Substrate Artificial Inteligence (AQSE:SAI.B) Piotroski F-Score

Substrate Artificial Inteligence Piotroski F-Score Chart

Competitive Comparison of Substrate Artificial Inteligence's Piotroski F-Score

For the Software - Infrastructure subindustry, Substrate Artificial Inteligence's Piotroski F-Score, along with its competitors' market caps and Piotroski F-Score data, can be viewed below:

* Competitive companies are chosen from companies within the same industry, with headquarter located in same country, with closest market capitalization; x-axis shows the market cap, and y-axis shows the term value; the bigger the dot, the larger the market cap. Note that "N/A" values will not show up in the chart.

Substrate Artificial Inteligence's Piotroski F-Score Distribution in the Software Industry

For the Software industry and Technology sector, Substrate Artificial Inteligence's Piotroski F-Score distribution charts can be found below:

* The bar in red indicates where Substrate Artificial Inteligence's Piotroski F-Score falls into.

Substrate Artificial Inteligence  (AQSE:SAI.B) Piotroski F-Score Explanation

The developer of the system is Joseph D. Piotroski is relatively unknown accounting professor who shuns publicity and rarely gives interviews.

He graduated from the University of Illinois with a B.S. in accounting in 1989, received an M.B.A. from Indiana University in 1994. Five years later, in 1999, after earning a Ph.D. in accounting from the University of Michigan, he became an associate professor of accounting at the University of Chicago.

In 2000, he wrote a research paper called "Value Investing: The Use of Historical Financial Statement Information to Separate Winners from Losers" (pdf).

He wanted to see if he can develop a system (using a simple nine-point scoring system) that can increase the returns of a strategy of investing in low price to book (referred to in the paper as high book to market) value companies.

What he found was something that exceeded his most optimistic expectations.

Buying only those companies that scored highest (8 or 9) on his nine-point scale, or F-Score as he called it, over the 20 year period from 1976 to 1996 led to an average out-performance over the market of 13.4%.

Even more impressive were the results of a strategy of investing in the highest F-Score companies (8 or 9) and shorting companies with the lowest F-Score (0 or 1).

Over the same period from 1976 to 1996 (20 years) this strategy led to an average yearly return of 23%, substantially outperforming the average S&P 500 index return of 15.83% over the same period.

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Substrate Artificial Inteligence (AQSE:SAI.B) Business Description