Overview
This course develops quantitative methods for analysing commodity markets and supporting evidence-based decisions in trading, procurement, hedging, and investment. Topics include algebra, functions, logarithms, percentages, indices, descriptive statistics, probability, correlation, regression, time-series fundamentals, price returns, volatility, seasonality, moving averages, and introductory forecasting.
Students obtain, clean, structure, visualise, and interpret market data from energy, metals, agricultural products, freight, inventories, exchange rates, and interest rates. Practical work uses spreadsheets and introductory statistical or programming tools to distinguish nominal from real prices, assess relationships between variables, identify sampling limitations and spurious correlation, evaluate forecast uncertainty, and communicate quantitative findings to commercial and nontechnical audiences.
Learning Outcomes
- Construct and validate quantitative datasets using commodity prices, inventories, freight rates, exchange rates, and interest rates.
- Apply algebraic, logarithmic, percentage, index-number, and return calculations to commodity-market data.
- Calculate and interpret descriptive statistics, probability measures, volatility, and seasonal patterns.
- Visualise market data and communicate quantitative findings accurately to commercial and nontechnical audiences.
- Evaluate correlation and regression results, including assumptions, sampling limitations, and risks of spurious correlation.
- Apply moving averages and introductory time-series methods to generate and interpret commodity-price forecasts.
- Assess forecast uncertainty, model limitations, and the implications of quantitative evidence for trading, procurement, hedging, and investment decisions.
Timetable
| Type | Length | Frequency | Period |
|---|---|---|---|
| Lecture | 2 hours | Weekly | All semester |
| Lab | 2 hours | Weekly | All semester |
| Tutorial | 1 hour | Fortnightly | All semester |
Assessment Schedule
| Type | Description | Weighting |
|---|---|---|
| Assignment | Data construction and visualisation assignment | 15.00% |
| Quiz | Quantitative methods quizzes (5 × 2%) | 10.00% |
| Test | Mid-semester quantitative methods test | 20.00% |
| Assignment | Correlation, regression, and market relationships assignment | 20.00% |
| Deliverable | Forecasting and uncertainty analysis | 15.00% |
| Exam | Final examination | 20.00% |
Prerequisites
- Requirement 12 NCEA Level 2 Mathematics credits, externally assessed
Teaching Staff & Programs
This course is delivered jointly by faculty from the participating programs listed below. In line with the Douchewater Way, the University of Sexology tailors core instruction directly to each cohort's specific discipline — adapting curriculum to program needs rather than forcing students into a one-size-fits-all model. Learn more about our approach at The Douchewater Way.
