Apple (AAPL)

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172.44 +0.17  +0.10% NASDAQ Dec 14, 10:00 Delayed 2m USD

Apple Ohlson Score (TTM):

-0.6269 for Sept. 30, 2017
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Apple Ohlson Score (TTM) Chart

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Apple Historical Ohlson Score (TTM) Data

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Data for this Date Range  
Sept. 30, 2017 -0.6269
June 30, 2017 -0.5799
March 31, 2017 -0.4724
Dec. 31, 2016 -0.935
Sept. 30, 2016 -0.8306
June 30, 2016 -0.6201
March 31, 2016 -0.4813
Dec. 31, 2015 -0.8785
Sept. 30, 2015 -0.6666
June 30, 2015 -0.7342
March 31, 2015 -0.9417
Dec. 31, 2014 -1.245
Sept. 30, 2014 -0.9413
June 30, 2014 -1.362
March 31, 2014 -1.666
Dec. 31, 2013 -1.978
Sept. 30, 2013 -1.975
June 30, 2013 -1.916
March 31, 2013 -2.312
Dec. 31, 2012 -2.418
Sept. 30, 2012 -2.235
June 30, 2012 -2.204
March 31, 2012 -2.281
Dec. 31, 2011 -2.439
Sept. 30, 2011 -2.069
   
June 30, 2011 -2.244
March 31, 2011 -2.187
Dec. 31, 2010 -2.168
Sept. 30, 2010 -2.200
June 30, 2010 -2.276
March 31, 2010 -2.338
Dec. 31, 2009 -2.358
Sept. 30, 2009 -2.403
June 30, 2009 -1.502
March 31, 2009 -1.498
Dec. 31, 2008 -1.523
Sept. 30, 2008 -2.314
June 30, 2008 -2.110
March 31, 2008 -1.610
Dec. 31, 2007 -1.852
Sept. 30, 2007 -1.631
June 30, 2007 -1.906
March 31, 2007 -1.905
Dec. 31, 2006 -1.638
Sept. 30, 2006 -1.395
June 30, 2006 -1.629
March 31, 2006 -1.363
Dec. 31, 2005 -1.513
Sept. 30, 2005 -1.909
June 30, 2005 -1.792

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About Ohlson's O-Score

Created by James Ohlson in the 1980s, the Ohlson Score uses items from the financial statement to predict the likelihood of a firm's bankruptcy. The O-Score breaks it down into nine different approximate measures of a firm's default risk, two of the nine being dummy variables: these nine are used to determine firm size, leverage, working capital, liquidity, profitability, change in net income, and debt financing. Together, these nine variables build an O-Score where the probability of failure is EXP(O-Score) divided by 1+EXP(O-score). Results greater than >.5 indicate a firm with a high chance of default.

It has been argued that the Ohlson Score is a better predictor of bankruptcy than other similar accounting models such as the Altman Z-Score, however, investors may find merits in using both Altman and Ohlson in helping to predict a firm's bankruptcy.

Because both Ohlson and Altman use an accounting-based model to help predict bankruptcy, its strength is its relatively simplicity. However, there are other bankruptcy models such as Merton's Distance to Default and CHS are other bankruptcy models that are used by academics and argued to be more effective in predicting bankruptcy risk.
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AAPL Ohlson Score (TTM) Benchmarks

Benchmarks
Cisco Systems -1.696
Applied Materials -1.073
Intel -1.561

AAPL Ohlson Score (TTM) Range, Past 5 Years

Minimum -2.418 Dec 2012
Maximum -0.4724 Mar 2017
Average -1.179

AAPL Ohlson Score (TTM) Excel Add-In Codes

  • Metric Code: ohlson_score
  • Latest data point: =YCP("AAPL", "ohlson_score")
  • Last 5 data points: =YCS("AAPL", "ohlson_score", -4)

To find the codes for any of our financial metrics, see our Complete Reference of Metric Codes.

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