market_data: Produces component and quality scores.

In anttsou/qmj: Quality Scores for the Russell 3000

Description

Calculates market growth, payouts, safety, and profitability of our list of companies for later processing.

Usage

market_data(companies = qmjdata::companies,
  financials = qmjdata::financials, prices = qmjdata::prices)

Arguments

companies	A data frame of company names and tickers.
financials	A data frame containing financial information for the given companies.
prices	A data frame containing the daily market closing prices and returns.

Details

All parameters default to package data sets and must be formatted similarly to a data frame produced by tidy_prices and tidyinfo.

Value

A data frame containing company names, tickers, profitability z-scores, growth z-scores, safety z-scores, payout z-scores, and quality z-scores. Organized by quality in descending order.

See Also

market_profitability

market_growth

market_safety

market_payouts

Examples

## Not run: 
## To immediately get quality scores using
## package data sets.

market_data()

## If we desire to produce a set of quality
## scores for a specific data frame of
## companies, which we'll call companies.

# Remove old temporary data, if present.
clean_downloads(companies)

# Get raw financial and price data.
raw_financials <- get_info(companies)
raw_prices <- get_prices(companies)

# Clean raw data for use in market_data.
financials <- tidyinfo(raw_financials)
prices <- tidy_prices(raw_prices)

quality_scores <- market_data(companies, financials, prices)

## End(Not run)

anttsou/qmj documentation built on May 10, 2019, 12:28 p.m.