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


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What is ContextLogic Mohanram G-Score?

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


ContextLogic Mohanram G-Score Historical Data

The historical data trend for ContextLogic'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.

ContextLogic Mohanram G-Score Chart

ContextLogic 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

ContextLogic Quarterly Data
Dec17 Dec18 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 ContextLogic's Mohanram G-Score

For the Internet Retail subindustry, ContextLogic'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.


ContextLogic's Mohanram G-Score Distribution in the Retail - Cyclical Industry

For the Retail - Cyclical industry and Consumer Cyclical sector, ContextLogic's Mohanram G-Score distribution charts can be found below:

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



ContextLogic 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

ContextLogic  (NAS:WISH) 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.


ContextLogic Mohanram G-Score Related Terms

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ContextLogic (ContextLogic) Business Description

Traded in Other Exchanges
Address
One Sansome Street, 33rd Floor, San Francisco, CA, USA, 94104
ContextLogic Inc is an online shopping store. The store provides personalized products, clothing products, accessories, gaming products and equipment, cosmetics, plastic products, mobile covers, and other products. Geographically, it derives a majority of revenue from Europe and also has a presence in North America; South America, and other countries.
Executives
Jerry Louis officer: Chief Technology Officer ONE SANSOME STREET, 33RD FLOOR, SAN FRANCISCO CA 94104
Stephanie Tilenius director C/O IRONPLANET, INC., 4695 CHABOT DRIVE, SUITE 102, PLEASANTON CA 94588
Mauricio Monico officer: Chief Product Officer ONE SANSOME STREET 33RD FLOOR, SAN FRANCISCO CA 94104
Jun Yan officer: CEO ONE SANSOME STREET, 33RD FLOOR, SAN FRANCISCO CA 94104
Ying Vivian Liu officer: CFO and COO ONE SANSOME STREET 33RD FLOOR, SAN FRANCISCO CA 94104
Lawrence M Kutscher director ONE DIAMOND HILL RD, MURRAY HILL NJ 07974
Brett Just officer: SVP, Finance ONE SANSOME STREET 40TH FLOOR, SAN FRANCISCO CA 94104
Shuyan (rachel) Wang officer: Head of Data Science ONE SANSOME STREET 33RD FLOOR, SAN FRANCISCO CA 94104
Tarun Kumar Jain officer: Chief Product Officer ONE SANSOME STREET 40TH FLOOR, SAN FRANCISCO CA 94104
Vijay Talwar director, officer: Chief Executive Officer 705 FIFTH AVENUE SOUTH, SUITE 900, SEATTLE WA 98104
Piotr Szulczewski director, 10 percent owner, officer: Founder, CEO, and Chairperson ONE SANSOME STREET 40TH FLOOR, SAN FRANCISCO CA 94104
Hans Tung director 3000 SAND HILL ROAD, BUILDING 4, SUITE 230, MENLO PARK CA 94025
Pai Liu officer: Vice President of Data Science ONE SANSOME STREET 40TH FLOOR, SAN FRANCISCO CA 94104
Devang Shah officer: General Counsel and Secretary 699 8TH STREET, SAN FRANCISCO CA 94103
Hamid Reza Kassaei officer: Chief Technology Officer ONE SANSOME STREET 40TH FLOOR, SAN FRANCISCO CA 94104