Quality Ratios Guide


Stock ratio analysis is an essential part of making investment decisions. The ratios reveal how a company is performing and how it compares to other companies within its industry. Boost your investment strategy by calculating quality ratios to help guide you toward wise stock choices.

How to Use Quality Ratios

Quality ratios can offer a window into the quality of the business by looking at a variety of statistics to predict stock market outperformance, bankruptcy risk and earnings manipulation.

How do you measure quality of earnings?

The quality of earnings – or quality of income – ratio is found by dividing the net cash from operating activities by net income. It does not include one-off revenue gained from another source. These figures are found on the cash flow and income statements. A ratio greater than 1 is a better quality of earnings since it shows that net operating income is less than operating cash flows.

Here are some examples of quality ratios:

Altman Z-score 

This is a score used for predicting the likelihood that a company will go bankrupt within the next two years.

Altman Z-score formula

Edward Altman developed this formula in 1968 when he was an assistant finance professor at New York University. The original formula was created for public manufacturing companies. There are two other Z-score formulas — for private manufacturing companies and private general companies. The formulas use five ratios derived from a company’s income statement and balance sheet. The lower the Z-score, the higher the likelihood a company will go bankrupt.

Piotroski F-score

This score is named after Stanford University accounting professor Joseph Piotroski, who developed it in 2000. The Piotroski F-Score is a 9-point scoring system that uses historical financial information to determine the strength of a company’s financial position. The score can help investors find the best value stocks.

Piotroski F-score screener 

The Piotroski F-score stock screen highlights companies with strong fundamentals and weeds out weaker companies. A score of 8 or 9 is considered to be a better score.

Beneish M-Score

The Beneish M-score  is a mathematical model published in 1999 by Indiana University accounting professor Messod Beneish. It uses financial ratios derived from a company’s accounting data to find how likely it is that a company’s earnings were manipulated. 

Calculating a Beneish M-Score

The score uses eight different indices. These include the days’ sales in receivables; gross margin; asset quality; sales growth; depreciation; sales, general and administrative expenses; leverage; and total accruals to total assets.

An M-score below -2.22 indicates a company likely did not manipulate earnings. A score greater than -2.22 means it is likely earnings were manipulated.

Analyzing financial data is an important step to take before investing in a stock. Quality ratios provide a fast way to scan many opportunities and gain a view into the quality of a business.

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