Luận văn retail bank key metrics and stock performance

Practical applicabilily, i any: Kirst of all, the study provides basic understanding and part of financial analysis of retail banks from different region all over the world, These banks

VIETNAM NATIONAL UNIVERSITY, HANOI

INTERNATIONAL SCHOOL

GRADUATION PROJECT

RETAIL BANK INDUSTRY:

KEY METRICS AND STOCK PERFORMANCE

Phing Minh Son

Llanoi - 2020

KEY METRICS AND STOCK PERFORMACE

SUPERVISOR: Dr 1 Bite Thith STUDENT: Phing Minh Son

CODF: 16071237 COHORT: AC2016C MAJOR: Accounting, Analyzing and Auditing

Hanoi - 2020

INFORMATION ON FINAL THESIS

1 Full name: Phimg Minh Sơn 2 Gender Male

3 Date of birth: August 5 1998 4 Place of birth: Ha Noi

$ Official thesis lille: Retail bank industry: Key metrics and stock performance

6 Major: Accounting, Analyzing aud Auditing

7, Code: 16071237

8 Guider Teclawer: Dĩ, Tê Đức Thịnh

9, Summary of the findings of the thesis:

The study analyze the correlation and p-value between seven key metrics and

tolal shareholders’ return, the results indicate that Net Loan and Tease lo Deposit has

more significant linear relationship with ISR 2 which is calculated according to

published date of annmal report Moreover, NIVAA, NLL/A, NLL/D, Growth rate of

Tolal Asscl and ROA have significant mpact on stock performance valculaled according to fiscal year The result of significant linear relationship of metrics on TSR

1 is more than the results on TSR 2

This study also uses the Regression models which use ROE as a dependent

variable and 6 metrics as independent variables which are NAA, NLL/A, NLL/D,

Growth rale of NLL, Growth rate of EPS and Pre-tax Profil Margin The results show

that Net Loan and Lease to Deposit and Pre-tax Profit Margin have very high

probabilities of appearing in any repression models Pre-tax Profit Margin has a positive linear relationship with Net Income/Average Equity while Net Loan and Lease

to Deposit has a negative linear relationship with ROL The Regression model also

uses ROA as dependent variable and 6 metrics independent variables as ROE, the

resulis show that Net Interest Income/ Average Assels and Net Loan and Lease to

Deposit both have a 100% probability of appearing in any regression models Net

Tutorest Income’ Average Assets has a positive lincer relationship wilh Net

Income/Average Asset while Net Loan and Lease to Deposit has a negative linear relationship with ROA

10 Practical applicabilily, i any:

Kirst of all, the study provides basic understanding and part of financial analysis

of retail banks from different region all over the world, These banks are ont top largest banks in their countries, which represent closcly the financial performance and stock price of their regions

The study is an acaden : research which anarlyzes ond provides summary of understanding about the impacts of featured and standard metrics on the effectiveness and efficiency of retail banks operating results which reflects on stock price of these banks in different regions

‘This study also includes the research about financial analysis which based on correlation of metrics and total shareholders’ retum so that the investor and financial analyst can have the overview about the important metrics in analyzing the relail banks stock performance and make the decision of investment

Date: 27/05/2020 Signature

Full name: Phimg Minh Son

Acknowledgement Wirt and foremost, | would like to express sincere thanks to my thesis advisor

Dr Le Due Thinh of the International School, Vietnam National University for the

continuous supporl of my study and research, for his helpful guidance, constant

advise and feedback during the time when I do the thesis Dr Thinh helps me a Iot

in research, data collection and thesis writing It’s such an honor and great opportunity for me to have chance to receive advice and support from Dr Thinh

T would also like to express my gratitude to my friends at university who gave

me continuous advice and support during the time when I analyze data and write thesis They also helped me analyze and comment about the retail banking industry

so that I can complete my thesis efficiently and effectively

Letter of Declaration

i hereby declare that the Graduation Project Retail Bank industry: Key metrics and stock performance is the thesis of my own research, analysis and has never been published before During the process of this project, Thave seriously taken research ethics; all results of this project are my own research and data collection: all references in this project are clearly cited according to regulalions

