closed
20462 B02 08:30:00 pm - 09:20:00 pm T        Enrolled:24 Limit:24 Closed
20460 P01 07:30:00 pm - 08:20:00 pm M        Enrolled:24 Limit:24 Closed
20459 P02 07:30:00 pm - 08:20:00 pm T        Enrolled:24 Limit:24 Closed