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17.61 (1y: -11%)
Market Cap 2.8 B P/E(ttm) 23.20
Enterprise Value 3.01 B P/B 2.10
ASNA- NAS (USA)
Ascena Retail Group, Inc.
  • Currently 4/5
Business Predictability Rank: 4-Star (On Watch)
Back Testing Results:
Average gain of all 4-Star stocks: 9.8% per year.
% of Stocks that are in still loss if held for 10yrs: 8%.
Read more:
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Top Ranked Predictable Companies
$17.61
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Ascena Retail Group, Inc. Earnings per Share: 0.2 ( as of Apr13)

* All numbers are in millions except for per share data ASNA 10-Y Financials »

Definition

Earnings per Share (eps) is the amount of earnings per outstanding share of the company’s stock. In calculating earnings per share, the dividends of preferred stocks need to subtracted from the total net income first. The formula of the calculation is

Earnings per Share (eps) = (Net Income - Preferred Dividends)/Total Shares Outstanding

Companies also reported diluted shares in their financial reports. Diluted shares include the shares of convertibles or warrants outstanding.

Formula

Earnings per Share (eps) = (Net Income - Preferred Dividends)/Total Shares Outstanding

Ascena Retail Group, Inc. per share eps Calculation

* All numbers are in millions except for per share data

Ascena Retail Group, Inc. Annual Data

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Ascena Retail Group, Inc. Quarterly Data

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Explanation

Earnings per Share (eps) is the single most important variable used by Wall Street in determining the earnings power of a company. But investors need to be aware that Earnings per Share can be easily manipulated by adjusting depreciation and amortization rate or non-recurring items.

Beaware

Compared with Earnings per share, a company’s cash flow is better indicator of the company’s earnings power.

If a company’s earnings per share is less than cash flow per share over long term, investors need to be cautious and find out why.

Related Terms

Net Income, Preferred Stock, Total Shares Outstanding
* All numbers are in millions except for per share data

Ascena Retail Group, Inc. Annual Data

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Ascena Retail Group, Inc. Quarterly Data

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Financial Dictionary

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