T bear full responsibility for the fidelity of the mumber and dala and other

contents of my graduation project

ddanoi, May 25" 2020

Phùng Minh Sơn

List of abbreviation

TSR

Average Assets Deposit

Harning per share Net Interes! Income Net Loan and Leases Retum on Average Uquity Return on Average Asscis

‘Yotal Assets Total Equi

Total slock return

Table of contents

Chapter 1; Introduction

1 The necessity of topic:

2 The goal of topi

3 Research outcomes:

2.1 Summary of Correlation of Companies between featured metrics and TSR 1

2.2 Summary of Correlation of Companies between standard metrics and TSR 1

1.3 Sinnmary of Correlation af Companies between featured metrics and TSR 2

2.4, Summary of Correlation af Companies between standard metrics and TSR 2

2.5 Companies with na stgnificant correlation hetween metrics and stack performance for both TSR 1 and TSR 2

2.6 Summary of signitcant correlation of metrics and TSR

3 Case study analysis of HSBC Holdings

4 Analyzing the multiple regression

4.1, Multiple regression models for ROK

Chapter 4: Conclusion, Implication and Recommendation

1, Conclusion and discussion

List of figures and table Figure 1.Real GDP growth by region 2013-2023

Figure 2 Average NLL/A and NLL/D of 20 banks from 2010 to 2019

Figure 3 Average Growth rate of NLL and TA of 20 banks from 2010 to 2019

Figure 4 Average ROA and ROE of 20 banks from 2010 (o 2019

Figure 5 Average NII/AA of 20 banks from 2010 ta 2019

Table 1 Summary significant correlations with p-value < 10% of TSR 1

Table 2 Summary significant correlations with p-value < 10% of TSR 2

Table 3 Summary of correlations among standard and fealured metrics

10

12

23

24 +

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39

Al 4B

Chapter 1: Introduction

1 The necessity of topic:

Retail banking, also known as consumer banking, is the provision of services by

a bank to the general public, rather than to companies, corporations or other banks,

which are often described as wholesale banking Retail banking is also distinguished

from investment banking or commercial banking It may also refer to a division or

department of a bank which deals with individual customers Retail banking provides financial services for individuals and families The three most important functions are

credit, deposit, and money management First, retail banks offer consumers credit to

purchase homes, cars, and furniture These include mortgages, auto loans, and credit cards The resulting consumer spending drives almost the economy They provide extra

liquidity to the economy this way Credit allows people to spend future earnings now

Second, retail banks provide a safe place for people to deposit their money Savings

accounts, certificates of deposit, and other financial products offer a better rate of

return compared to stuffing their money under a mattress Banks base their interest

rates on the fed funds rate and Treasury bond interest rates These rise and fall over

time Third, retail banks allow the customer to manage money with checking accounts

and debit cards *

A study by Farient Advisors LLC (2013), sponsored by the US Government, covering 1,800 companies, 24 Industry groups, and 14 years of data (1998-2011),

identifies the primary metrics used by companies, and then tests these metrics to determine whether the metrics used have the highest impact on total stock returns The

study found that, in aggregate, performance metrics are generally well-aligned with

share owner value Earnings growth, followed by returns and revenue growth, has the

greatest impact on stock prices The review also found that many industries have a

number of metrics to choose from However, the optimal use of measures differs

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considerably by industry This study is presented on “Harvard Law School Forum on

Corporate Governance and Financial Regulation” The limitation of this research is they only study standard metrics of corporate finance from U.S industry

Inspired by the research, this thesis aims to evaluate the correlation between key

performance ratio and stock performance of a specific industry — retail bank industry

Retail banks industry is one of the most developed competitive industry in the world According to global investment In the United States, most banks benefited from rising

interest rates, loan growth, and tax cuts Meanwhile, in other parts of the world, better

cost controls and growth in loan demand boosted profitability Banks are expected to

become more active, either by launching stand-alone digital banks or through

partnerships Online lenders’ growth in student loans, home equity, and personal loans can be expected as well.”

