Modelling and Data Analysis I

Code:

2MiF08

Acronym:

MDA 1

Keywords
Classification	Keyword
OFICIAL	Management Studies

Instance: 2022/2023 - 2S

Active?	Yes
Course/CS Responsible:	Master in Finance

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
MIF	51	Official Syllabus after 2020-2021	1	-	3	21	81

Teaching language

English

Objectives

The course aims to develop the skills to use and program in some of the most important software for modeling and data analysis.

Learning outcomes and competences

• Implement programs for the analysis, characterization and comparison of financial data.


• Build algorithms to simulate financial models.


• Develop critical thinking in data analysis and simulation results.

Working method

Presencial

Program

Introduction;
Modules:

1. Tools:




1. Jupyter working environment;


2. Markdown markup (text format);


3. programming in Python;


4. programming in R




2. Modelling and Simulation




1. Economic and Financial models;




3. Data Analysis, introduction to Big Data Analysis.

Mandatory literature

Yves Hilpisch; Python for Finance: Analyze Big Financial Data, O'Reilly, 2014. ISBN: 9781491945285
Clifford Ang; Analyzing Financial Data and Implementing Financial Models Using R, Springer, 2015. ISBN: 978-3-319-14075-9

Teaching methods and learning activities

The course is organized in lab sessions, based on modules. The teaching methodology in each module is structured as follows:

• description of the financial problem to solve;


• identification with explanation of the appropriate computacional methods for their resolution;


• exercises and simulation (sedimentation and knowledge exploitation).

Software

Jupyter
Python
R

Evaluation Type

Distributed evaluation without final exam

Assessment Components

Designation	Weight (%)
Apresentação/discussão de um trabalho científico	20,00
Teste	30,00
Trabalho prático ou de projeto	50,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Estudo autónomo	45,00
Frequência das aulas	21,00
Trabalho escrito	15,00
Total:	81,00

Eligibility for exams

According to the General Regulation for the Assessment of First Degreeand Master’s Degree students at the School of Economics and Management of the University of Porto all students enrolled in a course unit fulfill attendance requirements. (article 10th point 5)

Calculation formula of final grade

30% individual assessment + 70% group work