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:
Module version for: 2017/8

Module Convenor: Dr Ranoua Bouchouicha

Email: r.bouchouicha@reading.ac.uk

Summary module description:

The module covers quantitative techniques and methods and their use in the context of real estate.


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 course 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 and its impact upon the nature of applied quantitative analysis. Upon successful completion of the module students will:

- be familiar with a range of applied statistical techniques;
- be introduced to the concepts relating to econometric modelling;
- understand the application and the use of quantitative methods with real estate data;
- understand the core issues relating to investment based quantitative techniques concerning risk and return and portfolio analysis;
- be able to 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:
- Stylised characteristics of financial and real estate data
- Classical Ordinary Least Squares Estimation and Hypothesis Testing
- Multivariate OLS and Diagnostic Testing
- Dynamic models
- Cross section models
- Introduction to Panel Data Analysis
- Stationarity and Unit Root Processes, Applications to Real Estate Modelling
- ARMA models
- Vector Autoregression, Causality, Impulse Response and Variance Decompositions

Brief description of teaching and learning methods:
The module will comprise lectures and practical computer workshops. These workshops will complement the formal lectures and provide students with the opportunity to apply the methods taught.

Contact hours:
  Autumn Spring Summer
Lectures 20
Practicals classes and workshops 10
Guided independent study 170
       
Total hours by term 200.00
       
Total hours for module 200.00

Summative Assessment Methods:
Method Percentage
Written exam 60
Written assignment including essay 40

Other information on summative assessment:

Two or three students Group written assignment comprising of a report of 4000 or 6000 words. 


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
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

Length of examination:

Two hours


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

Reassessment arrangements:

A coursework of 2000 words.


Last updated: 15 May 2017

Letter 'IPO.MODCAT1STKT' - Generation started at 15/May/2017 15:20:55.00.

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