THE RELATIONSHIP BETWEEN PRICE EARNINGS RATIO AND
STOCK RETURN FOR FIRMS’ QUOTED IN NAIROBI
SECURITIES EXCHANGE
BY
TIMOTHY MUNIU MBURU
REGISTRATION NO: D61/65585/2013
THIS RESEARCH PROPOSAL HAS BEEN SUBMITTED IN PARTIAL
FULFILLMENT OF REQUIREMENT FOR THE AWARD OF THE
DEGREE OF MBA, SCHOOL OF BUSINESS UNIVERSITY OF
NAIROBI
OCTOBER, 2014
i
DECLARATION
This project proposal is my original work and has not been submitted for the examination
in any other university
Sign ………………………………………………
Name ……………………………………………
Date ……………………………………………….
Supervisor
This project proposal has been submitted for examination with my approval as the
university supervisor
Sign ………………………………………………
Name: Dr Josiah Aduda
Date ……………………………………………….
ii
ACKNOWLEDGEMENTS
I am grateful to the University of Nairobi for allowing me to pursue masters Course and
successfully guiding me through the programme. I am particularly grateful to the
teaching and administration staff of the School of Business, University of Nairobi, for
their tireless efforts in managing this programme.
I am also grateful to the various authors whose work has been quoted in this study. They
are in every sense a part of this study.
Special thanks go to my supervisor, Dr Josiah Aduda for his steady, guiding hand and his
enormous patience that enabled a successful completion of this project work.
And to my fellow MBA students, past and present, thank you for your mutual support
during the entire MBA course.
iii
DEDICATION
I dedicate this work to the University of Nairobi and to my family for their invaluable
support and patience during this study.
Special regard to my wife Irene, for continued support, my son Mike and daughters Ciku
and Mercy for their love even during hard times.
Also dedicate to all teachers and lecturers since I commenced my studies at tender age.
iv
ABSTRACT
The objective of the study is to assess the relationship between the P/E ratio and stock
returns for firms quoted in Nairobi Securities Exchange (NSE). The study adopted a
descriptive survey design. It involved a census survey of all the companies listed at the
NSE during the years 2009-2013. These were subdivided into 10 subsets corresponding
to the 10 sectors of the Exchange. Secondary data was obtained from the NSE
Handbooks covering the period from January 2008 to December 2013 which provided 5Year company financial performance summaries.
The data collected was summarized into yearly weighted averages for the test variables
for the NSE for the years 2009-2013. This summary data was then analyzed using
descriptive statistics. Multivariate correlation and regression analyses were used to test
the relationship between the price earnings ratio and the growth of earnings and stock
prices. The study found that there existed insignificant relationship between the stock
returns and P/E ratio but a positive relationship between the stock returns with ROE and
MBV
Research study further found different relationship when analysed per sector. Agriculture,
Energy, insurance and Manufacturing recorded positive but moderate association
between stock returns and P/E ratio. Banking, commercial and construction sector
recorded negative but weak relationship hence contradicting the general observations.
The study concluded that firms in different sectors behave differently according to the
future expectation of the firm, the required rate of return and the industry it is in.
The study also found that there is no significant relationship between stock returns and
P/E ratio and conclude P/E ratio not a good indicator of future performance. The study
concludes that there is strong relationship between ROE and MBV ,and MBV can be a
better predictor of stock returns than the P/E ratio.
Further research study is recommended to be undertaken in assessing whether the MBV
can predict the stock returns in both short and long term for firms listed in NSE.
v
TABLE OF CONTENTS
DECLARATION ................................................................................................................ ii
ACKNOWLEDGEMENTS ............................................................................................... iii
DEDICATION ................................................................................................................... iv
ABSTRACT ........................................................................................................................ v
ABBREVIATIONS ......................................................................................................... viii
CHAPTER ONE ................................................................................................................. 1
INTRODUCTION ........................................................................................................... 1
1.1
Background of the study ...................................................................................... 1
1.1.1
Price Earnings Ratio ..................................................................................... 1
1.1.2
Stock Return.................................................................................................. 3
1.1.3
Relationship Between Price Earnings Ratio and Stock Return .................... 3
1.1.4
Nairobi Securities Exchange ......................................................................... 5
1.2
Research Problem ................................................................................................ 5
1.3
Objective of the study ......................................................................................... 7
1.4
Value of the study ................................................................................................ 7
CHAPTER TWO ................................................................................................................ 8
LITERATURE REVIEW ................................................................................................... 8
2.1 Introduction ............................................................................................................... 8
2.2 Review of Theories ................................................................................................... 8
2.2.1 Random walk Theory ......................................................................................... 8
2.2.2 Efficient Market Theory ................................................................................... 10
2.2.3 Value Investing Theory .................................................................................... 12
2.3 Determinants of Stock Returns ............................................................................... 13
2.3.1 Profitability Level of the Firm .......................................................................... 13
2.3.2 Liquidity ........................................................................................................... 14
2.3.3 Growth Potential & Performance ..................................................................... 14
2.3.4 Price Level of Stock ......................................................................................... 15
2.3.4 Premium Returns /Dividends............................................................................ 15
2.4 Review of Empirical Studies ................................................................................... 16
vi
2.4 Chapter summary .................................................................................................... 20
CHAPTER THREE .......................................................................................................... 22
RESEARCH METHODOLOGY .................................................................................. 22
3.1 Introduction ............................................................................................................. 22
3.2 Research Design ...................................................................................................... 22
3.3 Population and Sample ............................................................................................ 22
3.4 Data collection......................................................................................................... 22
3.5 Data Analysis .......................................................................................................... 23
CHAPTER 4 ..................................................................................................................... 25
DATA ANALYSIS AND PRESENTATION OF FINDINGS ........................................ 25
4.1 Introduction ............................................................................................................. 25
4.2 Data Presentation..................................................................................................... 25
4.2.1 The Analysis of the NSE Quoted Firms ........................................................... 26
4.2.2 The Analysis of the Stock Returns and P/E Ratio for All Sectors for 2013 ..... 27
4.2.4: Correlation Analysis and Multiple Regression per Sector .............................. 31
4.3 Summary and Interpretation of Findings ................................................................ 32
CHAPTER 5 ..................................................................................................................... 35
SUMMARY, CONCLUSIONS AND RECOMMENDATIONS..................................... 35
5.1 Summary ................................................................................................................. 35
5.2 Conclusions of the Study......................................................................................... 36
5.3 Policy Recommendation ......................................................................................... 37
5.4 Limitations of the Study .......................................................................................... 38
5.5 Suggestions of Further Studies ................................................................................ 39
REFERENCES ................................................................................................................. 40
APPENDIX ....................................................................................................................... 46
vii
ABBREVIATIONS
ANOVA
Analysis of Variance
CMA
Capital Market Authority
E/P
Earnings to Price
EMH
Efficient Market Hypothesis
EPS
Earnings Per Share
EMT
Efficient Market Theory
GEMS
Growth Enterprise Market Segment
KLCI
Kuala Lumpur Composite Index
MBV
Market price to Book value
MCH
Mispricing Correction Hypothesis
MPS
Average Market Price for one Year
NSE
Nairobi Securities Exchange
P/BV
Price to Book Value
P/CF
Price to cashflows
P/E Ratio
Price Earnings Ratio
PEG
Price to Growth
P/S
Price to Sales
ROE
Return on Equity
S&P 500
Standard & Poor 500 Index
SSE
Stockholm Stock Exchange
viii
CHAPTER ONE
INTRODUCTION
1.1 Background of the study
Campbell & Schiller (1988), Fama & French (1992) and Danielson, Hirt & Block (2009)
through their studies found that stock returns in long term are influenced by variables
which include P/E ratio, previous returns, dividend yields and policy, organization term
structure, book to market ratios, risk/volatility of performance, default premiums and
quality of management .This was contrary to earlier studies which had a view that future
stock returns cannot be predicted.
Fama & French (1992) further observed that those variables after adjusting for market
risks with regard to all sectors of firms have explanatory and predictive capability.
Efficient market hypothesis indicate that all fundamentals are reflected in the current
stock value thus observation contradicts the hypothesis. P/E ratio studies and theories have
indicated mixed views in regard to relationship between P/E ratio and stock return while
others view P/E ratio as a better indicator of future stock returns.
1.1.1 Price Earnings Ratio
Liem & Sautma (2012) noted that P/E ratio is widely used in evaluating the expected
stock returns in stock market. P/E ratio was discovered around 1930s by Benjamin
Graham and David Dodd. Through studies, P/E ratio have different variants as it continue
been modified due to investor need as evaluation ratio. Liem & Sautma, (2012) stated
that the basic P/E ratio is derived as a ratio of firm’s market price of stock and earnings
per share. Ross & et al (2011) further observed that P/E ratio of a firm’s fund is the
weighted average of all held stocks P/E ratios in the firm’s fund portfolio. Ross further
asserted that P/E ratio of a firm which compaires firm’s stock and earnings per share is
computed by dividing firm’s stock prices with earnings per share. For comparison,
average P/E ratio is computed by proportion or weight of each equity assets it holds in
deriving the firm’s fund P/E.
