代做AG930 Advanced Theories in Finance 2023/24调试Matlab程序

日期：2025-02-18 11:27

 

DEPARTMENT OF ACCOUNTING AND FINANCE

AG930 Advanced Theories in Finance (PhD)

2023/24

CLASS DESCRIPTION

The class examines different econometric approaches for evaluating asset pricing models.

CLASS AIMS

This course is designed for doctoral students specialising in finance and the aim is to introduce students to Asset Pricing, and the related empirical methods.  Students are expected to take this module in the first year of their doctoral (MRes) programme.

LEARNING OUTCOMES

Subject-specific knowledge and skills

On completing this class the student will have the ability to:

A.1 Understand the time-series regression approach to evaluate linear factor models.

A.2 Test linear factor models using Matlab and interpret the resulting empirical findings.

A.3 Explain the factor spanning regression tests.

A.4 Discuss the alternative econometric approaches to evaluating the performance of linear factor models.

Cognitive abilities and non-subject specific skills

During the class you will:

B.1 Develop academic skills in reading and understanding academic research papers.

B.2 Develop computational skills in undertaking empirical research through the use of Matlab in the areas covered by the class that are also applicable to other areas of Finance.

B.3 Develop analytical skills in interpreting empirical findings and recognising some of the limitations faced by empirical researchers.

B.4 Exercise independent judgement in assessing what are relevant research papers and in the evaluation of research findings.

ASSESSMENT

The modes of assessment are: 

Coursework                    100%

TEACHING AND LEARNING

The teaching and learning strategy adopted in the class to meet the learning outcomes employs a variety of approaches.  Students will learn through directed reading, independent reading, formal class contact, undertaking empirical analysis through the problem sets, and electronic resources.  

The class contact for this class will be 20 hours.

REQUIRED READING

There will also be readings from journal research articles which will be given in class.

LECTURE PROGRAMME

The following topics will be considered:

1. An introduction to linear factor models.

2. Using the time-series regression approach to evaluate linear factor models.

3. Alternative approaches to testing linear factor models.

a) Traditional

b) Generalized Method of Moments

c) Bootstrap Methods

d) Bayesian