Course Syllabus

Course Information：

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Fall Semester Year 2026	362123	Introduction to Financial Engineering	1	3.0	3	★	Liu, Liang-chih	4IFM3	49	0

Course Plan：

Instructor	Liu, Liang-chih　Office Hours
Email	lcliu@ntut.edu.tw
Last Updated	2026-06-17 08:19:04
Course Objective	This course will shed light on the methodology for evaluating derivatives, hedging and managing investment risk. The pricing algorithm will be implemented in C language and Matlab. The problems that will be dealt with include the approximation of internal rates of returns via the bisection and Newton method, and the calculation of spot rate curves via the bootstrap method.
Course Schedule	Week 1 : Course Introduction and Preliminary Week 2 : The Tool for Coding C Language and MATLAB Week 3 : If /Else Structure and For/While Loop Week 4 : Cash Flow Evaluation / Bisection and Newton Method-1 Week 5 : Cash Flow Evaluation / Bisection and Newton Method-2 Week 6 : Cash Flow Evaluation / Bisection and Newton Method-3 Week 7 : Cash Flow Evaluation / Bisection and Newton Method-4 Week 8 : Arrays Week 9: Introduction to Interest Rates / Bootstrap Method-1 Week 10: Introduction to Interest Rates / Bootstrap Method-2 Week 11: Introduction to Interest Rates / Bootstrap Method-3 Week 12: Introduction to Interest Rates / Bootstrap Method-4 Week 13: Bond Price Volatility and Hedge-1 Week 14: Bond Price Volatility and Hedge-2 Week 15: Bond Price Volatility and Hedge-3 Week 16: Final Exam Week 17+18: Course Review
Evaluation and grading policy	Exercise: 60% (A 40% score deduction for late submission) Take Home Mid-Term Exercise: 10% Final Exam: 30% Participation in Weeks 17 and 18 will earn 2 additional points for the final course score (maximum final grade: 99)..
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:No Options, Futures, and Other Derivatives, by J. C. Hull, 8TH Edition, Prentice Hall
The access to curricular consultation	You can contact me in the office hours (announced later) in Room 433 in Technology Building
Expanding teaching and resources	● 參與式創新教學 (Participatory & Innovative Teaching) 強調學生參與與產出，導入翻轉、PBL/專題、設計思考或遊戲化等策略。 Emphasizes student engagement and outcomes by adopting strategies such as Flipped Classroom, PBL (Problem/Project- Based Learning), Design Thinking, or Gamification.
The course corresponds to the SDGs	SDG4：優質教育（Quality Education） SDG9：產業創新與基礎設施（Industry, Innovation and Infrastructure）
Does the course incorporate AI	● 鼓勵學生使用生成式AI工具（Encourage students to use generative AI tools）
Note	Weeks 17&18 Flexible Learning Week Arrangement: (1) Category: Others - Detailed review of all assignments and examination questions. (2) Content: Week 17: Go through the solutions to the Final Exam questions. Week 18: Review all assigned exercises, together with the Midterm Exercise in detail. (3) Total hours: 6 hours (4) Learning outcome: Students will develop a complete understanding of the underlying logic behind each exercise and exam problem. (5) Assessment weight: Participation in this activity earns 2 bonus points (maximum final grade: 99).