market_profitability

Given a data frame of companies (names and tickers) and
a data frame of financial statements, calculates GPOA, 
ROE, ROA, CFOA, GMAR, ACC and determines the z-score of 
overall profitability for each company based on the paper 
Quality Minus Junk (Asness et al.) in Appendix page A2.

Produces quality scores for each of the US companies from
the Russell 3000, following the approach described in
"Quality Minus Junk" (Asness, Frazzini, & Pedersen, 2013)
<http://www.aqr.com/library/working-papers/quality-minus-junk>.
The package includes datasets for users who wish to view the most recently
uploaded quality scores. It also provides tools to automatically gather
relevant financials and stock price information, allowing users to update
their data and customize their universe for further analysis.

Yanrong Song

Quality Scores for the Russell 3000

Anthoney Tsou

Eugene Choe

David Kane

Ryan Kwon

Zijie Zhu

market_profitability function

<dl><dt>companies</dt>
<dd>A data frame of company names and tickers.
Requires a 'ticker' column. Defaults to provided companies
data set.</dd>
<dt>financials</dt>
<dd>A data frame containing financial 
statements for every company. Defaults to provided
financial data set.</dd></dl>

Arguments

Collects profitability z-scores for companies — market_profitability

<dl>

<dt>companies</dt>
<dd>A data frame of company names and tickers.
Requires a 'ticker' column. Defaults to provided companies
data set.</dd>


<dt>financials</dt>
<dd>A data frame containing financial 
statements for every company. Defaults to provided
financial data set.</dd>

</dl>

market_profitability: Collects profitability z-scores for companies

Description

Usage

Value

Arguments

See Also

Examples