Assessment and support

How is assessment different here?

Traditional exams measure recall. Here, assessment is an ongoing test of your ability to defend methods, critique models, and adapt when the numbers don’t add up. Module assignments use live data, so every task has room for ambiguity—and error.

The final project asks you to build, test, and explain a volatility forecasting model in a market of your choice. You’re not just submitting a solution; you’re exposing your process to feedback from both faculty and peers. Mistakes are not penalized—they’re a learning requirement.

No multiple choice. No hidden grading curve. Just the data and your judgment.

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Assessment at a glance

Assessment is designed to mirror real-world uncertainty and scrutiny, not rote learning.

  • Module tasks: reports, critiques, and forecasts
  • Bi-weekly deadlines, fully online
  • Peer review and open feedback
  • Final project using real-world data
  • Faculty with applied analytics experience
  • Transparent grading and moderation
  • Distinction for outstanding contributions

Assessment: what actually happens?

Module assessments in detail

Forget one-size-fits-all testing. Module assessments include technical critiques, live data forecasting, and peer-reviewed reports. The result: you’re judged by your reasoning, not your ability to memorize formulas.
  • Assessment types: Technical write-ups, case reviews, data clinics, and scenario-based tasks.

The final project

The final project is where theory meets accountability. You select a market, build a forecasting model using real datasets, and defend your choices. Feedback is direct—mistakes are not just allowed, they're expected.
  • Final project: Build and present a model using your chosen data and methodology.

Feedback and support

No model is perfect, and neither is our feedback. Expect faculty to question your assumptions, highlight blind spots, and push for evidence over opinion. Peer reviews mirror real-world scrutiny: everyone is both judge and judged.
Learning support overview

Distinction and academic awards

Distinction isn’t handed out for showing up. To stand out, your project must impress both faculty and peers, with clear reasoning and robust evidence. Recognition goes to those who contribute new perspectives or challenge established assumptions.
  • Distinction: Awarded for exceptional final projects and peer feedback.
  • Faculty recognition: Select work may be highlighted in technical forums.
View a sample lecture for a taste of the assessment style.
The final project wasn’t about being right. It was about proving every assumption—and defending them when challenged. The feedback was frank, sometimes uncomfortable, and always valuable.
Paige Stewart Financial Modelling Specialist – North American Consulting
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