2018 Special lectures on advanced topics in Mathematics Q

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Academic unit or major
Graduate major in Mathematics
Instructor(s)
Ninomiya Syoiti 
Course component(s)
Lecture
Mode of instruction
 
Day/Period(Room No.)
Intensive ()  
Group
-
Course number
MTH.E440
Credits
2
Academic year
2018
Offered quarter
2Q
Syllabus updated
2018/6/26
Lecture notes updated
-
Language used
Japanese
Access Index

Course description and aims

Algorithmic trading is now widely utilized in the worldwide financial market. This lecture is about that. I will narrate the microstructure of investments and trading from rather a practitioner's point of view, and then examine the mathematical techniques used there one by one.

Students are expected to learn what sort of mathematical techniques are used through examples about alpha identification, strategy building and system integration in the real financial markets.

Student learning outcomes

・Understand algorithmic trading in a practical way
・Understand mathematical techniques used in alpha integration and strategy building
・Understand techniques required when building automatic trading systems

Keywords

algorithmic trading, high-frequency trading, alpha

Competencies that will be developed

Specialist skills Intercultural skills Communication skills Critical thinking skills Practical and/or problem-solving skills

Class flow

This is a standard lecture course. There will be some assignments.

Course schedule/Required learning

  Course schedule Required learning
Class 1 ・Market micro structure Details will be provided during each class
Class 2 ・Mathematics of strategies Details will be provided during each class
Class 3 ・Mathematics of alpha Details will be provided during each class
Class 4 ・Mathematics behind some financial events Details will be provided during each class
Class 5 ・ Related topics Details will be provided during each class

Textbook(s)

Adachi, T., "Algorithmic Trading", Asakura, ISBN978-4-254-27584-1 (in Japanese)

Assessment criteria and methods

Assignments (100%).

Related courses

  • MTH.C361 : Probability Theory
  • MTH.C507 : Advanced topics in Analysis G1
  • MTH.C508 : Advanced topics in Analysis H1

Prerequisites (i.e., required knowledge, skills, courses, etc.)

None in particular

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