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Fastly (Fastly) Mohanram G-Score : N/A (As of Dec. 2023)


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What is Fastly Mohanram G-Score?

Fastly does not have enough data to calculate Mohanram G-Score.


Fastly Mohanram G-Score Historical Data

The historical data trend for Fastly's Mohanram G-Score can be seen below:

* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.

* Premium members only.

Fastly Mohanram G-Score Chart

Fastly Annual Data
Trend Dec17 Dec18 Dec19 Dec20 Dec21 Dec22 Dec23
Mohanram G-Score
Get a 7-Day Free Trial N/A N/A N/A N/A N/A

Fastly Quarterly Data
Mar19 Jun19 Sep19 Dec19 Mar20 Jun20 Sep20 Dec20 Mar21 Jun21 Sep21 Dec21 Mar22 Jun22 Sep22 Dec22 Mar23 Jun23 Sep23 Dec23
Mohanram G-Score Get a 7-Day Free Trial Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only N/A N/A N/A N/A N/A

Competitive Comparison of Fastly's Mohanram G-Score

For the Software - Application subindustry, Fastly's Mohanram G-Score, along with its competitors' market caps and Mohanram G-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.


Fastly's Mohanram G-Score Distribution in the Software Industry

For the Software industry and Technology sector, Fastly's Mohanram G-Score distribution charts can be found below:

* The bar in red indicates where Fastly's Mohanram G-Score falls into.



Fastly Mohanram G-Score Calculation

The calculation of the Mohanram G-score consists of eight criteria. Assign one point for each criterion met, then add up all the points to get the G-Score.

Profitability

Question 1. Return on Assets (ROA)

ROA % is calculated as Net Income divided by its average Total Assets over a certain period of time. It measures how well a company uses its asset to generate earnings.

Score 1 if ROA > ROA Industry Median, 0 otherwise.

Question 2. Cash ROA

Cash ROA equals to Cash Flow from Operations divided by average Total Assets. It measures how well a company uses its asset to generate cash.

Score 1 if Cash ROA > Cash ROA Industry Median, 0 otherwise.

Question 3. CFO and Net Income

Score 1 if CFO > Net Income, 0 otherwise.

Earnings Predictability

Question 4. Earnings Variability

Earnings Variability is measured as the variance of a firm's ROA in the past five years.

Score 1 if Earnings Variability < Earnings Variability Industry Median, 0 otherwise.

Question 5. Sales Growth Variability

Sales Growth Variability is measured as the 5-year variance in sales growth.

Score 1 if Sales Growth Variability < Sales Growth Variability Industry Median, 0 otherwise.

Accounting Conservatism

Question 6. Research & Development Intensity

Research & Development Intensity is calcualted by Research & Development divided by the beginning Total Assets.

Score 1 if Research & Development Intensity > Research & Development Intensity Industry Median, 0 otherwise.

Question 7. CAPEX Intensity

CAPEX Intensity is calcualted by Capital Expenditure divided by the beginning Total Assets.

Score 1 if CAPEX Intensity > CAPEX Intensity Industry Median, 0 otherwise.

Question 8. Advertising Expenditure Intensity

Advertising Expenditure Intensity is calcualted by Advertising Expenditure divided by the beginning Total Assets. Note that Advertising Expenditure is not reported as a seperate line item for many companies, thus Selling, General, & Admin. Expense is used in this calculation.

Score 1 if Advertising Expenditure Intensity > Advertising Expenditure Intensity Industry Median, 0 otherwise.

* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.

* Note that all the Industry Median used for comparison in his original research, are substituted with Sector Median due to the limitation of data within certain countries.

Good or high score = 6, 7, 8
Bad or low score = 0, 1

Fastly  (NYSE:FSLY) Mohanram G-Score Explanation

Partha Mohanram is the John H. Watson Chair in Value Investing at Rotman and the Acting Vice-Dean of Research Strategy and Resources.

In 2000, he wrote a research paper called "Separating Winners from Losers Among Low Book-to-Market Stocks Using Financial Statement Analysis".

This paper tests whether a strategy based on financial statement analysis of low book-to-market (growth) stocks is successful in differentiating between winners and losers in terms of future stock performance. Based on the research, a strategy based on buying high G-score (6, 7 or 8) firms and shorting low G-score (0 or 1) firms consistently earns significant excess returns. Further, the results do not support a risk based explanation for the book-to-market effect as the strategy returns positive returns in all years, and firms that ex-ante appear less risky have better future returns.

To conclude, one can use a modified fundamental analysis strategy (G-score) to identify mispricing and earn substantial abnormal returns.


Fastly Mohanram G-Score Related Terms

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Fastly (Fastly) Business Description

Traded in Other Exchanges
Address
475 Brannan Street, Suite 300, San Francisco, CA, USA, 94107
Fastly operates a content delivery network, which is necessary for entities to provide faster and more reliable online content. Fastly's strategy differs from traditional CDNs, which focus on locating servers in as many locations as possible to store copies of files that consumers most use. Fastly is in far fewer sites than traditional CDNs, but it houses servers in the most network-dense data centers. Instead of simply storing static content, it allows its customers to program on its platform, enabling edge computing and better service of the more dynamic content that was traditionally not well served by CDNs. Fastly gears its service to the largest, most sophisticated enterprises rather than small companies and generated nearly three fourths of its revenue in the United States in 2022.
Executives
Ronald W Kisling officer: Chief Financial Officer 2400 BRIDGE PARKWAY, REDWOOD SHORES CA 940651166
Artur Bergman director, 10 percent owner, officer: Chief Executive Officer C/O FASTLY, INC., 475 BRANNAN STREET, SUITE 300, SAN FRANCISCO CA 94107
Brett Shirk officer: Chief Revenue Officer 350 ELLIS STREET, MOUNTAIN VIEW CA 94043
Christopher B Paisley director 14870 THREE OAKS COURT, SARATOGA CA 95070
Todd Nightingale director, officer: CEO C/O FASTLY, INC., 475 BRANNAN SUITE 300, SAN FRANCISCO CA 94107
David Hornik director, 10 percent owner 2480 SAND HILL ROAD, SUITE 101, MENLO PARK CA 94025
Joshua Bixby officer: President C/O FASTLY, INC., 475 BRANNAN STREET, SUITE 300, SAN FRANCISCO CA 94107
Richard Devon Daniels director 3005 TASMAN DRIVE, SANTA CLARA CA 95054
Paul Luongo officer: General Counsel C/O FASTLY, INC., 475 BRANNAN STREET, SUITE 300, SAN FRANCISCO CA 94107
Vanessa C. Smith director C/O FASTLY, 475 BRANNAN STREET, SUITE 300, SAN FRANCISCO CA 94107
Adriel G Lares officer: Chief Financial Officer C/O FASTLY, INC., 475 BRANNAN STREET, SUITE 300, SAN FRANCISCO CA 94107
Charles J Meyers director 301 VELOCITY WAY, 5TH FLOOR, FOSTER CITY CA 94404
Paula Loop director C/O ROBINHOOD MARKETS, INC., 85 WILLOW ROAD, MENLO PARK CA 94025
Abdiel Qualified Master Fund Lp 10 percent owner 90 PARK AVENUE, 29TH FLOOR, NEW YORK NY 10016
Abdiel Capital Lp 10 percent owner C/O ABDIEL CAPITAL ADVISORS, LP, 90 PARK AVENUE, 29TH FLOOR, NEW YORK NY 10016