Fetching Stock Data for Fundamental Analysis

The project relies on data provided by gurufocus.com and tipranks.com

This webscraping toolset provides functionalities for easily gathering stock data for up to the last five fiscal years.

📚 Extensive data for 6.000+ unique listings.
📅 Data for the company's last five fiscal years and current years TTM value.
♻️ Convenient merging-abilities for updating past scraping results.

Installation

# Github Download 'quant'-package (dev version)
devtools::github_install('OliverHennhoefer/quant')

Application

df <- data.frame("symbol" = c("AAPL", "MSFT", "BABA"))

# Diluted Earnings per Share
df %>%
  get_diluted_eps() 
  
>   Symbol EPS_2017 EPS_2018  EPS_2019  EPS_2020  EPS_2021  EPS_TTM
  1 AAPL   2.30    2.98       2.97      3.28      5.61      6.04
  2 BABA   2.46    3.88       4.97      7.97      8.40      3.74
  3 MSFT   3.25    2.13       5.06      5.76      8.05      9.39

Easily fetch several data for the most common financial measures or even more uncustomary ratios:

df <- data.frame("symbol" = c("AAPL", "MSFT", "BABA"))

# GICS Sectors, Profitability Rank, Probability of Financial Distress 
df %>%
  get_sectors() %>%
  get_profitability %>%
  get_financial_distress
  
>   Symbol Sector             Subsector         Fin.Distress  Profitability  
  1 AAPL   Technology         Hardware          0.02          10
  2 BABA   Consumer Cyclical  Retail - Cyclical 0.29          9                                 
  3 MSFT   Technology         Software          0.03          10

jslearn81/quant

Fetching Stock Data for Fundamental Analysis

Installation

Application