firms_US

<p>Data on Apple (AAPL), General Motors (GM), and British American Tobacco (BTI) extracted from Yahoo! Finance (on May 20, 2023) and formatted a <code>firm</code> objects.</p>

datasets

Providing classes, methods, and functions to deal with financial networks.
Users can easily store information about both physical and legal persons by using pre-made classes that are studied for integration with scraping packages such as 'rvest' and 'RSelenium'.
Moreover, the package assists in creating various types of financial networks depending on the type of relation between its units depending on the relation under scrutiny (ownership, board interlocks, etc.), the desired tie type (valued or binary), and renders them in the most common formats (adjacency matrix, incidence matrix, edge list, 'igraph', 'network').

Fabio Ashtar Telarico

FinNet

Quickly Build and Manipulate Financial Networks

firms_US function

<p>Three objects of class <code>firm</code>.</p>

firms_US: Three US firms

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