FIN 580

Summer 2021 All Classes

All Classes

Special Topics in Finance

SHOW FINAL EXAM SCHEDULE

Credit: 0 TO 4 hours.

Lectures and discussions relating to new areas of interest. See class schedule for topics and prerequisites.

0 to 4 graduate hours. No professional credit. Approved for Letter and S/U grading. May be repeated to a maximum of 18 hours in a semester; may be repeated to a maximum of 32 hours in subsequent semesters. Credit is not given for FIN 528 and FIN 580 (66393), Section ADF. Prerequisite: Varies by section.

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FIN 580 class schedule data for summer 2021
	CRN	Type	Section	Time	Day	Location	Instructor	Section Details
	38725	Independent Study	INT	ARRANGED	n.a.	Location Pending	Widdicks, M	Part of Term: SF Date Range: 05/17/21-08/05/21 Special Approval: Departmental Approval Required Section Title: Internship Section Info: Instructor Approval Required, 0 credit hour section. Course is required for students completing an internship within finance field during the summer term. Restricted for MS Finance students. Students must have confirmed an internship in order to take the course. Students on F1 visa must also submit CPT documents to International Student and Scholar Services (ISSS). S/U grading only.
	33999	Online	R1	9:30AM -10:50AM	MTWR	n.a.	Gao, X	Part of Term: S2 Date Range: 06/14/21-08/05/21 Credit: 4 hours Section Title: Python: Finance Applications Section Info: Python: Finance Applications. This course implements a variety of popular data analytics techniques in Python to tackle problems in finance and business. The first part of the course presents backtesting of trading strategies based on simple moving averages, momentum, mean-reversion, and machine learning-based prediction. The second part of the course introduces supervised learning methods for predictive analytics. Methods include Multiple Linear Regression, k-Nearest Neighbors, the Naïve Bayes Classifier, Classification and Regression Trees, Logistic Regression, Neural Nets, and Discriminant Analysis. The third part of the course focuses on business time series forecasting. Handling time series, regression-based forecasting, and smoothing-based forecasting will be discussed Restriction(s): Restricted to MS:Finance -UIUC, MS: Finance Cost Rec -UIUC, MS: Financial Engineering, MS: Finance - UIUC, or MS: Finance Cost Rec - UIUC.