Another year has passed and now its time to discuss what happened in this cycle, along with future projects.
Year 2023 passed by very quickly, and I’m grateful for everything I’ve learned and experienced. Here are the highlights from my work.
Highlights of 2023 and 2022 Academic Papers I co-authored a single academic papers during this period:
What is the sustainable withdraw rate for Brazil? However, many papers are ready (or almost ready) for submission. I expect that 2024 will be a year with many publications.
Books I revised book Analyzing Financial and Economic Data with R for its second edition.
Back in 2020 I started to compile and share financial data in dataverse. The data covers corporate finance events from the DFP and FRE systems. The available tables are the same I use for my research and teaching material, and will be updated once a year.
Today I updated all datasets. The available data are:
R Package Source of Data Description Direct Link Last Update GetTDData Tesouro Nacional Prices and yields of brazilian sovereign bonds Link 2023-04-18 GetFREData CVM Corporate dataset from FRE systems Link 2023-04-18 GetDFPData2 CVM Annual Financial Reports from DFP system Link 2023-04-18
It is with great pleasure that I announce the third edition of “Analyzing Financial and Economic Data with R”. This work is an international edition of my R book and a lifelong project. My plan is to keep improving the content as much as possible over the next years. I’m happy to see that, just like good wine, the content of the book only gets better with time.
Besides the usual revision and improvement of the text, here are the main changes:
New pipeline operator A new pipeline operator (|>) was introduced in R version 4.
The third edition of Analyzing Financial and Economic Data with R provides a total of 98 end-of-chapter exercises. All activities are freely available in the exams format, meaning that any R tutor can export the same exercises and solutions to use in their own class. In this post I’ll show how to compile exercises to pdf, html, Moodle and blackboard.
Installation The first step is to install package afedR3 with devtools:
if (!require(devtools)) install.packages('devtools') devtools::install_github('msperlin/afedR3') Another requirement is a working Latex instalation. For that, use tinytex:
tinytex::install_tinytex() Compiling Exercises How it works?
Every end of year I write about what happened during the yearly cycle and what’s to come.
This year was very special and impactful for me. I learned a lot about myself, about what I do and why. Here are the highlights.
Highlights of 2022 and 2021 Academic Papers I published and co-authored several academic papers during this period:
What drives the release of material facts for Brazilian stocks? The Academic Inbreeding Controversy: Analysis and Evidence from Brazil Board gender diversity: performance and risk of Brazilian firms O Impacto da Titulação Acadêmica de Conselheiros e Diretores sobre a Performance de Empresas Negociadas na B3 Books The first edition of book Visualização de Dados com o R was published in October 2022.
It is with great pleasure that I officially announce the publication of my book Visualização de Dados com o R. The content of the book is an extension of chapter 10 of afedR. The book is written in portuguese and available at Amazon and online:
ebook paperback hardcover Online version (chapters 01-03) You can find more details in its own blog page.
Back in 2020 I started to compile and share financial data in dataverse. The data covers corporate finance events from the DFP and FRE systems. The available tables are the same I use for my research and teaching material, and will be updated once a year.
Today I updated all datasets. The available data are:
R Package Source of Data Description Direct Link Last Update GetTDData Tesouro Nacional Prices and yields of brazilian sovereign bonds Link 2022-04-06 GetFREData CVM Corporate dataset from FRE systems Link 2022-04-06 GetDFPData2 CVM Annual Financial Reports from DFP system Link 2022-04-06
Package BatchGetSymbols facilitates importation of Yahoo Finance data directly into R and is one of my most popular R packages, with over 100k installations since conception (around 2500 downloads per month). However, I developed BatchGetSymbols back in 2016, with many bad structural choices from my part.
For years I wanted to improved the code but always restrained myself because I did not want to mess up the execution of other people’s code that was based on BatchGetSymbols. In order to implement all the breaking changes and move forward with the package, I decided to develop a new (and fresh) package called yfR.
Hadley Wickham recently released an online version of Mastering Shiny. The book is great! If you haven’t read it, do it fast! On a side note, it is really amazing how much of good and curated content you can get for free in R. When I started programming back in 2007, the first step was buying a brand new – and sometimes expensive – book about the language. There were blogs and other sites, but most content was very basic and not curated, meaning that the posted code most of the time did not work.
Back in 2020 I started to compile and share financial data in dataverse. The data covers corporate finance events from the DFP and FRE systems. The available tables are the same I use for my research and teaching material, and will be updated once a year.
Today I updated all datasets. The available data are:
R Package Source of Data Description Direct Link Last Update GetTDData Tesouro Nacional Prices and yields of brazilian sovereign bonds Link 2021-04-09 GetFREData CVM Corporate dataset from FRE systems Link 2021-04-09 BatchGetSymbols Yahoo Finance Daily adjusted and unadjusted prices and trading volumes of stocks Link 2021-04-09 GetDFPData2 CVM Annual Financial Reports from DFP system Link 2021-04-09