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FI5440 Applied Financial Econometrics

Academic year

2025 to 2026 Semester 1

Further information on which modules are specific to your programme.

Key module information

SCOTCAT credits

30

The Scottish Credit Accumulation and Transfer (SCOTCAT) system allows credits gained in Scotland to be transferred between institutions. The number of credits associated with a module gives an indication of the amount of learning effort required by the learner. European Credit Transfer System (ECTS) credits are half the value of SCOTCAT credits.

SCQF level

SCQF level 11

The Scottish Credit and Qualifications Framework (SCQF) provides an indication of the complexity of award qualifications and associated learning and operates on an ascending numeric scale from Levels 1-12 with SCQF Level 10 equating to a Scottish undergraduate Honours degree.

Availability restrictions

Not available as an optional module for any programme.

Planned timetable

To be arranged.

This information is given as indicative. Timetable may change at short notice depending on room availability.

Module coordinator

Dr X Chen

Dr X Chen
This information is given as indicative. Staff involved in a module may change at short notice depending on availability and circumstances.

Module Staff

Dr Jimmy Chen

This information is given as indicative. Staff involved in a module may change at short notice depending on availability and circumstances.

Module description

The aim of this module is to equip students with econometric tools and techniques to analyse and interpret financial data. Students will learn how to organise and characterise financial and/or economic dataset (cross-section, time series, and panel data) as well as analysing it using appropriate econometric techniques. The module also develops student’s ability to estimate various econometric models and perform various tests using EViews and STATA. The final end of the module is to develop student’s ability to undertake empirical research in finance.

Relationship to other modules

Anti-requisites

YOU CANNOT TAKE THIS MODULE IF YOU TAKE EC5203

Assessment pattern

100% coursework

Re-assessment

100% coursework

Learning and teaching methods and delivery

Weekly contact

Lectures: 2 hour x 10 weeks Lab-based tutorials: 1 hour x 9 weeks

Guided independent study hours

30

The number of hours that students are expected to invest in independent study over the period of the module.

Intended learning outcomes

  • Conduct and interpret OLS regressions
  • Conduct diagnostics tests on the residual term and rectify any issues detected
  • Conduct and interpret univariate time series models, and to generate forecasts based on the estimated models.
  • Understand the concept of stationarity, perform cointegration test, and estimate error-correction model
  • Estimate and interpret conditional volatility (GARCH) models, and to perform related diagnostic tests.
  • Estimate and interpret panel regression models, and to perform related diagnostic tests.