REMF37-Quantitative Techniques

Module Provider: Real Estate and Planning
Number of credits: 20 [10 ECTS credits]
Level:7
Terms in which taught: Autumn term module
Pre-requisites:
Non-modular pre-requisites:
Co-requisites:
Modules excluded:
Current from: 2022/3

Module Convenor: Dr Yiquan Gu
Email: yiquan.gu@henley.reading.ac.uk

Type of module:

Summary module description:

The module covers quantitative techniques and methods and their applications in the context of real estate. It aims to provide students with knowledge in statistics and econometric modelling with a focus on real estate data. This module will also introduce statistical software.

Aims:

The module aims to provide students with a comprehensive introduction to quantitative techniques and methods, and their use and application in the context of real estate investment. The module will cover a wide range of core econometric topics. Case studies from the academic literature are employed to demonstrate the potential uses of each approach in both a general finance and specific real estate context. Extensive use is also made of econometric software to demonstrate the application of the techniques in practice.

Assessable learning outcomes:

 

The module introduces contemporary statistical and econometric techniques. The importance of the unique characteristics of property markets will be emphasised, as well as their impacts upon the nature of applied quantitative analysis. Upon completion of the module, students should be able to: 

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  demonstrate familiarity with a range of applied statistical techniques; 

  
  


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  understand concepts relating to econometric modelling; 

  
  


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  understand the application and the use of quantitative methods with real estate data; 

  
  


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  critically discuss the core issues relating to investment-based quantitative techniques concerning risk and return and portfolio analysis; 

  
  

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  evaluate the outcome of empirical research.

  
  

Additional outcomes:

The module will aid students in developing their technical and quantitative skills. It will also enhance students’ ability to analyse the economic and investment environments of real estate markets. 

Outline content:

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  Simple linear regression 

  
  


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  Hypothesis testing 

  
  


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  Multiple regression: The Classical Linear Regression Model (CLRM) 

  
  

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  Violations of the CLRM assumptions and diagnosis

  
  


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  Seasonality, parameter stability tests

  
  


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  Panel data

  
  

Global context:

This module may incorporate international situations and examples. 

Brief description of teaching and learning methods:

Contact hours:

	Autumn	Spring	Summer
Lectures	20
Tutorials	9
Guided independent study:
Wider reading (independent)	40
Wider reading (directed)	60
Exam revision/preparation	41
Preparation for tutorials	30
Total hours by term	200	0	0
Total hours for module	200

Summative Assessment Methods:

Method	Percentage
Written exam	60
Written assignment including essay	40

Summative assessment- Examinations:

One two-hour examination 

Summative assessment- Coursework and in-class tests:

Individual written assignment comprising approximately 2,000 words to be submitted in week 16 of the autumn term. 

Formative assessment methods:

For the computer workshops a range of datasets will be used to explain concepts, methods and tests presented in the lectures. 

Penalties for late submission:

Penalties for late submission on this module are in accordance with the University policy. Please refer to page 5 of the Postgraduate Guide to Assessment for further information: http://www.reading.ac.uk/internal/exams/student/exa-guidePG.aspx

Assessment requirements for a pass:
The pass-mark for this module is 50%.

Reassessment arrangements:

By examination only, in a two-hour exam (100%), as part of the overall examination arrangements for the MSc programme.

Re-sit examination to be taken in August/September.

Additional Costs (specified where applicable):

1. Required text book: Approximately £50

2. Specialist equipment or materials: Approximately £40

 

Last updated: 24 November 2022