The aim of this module is to introduce students to the software package Matlab and to provide them with the necessary skills to utilise the software to analyse financial data. Students will be taught the usefulness of matrix algebra and how vectors and matrices can be manipulated in Matlab. Following this introduction, they will be taught how the software can be used in a number of financial applications including portfolio optimisation, testing for unit roots, cointegration and option pricing. A brief introduction to simulation will also be covered.
Module Aims
The main aims of the module are:
1) To develop and transmit knowledge about the Matlab software package and its usefulness in financial applications.
2) To give students knowledge of a number of key concepts in empirical finance and how Matlab can be used to analyse empirical data.
3) To provide students with a firm foundation for developing their own programmes in Matlab to tackle non-standard testing problems.
Learning Outcomes
After completing this module students will be able to:
1. Have an understanding of matrix algebra and how matrices and vectors can be manipulated in Matlab;
2. Import data and manipulate series in Matlab to calculate financial measures;
3. Construct an optimal or minimum variance portfolio and the efficient frontier;
4. Understand the concept of regression and perform regressions in Matlab;
5. Test for non-stationarity in financial data and examine the possibility of cointegration between one or more series;
6. Have a basic understanding of the Black-Scholes option pricing model and how option prices can be calculated using a Matlab toolbox;
7. Use loop commands in Matlab to perform multiple calculations and understand the relevance of these commands in performing Monte Carlo simulation exercises.
Skills for Your Professional Life (Transferable Skills)
By the end of this module students will be very familiar with the Matlab computer software, being able to perform basic command based operations and gaining knowledge of creating their own programmes to perform non-standard analysis. Such programming skills will be transferrable to other programming languages and are highly desirable for employers and very useful if further studies are pursued.
Module Aims
The main aims of the module are:
1) To develop and transmit knowledge about the Matlab software package and its usefulness in financial applications.
2) To give students knowledge of a number of key concepts in empirical finance and how Matlab can be used to analyse empirical data.
3) To provide students with a firm foundation for developing their own programmes in Matlab to tackle non-standard testing problems.
Learning Outcomes
After completing this module students will be able to:
1. Have an understanding of matrix algebra and how matrices and vectors can be manipulated in Matlab;
2. Import data and manipulate series in Matlab to calculate financial measures;
3. Construct an optimal or minimum variance portfolio and the efficient frontier;
4. Understand the concept of regression and perform regressions in Matlab;
5. Test for non-stationarity in financial data and examine the possibility of cointegration between one or more series;
6. Have a basic understanding of the Black-Scholes option pricing model and how option prices can be calculated using a Matlab toolbox;
7. Use loop commands in Matlab to perform multiple calculations and understand the relevance of these commands in performing Monte Carlo simulation exercises.
Skills for Your Professional Life (Transferable Skills)
By the end of this module students will be very familiar with the Matlab computer software, being able to perform basic command based operations and gaining knowledge of creating their own programmes to perform non-standard analysis. Such programming skills will be transferrable to other programming languages and are highly desirable for employers and very useful if further studies are pursued.
Category: Finance