GetDFPData is an academic project to provide free and unrestricted access to financial reports from B3, the brazilian exchange. Back in 2020 I split the code of GetDFDData into two distinct packages: GetDFPData2 and GetFREData. In short, I’ve found a new data source at CVM (comissão valores mobiliários) that is much easier to work than B3’s site. While the code in GetDFPData2 is becoming stable and will soon be released in CRAN, the shiny app was missing this important update.
Finally got some free time to work on the shinny app once again.
The revised second edition of Analylzing Financial and Economic Data with R presents more than 100 exercises at the end section of all chapters. All exercises are freely available in the exams format, meaning that any R tutor can export the same exercises to pdf, html or e-learning platforms. In this post I’ll show how to compile exercises to pdf, html, Moodle and blackboard.
Installation The first step is to install package afedR with devtools:
devtools::install_github('msperlin/afedR') Another requirement is a working Latex instalation. For that, use tinytex:
tinytex::install_tinytex() Compiling Exercises How it works?
I recently launched the third edition of my portuguese R book (adfeR-pt-br), with many due changes from the international version (afedR-en). To make it clear, the second edition of afedR (en) was ahead in content and the third edition of adfeR (pt-br) closed that gap.
But, as it usually is with a time evolving platform such as R, the code in afedR-en changed with the deprecation and arrival of new functions and packages. In order to keep the content up to date, I published a revision of the book in Amazon and its web version.
É com muito prazer que comunico o lançamento oficial da terceira edição do livro Análise de Dados Financeiros e Econômicos com o R. Encontrarás a obra na Amazon.com.br como um ebook ou livro impresso. A versão online do livro com os primeiros sete capítulos está disponível neste link. Maiores detalhes, incluindo material suplementar, encontram-se na página do livro.
A primeira edição foi lançada em 2016 e, desde então, venho atualizando o conteúdo com novos pacotes e novos capítulos. A terceira edição contempla as seguintes mudanças:
Todo o conteúdo do livro agora é disponibilizado via pacote adfeR – link github – facilitando muito a reprodução de todos os exemplos de código.
A terceira edição do livro Análise de Dados Financeiros e Econômicos contém mais de 100 exercícios de final de capítulo, com todas soluções disponíveis na página do livro. Alternativamente, professores e instrutores podem compilar arquivos pdf dos exercícios para seus alunos com o pacote adfeR.
O primeiro passo é instalar o pacote via devtools e também o exams:
devtools::install_github('msperlin/adfeR') Outro requisito é a instalação do tinytex e Latex/texlive para a compilação em pdf:
tinytex::install_tinytex() Como funciona? Todos exercícios do livro estão no formato do pacote exams. Cada exercício é um arquivo .
Wow, what a long year! The pandemic affected everyone, changing the way we live and relate to one another. This was a year full of lessons and we must be thankful and be able to appreciate life even more. Events such as these show how little our “problems” are when put into perspective.
I’m lucky that, despite the lockdown, I was able to work from home this year. Lets have a look at the highlights.
Highlights of 2020 Academic Papers This year I published and co-authored two academic papers:
Back in 2017 I wrote the first version of package GetDFPData, along with a paper describing the code and providing an empirical application.
However, maintaining the package over the years has been frustrating. The code is becoming increasingly complex, much due to the fact that it handles FRE and DFP data in a single package. Execution speed for large scale importation – many years and many companies – is not reasonable. In top of that, B3’s website is unstable as a source of data and it seems it will stay like that for a long time.
2020-07-22 Update: The final version of the paper is now published at RAC.
Back in May 2020, I started to work on a new paper regarding the use of Garch models in R. Today we finished the peer review process and finally got a final version of the article and code. I’m glad to report that the content improved significantly.
In a nutshell, the paper motivates GARCH models and presents an empirical application using R: given the recent COVID-19 crisis, we investigate the likelihood of Ibovespa index reach its peak value once again in the upcoming years.
Myself and Henrique Martins (PUC Rio) organized a call for papers on data reuse, for publication in RAC – Revista de Administração Contemporanea. The deadline for submission is 10th october 2020, with expected publication date in july 2021.
We will select quality papers that use data already published and shared in other scientific outlet to test new theories or present a tutorial article, helping students see how an econometric result was achieved in practice.
You can find more details about this call for papers in this pdf file. I encourage everyone to submit their work.
I’ve been researching financial data for over 10 years and gathered a great deal of compiled tables. Most of these comes from my R packages and have been used for creating class material, doing research and even writing a book. These files were mostly found in many copies across different projects.
Last week I started to organize and centralize all my data files and noticed how valuable these tables could be for other researchers and teachers.
As of today, I’ll be hosting all public compiled data in my dataverse website.