Contact StarMine Analytical and Methodology Support: 888-888-1082 (US)
   What is the Earnings Quality model?
   The Earnings Quality model is a percentile (1-100) ranking of stocks based on sustainability of earnings, with 100 representing the highest rank.

StarMine defines earnings quality as a measure of the degree to which past earnings are reliable and are likely to persist. High quality earnings accurately reflect a company's current and past operating performance, are indicative of future operating performance, and are reliable valuation measures for the company, regardless of the level of earnings. Companies with poor earnings quality are not necessarily engaging in earnings manipulation; in most cases, low earnings quality reflects a likelihood of deteriorating fundamentals relative to the past. Furthermore, earnings quality can be measurably high: companies with very persistent earnings have strengthening fundamentals and are likely to outperform their benchmarks in the future.

The Earnings Quality model is broken down into four components:

Earnings can be decomposed into two parts: Cash Flow and Accruals. The accrual accounting doctrine requires companies to record revenues and expenses when they are earned and incurred, which is not necessarily when cash is received or paid; the difference between cash earnings and reported earnings are termed "accruals." Accruals, unlike cash flow, are subject to estimation errors and judgment.

We measure accruals as changes in operating assets and liabilities from four quarters ago to the most recent quarter. We measure changes in both current and non-current operating assets and liabilities. Accruals are scaled by average assets.

Cash Flow
The second half of earnings is cash flow. Like accruals, operating cash flow is a component of earnings. Operating cash flow is defined as the net of cash flow from operations and cash flow from investment. Unlike accruals, cash flow is relatively free of estimation error and therefore is more reliable than accruals.

We measure cash flow as the annualized (T4Q) free cash flow. Cash flow is scaled by average assets.

Operating Efficiency
Return on Assets (ROA) is the primary measure of operating efficiency. ROA reflects the internal rate of return on company projects. Our research indicates that on average, 70% of current-year ROA persists into the next year.

To identify the sources of differences in ROA persistence, we can decompose ROA into a profit margin sub-component and an asset turnover sub-component similar to a DuPont analysis.

 ROA = Earnings

= Earnings

* Sales


The profit margin sub-component indicates the company's effectiveness in controlling the cost of sales. The turnover ratio sub-component indicates the level of sales which can be generated from a given asset base. The third and final sub-component measures changes in asset turnover.

We evaluate asset turnover and profit margin against sector benchmarks because of the structurally different ways in which companies in various industries produce similar levels of ROA. For example, a shipbuilder exhibits high margins but low turnover, whereas a supermarket exhibits low margins but high turnover, but the two companies might have the same ROA.

Profit margin is measured using the annualized (T4Q) operating profit margin as a percentage of annualized sales. Asset turnover is calculated using the annualized sales to average net operating assets. Change in asset turnover measures the annualized asset turnover for the most recent quarter minus the annualized asset turnover from four quarters ago.

Exclusions (North America Only)
The final concept used by the StarMine Earnings Quality model is a measure of the degree to which reported earnings reflect operating earnings. Companies commonly define their own "pro forma", or reported, earnings measure and report this measure in their quarterly press releases. Companies defend the use of pro forma earnings by suggesting that the items included in GAAP earnings, but excluded from pro forma, are typically not core operating earnings and therefore do not reflect the company's ongoing earnings potential. As such, pro forma earnings are typically close to operating earnings before interest and taxes, but after depreciation and amortization. However, the practice is sometimes abused, and pro forma earnings can allow companies to present to the public "earnings before the bad stuff." Companies may also adjust the basis used in pro forma earnings in order to beat a benchmark such as analysts' expectations, prior reported earnings, or zero earnings.

We can attribute the difference between pro forma earnings and operating earnings to "special items" and "other exclusions." Both of these sources - special items and other exclusions - have a negative impact on future earnings growth.

The Exclusions component of the model breaks exclusions into two sub-components:
  • Special Items
  • Other Exclusions
We measure the two Exclusions sub-components using the most recent quarterly value scaled by average assets.

Certain companies are not eligible to receive an EQ score even if we have financial statement data for the company. We do not score companies under the following conditions:

North America
  1. OTC/Pink Sheet securities - we do not score companies that are traded exclusively over-the-counter (OTC) or are trading in the "pink sheets".
  2. US and Canadian securities with financial data older than 225 days - we do not score companies that have missed their last two filing dates.
  3. ADR/ADS securities with financial data older than 460 days - We do not score non-US companies traded on US exchanges that have missed their last annual filing date.
Outside North America
  1. Companies with financial data older than 640 days - We do not score companies traded on exchanges outside of North America with very old, stale data
Companies with multiple securities trading on different exchanges receive only one EQ score for each region. The score for these companies is based on the data they report to the their regulatory body. This single score is displayed for all securities related to the company in the region.

The Ranking boxes on a security's Ticker|Models page display how the stock compares on each measure to all other stocks in the universe. The left-most box indicates that a stock is in the lowest 10 percent of stocks; the second box indicates a stock is in the 11-30th percentiles; the middle box corresponds to the middle 40 percentiles; the fourth box indicates a stock is in the 71-90th percentiles; the right-most box indicates that a stock is in the top 10 percent of stocks.

StarMine Help Center Welcome Page