IE 423

Course Code & Number
IE 423
Course Title
Optimization Models in Finance
Level
BS
Credit Hours/ ECTS Credits
(3+0+0) 3 TEDU Credits, 5 ECTS Credits
Year of Study:
Senior
Semester:
Fall
Type of Course:
Elective
Mode of Delivery:
Face-to-face
Language of Instruction:
English
Pre-requisite / Co-requisite:
Pre-requisites: IE 222 AND IE 232 AND IE 332 AND MATH 232
Co-requisites: NONE
Catalog Description
Introduction to Mathematical Programming models used in computational finance. Asset-Liability Management, Arbitrage and Asset Detection with Linear Programming, Mean-variance models with Quadratic Programming, Portfolios with Combinatorial Constraints with Mixed Integer Programming; Asset-Liability Management using Risk Measures with Stochastic Programming; Multi-period Portfolio Optimization, Binomial Pricing with Dynamic Programming; Robust Profit Opportunities in Risky Portfolios, Robust Portfolio Selection with Robust Optimization. Introduction to Mathematical Programming models used in computational finance. Asset-Liability Management, Arbitrage and Asset Detection with Linear Programming, Mean-variance models with Quadratic Programming, Portfolios with Combinatorial Constraints with Mixed Integer Programming; Asset-Liability Management using Risk Measures with Stochastic Programming; Multi-period Portfolio Optimization, Binomial Pricing with Dynamic Programming; Robust Profit Opportunities in Risky Portfolios, Robust Portfolio Selection with Robust Optimization.
Course Objectives

The main objective of this course is to introduce useful optimization models with emphasis on financial applications.

Course Learning Outcomes

1. Use Linear Programming for Asset-Liability Management, Arbitrage and Asset Detection (c),
2. Solve Mean-variance models via Quadratic Programming (c),
3. Formulate Mixed lnteger Programming Portfolio models with Combinatorial Constraints (c, i), 4. Construct Stochastic Programming models ta solve Asset-Liability Management problems with appropriate Risk Measures (c, h),
5. Develop Dynamic Programming models for Multi-period Portfolio Optimization (e),
6. Price options with binomial lattice model (e, i),
7. Detect profit opportunities in risky portfo]ios, and select optimal portfolios (c, h).

Course Coordinator:
Çağrı Latifoğlu