1
Danielson, Hirt & Block (2009) observed that a stock that has a high required rate of
return will generally have a low P/E ratio because it’s risky. Similarly, a stock with a low
required rate of return will normally have high P/E ratio because of the predictability of
positive future performance. Further stated that a firm that have good expectation for
future tend to trade at high P/E ratio .Illustrated with an example in USA where he noted
that, the average P/E for S &P 500 Index firms was 20 in mid 2007 but E-bay traded at a
P/E of 40 because of its overall strength.
Petterson (2011) outlined three generally used P/E ratios namely trailing, current and
forward. Trailing, one of the widely used P/E ratios as compared to other two is
computed by dividing the market price of the stock by four previous quarters of actual
earnings per share. As the ratio uses four previous quarters, it is also used to project
earnings in the next four quarters. Current ratio only differs with trailing ratio as it uses
data from previous two quarters. The ratio can only predict next two quarters thus used
only as short term estimator. Those two ratios use actual data thus regarded as more
accurate. Forward P/E ratio use estimated EPS mainly from analysts rather than actual
previous data. The ratio is regard inferior due to the use of estimations hence is mostly
used hand in hand with trailing P/E ratio.
Estrada (2003) indicated that a high P/E usually indicates that the market will pay more to
obtain the company's earnings because it believes in the firm's ability to increase its
earnings. Companies in those industries enjoying a surge of popularity (e.g.
telecommunications, biotechnology) tend to have high P/E ratios, reflecting a growth
orientation. A low P/E indicates the market has less confidence that the company's
earnings will increase; however, a fund manager or an individual with a 'value investing'
approach may believe such stocks have an overlooked or undervalued potential for
appreciation. More industries, such as utilities and mining, tend to have low P/E ratios,
reflecting a value orientation. A major limitation of P/E ratio arises when earnings are
artificially inflated if a company has very weak trailing earnings, and thus a very small
number in this equation's denominator resulting into high P/E ratio.
2
1.1.2 Stock Return
According to Ross & Westerfield (1999) the return on any stock traded in a financial
market can be categorized as either normal / expected return or uncertain returns. Normal
returns arise where shareholders in the market can predict the returns depending on the
information shareholders have that bears on the stock. The second is the uncertain or
risky return where the returns come from unexpected information revealed within the
year like unexpected interest rate, news about research findings.
Fischer & Jordan (2001) indicated that return on a typical investment consists of two
components. The first component is the periodic cash receipts inform of dividends and
the changes in the price of the asset commonly called the capital gain or loss as second
component. This element of return is the difference between the purchase price and price
at which the asset can be or is sold, therefore it can be a gain or a loss. Thus the correct
measurement of stock return consist of both income and price change into a total return
covering returns across time or from differed securities.
Fischer & Jordan (2001) used the equation to illustrate the computation of return as
follows: Total return= (cash payments received+ price change over the period)/purchase
price of the asset. The price change over the period is the difference between the
beginning (or purchase) price and the ending (sales price) which can be either positive or
negative.
1.1.3 Relationship Between Price Earnings Ratio and Stock Return
According to Lasher (2008) P/E ratio compares the stock’s market price with EPS as
published in financial statements. EPS, which is the denominator is the annual net income
over the number of common stock held. P/E ratios indicate how investors are willing to
pay for dollar of company’s earnings. He illustrated with an example that if a company’s
P/E ratio is 10 times and EPS are $ 4.5, the stock is selling for $45.Stock market people
would say “The company is selling for 10 times earnings”. The higher the P/E ratio, the
3
better, because a dollar of earnings translates into more shareholder wealth at higher P/E.
He observed that the key factor is the high expected level of growth by the firm.
The stock price and the EPS determine the value of the ratio. P/E ratio increases in three
scenarios. First, P/E ratio increases if earnings remain stable but investors are ready to
pay more per unit of earnings. Secondly, P/E can raise when both the stock price and the
EPS increase, but the increase of stock price more as compaired to the increase in the
EPS. Last, scenario where P/E ratio increases is when stock price do not change but EPS
decreases. However, no change on the P/E ratio if there is a balance between the change
on the stock price and the EPS ( Lasher ,2008).
Fama (1991), Ferson and Harvey (1991) observed that return predictability is due to
variations in expected returns and risk sensitivities but not indicator of stock market
inefficiencies .However, Harvey (1995) concluded that returns in developing market
which are mostly semi strong market can be predicted better as compared to developed
market returns. Ou, Jane & Stephen (1989) indicated that although P/E ratio can reveal
current and projected earnings, they do not always result to excess profits in the stock
market. Balvers, Cosamino, & MacDonald (1990) concluded that advantages derived
from predictive ability are offset by proceeding fluctuations in stock returns, a positions
which was also supported by mean revision of stock prices where the P/E ratio revert to
its sector mean in a process known as reverse repricing effect.(Weigand& Irons 2004).
From the study, the P/E ratio was expected to have inverse relationship with the stock
return, where high P/E ratio was expected to record low returns. Also expected that the
high P/E ratio can predict the future falls in stock prices hence provide support for a P/E
based trading strategy which can assist investor to record abnormal returns.
4
1.1.4 Nairobi Securities Exchange
NSE was formed in 1954 as Nairobi Stock Exchange and registered under the Societies
Act. The NSE which has changed to Nairobi Security Exchange is a member of the
African Stock Exchanges Association and fourth largest stock exchange in Africa when
based on trading volumes, and in basis of market capitalization as a percentage of GDP,
fifth. As at beginning of 2014, NSE had 61 listed companies with the market
capitalization of Kshs1.662 trillion categorized as main investment market and the
growth enterprise market segments and further classified in 11 sectors.
NSE has indices which measure the Stock market performance namely the NSE 20 Share
Index and the NSE All Share Index. The NSE 20 Share Index, the benchmark index of
the NSE, is a price-weighted index. Computed NSE 20 Share Index generally reflects the
performance of the whole market currently 4834 points, reflecting an overall robust
growth in stock prices and NSE. P/E ratio is computed for each firm and sector separately
by using the highest price for the week divided by EPS.
The weekly P/E ratio is published in local dailies and NSE website (Mwai, 2014). The
brief analysis of P/E ratios indicate that Commercial & Services segment have the highest
segment P/E ratio of 70.19 which was driven by one firm (700) followed by GEMS of 88.
The lowest was in Energy & petroleum with 6.12.Study by Odera, Otieno, Kieran & Jaafar
(2012) observed that the NSE 20 Share Index, being a geometric index, is independent of
the base rate but has consistently understated stock price rises and consistently overstated
stock price falls casting doubts about its representativeness of the NSE and by extension
future stock performance. The study conducted by Odiero (2013) concluded NSE as an
efficient market in the weak form, with growth rather than value shares dominating the
exchange.
1.2 Research Problem
Three theories relating to P/E ratio explains how the ratio relates to future firms share
performance and how the ratio can predict future returns. Random Walk theory by
Malkiel (1973) suggests that price behavior is never based on anything predictable, but is
5
completely random while efficient market theory suggests that stock is always efficiently
priced and investor cannot outperform the market except as a consequence of luck. Value
investing theory by Graham & Dodd (1934) and further researched by Reilly & Brown
(1997) suggested more predictive returns where investor can influence returns by buying
stocks which appear underpriced by some of its fundaments, notion disputed by Malkiel
as intrinsic value relies on subjective estimates of future earnings using factors like
expected growth rates and expected dividend payouts.
Odiero (2013) concluded that P/E ratio and the growth of stock prices have moderate
positive association. Osano (2010) concluded that P/E ratio and P/B values have
predictive capability of expected future stock returns of companies listed at the NSE and
also found that portfolio with high P/B and P/E ratios performed worse as compaired to
portfolio with low P/E and P/B ratios. Githinji (2011) found out that stock performance
do not have any significant relationship with P/E ratio and PEG ratios for NSE listed
firms and recommended investors should use a combination of methods instead of relying
only with P/E and P/B a ratios while making investment decisions. Study undertaken by
Kihara (2009) concluded that earnings changes can be predicted by E/P ratios and can
identify firms with potential to grow.
Therefore, for Random Walk theory; investors do not consider existence of any
relationship of share performance and the P/E ratio. Second theory, efficient market
theory indicates that stock is always efficiently priced thus analysis meaningless. Both
theories indicate that P/E ratio is not a good predictor of future earnings. last theory,
value investing theory conclude that investor focus on underpriced stocks for buying thus
shows P/E ratio having predictive capability. Empirical studies done by local researchers
concluded that the P/E ratio is effective tool to use when evaluating and predicting future
earnings as per Odiero (2013), Osano (2010) and Kihara (2009). However, other study by
Githinji (2011) indicates contrary. This results to diverging positions.
Also noting that, previous studies on P/E ratios focused on relationship between P/E ratio
and stock prices but no study carried out on stock returns with P/E ratio, and notion on
6
whether firms in NSE with low P/E ratio actually record high returns. Thus the study
analysed if one can make better returns by relying with P/E ratio analysis. The
relationships between the P/E ratio and stock returns and ability of predicting future
performance in context of Kenyan scenario is required.
