SOAS University of London

School of Finance and Management

Advanced Quantitative Research Methods- not running 2019/20

Module Code:
15PFMC083
Status:
Module Not Running 2019/20
Credits:
15
Year of study:
Year 1 or Year 2

This course covers advanced topics in developing and testing theories using quantitative methods. The module consists of three parts: (1) theoretical modelling: assumptions, deriving testable hypotheses or theorems; (2) panel data analysis; (3) time series analysis. Students will learn STATA (including programming in STATA) and Openbugs (Bayesian analysis using Markov-Chain Monte-Carlo Simulations).

Lectures will introduce a broad range of topics (e.g. ARCH/GARCH). However, you will discover that by understanding and applying some basic concepts various issues can be analysed in a similar manner. In particular, we will introduce basic theoretical concepts developed in statistics and econometrics. Understanding the main theoretical methods is essential to appreciate the analytical tools and their applications in finance and management.

The purpose of this module is to provide the necessary skills to conduct panel data analysis, time series modelling and forecasting. Using problem-based learning methods, the participants apply statistical methods to analyse data. Hence, the main learning objective is to enable participants to understand and apply statistical methods using statistical software packages (STATA, Openbugs).

Objectives and learning outcomes of the module

At the end of the course, a student should be able to…

A. Knowledge and Understanding

  • Demonstrate an understanding of advanced econometric modelling
  • Develop a insights into forecasting of time series
  • Demonstrate competence in using econometric software package (STATA, Openbugs)


B. Subject Specific Intellectual (Cognitive) Skills

  • Analyse panel and time series data used in financial and management studies
  • Assess out-of-sample properties and model fit
  • Interpret statistical output
  • Critically evaluate statistical models and forecasting tools 

 
C. Transferable (Key/General) Skills

  • Develop general skills in analysing and exploring data, which can be used in other fields

Workload

Lectures
This module consists of a 2-hour weekly lecture over 10 weeks of term plus a revision lecture in term 3 as preparation for the final examination. Students will be supplied with a syllabus with a breakdown week by week of required and additional reading. Reading materials are usually accessed electronically from the BLE and students should come to class prepared.

Tutorials
This module also has a weekly 1-hour tutorial where the questions posed by the tutor relevant to the lecture are explored and discussed by the students. Students also prepare and deliver a short presentation.

Total Work load:
Students on this module will have 3 taught hours each week. Additionally, adequate personal study time should be allocated for reading and class preparation.

Method of assessment

Assessment for this module is in two elements:

  1. One essay of 4,000 words at 50%
  2. One unseen 2-hour written examination at 50%

All elements may be resubmitted.

Suggested reading

TBC

Disclaimer

Important notice regarding changes to programmes and modules