Unit COMPUTER LAB 2
- Course
- Finance and quantitative methods for economics
- Study-unit Code
- 20A00008
- Location
- PERUGIA
- Curriculum
- Finanza ed assicurazione
- Teacher
- Gianna Figa' Talamanca
- Teachers
-
- Gianna Figa' Talamanca
- Hours
- 21 ore - Gianna Figa' Talamanca
- CFU
- 3
- Course Regulation
- Coorte 2019
- Offered
- 2020/21
- Learning activities
- Altro
- Area
- Altre conoscenze utili per l'inserimento nel mondo del lavoro
- Academic discipline
- NN
- Type of study-unit
- Obbligatorio (Required)
- Type of learning activities
- Attività formativa monodisciplinare
- Language of instruction
- Italian
- Contents
- A brief course in Matlab whith special focus on financial applications
- Reference texts
- Business Economics and Finance with MATLAB, GIS, and Simulation Models,
Anderson, Patrck, L.
Editore: Taylor & Francis Ltd, 2004.
Online Matlab documentation - Educational objectives
- Provide students with the ability of code programming in Matlab based on mathematical and statistical functions for the simulation and estimation of financial models.
- Prerequisites
- Basic calculus, financial mathematics and statistics
- Teaching methods
- Lab classes and homeworks
- Learning verification modality
- Written/Lab test and homeworks evaluation
- Extended program
- 1. Basic
a. Matlab layout
b. Variables, numbers and formats
c. Variables and logical
d. Predefined functions
e. Saving and loading the workspace
2. Input/Output
a. Reading/writing data
b. Reading/writing Excel data
c. 2-D graphics
d. Type of graphics
f. Multiple graphs
g. Handling graphs
3. Array and matrices
a. Building matrices manually
b. Functions to get information on matrices
c. Extractin of a part of matrix
d. Matrix manipulation functions
e. Matrix operations
4. Scripts and functions
a. Purposes and differences
c. inline functions and functions of functions
d. Cycles (for,while)
e. Condistional structures (if, switch)
5. Randon numbers generations
a.Fundamentals
b. Generating from a uniform random variable
c. Generating from a normal random variable
d. Generating from a multivariate normal random variable
6. Performance optimization
a. Diagnosis tools for time masurament
b. Using functions
c. Pre-allocating memory