DATA609
Download as PDF
Modelling of Financial and Energy Markets Data
Computer Science
SC - Faculty of Science
Subject
DATA - Data Science
Description
Coverage of main tools and techniques for modelling, machine learning and statistical analysis of big data in financial and energy markets. Topics will include: a simple financial and energy market models; risk-free and risky assets data modelling; discrete-time and continuous-time financial and energy market data modelling (CRR, Black-Scholes); modelling of forwards, futures, swaps in financial and energy markets; risk-neutral valuation, options, option pricing with financial and energy markets data; world energy data trends-crude oil, natural gas, and electricity; renewable energy data modelling: wind, solar, etc.
Prerequisite(s): Data Science 601, 602, 603 and 604, and admission to the Graduate Diploma in Data Science and Analytics or the Master of Data Science and Analytics with a specialization in Financial and Energy Markets Data Modelling.
Prerequisite(s): Data Science 601, 602, 603 and 604, and admission to the Graduate Diploma in Data Science and Analytics or the Master of Data Science and Analytics with a specialization in Financial and Energy Markets Data Modelling.
Course Attributes
Fee Rate Group(Domestic) - H, Fee Rate Group(International) -G, GFC Hours (3-0)
Courses may consist of a Lecture, Lab, Tutorial, and/or Seminar. Students will be required to register in each component that is required for the course as indicated in the schedule of classes. Practicums, internships or other experiential learning modalities are typically indicated as a Lab component.
Component
LEC
Units
3
Repeat for Credit
No
Subject code
DATA
Understanding Course Information
Please refer to Course Terminology and Description to better understand how to interpret course information such as GFC Hours, pre-requisites, course levels, etc.