bookdown + exams + webex

It’s been three years since I’ve been using package bookdown for compiling and distributing three different books in Amazon and the web. It helped me greatly in all my book projects and I’m always grateful to Yihui Xie for providing such a useful tool at the right time. However, bookdown offers no support for chapter exercises of any sort. While you can write exercises in plain RMarkdown, it is not a good solution for a long term project such as a technical book. When writing the latest edition of Analyzing Financial and Economical Data with R, I aimed for a work cycle where the 100 plus exercises and their solutions were reproducible and easier to maintain.

Ten years as a professor -- six advices to young academics

In the 18th of march 2021 I’ll complete exactly ten years since finishing my PhD and taking a professorship position at UFRGS, south of Brazil. In this post I’ll write about what I learned during this period and, hopefully, help other academics that are just starting out. This post is the summary of a talk I had with a former PhD student. I’m fully aware that academic work can be very different across countries and institutions. I don’t claim to have all the answers to all the problems. But, these are a couple of advice that would certainly help me in my starting years.

Update on the Shiny/Web Interface of GetDFPData2

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.

Compiling Book Exercises to pdf | html | Moodle | Blackboard

The revised second edition of Analyzing 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?

Revision of book "Analyzing Financial and Economic Data with R"

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.

LANÇAMENTO - Análise de Dados Financeiros e Econômicos com o R (Terceira Edição)

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.

Compilando Exercícios do Livro para pdf | html | Moodle | Blackboard

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 .

Looking back at 2020 and plans for 2021

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:

New Packages: GetDFPdata = GetDFPData2 + GetFREData

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.

A GARCH Tutorial in R (revised)

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.