Modelling of Financial and Energy Markets Data

3 credits · Graduate Programs

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.