BatchGetSymbols 2.2

One of the main requests I get for package BatchGetSymbols is to add the choice of frequency of the financial dataset. Today I finally got some time to work on it. I just posted a new version of BatchGetSymbols in CRAN. The major change is that users can now set the time frequency of the financial data: dailly, weekly, monthly or yearly. Let’s check it out: library(BatchGetSymbols) ## Loading required package: rvest ## Loading required package: xml2 ## Loading required package: dplyr ## ## Attaching package: 'dplyr' ## The following objects are masked from 'package:stats': ## ## filter, lag ## The following objects are masked from 'package:base': ## ## intersect, setdiff, setequal, union ## library(purrr) ## ## Attaching package: 'purrr' ## The following object is masked from 'package:rvest': ## ## pluck library(ggplot2) my.

Investing for the Long Run

I often get asked about how to invest in the stock market. Not surprisingly, this has been a common topic in my classes. Brazil is experiencing a big change in its financial scenario. Historically, fixed income instruments paid a large premium over the stock market and that is no longer the case. Interest rates are low, without the pressure from inflation. This means a more sustainable scenario for low-interest rates in the future. Without the premium in the fixed income market, people turn to the stock market. We can separate investors according to their horizon.

Research Awards

2018 Article “Is predatory publishing a real threat? Evidence from a large database study” in the top 5% of all research outputs scored by Altmetric. [link] Top 10% of authors on SSRN by all-time downloads. [link] Top 10% of authors on SSRN by total new downloads within the last 12 months. [link] 2016 RBFIN best paper of 2015 (Honorary mention) - Award from the Brazilian Finance Society for best paper published in the Brazilian Review of Finance for the year of 2015. Title of paper: The researchers, the publications and the journals of Finance in Brazil: An analysis based on resumes from the Lattes platform.