This study attempted to answer the following research question; Is there any relationship
between the average P/E ratio and stock returns?
1.3 Objective of the study
The main objective of the study was to assess the relationship between the P/E ratio and
stock returns for firms in NSE.
1.4 Value of the study
The study sought to provide empirical evidence of relationship between the average P/E
ratio and stock returns, The study will be of beneficial to the following categories; First,
investors who are concerned on evaluating different stocks listed in securities exchange
and select one which has high chance of better returns will use P/E ratio as one of the
evaluations method.
Second, Capital market regulators whereas CMA seeks to have strong market, one of the
fundamentals is access to information. Thus the study will assist the CMA in assessing
how effective P/E ratio can be used as one source of financial information. Third, finance
managers and fund managers in which they are required to thoroughly analyze the
financial data and predict the future performance of various stocks. The study will assist
the managers as an evaluation tools and lastly, scholars/students in understanding the
relationship between P/E ratio and stock returns thus add body of knowledge.
7
CHAPTER TWO
LITERATURE REVIEW
2.1 Introduction
This section outlines theories and empirical studies relating to P/E ratio and stock returns.
Section 1 introduces the chapter; section 2 reviews three main theories; section 3
examines the recent previous empirical studies both foreign and local; and section 4
presents a summary of the literature review.
2.2 Review of Theories
Three theories regarding the prediction of stock performance in relation to investors’
behavior and effects in market efficiency are discussed namely Random walk theory,
efficient market hypothesis and value investing theory. Determinants of stock returns are
highlighted as regarded as key variables in stock performance and previous studies and
conclusion indicating diverging view in relation to stock returns and P/E ratio.
2.2.1 Random walk Theory
Random walk theory was first introduced by Kendall (1953), advanced by Cootner
(1964) and Malkiel (1973). They observed that price behavior cannot be predicted
because it does not act on any predictive fundamental or technical indicators. Simply put,
there is an equal chance that stock’s price will either rise or fall from current levels hence
coined “The random Walk Theory”. The theory states that market and securities prices
are random and not influenced by past events. The random walk theory is a close
counterpart of the efficient market hypothesis.
The central idea behind the random walk theory is that the randomness of stock prices
renders attempts to find price patterns or take advantage of new information futile. The
theory claims that daily stock prices are independent of each other, meaning that
momentum does not generally exist and computations of past earnings growth does not
predict future growth. The random walk theory proclaims that it is impossible to
8
consistently outperform the market, particularly in the short-term, because it is
impossible to predict stock prices (Kendall 1953).
The random walk theory contradicts the widely accepted belief by both fundamental and
technical analysts. Under the theory of fundamental analysis, the long term value of a
firm is based on competitive strength, profitability, revenue and market expansion,
working capital controls and capitalization. Under the theory of technical analysis, price
is predictable based on chart patterns, momentum indicators. (Thomsett, 2013)
The random walk theory considers technical analysis undependable because, according to
Malkiel (1973), chartists buy only after price trends are established and sell only after
price trends are broken; essentially, the chartists buy or sell too late and miss the boat.
According to the theory, this happens because stock prices already reflect the information
by the time the analyst moves on the stock. He also noted that the widespread use of
technical
analysis
reduces
the
advantages
of
the
approach.
However, Cootner (1964) and Malkiel (1973) acknowledged some statistical anomalies
pointing to some exceptions to the random walk theory. These exceptions were, first;
prices of small, less liquid stocks seem to have some serial price correlation in the shortterm because they do not incorporate information into their prices as quickly, contrarian
strategies tend to outperform other strategies because reversals are often based on
economic facts rather than investor psychology, there are seasonal trends in the stock
market, especially at the beginning of the year and the end of the week, high-dividend
stocks tend to provide higher returns over time because during down markets the high
dividend yields often create demand for these stocks and thus increases the price and
stocks with low P/E ratios tend to outperform those with high P/Es, although the
tendency is volatile over time.
Molodovsky (1953) found that stocks had mispricings which were noted as having
“overreaction” before the information was released but the shares prices adjusted and
corrected themselves after the news but noted as having “underreaction”. Further
explained that the increasing stock price increases the firm’s P/E ratio, such that in long
9
run the P/E ratios revert to an average or market ratio. The high P/E ratio stocks
underperforms in the market, while their low P/E ratio in similar market environment
outperforms the market which Molodovsky (1953) had described as mean reverting
process where he observed that while stocks fluctuate, they will do so approximately a
computable value which Weigard & Iron (2004) called comparable firm average.
The random walk theory concludes that all methods of predicting stock prices are futile in
the long run. Malkiel (1973), calls the notion of intrinsic value undependable because it
relies on subjective estimates of future earnings using factors like expected growth rates,
expected dividend payouts, estimated risk, and interest rates. However, from exceptions
of Random walk Theory as highlighted, use of P/E ratio as a prediction tool is supported.
2.2.2 Efficient Market Theory
Efficient Market Theory by Fama (1970) derived with premise that the current price of
stock has already been adjusted for all known information about that firm. Thus, EMT
observes that analyzing a firm’s financial reports or studying stock charts is meaningless.
Since all prices are fair and efficient because the ‘smart’ investors have already bid prices
to their proper levels, there is never a discrepancy between price and value (Bogle, 1991)
Article by Fama (1970) noted that the EMH can be categorized into three sub hypotheses
namely weak form, semi strong form and strong form which is according to the
information available in the market. The weak form EMH is where the current stock
market prices reflect all security market data like trading volume data and the historical
rates of return. This form indicates that no relationship between the stock exchange data
and expected rate of return. Semi strong form EMH arise when all public information
involving market and non-market information like political news and dividends
announcements are incorporated fully in stock market price. Investor using these news
which is not public cannot benefit by making better investment decision. Lastly, the
strong form EMH arise when both public and private information are fully reflected in
the current stock market prices. Thus, even the insider trading is not possible for this
form.
10
According to Reilly & Brown (1997) fundamental analysis is the procedure where every
individual stocks, sector and entire stocks market have its respective intrinsic value
reflecting the current corresponding economic factors. The intrinsic price of a share is the
present value of these expected future cash flows (Penman and Sougiannis, 1995). While
determining the intrinsic value of certain stock, a fundamental analyst evaluate and
analyze the relevant variables like political risk, current market interest rates and the
investment’s future earnings capability; variables that an impact on the price of the stock.
The extents to which the above fundamentals are reflected in stocks indicate the
efficiency of the market. The implication of efficient capital markets on fundamental
analysis is key area while assessing the relationship between the P/E ratio with stock
return. (Balvers, Cosamino, & MacDonald, 1990)
Fundamental analysis assuming efficient capital markets on stock prices indicate that if
the intrinsic value of the stock and prevailing market price is not equal, investors will
decide whether to buy or sell if by taking into consideration transaction cost. The actions
may involved selling the security if the intrinsic value is lower than its market price and
buy if it is high. The process will continue until it subsequently correct itself. (Reilly &
Brown, 1997). This hypothesis usually happens in weak form EMH but runs contrary to
the semi strong form EMH and strong form EMH. Peavy and Goodman (1983) asserted
also that the after adjusting for risk, stock returns the lowest P/E ratio quintile were
relative superior than that those in the highest quintile.
Reilly & Brown (1997) indicated that although efficient capital markets are efficient in
accordance to various sets of information, recent studies shown that the market in fact
does not adjust to public information accordingly thus weak and semi strong form. Basu
(1977) concluded that P/E ratio information was not fully reflected in security prices in as
swiftly as suggested in the semi-strong form EMH showing that investor can record
abnormal returns. Also found that there existed a relationship between historical P/E
ratios and stock market performance which contradicted the semi strong form EMH as it
suggests that investors could employ publicly available P/E ratios to forecast future rates
of return.
11
2.2.3 Value Investing Theory
Graham & Dodd (1934) illustrated that the main idea behind value investing theory
involves buying stocks whose prices appear undervalued by the underlying fundamentals
since the securities might have been trading at discounts to their corresponding earnings
multiples, book value and sales. Reilly & Brown (1997),while addressing question on
what makes investors value oriented observed that value oriented investor tends to
express his/her attention on certain feature of the P/E equation in making investment
decisions expressed as P/E Ratio = Current Price per Share/ Earnings per Share.
Investor, using the ratio as given may; focus on the price component of the equation,
which is the numerator. The price of the share must be apparently low priced enough as
compared with its other similar stocks for the investors. Second way is to partly overlook
the share’s current earnings and its subsequent growth drivers; and third option is to
assume the P/E ratio is trading well below its mean or comparable average and the
market will soon correct the gap by prices increasing with no effects on earnings (Ferson,
Wayne & Harvey, 1997).
Reilly & Brown(1997) further observed that value oriented investors would focus on the
stock price fluctuations with expectation of future market correction as a result of
underlying better fundamentals of firm. However, the theory have key limitation in
classifying individual securities, sectors and even the aggregate stock markets into the
value category and also identify securities which have better fundamentals which are
better to buy. Further, noted that in depth security analysis is costly and time consuming
hence most financial analyst use readily available information like dividend yield, EPS
growth rate and P/E ratio.
