with quantmod

Author

Tony Duan

This document provides a guide to sourcing and analyzing financial data in R. We will explore several packages that provide access to financial data from various sources, including Yahoo Finance and Quandl. We will also demonstrate how to use these packages to retrieve stock prices and financial statements, and how to visualize the data using plotly.

Code 
pak::pak(c("Quandl"))
Code 
# Load necessary libraries
library(quantmod)
library(tidyverse)
library(yahoofinancer)
library(Quandl)
library(plotly)
#library(finreportr)
library(rvest)
library(chromote)
library(httr)
library(janitor)
library(knitr)

1. Retrieving Stock Prices

There are several packages available for retrieving stock price data in R. We will explore two popular options: quantmod and yahoofinancer.

Using yahoofinancer

The yahoofinancer package provides a simple and intuitive interface for retrieving data from Yahoo Finance.

Retrieving Index Data

Here, we retrieve the historical data for the NIFTY 50 index (^NSEI). We then normalize the adjusted close price to compare its performance with other assets.

Code 
nifty_50 <- Index$new('^NSEI')

data001 = nifty_50$get_history(start = '2023-01-01', interval = '1d') %>% unnest(cols = adj_close)

a = head(data001$adj_close, 1)[[1]]

data001b = data001 %>% mutate(adj_close2 = adj_close / a)

Retrieving Stock Data

Similarly, we can retrieve the historical data for an individual stock, such as Apple Inc. (AAPL).

Code 
aapl <- Ticker$new('aapl')

data002 = aapl$get_history(start = '2023-01-01', interval = '1d') %>% mutate(adj_close = as.numeric(adj_close))

a = head(data002$adj_close, 1)[[1]]

data002b = data002 %>% mutate(adj_close2 = adj_close / a)

Visualizing Stock Prices

We can use plotly to create an interactive chart comparing the normalized performance of the NIFTY 50 and Apple stock.

Code 
# Initialize plot
fig <- plot_ly()

# Add data from the first dataframe
fig <- fig %>%
    add_lines(data = data001b, name = "NSEI50", x = ~date, y = ~adj_close2)

# Add data from the second dataframe
fig <- fig %>%
    add_lines(data = data002b, name = "Apple", x = ~date, y = ~adj_close2)

# Show figure
fig

2. Other Packages for Financial Data

quantmod

The quantmod package is another popular choice for financial data analysis in R. It provides a wide range of functions for retrieving, analyzing, and visualizing financial data.

finreportr

The finreportr package provides functions for retrieving financial reports from the SEC’s EDGAR database.

Quandl

The Quandl package provides access to a vast collection of financial and economic data from the Quandl platform.

3. Conclusion and Further Resources

This document has provided an overview of how to source and analyze financial data in R using various packages. By leveraging these tools, you can easily retrieve and analyze a wide range of financial data to inform your investment decisions.

For more information, please refer to the following resources:

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