MATH 5670 – Financial Programming and Modeling
Fall Semesters – Open to undergraduate students
Instructor: Prof. Do
Office hours: by appointment only (Webex)
Email: cuong.do@uconn.edu
Description
Practical Python programming with common packages, databases, internet data (XML, JSON, HTML); object oriented programming; unified modeling language; data structures and algorithms (Arrays, strings, linked lists, stacks, queues, heaps, hash tables, trees, graphs, recursion, dynamic programming, searching, sorting); quadratic programming with applications in portfolio optimization; data envelopment analysis with applications in investment efficiency evaluation; principal component analysis and independent component analysis with applications in ranking; reinforcement learning; prompt engineering in financial applications.
Classes are fully online. Lectures are pre-recorded and released weekly on HuskyCT, together with reading materials, handouts, and sample scripts.
Textbook
Textbooks are not required. Slides are provided by the instructor, posted at http://huskyct.uconn.edu together with other study materials.
Software
Programming languages: Python, used with Google Colaboratory at colab.research.google.com
Reference Books
1. Elements of Programming Interviews in Python – The Insiders’ Guide by Adnan Aziz, Tsung-Hsien Lee, Amit Prakash
2. Cracking the Coding Interview 6th edition, Gayle Laakmann McDowell
3. Python for Finance, 2nd Edition, Yves Hilpisch
4. Numerical Methods and Optimization in Finance, Manfred Gilli, Dietmar Maringer, Enrico Schumann
5. Numerical Methods in Finance and Economics: A MATLAB-Based Introduction (Statistics in Practice), Paolo Brandimarte
Grading
Grades are based on group assignments and projects following this distribution:
Group assignments 50%
Group project 40%
Class participation 10%
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Note: The instructor reserves the right to make changes to the syllabus as needed.
If there is any change, you will be notified in class or by your UConn e-mail address