Study by Capaul, Wrowley and Sharpe (1993) found that value oriented portfolio
management had high chances of making better results. In their study they compared
global value shares with global growth shares and the former performed better by an
average of 3.3% per year between 1883-1992.The research focused on six countries,
12
which are France, Japan, Germany, the US, Switzerland and the United Kingdom (UK)
where they noted that the value oriented stocks performed better in all the states. The
study concluded that growth oriented investors are more interested to focus on the current
and future earnings capabilities of the firms or markets, but value oriented investor has
more interest on share valuation.
2.3 Determinants of Stock Returns
Various studies have found that the profitability measured by Return on equity, share
liquidity measured by market capitalization , growth potential measured by P/E ratio ,
price levels measured in book-to-market ratio and cash flow provided by stock
measured by dividend yield are key determinant of stock returns. The variables can
strongly predict stock returns.
2.3.1 Profitability Level of the Firm
Profitability ratios indicate ability of the management to convert sales into profits and
cash flow. The main ratios commonly used are gross margin, operating margin and net
income margin. The gross margin is the ratio of gross profits to sales. The gross profit is
equal to sales minus cost of goods sold. The operating margin is the ratio of operating
profits to sales and net income margin is the ratio of net income to sales. The operating
profit is equal to the gross profit minus operating expenses, while the net income is equal
to the operating profit minus interest and taxes (Kheradyar, Ibrahim & Mat ,2011)
The return on asset ratio, which is the ratio of net income to total assets, measures a
company's effectiveness in deploying its assets to generate profits. The return on
investment ratio, which is the ratio of net income to shareholders' equity, indicates a
company's ability to generate a return for its owners. Profitability is also measured by
return on equity (Haugen, Talmor & Torous ,1991
13
2.3.2 Liquidity
Amihud & Mendelson (1986) observed that investors while rebalancing their portfolios
must buy at asked prices and sell at bid prices. The bid-asked spread serves as part of the
cost of trading hence differences in the liquidity of stocks, a key variable in stock returns.
Stoll & Whaley (1983) further noted the market impact of a trade is also important due to
the fact that individual stocks have widely differing degrees of liquidity. Share liquidity is
measured by market capitalization.
To keep the expected rates of return, net of trading costs, commensurate, stocks must
have gross expected returns that reflect the relative cost of trading and factors associated
with liquidity include price per share, the annual average volume of daily trading relative
to annual average total market capitalization (price-per-share times the total number of
shares outstanding), the five year time trend in this variable, and contemporary total
market capitalization. Overall, an investor should expect the payoffs to the various factors
that represent differentials in liquidity to be negative, with the liquid stocks having the
lower expected returns ( Chan and Chen,1991)
2.3.3 Growth Potential & Performance
According to French, Schwert and Stambaugh (1987), factors related to growth potential
indicate the probability for faster (or slower) than average future growth in a stock's
earnings and dividends. Within the cross-section, relatively profitable firms will tend to
grow faster, at least until competitive entry into their lines of business forces profits to
normal levels. Based on the assumption that firms that are currently relatively profitable
have greater potential for future growth, several measures of profitability as predictive
factors include the ratios of net earnings to book equity, operating income to total assets,
operating income to total sales, total sales to total assets, and the trailing, five year time
trends in these variables. Also included the trailing, five year time trend in earnings-per
share, expressed as a percentage of average earnings over the five year period.
14
Given the size of the factors that reflect the price-level of a stock, the greater the growth
potential for profits and dividends, the greater the expected future rate of return. If the
market mistakenly assigns identical prices to stocks with differing growth potential, one
would expect the payoffs to the growth potential factors to be collectively positive.
Growth potential and performance can be measured by use of P/E ratio (Reilly & Brown,
1997).
2.3.4 Price Level of Stock
Factors related to price-level indicate the level of current market price relative to various
Accounting numbers. These measures indicate whether a stock is selling cheap or dear.
Factors representing cheapness in price include contemporary market price relative to
earnings-per share, cash flow-per-share, dividends-per-share, book value-per-share, and
sales-per-share (Haugen, 1995)
The trailing five year time trends and variability about trend in these variables are also
included as factors. Recent research has shown that stocks with low ratios of price to
current cash flows have earned relatively high rates of return in recent decades. The
source of these higher returns is the subject of much controversy. One of the measures of
price levels is using book to market ratio. (Haugen, Talmor & Torous ,1991)
2.3.4 Premium Returns /Dividends
Fama and French (1992) stated that value stocks are "fallen angels" and therefore are
more risky, therefore, premium returns to these stocks are expected and required. Haugen
(1995) noted that the premium returns to value stocks are unexpected and systematically
surprise investors. They believe that investors over react to the past records of success
and failure by firms. Proponents of over-reactive markets believe that the forces of
Competition in a line of business tends to quickly drive profits to normal levels.
By projecting prolonged rapid growth, investors in growth stocks can drive prices too
high. As the forces of competition come into play faster than these investors believe, they
15
tend to be disappointed by the earnings reports of growth stocks. The future dividends
and capital gains on these stocks tend to be smaller than expected and returns tend to be
relatively low. The converse tends to be true of value stocks. Cash flow provided by
stock can be measured by dividend yield (Jegadeesh, 1990).
2.4 Review of Empirical Studies
Study carried out by Vorek (2009) with an objective of evaluating value investing
strategy on predicting future stock returns for firms listed in Czech stock market. The
value investing analysis using data of 1973 and 2007 prepared estimates of intrinsic value
of common stock using P/E ratio, P/S, P/CF, and P/BV. Using charts and regression
model, the research observed that in short run(1-3 years) investments with low P/E ratio
recorded higher returns as compaired to firms with high to earnings ratio for period 19732000.However, in long run (5 years) there were no significant relationship and concluded
P/E ratio not a good indicator of future performance. The researcher attributed the short
term deviations as a correction period.
Study carried out by Ong, Yichen & The (2010) in Malaysian stock market index, the
Kuala Lumpur Composite Index and its P/E ratio and investigated the capability of value
investing strategy on the projection of stock performance, but with regards to the fall in
stock prices in Malaysia. The study covered between 1994 -2008.The methodology
employed was based mostly on fundamental analysis and financial markets theory.
Regression and correlation analysis was used to testify the hypothesis. Observed that high
levels of P/E Ratio could have resulted in general the fall of stock Market, returns in the
Malaysia context was rejected in this study, the results show that P/E ratio can project
future performance for stocks listed in KLCI.
Kelly (2011) undertook a study of industrial firms listed in Australian stock exchange.
The objective of the study was to investigate the association between the investment
performance and P/E ratios in order to evaluate potential for a P/E based trading strategy.
The study collected data for 1310 industrial firms for the period between 1998 and 2006
for 9 years. The returns and corresponding P/E ratio were ranked. The observed that
16
Australian capital market experience low P/E effect. Also noted that, even with use of
two business failure prediction models, better returns were reported. Returns even after
adjusting for risks concluded that by applying P/E based trading strategy, it is possible to
predict and record better returns. These, however violate the efficient market hypothesis,
semi strong form which Australia strong exchange is regard to have.
Study carried out by Pettersen (2011) covering 2000-2009 on firms listed in Stockholm
Stock Exchange examined if by understanding the use of price per share effect investor
can make abnormal returns and whether such an effect existed on the SSE. Researcher
constructed a portfolio with stocks with low P/E ratios. The P/E ratios for stock within
the large, mid and small cap on the SSE were calculated for period covering 1999-2008,
and then sorted from highest to lowest. A portfolio comprising 25 stocks with the lowest
ratios at the beginning of every year was selected and analysed and the portfolio return
for every year computed for 10 years, and Jensen’s index used to adjust for risk. The
research concluded that by use of P/E ratio, it is possible to make abnormal returns.
Study by Becker, Lee & Gup (2012) examined if S&P 500 P/E ratios mean reverting. The
study divided data into unit roots and multiple structural breaks. The concluded that the
P/E ratio is non stationary in short run around multiple breaks indicating in long run it
will be non stationary thus reverting to comparable average hence confirm mean revision
process. This result supported evidence that high P/E ratios relative to the current longrun mean will be followed by slow growth in stock prices and/or high earnings growth.
Leim & Sautma (2012) analysed predictability of stock return by using P/E Ratio and
also tested whether securities with low P/E Ratio record high future stocks return and on
the contrary, stocks with high P/E Ratio record low future stocks return. The study used
historical data covering 2005 -2010 from 45 listed firm of Indonesia. The research found
out that within short term (6 months), there is significance difference in returns of
portfolios between firms with low and high P/E ratio. However, in long run, where study
focused on stock held for more than six months up to four years, there were no significant
difference. The research concluded that there is no significant relationship between
17
trailing P/E ratio and stock returns hence P/E ratio is not a good predictor of long term
stock returns.
Davis, Aliaga & Thomas (2012) through their research on U.S. stock returns since 19262011entitled “forecasting stock returns: what signals matter?, what do they say now?”
