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Financial Institutions (Financial Institutions) Mohanram G-Score : 2 (As of Dec. 2023)


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What is Financial Institutions Mohanram G-Score?

Mohanram G-Score is a financial indicator developed by professor Partha Mohanram to help investors find the best investment opportunities in the growth stocks. Companies have higher G-score tends to generate higher return. According to his study, the best growth stocks that have a G-Score greater than 6 tend to beat the market, while those with a G-Score lower than 1 tend to have negative absolute returns.

Thus, the zones of discrimination were as such:

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

Financial Institutions has an G-score of 2.

The historical rank and industry rank for Financial Institutions's Mohanram G-Score or its related term are showing as below:

FISI' s Mohanram G-Score Range Over the Past 10 Years
Min: 1   Med: 3   Max: 5
Current: 2

During the past 13 years, the highest Piotroski G-score of Financial Institutions was 5. The lowest was 1. And the median was 3.


Financial Institutions Mohanram G-Score Historical Data

The historical data trend for Financial Institutions'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.

Financial Institutions Mohanram G-Score Chart

Financial Institutions Annual Data
Trend Dec14 Dec15 Dec16 Dec17 Dec18 Dec19 Dec20 Dec21 Dec22 Dec23
Mohanram G-Score
Get a 7-Day Free Trial Premium Member Only Premium Member Only 4.00 3.00 3.00 5.00 2.00

Financial Institutions 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 5.00 5.00 4.00 5.00 2.00

Competitive Comparison of Financial Institutions's Mohanram G-Score

For the Banks - Regional subindustry, Financial Institutions'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.


Financial Institutions's Mohanram G-Score Distribution in the Banks Industry

For the Banks industry and Financial Services sector, Financial Institutions's Mohanram G-Score distribution charts can be found below:

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



Financial Institutions 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

Financial Institutions has an G-score of 2.

Financial Institutions  (NAS:FISI) 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.


Financial Institutions Mohanram G-Score Related Terms

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Financial Institutions (Financial Institutions) Business Description

Traded in Other Exchanges
Address
220 Liberty Street, Warsaw, NY, USA, 14569
Financial Institutions Inc operates as a financial holding company, engages in the provision of a wide range of consumer and commercial banking services to individuals, municipalities, and businesses in Western and Central New York. It operates through the following segments: The Banking segment which includes all of the company's retail and commercial banking operations and All Other includes the activities of SDN, a full-service insurance agency that provides a broad range of insurance services to both personal and business clients.
Executives
Donald Boswell director WESTERN NY PUBLIC BROADCASTING ASSOC, HORIZONS PLAZA 140 LOWER TERRACE, BUFFALO NY 14202
Susan R Holliday director 220 LIBERTY ST, WARSAW NY 14569
Samuel M Gullo director 220 LIBERTY ST, WARSAW NY 14569
Robert N Latella director 220 LIBERTY, WARSAW NY 14569
Robert M Glaser director 220 LIBERTY STREET, WARSAW NY 14569
Dorn Andrew W Jr director 2421 MAIN STREET, BUFFALO NY 14214
Plants William Jack Ii officer: Chief Financial Officer 220 LIBERTY STREET, WARSAW NY 14569
Burruano Samuel J Jr officer: Senior Vice President 220 LIBERTY STREET, WARSAW NY 14569
Martin Kearney Birmingham officer: Senior Vice President 220 LIBERTY STREET, WARSAW NY 14569
Gary A. Pacos officer: Chief Risk Officer 220 LIBERTY STREET, WARSAW NY 14569
Bruce W Harting director 1185 PARK AVENUE, 6D, NEW YORK NY 10128
Laurie R Collins officer: Senior Vice President 220 LIBERTY STREET, WARSAW NY 14569
Mark Zupan director 1041 PITTSFORD VICTOR ROAD, PITTSFORD NY 14534
Mauricio F Riveros director 220 LIBERTY STREET, WARSAW NY 14569
Kevin B Quinn officer: Senior Vice President 220 LIBERTY STREET, WARSAW NY 14569