‘this thesis base on the data collection of metrics in financial analysis to evaluate the correlation between the metrics and total shareholders’ return which is calculated

dy growlh ale of stock price per year so thal ihe investor can base on the result lo have

investments In addition, this thesis collect information from different regions which include America, Europe, UK and Asia so the result is the overall financial analysis

which represent the global retail banks

2 The goal of topic:

This thesis provide an empirical study to identify the relationship between key

anetrics including financial ratios or featured indicators and total stock retwn of retail

‘banks to see whether those metrics has any significant impacts on the fluctuation of

retail banks’ slock price

Annual data including ratios are collected from the financial statement and amnual report of the greatest banks all over the world then used to calculate the

necessary metrics and the correlations botween these metrics and TSR Subsequently, the data from all the analyzed banks are used to create a multiple regression model to

evaluate the impact and relations] ap of each metric to the TSR

3 Research outcomes:

This study analyzes data of twenty banks in the US, UK, Iurope and Asia: total

sharcholder returms (TSR) and ten metnes for banks are used in the analysis The

correlations results between these metrics and TSR are calculated to evaluate if there

are positive or negative and strong or weak linear relationships between stock-retumns and eight metrics [his thesis also finds a multiple linear regression model between TSR and the key metrios

4 Practical contributions:

The study provides the helplid knowledge about retail bank industry, which analyzes the impact of featured metrics in the industry As a result, the investors can

consider the necessary indicators in the mvestinenls m banks based on the annual

results and ratio of the banks

Chapter 2: Literature review and Research methodology

1 Literature review

1.1 Theoretical background

In the study “Liquidity-preference as a behavior towards risks” by T Jeremy in

1958, it stated that the measurement of liquidity should answer the question on how the

company could pay its short-term debts and Loan to Deposit is the measurement in picturing liquidity as for finance company As for finance company, loan is their

current asset and deposit is their current liability,

In addition, there was also a study about “Predicting Japanese bank stock

performance with a composite relative efficiency metric: A new investment tool” by

Neemi K Avkiran and Hiroshi Morita The purpose of the study was to predict bank stock performance one year ahead with a composite efficiency metric from relative

contextual financial analysis It had the fundamental analysis in evaluating the

company financial performance for investment.*

In 2007, Beverly J Hirtle and Kevin J Stiroh conducted a study about “The

return to retail and the performance of US banks” It examined the impact of banks’

retail intensity on performance from 1997 to 2004 by developing three complementary definitions of retail intensity (retail loan share, retail deposit share, and branches per

dollar of assets) and comparing these measures with both equity market and accounting

measures of performance It concluded that a focus on retail activities is not associated

with improved performance, measured by equity market retums and volatility, for the

largest banks, and may actually lower performance for small and medium-sized

institutions.*

In 2007, D Byard and F Cebenoyan through study “Alternative evidence on

financial analysts' use of financial statement information” concluded that Return on

* https://sci-hub.twéhttps:/mww.sciencedirect com/science/article/pii/$0927538X1000003X

* https://sei-hub.tw/https:/Avww sciencedirect.com/science/article/abs/pii/S0378426606002846

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Asset (ROA) is one of the best measurements of efficiency in order to assess the

company’s performance ROA had been widely used as a measurement for profitability and it reflects the ability of management to generate income on a given amount of total

assets °

In 2010 Aggeliki Liadaki and Chrysovalantis Gaganis were done a study with

the topic “Efficiency and stock performance of EU banks: Is there a relationship ?”

with the purpose of examining if the stock performance of EU listed banks is related to

their efficiency The efficiency estimates in this study used the stochastic frontier

approach (SFA) The main argument for the SFA over the non-parametric techniques,

such as data envelopment analysis (DEA), it allows for a random error, which accounts for measurement errors and other random factors in the estimation of efficiency It used

the output of total customer loans, other earning assets and non-interest income to

calculate the translog function to evaluate the efficiency of banks in EU They

concluded that changes in profit efficiency were statistically significant and positively

related to stock returns However, there was no evidence of a significant relationship

between cost efficiency and stock returns.”

