Python for Finance (PFF)
Área
AC Gestão > UC Mestrados
Activa nos planos curriculares
Finance > Finance > 2º Ciclo > Unidades Curriculares Optativas > Optional Course 1 > Python for Finance
Nível
2º Ciclo (M)
Tipo
Estruturante
Regime
Semestral
Carga Horária
Aula Teórica (T): 0.0 h/semana
Aula TeoricoPrática (TP): 2.0 h/semana
Trabalho Autónomo: 48.0 h/semestre
Créditos ECTS: 0.0
Objectivos
Python has become one of the most important programming languages for professional finance worldwide. This workshop intends to present and to practice Python basic components and features together with several practical examples of Python applications related to finance. It will be presented mainly through exercises to practice during classes. Students are encouraged to bring their laptops to classes and practise ongoing exercises. At the end, students will be able to develop basic Python applications with Data Extraction, Data Analysis and Data Output features.
Programa
1?Basics 1
.Python Language History and Overview
.Python Installation, Interpreters and Versions
.Variables
2?Basics 2
.Functions and Loops
.Data and Variable Types
.Data Input and Output
3?Modules 1
.Python Modules?general view
.Python Module installation
.Numpy
.SciPy
4?Modules 2
.Matplotlib
.Statsmodels
.Pandas
.Other useful Python modules for finance
5?Sources of Data, Extracting Output Data
.Sources of Data
.From Financial APIs
.From Excel file
.Extracting Output Data
.to a text file
.to a .csv file
.to a Excel file
.Using Pandas DataFrame
6?
.Special DataSets-Dictionaries
.Financial Applications A-Examples
.NPV and IRR
.Stock Price Movements, Return Distributions
7?Financial Applications
.Financial Applications B-Examples
.Bond Valuation
.CAPM?computing beta
.Time Series Analysis
.Portfolio Theory
8?Financial Applications?C
.Options
.VaR and Expected Shortfall
.Monte Carlo Simulation
Metodologia de avaliação
Brief presentation of Python main concepts, features and modules as well as its proper installation. Practical exercises during classes to be performed by teacher and students in their laptops will be the main methodology in order to achieve workshop learning objectives. Final qualitative evaluation will consist on the development of a financial application by each one of the students to be delivered at the end of the Workshop.
Bibliografia
Principal
Python for Finance
Yan, Yuxing
2017
2th Ed, Packt
Python for Finance
Hilpisch, Yves
2015
1st Ed, O´Reilly
Secundária
Não existem referências bibliográficas secundárias.