Concluded that, future stock market returns have an inverse or mean-reverting
relationship, with valuation metrics like P/E ratio but only relevant in long horizons with
moderate explanation of about 40% of the time variation in net-of-inflation returns. This
is by plotting geometric and arithmetic annualized returns for 1935-2010 he predicted
historical stock returns. The researcher indicated that the results were uniform with both
cases where trailing earnings were cyclically adjusted .However, observed that as there
were large unexplained returns, the best conclusion is to assume a probabilistic
framework rather than good predictor of future returns thus not capable to predict in short
run.
Study undertaken by Kihara (2009) was to determine whether earnings growth can be
predicted by E/P ratio's of the companies listed at the Nairobi Stock and whether NSE
exhibits same results as in USA and Australia. The E/P ratio's for companies for
companies whose financial year end on December 31st were computed and assigned in to
quintiles. The findings showed that E/P ratios can be used to predict earnings changes.
This indicates that investors can use E/P ratio to establish the potential of growth of their
investment.
Osano (2010) through his study on an evaluation of price to earnings and price to book
values as predictors of stock returns of firms listed at the NSE tested on the extent of
predictive ability of price to earnings and price to book value in determining future share
returns. The use of P/E and PIB ratios as forecasting variable was examined using NSE
data from 1998 to 2002.The study focused on two portfolios of the firms: those which
had higher P/E and P/B ratios and those that had lower P/E and P/B ratios during the
preceding period i.e. 1998 to 2002.The firms which had median P/E and P/B ratio were
dropped. The returns for the subsequent five years 2003 to 2007 were used to evaluate the
predictive power of the two valuation multiple. A qualitative analysis was conducted by
18
use of paired T -tests to confirm whether there was significant difference between the
average returns for the two types of portfolios.
The conclusions drawn from the research were that the portfolio for firms with low P/E
and PIB ratios performed significantly better by achieving higher returns than the
portfolio for firms with high P/E and P/B ratios. Portfolio with low P/E performed best
then followed by portfolio with low P/B ratio. Coefficient of variation was used to
measure performance and it turned out that portfolio with low P/E' had lower coefficient
of variation, followed by low PIB portfolio. The worst performers were portfolio with
high P/B and P/E ratios. Study concluded that to enhance measurement and predicting
stock returns, it is important that the policy and decision makers' needs to regulate the
process of production of financial information so that they show accurate and correct data
which analysts and other users may rely on. Also recommended that, it is important to
enforce provision of accurate information which may be useful to users of financial
information, and investors and market players to can use these valuation multiples and
results could be compared with other valuation measures such as discounted cash flow
techniques.
Another study was carried out by Githinji (2011) with objective of determining the
relationship between P/E ratio and share prices of companies quoted at the NSE and to
establish the relationship between adjusted P/E ratios and share prices of companies listed
on the NSE. The study adopted a descriptive survey design. The population of interest
comprised all the firms listed on the NSE with a sample of 50 firms used in the study.
Secondary data was collected on P/E ratios for the selected firms as well as share prices
for a four year period beginning 2007-2010. Descriptive analysis correlation analysis and
regression analysis were carried out. The study concluded that both P/E ratio and PEG
ratios do not significantly influence stock performance of firms listed on the NSE. The
study recommended that investors should use a combination of methods to value stocks
in which to invest.
19
Local study carried out by Odiero (2013) was to establish the effect of the growth of
earnings and the growth of stock prices on the price earnings ratio of companies listed at
the NSE. The study population was all the companies listed at the NSE during the years
2003 – 2012 subdivided into 10 sectors of the Exchange. Secondary data was obtained
from the NSE Handbooks and adopted a descriptive survey design, Multivariate
correlation and regression analyses to test the relationship between the price earnings
ratio and the growth of earnings and stock prices. The study found that there existed a
moderate but positive association between the price earnings ratio and the growth of
stock prices, but an insignificant relationship between the price earnings ratio and the
growth of earnings. However, it found a moderate to strong positive association between
the growth in the price earnings ratio and the growth in stock prices, and a moderate and
negative association between the growth in price earnings ratio and the weighted average
annual riskless rate (the 91-day T-Bill rate). The association between the growth in price
earnings ratio and the growth in earnings was not insignificant.
The study found that these associations were more pronounced for shorter periods, i.e.
2003 – 2007 and 2008 – 2012, than for the entire 10 year period, and more pronounced
for 2008 – 20012 than for 2003 – 2007.The study concluded that the associations
determined for the NSE reflected similar empirical studies of other exchanges, and they
also suggested an efficient market in the weak form, with growth rather than value shares
dominating the exchange. The study recommended reform of the NSE to move it to an
efficient market in the semi-strong to strong form. It also suggested that further research
be undertaken using more refined data to authenticate these findings.
2.4 Chapter summary
The objective of the study is to assess the relationship between the P/E ratio and stock
returns for quoted firms in NSE. From the theories discussed diverging views are noted
where efficient market theory indicate that the existing relationship have been already
adjusted thus meaningless to compute P/E ratio. Random walk theory indicate that there
is no relationship but explained that these is due to behavior of investors in selecting
stocks which is random without considering fundamentals. However, value investing
20
theory indicate P/E ratio as a good predictor of future stock prices by computing the
intrinsic value and selecting the shares which appear undervalued. While EMT suggests
that stock is always efficiently priced and therefore you cannot outperform the market,
random walk theory suggests that price behavior is never based on anything predictable,
but is completely random.
Various foreign empirical studies conclude that there exist negative relationship between
the P/E ratio and stock returns on but local study found that there existed a moderate but
positive association between the price earnings ratio and the growth of stock prices.
However, the some studies indicate that P/E ratio can be used to prepare the investment
portfolio for long term while others indicate that expected stock returns are best stated in
a probabilistic framework, not as a “point forecast,” and only forecast on long horizon.
Other studies have found that there is no significant relationship between stock return and
P/E Ratio which suggesting that P/E ratio is not useful in estimating both in short term
and long term proposing using other methods. Others studies have concluded that the
high P/E ratio predict the future falls in stock prices and also the P/E ratio could act as an
indicator of the coming bear market. These observations provide support for a P/E based
trading strategy which can assist investor to record abnormal returns.
21
CHAPTER THREE
RESEARCH METHODOLOGY
3.1 Introduction
This chapter highlights the research design to use, the population from which the sample
were chosen, sampling size and technique applied, data collection and analysis method
that evaluated the data collected.
3.2 Research Design
The empirical study assessed the relationship between the P/E ratio and stock returns for
quoted firms in NSE. The study adopted descriptive research design and involved
collecting secondary data from NSE covering 2008-2013 for all listed firms. According
to Kothari (2004) descriptive research studies is concerned with specific predictions, with
narration of facts and characteristics concerning situation which fits well with our study.
3.3 Population and Sample
The research population will include all 61 quoted firms in NSE as at closing of calendar
year 2013. This is the only stock market in Kenya where securities are traded. The
sample consist of firms that have remained active during the period 2008-2013 to allow
sufficient data for computation of 3 months,6 months, 1 year, 2 year and 5 year. The
results are thus representative of the entire NSE for that period, giving good conclusive
validity. The study sampling design involved all the firms which Kothari (2004)
described as census inquiry as the number of firms are small and will result into high
chance of accuracy.
3.4 Data collection
The study used secondary data from the Nairobi Securities Exchange. 5 Year NSE
Handbooks, that provided listed company financial performance information for 5-year
22
periods, i.e. years 2008– 2012 and 2009-2013 hence all the data used in the study were
sourced from these two NSE Final Handbooks. From the data from NSE handbook, the
yearly returns were computed for five years. Kothari (2004) outlines that for secondary
source to be satisfactory, it should have the following characteristics namely reliability,
suitability and adequacy of data which NSE handbook we considered to have.
3.5 Data Analysis
The dependent variable in this research was stock return while the independent variable
as P/E Ratio. The returns were computed as follows:
Holding period Return (HPR) =Pt-Pt-1/ Pt-1
Where: Pt = Stock price at time t
Pt-1= Stock price at time t-1
Stock returns = Holding Period Return + Dividends received
The monthly stock returns were computed using the closing prices of stocks and any
dividends given. The mean were computed to obtain a representative return of each stock.
The data were also aggregated for each sector. In analyzing data, a time series auto
correlation of P/E ratio and returns on stock were conducted to check for consistency. A
time series auto correlation is a diagnostic tool for time series data analysis and helps in
describing the evolution of the process through time. Descriptive statistics and ANOVA
will be carried out to examine.
To ascertain the relationship between the P/E ratio and stock returns, the data of the
annualized return of sampled quoted firms in NSE and P/E ratio between 2008 and 2013
were presented in a graph to determine whether there exists a possible linear relationship.
Multiple regression between P/E Ratio and stock return were carried out to examine the
relationship between both variables. Control variables included return on equity and
Market price to Book value.
23
The linear regression model was derived from previous studies described in the literature
review as the major determinants of stock returns. Githinji (2011) & Odiero (2013) in
their studies also used the model as follows:-
Yi = Bo + M1Xi + M2X2 +M3X3+ et
Where Yi = average stock return for holding period one, two and five years.