This thesis is refered to the most recent document which is graduation project of

Nguyen Ngoc Lam from IS-VNU about “Airline Industry: Key metrics and stock

performance” The result of this thesis shows that the metrics specially used in

analyzing the operational conditions including Load factor, Revenue per available seat

miles, Passenger revenue per available seat miles and Cost per available seat miles of

airlines have more significant relationship with TSR than other standards metrics like

Gross Margin, ROA, Quick ratio and Debt/Equity ratio It is also noteworthy that for

all 15 airlines, the Debt/Equity ratios do not have any significant impact on TSR This may be resulted from the special characteristic of airline companies as they usually

have large amount of debt from lease Another remarkable finding is that featured

° http:/Avww.ijtef org/papers/327-B10029 pdf

" huttps://sci-hub.tw/https://www.seiencedirect.conv/science/article/abs/pii/$030S048309000395

metrics of airlmes from the US has more significant on I'SR than that of other

countries *

The Stale Board of Administration (SBA) sponsored an execulive comperisalion

research study by Farient Advisors LLC, covering 1,800 companies, 24 Industries and fourleen years of dala from 1998 to 2011 The research project identifies the primary

suctrics which reflect financial performance of the companies, overall and by industry, company size and valuation premiums, and tests the correlation of these metrics to

determine whether the meiries have the highest impact, on total stock returns (or total

shareholder retumis LSR) The melrics used in this research are Harnings Growth,

Revenue Growth, Retums (ie ROA, ROB), Cash Flow, Earnings Margins Earnings

Growth measures have the strongest currelalion to value (TSR) Firstly, i was moi

‘unusual to see all three Liarnings Growth metrics that were tested LPS, Net Income

and Operating Income — near or at the top of the correlation results Revenue Growth

was oflon the seeond most highly correlated metric certain Industry Groups have significantly higher or lower correlation resuilts overall, as summarized in the following

table (which is based on the mdustnes with the overall Iighesl and lowest correlation

coefficients) Some of these groups, like Pharmaceuticals, Biotechnology & Lite Sciences, are comprised of very different businesses It is fair to say that correlation analysis is best conducted on a well-constructed peer scl of similar companies The more disparate the peer set, the more likely that the correlations will be poor Poor

correlations also likely are due to the fact that financial measures do not necessarily do

a good job of predicting value in certain types of companies, such as early stage life

sciences companies Industries with weak correlation results or a limited set of metrics

to choose from could benefit from using TSR directly as a valid metric

The result of Fanenl Advisors LLC shows thal performance metrics are generally well-alipned with shareholder value Eamings Growth, followed by Retums

* Reference in person: Nguyen Ngoc Lam — Graduated Suudent covering airline industry in U.S

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and Revenue Growth, has the greatest impact on TSR In general, this matches the use

patterns for financial metrics in long-term incentive: Earnings Growth is the most

popular financial measure, followed by Returns and Revenue Growth TSR (usually

measured on a relative basis) is used as a direct measure of shareholder value in over

40% of companies with performance-based long-term incentive It is important to

acknowledge that certain industries may have been rational in not using metrics that correlated to value over the entire 1998-2011 timeframe, i.e., the period included in the

study This could have been due to the fact that the metrics correlating most strongly to

value change over time and/or with the economic cycles — what works well in growth

markets does not necessarily work well in recessionary environments For example, in the Semiconductor & Semiconductor Equipment industry, Revenue Growth was the

leading financial metric used over the time period studied (1998-2011) While Revenue

Growth was most strongly correlated to TSR during the growth cycles, Retums and Cash Flows were better metrics to use during the recessionary periods This underscores the fact that certain companies may be best served focusing on different metrics in different economic situations Banking industry gives the moderate result

For banking industry, it concluded that Banking Industry has low correlation and ROE

correlates well to Market to Book value.”

° https://corpgov.law:harvard.edu/201 3/02/20/performance-metries-and-their-link-to-value!

