market_payouts

Given a data frame of companies (names and tickers) and a data frame of 
financial statements, calculates EISS, DISS, NPOP and determines the 
z-score of overall payout for each company based on the paper Quality 
Minus Junk (Asness et al.) in Appendix page A3-4.

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_payouts function

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

Arguments

<ul>
<li><code>market_payouts()</code>: Returns all rows in x that aren't in y,
where x and y are data frames.</li>
</ul>

Functions

Collects payout z-scores for companies — market_payouts

<dl>

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


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

</dl>

market_payouts: Collects payout z-scores for companies

Description

Usage

Value

Arguments

Functions

See Also

Examples