Bo = Intercept of regression line
M1 = Coefficient of P/E ratio
M2= Coefficient of Return on equity (ROE)
M2= Coefficient of Market price to Book value (MBV)
X1 = P/E ratio
X2 = Return on equity (ROE)
X3 = Market price to Book value (MBV)
et = Error term
To ascertain the ability of P/E ratio in predicting future returns, we measured the degree
of relationship between the variables using Karl Pearson’s co-efficient of correlation (r)
which measure both the nature and strength that exist between the two variables. The
computed value by Excel was expected to be between
-1 and +1.Positive indicate
positive correlation between P/E ratio and stock return while negative indicate negative
correlation meaning inverse relationship. A zero value of ‘ r’ was to indicate that there is
no association between the two variables. In predicting, the value of ‘ r’ nearer to +1 or -1
indicates high degree of correlation between the stock returns and P/E ratios hence level
of predictability. Hypothesis testing of correlation co-efficient to determine whether
Correlation co-efficient is indicative of significant correlation was carried out using t test,
95 % confidence level and degree of freedom as n-2.
24
CHAPTER 4
DATA ANALYSIS AND PRESENTATION OF FINDINGS
4.1 Introduction
This chapter lays out the method used to analyse the data collected for this study and the
results obtained from that analysis. It also discusses the nature and meaning of these
results. Section 2 explains the methods employed in the analysis, and sets out the results
from the analysis, while section 3 discusses those results.
4.2 Data Presentation
The study developed several excel spreadsheets to capture for each listed company the
data required to determine the envisaged relationship between the dependent variable
(Stock return) and the independent variables which are P/E ratio, ROE and MBV. As a
starting point, the study created a master spreadsheet (master 1) divided into 13 sections
for 2009-2013. One section contained a column of the listed companies grouped by
sector. These were 61 companies classified into 10 sectors. The next section contained a
column for the stock returns computed by calculating the annual change using the share
price as at the closure of financial year for every firm and also adding the dividends per
share paid.
The last three columns were inserted the three independent variables namely P/E ratio,
ROE and MBV for all the firms. For the actual data analysis, 34 firms as firms with
missing data and those firms not operating for the entire five years in review were not
considered in the analysis. Using Ms-Excel, the data were run and multiple regression
results were recorded. Correlations of variables were also undertaken and correlation
coefficient results also recorded.
25
4.2.1 The Analysis of the NSE Quoted Firms
NSE FIRMS
Agricultural Sector
Automobiles and Accessories
Banking
Commercial and Services
Construction and Allied
Energy and Petroleum
Insurance
Investment
Manufacturing and Allied
Figure 1.1: NSE listed firms
According to figure 1.1 above that represents the all 61 quoted firms in NSE as at January
2014 with 10 sectors. Banking sector is the largest sectors with 16% followed by
commercial and service sector with 13%. Telecommunication & Technology is the
lowest with 3% of the total firms quoted. Agriculture, which is one of the country
economic sector and Manufacturing both have 11% each. The analysis per sector can be
linked to Kenya Economic review report 2013 where financial sector is expected to drive
high levels of savings and financing of Kenya’s investment needs.
The Economic report further states that these has resulted to increases institutions in the
sector where both quoted and non quoted are 43 commercial banks,1 mortgage finance
company, 5 representative offices of foreign banks, 8 deposit taking microfinance
26
institutions, 112 foreign exchange bureaus. The manufacturing sector in Kenya
constitutes 70 per cent of the industrial sector’s contribution to GDP with building,
construction, mining and quarrying cumulatively contributing the remaining 30 per cent.
Agriculture is another key sector although its returns are affected by climate. Report also
indicates that recent country growth has largely been driven by growth in domestic
household consumption and investment. These have direct relations with the number of
firms in each sector of listed firms.
4.2.2 The Analysis of the Stock Returns and P/E Ratio for All Sectors
for 2013
50.00
40.00
30.00
20.00
stock return
P/E ratio
10.00
-
(10.00)
Figure 2: Stock returns & P/E ratio per sector
27
According to the figure 2 above, various sectors record different P/E ratios differing with
sectors. These were also recorded among the firms in the sector. The graph indicate
mixed relationship where high stock return for insurance and manufacturing sector have
record low P/E ratio. But the relationship is positive. However in Energy sector, the
negative stock returns have zero P/E ratios while Low stock return for Automobile and
Accessories have high P/E ratio. Also noted, that the Banking sector has the highest
average P/E ratio for 2013 as compaired to other sectors. The banking sector has been
recording good performance for the last five years.
4.2.3: Correlation Analysis Between Stock Return Versus P/E Ratio,
ROE and MBV for All NSE Firms
The data on Stock return versus P/E Ratio, ROE and MBV was analyzed for correlation
using the Ms-Excel and the results were as indicated in the table below.
Table 1
Stock return
PE Ratio
ROE
MBV
Stock return P/E Ratio
1
-0.05657
1
0.295867
-0.58254
0.415436
-0.10122
ROE
1
0.584075
MBV
1
Correlation analysis is helpful in revealing whether there is a positive or negative
relationship between the independent and dependent variables. According to Rasli
(2006), if the absolute r-value is above 0.196, then there is a mild correlation. A
correlation can be concluded if the absolute r-value is above 0.5 at 95 % confidence level
and degree of freedom as n-2. The value of ‘ r’ nearer to +1 or -1 indicates high degree of
correlation between the stock returns and P/E ratios hence level of predictability .The
results of the table were interpreted as follows:
There was insignificant negative
relationship between stock returns and P/E ratio since the coefficient of correlation was 0.05657; There was a mild positive relationship between stock return and ROE since the
coefficient of correlation was 0.295; There was a positive relationship between stock
returns and MBV since the coefficient of correlation was 0.415. However, the analysis
28
indicates moderate negative relationship between P/E ratio and ROE since the correlation
was -0.58254. Also moderate positive relationship between MBV and ROE since the
coefficient of correlation was 0.584075.The positive correlations among stock return,
ROE and MBV and negligible negative correlation of P/E ratio confirm some degree of
consistency in the data analysis using multiple regression. These is in a agreement with
study Githinji (2011) that concluded that both P/E ratio and PEG ratios do not
significantly influence stock performance of firms listed on the NSE and Vorek (2009)
which concluded that in long run (5 years) there were no significant relationship and
concluded P/E ratio not a good indicator of future performance.
4.2.4: Multiple Regression with Stock Return and P/E Ratio, ROE and
MBV for All NSE Firms
A multiple regression analysis was carried out on the three independent variables (P/E
Ratio, Return on equity and market price to book value) against one dependent variable
(Stock return) and the results were as shown in the table below:
Table 2. Multiple linear regression results table
Intercept
X Variable 1
X Variable 2
X Variable 3
Coefficients
-9.8379
0.063756
25.71168
8.848523
Standard
Error
t Stat
P-value
10.70708 -0.91882 0.365518
0.288022 0.22136 0.826312
57.75921 0.445153 0.659405
5.519444 1.603155 0.119379
Where:
X 1: P/E Ratio
X 2: Return on equity
X 3: market price to book value
Table 2 above clearly shows that market price to book value have strong influence to
Stock return while P/E Ratio and ROE have very low insignificant relationship. However,
all the three variables have positive relationship. When the table is reduced into a
regression model, the following would be the regression equation:Y = -9.8379 + 0.063756X1 + 25.71168X2 + 8.848523X3
29
Given that the coefficients values of X1, X2 and X3 were all positive (0.063, 25.71 and
8.84) there is insignificant but positive relationship between the three variables and stock
returns. This indicates that increase (decrease) of P/E ratio, ROE and MBV result in
increase (decrease) in stock returns.
Table 3: Summary Output
Regression Statistics
Multiple R
0.422171
R Square
0.178228
Adjusted R Square
0.096051
Standard Error
25.76946
Observations
34
The coefficient of determination (R Square) of 0.178228 showed that the predictability
strength of the model is very low. The regression results therefore indicated that P/E ratio
was not a good determinant of the stock returns.
The reliability of the above model is supported by the following ANOVA table 4 below:
Table 4: ANOVA results table
df
Regression
Residual
Total
3
30
33
SS
4320.736
19921.94
24242.68
MS
1440.245
664.0648
F
Significance F
2.168832
0.112392
The ANOVA table further described that the strength of the regression model specified
was low. This was because F values were very low (0.112392) at 95% confidence level.
The critical F is estimated at 2.50 while the actual F is 2.168832. This means that since
the actual F is less than the critical F statistic, null hypothesis (P/E ratio not a good
predictor of stock return) is to be accepted. Therefore investors cannot rely and make
abnormal returns using P/E ratio as there is no good relationship between stock return and
P/E ratio.
30
4.2.4: Correlation Analysis and Multiple Regression per Sector
The tables in the Appendix represent the relationships identified by the specific
correlation and regression analyses for the 10 sectors of the NSE over the 5year period.
The stock returns and P/E ratio had positive weak correlation (0.221413) with both ROE
and MBV have positive but still weak correlation (0.340972 and 0.302377) in the
Agricultural sector. However, positive strong relationship between ROE and MBV were
recorded of 0.899631.In banking sector, the stock returns and P/E ratio negative weak
correlation (-0.35386) but moderate negative correlation with ROE (-0.49597) and strong
negative correlation with MBV (-0.69448). Also positive strong relationship between
ROE and MBV were recorded of 0.813899.