1.2 Key metrics

1.21 Total Stock Return (TSR)

TSR 1 is the tofal relumn of a stock Lo an mvestor, or he slock price according to fiscal

‘year

TSR 2 is the total retum of @ stock 1o an investor, or the stock price according to lhe

published date of annual report of retail banks

‘TSR can be calculated with the following formula:

(Ending Price — Beginning Price) + Dividends

Beginning Price

= (Ending ajusted closing price — Beginning adjusted closing price)

Beginning adjusted closing price

The stock price used in this study is adjusted close price that already includes the dividend I obtain stock price from Yahoo Finance

Ratio, fhe metrics that | choose are typically representative ratio according to previous

study and research The below metrics are not too difficult to collect data and information to calculate

1 Net interest margin (NIM) is the liquidity ratio, is a measurement comparing the

net interest income a financial firm generates from credit products like loans and

mortgages, with the oulgoing interest i pays holders of savings accounts and

certificates of deposit (CDs) Expressed as a percentage, the NIM is a profitability

indicator thal telegraphs the hkelhood of a bank or investment finn thriving over the

long haul This metric helps prospective investors detormme whether or not to invest in

a given financial services firm Simply put: a positive net interest margin suggests that

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an entity operates profitably, while a negative figure implies investment inefficiency

In the latter scenario, a firm may take corrective action by applying funds toward oulslanding debt or shifling those assets (owards more profitable investments

Net Interest Income = Interest Income — Interest Expense

Net interest income

loans and lease-to- Is ratios derive a relatively larger portion of their total incomes

from more-diversificd, noninterest-carning sources, such as asset management or trading Banks with lower net loan and lease-to-assets ratios may fare better when

interest rates are low or credit is tight They may also fare better during econamic

downtums

Net Loan and Lease

NLL/A = Total Assets

3 Net Luan and Lease to Deposit (NLI/D) is the liquidily ratio Ti is calculated by dividmg NLL by Deposit (which includes Deposit from bank and Deposit from

customers) If the ratio is too high, it means that the bank may not have enough

liquidity 10 cover any unforescen fund requirements Conversely, if the ratio is too low, the bank may not be earning as much as it could be

NEL/D = Net Loan and Lease

Deposit

4 Growth rate of Net Loan and Leases (NLL) refers to the measurement of

changing percentage of net loan and leases from previous year to current year

123 Standard metric

5 Growth rate of Total Assets (TA) refers to the measurement of changing

percentage of Lolal assets from previous year lo current! year

19

6 Net Income/ Average Equity (ROE) is the Eamings and Profitability Ratio It

measwes the performance of a company based on its average shareholders’ equity

ROR is considered a measure of how effectively managemenl is using a company’s

assets to create profits

Net income

~ Average equity

7 Net Income/ Average Asset (ROA) is (he Earmings and Prolitability Ratio The

ratio shows how well a firm's assets are being used to generate profits, Itis frequently

applied to banks because the cash flow analysis is more difficult to accurately construct

and iLis considered an important profitability ratio

Net income

ROA =

Average Assets

ROR

8 Totat Equily/ Total Asset (TE/TA) is standard ratio that reflects the percentage of

equity to asset The Equity-To-Asset ratio specifically measures the amount of equity

the bank has when compared to the total assets owned by the bank

9 EPS Growth is standard ratio calculated by the following fomula:

EPS of current year — FPS last year

Pre — tax profit

Pre — tax @ — tax Profit Margin = Profit Margin Revenue

2 Research questions, methodology and scope

2.1, Research questions

— What are the motrics that have impacts on TSR of retail bank ?

— Which metrics have negative and positive linear velationship with TSR for cach retail bank ?

Analyze a linear multiple regression model between TSR and key metrics with each analyzed retail bank as a sample

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2.2 Methodology

— Qualitative: study key featured metrics for retail bank such as NI/AA, NLL/A;

NLL/D, Growth rate of NLL and standard metrics such as Growth rate of TA

ROE, ROA, TE/TA, EPS Growth and Pretax profit margin used in basic

analysis

— Quantitative:

The data used for the calculation purpose of metrics had been collected from annual

report of 18 largest retail bank all over the world in which 9 banks from United States,

