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Piotroski F-score is a number between 0 and 9 which is used to assess strength of company's financial position. The score is used by financial investors in order to find the best value stocks (nine being the best). The score is named after Stanford accounting professor Joseph Piotroski. [1]
The Piotroski F-score is a 9-point valuation metric derived on this research. Through back-testing, Piotroski found that buying the top stocks in the market according to his methodology and shorting those that got the worst scores would have resulted in 23% annualized gains from 1976 through 1996, more than double the S&P 500 broad market index ...
Precision and recall. In statistical analysis of binary classification and information retrieval systems, the F-score or F-measure is a measure of predictive performance. It is calculated from the precision and recall of the test, where the precision is the number of true positive results divided by the number of all samples predicted to be positive, including those not identified correctly ...
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The formula for the one-way ANOVA F-test statistic is =, or =. The "explained variance", or "between-group variability" is = (¯ ¯) / where ¯ denotes the sample mean in the i-th group, is the number of observations in the i-th group, ¯ denotes the overall mean of the data, and denotes the number of groups.
An F-score is a combination of the precision and the recall, providing a single score. There is a one-parameter family of statistics, with parameter β, which determines the relative weights of precision and recall. The traditional or balanced F-score is the harmonic mean of precision and recall:
Scoring algorithm, also known as Fisher's scoring, [1] is a form of Newton's method used in statistics to solve maximum likelihood equations numerically, named after Ronald Fisher. Sketch of derivation