Stock return had negative weak relationship between the P/E ratio (-0.16342) and ROE (0.03257) but strong positive correlation with MBV (0.8114) in the Commercial and
Investment segments. Negative strong relationship was noted between the P/E ratio and
ROE. In construction sector, the stock returns have moderate negative relationship (0.5334) and weak negative correlation with MBV (-0.26933) but positive weak
relationship with ROE (0.128313).However, P/E ratio has strong correlation with ROE
and MBV. ROE have strong positive relationship with MBV of 0.911548.
Energy, Insurance and Manufacturing sectors have weak positive relationship between
the stock returns and P/E ratio (0.165351, 0.05447 & 0.381515) but ROE have strong
positive relationship with stock return for all the three sector ( 0.928852, 0.976964 &
0.932369).Also ROE have strong positive relationship with MBV for all the sector. These
indicate that ROE can be a better estimate of stock returns as compaired to P/E ratio.The
general positive weak relationship between the stock returns and P/E ratio is widely
reflected in almost all sectors. These indicate that stock return is not a good predictor of
stock return as it has low correlation. However, analysis indicate stock returns can be
better explained by ROE as it has moderate to strong positive correlation in major sector
namely Energy sector, insurance and manufacturing sectors.
31
4.3 Summary and Interpretation of Findings
The research analysed 61 firms quoted in NSE for the period 2009-2013 for 10 sectors.
Each firm P/E ratio, ROE, MBV and stock returns were analysed and presented in
graphs. First, according to the percentage of firms in a certain sector, the banking has the
highest. These is attributed to recent good performance by the financial institutions with
recorded better financial transactions .Telecommunication & Technology is the lowest
with 3% of the total firms quoted as the countries is embracing the technology.
Further, analysis of stock returns with P/E ratio for various sectors recorded different P/E
ratios differing with sectors. These were also recorded among the firms in the sector. The
observations contradicts the Estrada (2003) study which concluded that Companies in
sectors like telecommunications tend to have high P/E ratios reflecting a growth
orientation due to the fact that industries enjoy a surge of popularity and industries in
utilities and mining tend to have low P/E ratios reflecting a value orientation. The
analysis indicates low P/E ratios recorded in telecommunication and technology and high
P/E ratio in Automobiles and Accessories.
Also noted that the Banking sector has the highest average P/E ratio for 2013 as
compaired to other sectors. These concurred with Danielson, Hirt & Block (2009) that a
firm that have good expectation for future tend to trade at high P/E ratio .The banking
sector has been recording good performance for the last five years.
The graph indicated mixed relationship where high stock return for insurance and
manufacturing sector have record low P/E ratio. But the relationship is positive. However
in Energy sector, the negative stock returns have zero P/E ratio while Low stock return
for Automobile and Accessories have high P/E ratio. These finding indicate mixed
observations concur with finding by Leim & Sautma (2012) there is no significant
relationship between trailing P/E ratio and stock returns hence P/E ratio is not a good
predictor of long term stock returns.
32
Correlation Analysis between Stock return versus PE Ratio, ROE and (MBV) were
computed using Ms Excel and the observations were a mild positive relationship between
stock return and ROE since the coefficient of correlation was 0.295; There was a
somewhat positive relationship between stock returns and MBV since the coefficient of
correlation was 0.415.However,the analysis indicate moderate negative relationship
between P/E ratio and ROE since the correlation was -0.58254.Also moderate positive
relationship between MBV and ROE
since the coefficient of correlation was
0.584075.The positive correlations among stock return, ROE and MBV and negligible
negative correlation of P/E ratio confirm some degree of consistency in the data analysis
using multiple regression.
These is in a agreement with study by Githinji (2011) that concluded that both P/E ratio
and PEG ratios do not significantly influence stock performance of firms listed on the
NSE and Vorek (2009) all observed that in long run (5 years) there was no significant
relationship and concluded P/E ratio not a good indicator of future performance.
However the study concluded that there was strong relationship between ROE and MBV
and MBV can be a better predictor of stock returns than the P/E ratio.
Due to the insignificant correlations coefficients of stock returns and P/E ratio, these
concurs with Ou, Jane & Stephen (1989) who observed that although P/E ratio can reveal
current and projected earnings, they do not always result to excess profits in the stock
market. These was further explained by Balvers, Cosamino, & MacDonald (1990) who
concluded that the advantages derived from predictive ability of stock returns using P/E
ratio are offset by proceeding fluctuations in stock returns.
A multiple regression analysis carried out on the three independent variables (P/E Ratio,
Return on equity and market price to book value) against one dependent variable (Stock
return) and the results indicated that market price to book value have weak influence to
Stock return while P/E Ratio and ROE
have very low insignificant relationship.
However, all the three variables have positive relationship. These insignificant
relationship can be explained by observations of Reilly & Brown (1997) that in depth
security analysis is costly and time consuming hence most financial analyst use readily
available information like dividend yield, EPS growth rate and P/E ratio. These as a
33
result, value oriented investors would focus on the stock price fluctuations with
expectation of future market correction as a result of underlying better fundamentals of
firm.
The study also concurred with Davis, Aliaga & Thomas (2012) who found that the stock
returns and valuation metrics like P/E results were uniform with both cases where trailing
earnings were cyclically adjusted .However, observed that as there were large
unexplained returns, the best conclusion is to assume a probabilistic framework rather
than good predictor of future returns thus not capable to predict in short run.
The study concluded that there is low relationship between stock returns and P/E ratio.
These can be concluded that the NSE is weak to semi strong form EMH is where the
current stock market prices reflect all security market data like trading volume data and
the historical rates of return. This form indicates that no relationship between the stock
exchange data and expected rate of return. Although it has some characteristics of Semi
strong form EMH where some public information involving market and non-market
information like political news and dividends announcements are incorporated fully in
stock market price, the NSE need to develop to strong EMH.
34
CHAPTER 5
SUMMARY, CONCLUSIONS AND RECOMMENDATIONS
5.1 Summary
The objective of the study was to assess the relationship between the P/E ratio and stock
returns for firms quoted in NSE. Review of literature was undertaken and stock return
which was the dependent variable was noted as composing of stock appreciation
/depreciation and dividends paid. P/E ratio was the independent variable which was to be
assessed as to whether relationship with the stock returns.
Three theories relating to P/E ratio namely Random Walk theory by Malkiel (1973),
efficient market theory and Value investing theory by Graham & Dodd (1934) explains
how the ratio relates to future firms share performance and how the ratio can predict
future returns. The theories have mixed conclusions with random walk and efficient
market theory indicating no relations that exist but Value investing theory concludes that
one can make better results thus positive relationship between P/E ratio and stock return.
The researcher collected the secondary data from NSE handbook and extracted the stock
returns, P/E ratio, ROE and MBV for all 61 for quoted firms. Ms Excel was used to
analyze the data and presented through pie charts and bar graphs. Pearson’s correlation
coefficient and multiple regressions were carried out to analyze the data.
The researcher found out that there exist insignificant relationship between P/E ratio and
stock return but the relationship is positive using correlation. However, P/E ratio has
inverse relationship with ROE which is moderate .ROE have moderate positive
relationship with MBV.
Also found out that different sector record different P/E ratios which also vary per firm in
a sector. These also cut across from telecommunication sector to agriculture. These can
be contributed to the optimistic performance the individual firm have and how investors
view the future performance of the firm.
35
5.2 Conclusions of the Study
The study on the relationship between the P/E ratio and stock returns for firms quoted in
NSE indicate that the relationship is positive but insignificant. These is confirmed by the
‘t’ Stat of 0.22136 and P value of 0.826312.These concurs with Odiero (2013) concluded
that P/E ratio and the growth of stock prices have moderate positive association. Also
concurred with Githinji (2011) that stock performance do not have any significant
relationship with P/E ratio and PEG ratios for NSE listed firms.
The observations supported Random Walk theory by Malkiel (1973) which suggested
that price behavior is never based on anything predictable, but is completely random and
efficient market theory suggests that stock is always efficiently priced and investor
cannot outperform the market except as a consequence of luck.
Previous studies indicated that some sectors like telecommunications tend to have high
P/E ratios due to the fact that industries enjoy a surge of popularity
while others like
utilities and mining tend to have low P/E ratios reflecting a value orientation. These are
not the case in NSE listed firms in Kenya as they have different P/E ratios.
Literature review had indicated that firm that have good expectation for future tend to
trade at high P/E ratio ,a position confirmed where the banking sector have the highest
P/E ratio as compaired to other sectors and can be ranked as sector with good
expectations as compaired with sectors like Agriculture. Investors and market players
should be encouraged to use these valuation multiples and results could be compared
with other valuation measures such as Discounted Cash flow Techniques.
The study also confirmed that there is no significant relationship between stock returns
and P/E ratio and conclude P/E ratio not a good indicator of future performance.
However, the study concludes that there is strong relationship between ROE and MBV
and MBV can be a better predictor of stock returns than the P/E ratio.