3 banks from UK, 2 banks from Europe and 4 banks from Asia There are some metrics

that are already calculated by websites or annual report that provide the information

about these banks The metrics that are already calculated also follows the calculation

method that I mentioned above for the consistent purpose

The data and reported information from the retail banks can be reported in million

or billion units

The correlation between TSR and 10 key metrics for retail bank are calculated by

the metrics used the original currency which was reported on the annual report of the

retail bank and the metrics are calculated into ratio so that the correlation is not

affected by the exchange rate

2.3 Scope of research

The retail banks that are used for metrics calculation are from various region to

cover the retail bank industry on the world The diversity of the region and data collected from retail banks will be appropriate to provide information about the

overview of each region The list of banks that are chosen had been collected from

Business Insider and Relbanks'® Twenty retail banks include:

— Nine (09) banks are from the US

— Three (03) banks from UK

*° https:/Avww.relbanks.com/worlds-top-banks/assets and hitps://www.businessinsider.conv/largest-banks-us-list

— Two (02) banks from Europe

— Four (04) banks from Asia

3 Facilities and the difficulty of the researching process

3.1 Facilities:

I obtain 10 years of data (2010-2019) from annual reports of 18 banks and their

stock prices from Yahoo Finance.'!

3.2 Difficulty:

The structure and outline of the report are different among the retail banks so it is difficult to collect data to calculate metrics Some banks had not listed on the stock market from period 2010 to 2015 so stock price of the bank at that time were equal to zero There is not enough date collection to have result on regression model for both

TSR

* https://finance.yahoo.com/

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Chapter 3: Main results

1 Descriptive statistics:

Net Loan and Lease is one of the most key important indicators of retail banks

in the industry, which reflect the financial performance of bank through loans for other

banks and loans for customers The figure below illustrate the average result of Net

Loan and Leases to Assets and Net Loan and Leases to Deposit

Net Loan and Lease to Deposit is higher than Net Loan and Lease to Asset American

banks seem to have lower average NLL/A and NLL/D than banks in Europe and Asia

Loan and Lease accounts for sigmficant amount of Total Assets which is up to

approximately 80% for banks in Vietnam Almost banks have amount of Net Loan and

Lease which is smaller than Deposit

Growth rate B Growth rate

Net Loan & leases Intal Asset

Figure 3 Average Growth rate of NLL and ‘!'A of 20 banks from 2010 to 2019

Net Loan and Leases plays a key role in the financial performance of retail banks, Viemamese banks (ie VCB and BIDV) have highest growth rate of Net Loan

and Leases and Total Asset which are from 15% to approximately 20% in average

Lloys Banking Group has the average growth rate of both Net Loan and Leases and

Total Asset which are negative and Citibank experience the same situation for

average growth rate of Total Assct and Bank of New York Mellon Corp also has negative average growh rate of Net Loan and Leases

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Capital One Financial Corporation Bank of New York Mellon Corp PNC Financial Services Group

US Bancorp Morgan Stanley Goldman Sachs Group

Wells Fargo Bank of Ametica

Citibank JPMorgan Chase & Co

Santander UK

To Bank BNP Paribas Uoyds Banking Group Societe Generale HSBC Holdings

Figure 4 Average ROA and ROE of 20 banks from 2010 to 2019

Return on equity are much greater that Return on assets and VCB is the bank

that has highest average ROE while U.S, Bancorp is the bank that has highest ROA

Lloyds Banking Group is the bank with lowest ROA and ROE

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Capital One Fitancial Corporation TT 0.038 Bank of New York Melon Cor) — 0.010

PNC Financial Services Group TT 0,028

Morgan Stanley 0,014 Goldman Sachs Group 0,009

CC — 0.013

= 0,005 0.010 0.015 0.020 0.025 0.030 0.035 0.040

Figure 5, Average NII/AA of 20 banks from 2010 to 2019

The range of average Net Interest Income/ Average Assets of 20 banks is quite small from 5% to approximately 4% The amount of Net Interest Income is quite low

compared to the amount of asset of 20 banks American banks tend to have highest

average Net Interest Income/ Average Assets among 20 banks in which Capital One

Financial Corporation has the highest amount of this average ratio

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