36
5.3 Policy Recommendation
Financial information is one of the key components guiding the classification of security
market as weak, semi-strong or strong form. The comprehensive financial data as per the
NSE is found in NSE Handbook which is prepared on yearly basis. However, the
Handbook is released too late (after 1 year).Some of the information are not accurate
while others missing. We recommend the NSE to invest further on the financial
information, and prepare the handbook on time and accurate. The handbook needs to be
freely accessible by putting in their website. Also need to consider have one Hand book
which is continuous thus covering the short term (recent six month data) and long term
(more than 5 years)
Ratios can be used to assess the financial strength and capacity of the firm. However, the
ratios and financial statements are limited to new information which affects the investor’s
returns. We recommend the NSE to post all the key information in their website for
investors to access and make informed decisions. Also need to include strength of the
audit committees and other major internal controls.
All quoted firms prepare their financial reports annually for annual general meeting to the
shareholders. However, the financial statements are prepared with different treatment
where the International Accounting Standards have the benchmark and alternative
treatments. These can bring inconsistent view according to which approach it is recorded.
We recommend having one treatment for uniformity and also ensuring all firms comply
with the standards.
With advanced technology, the financial statements of all quoted firms can be readily
available and analysed easily. We recommend the NSE to have in their website, software
for computing all the ratios and interrogating financial statements with ease like
predicting the expected stock returns or return on equity with the financial data given.
These will make the NSE a strong market.
37
5.4 Limitations of the Study
This study has tested only the relationship between high P/E ratios and stock quoted in
NSE. The research covered five years between 2009-2013.These is limited as it cannot be
clearly indicate the relationship in long run. Future researchers could expand the time
horizon to be more accurate.
The data required was in NSE Handbook for 2013 and 2014. However, some of the data
was not available as some firms were not in operation in the entire period like Uchumi
while other data were not indicated in the Handbook. Others had not been listed by then.
This was the case for the various sectors like the banking, insurance, investment and
energy segments. This limitation meant that instead of all 61 firms listed, only 34 firms
were analysed as they had complete data covering five years. These affected the some
sectors like Telecommunication sector which had two firms but only one firm had data
(Access Kenya) hence not used. Also challenge where some sectors had more firms as
compaired to other sectors.
The computations of P/E ratios used market price per share as at the end of financial year.
However, firms have different financial year end dates. These may affect the observations
made and also the comparability as they may be affected by the country atmosphere like
in the month of election.
Comparison of various sectors and firms require firm to have similar shares through out
or adjusted for the changes in share holding. The information for various share
movements like split orders, bonus shares and whether the EPS is diluted or basic .These
shareholding transactions is not clearly indicated in the NSE handbook .In some cases,
firms published their financial statements using IFRS –compliant formats. Others stuck to
traditional formats, resulting in different formats of presenting income and per share data.
IFRS compliant formats require a two stage income presentation: the Income Statement
and the Statement of Comprehensive Income. The traditional method is the basic Profit &
Loss A/c.
38
5.5 Suggestions of Further Studies
Further research should be conducted using more refined data than used in this study. For
example, per share data should be based on average number of shares outstanding for the
year rather than the number of shares outstanding at the end of the year. Market price per
share should similarly be a weighted average stock price for the Year, rather than the
closing stock price, which may not reflect the share’s performance for the entire year or
relate realistically to the company’s overall performance for that year.
This research uses P/E ratio as reported in the company’s audited financial statement. The
earnings as denominator to some firms include extra ordinary items where other exclude.
For further research, the usage of normalized EPS (exclude extraordinary items from
earnings) or estimate EPS instead of reported EPS could be explored. This research could
be extended in term of period of analyses, portfolio rebalancing, and other independent
variables or research methodologies. Decomposition of P/E Ratio into a fundamental
component and a mispriced component can be carried out to gain deeper under-standing
and more useful investment tools for investment strategy.
The study analysed the firms listed in the NSE in Kenya for five years in 2009-2013.
These are limited as it cannot be clearly indicate the relationship in long run. Future
researchers could expand the time horizon to be more accurate .As such it can cover 20
years and as if P/E ratio is a good predictive model of stock return.
The investor main objective is to make return. The study has indicated moderate
relationship between market to book value and stock return than P/E ratio and stock
return. Further study can be carried out to assess whether the MBV can predict the stock
returns in both short and long term for firms listed in NSE.
39
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45
APPENDIX
Firms Quoted in Nairobi Securities Exchange
SEGMENT
FIRMS LISTED IN THE SEGMENT
Agricultural
Telecommunication & Technology
Eaagads Ltd, Kakuzi Ltd, Kapchorua Tea Company
Ltd, Limuru Tea company Ltd, Rea Vipingo
Plantations Ltd, Sasini Tea and Coffee Ltd,
Williamson Tea Kenya Ltd
Car and General (Kenya) Ltd, CMC Holdings Ltd,
Marshalls (EA) Ltd, Sameer Africa Ltd
Barclays Bank of Kenya Ltd, CFC Stanbic Bank
Ltd, Diamond Trust Bank Kenya Ltd, Equity Bank
Ltd, Housing Finance Company of Kenya Ltd,
I&M Holdings Ltd, Kenya Commercial Bank Ltd,
National Bank of Kenya Ltd, NIC Bank Ltd,
Standard Chartered Bank Ltd, Co-operative Bank
of Kenya Ltd
Express Kenya Ltd, Kenya Airways Ltd, Longhorn
Kenya Ltd, Nation Media Group Ltd, Scan group
Ltd, Standard Group Ltd, TPS (EA) Ltd, Uchumi
Supermarket Ltd.
Athi River Mining Ltd, Bamburi Cement Company
Ltd, Crown-Berger Kenya Ltd, East African Cables
Ltd, East African Portland Cement Company Ltd
KenGen co. Ltd, KenolKobil Ltd, Kenya Power &
Lighting Ltd, Total Kenya Ltd , Umeme Ltd.
British America Investment Co Ltd, CIC insurance
Group Ltd, Jubilee Holdings Ltd, Kenya
Reinsurance Corporation Ltd, Liberty Kenya
Holdings Ltd, Pan Africa Insurance Company Ltd
Centum Investment Company Ltd (ICDCI),
Olympia Capital Holdings Ltd, Trans-century Ltd.
BOC Kenya Ltd, British American Tobacco Kenya
Ltd, Carbacid Investments Ltd, East African
Breweries Ltd, Eveready East Africa Ltd,Kenya
Orchards Ltd, Mumias Sugar Company Ltd, Unga
Group Ltd
Safaricom Ltd
Growth Enterprise Market Segment
Home Afrika Ltd
Automobile & Accessories
Banking
Commercial and Services
Construction & Allied
Energy & Petroleum
Insurance
Investment
Manufacturing & Allied
Source: Nairobi Exchange Website
46
Table A1: Agriculture
Stock return
1
0.221413
0.340972
0.302377
Stock return
P/E Ratio
ROE
MBV
P/E Ratio
ROE
MBV
1
0.416149
1
0.2475 0.899631
1
Table A2: Banking
Stock return
P/E Ratio
ROE
MBV
Stock return P/E Ratio
ROE
MBV
1
-0.35386
1
-0.49597
0.149175
1
-0.69448
-0.14205 0.813899
1
Table A3: Commercial service
Stock return
P/E Ratio
ROE
MBV
Stock return P/E Ratio
ROE
MBV
1
-0.16342
1
-0.03257
-0.97307
1
0.8114
-0.52894 0.424734
1
Table A4: Construction
Stock return
Stock return
P/E Ratio
ROE
MBV
1
-0.5334
0.128313
-0.26933
P/E Ratio
ROE
MBV
1
0.633317
1
0.757648 0.911548
Table A5: Energy
Stock return
P/E Ratio
ROE
MBV
Stock return P/E Ratio
ROE
MBV
1
0.165351
1
0.928852
-0.21177
1
-0.15293
0.949345 -0.50815
1
47
1
Table A6: Insurance
Stock return
P/E Ratio
ROE
MBV
1
Stock return
-0.05447
1
P/E Ratio
0.976964
0.158721
1
ROE
0.702945
0.592961 0.828147
1
MBV
Table A7: Manufacturing
Stock return
P/E Ratio
1
0.381515
0.932369
0.933783
Stock return
P/E Ratio
ROE
MBV
ROE
MBV
1
0.308718
1
0.45586 0.987276
1
Table A8: Summary Output -Agriculture
Regression Statistics
Multiple R
0.985181
R Square
0.970582
Adjusted R Square
0.882328
Standard Error
13.70127
Observations
5
ANOVA
df
Regression
Residual
Total
Intercept
X Variable 1
X Variable 2
X Variable 3
SS
MS
F
3 6193.544 2064.515 10.99756
1 187.7247 187.7247
4 6381.268
Standard
Coefficients
Error
t Stat
P-value
89.60409 25.8834 3.461837 0.179023
-0.31004 1.286151 -0.24106 0.849408
-366.927 237.6231 -1.54416 0.365858
-6.73098 25.51625 -0.26379 0.835805
48
Significance
F
0.217307
Lower 95%
-239.276
-16.6521
-3386.21
-330.946
Upper
95%
418.4838
16.03206
2652.361
317.4838
Table A9: Summary Output –Banking Sector
Regression Statistics
Multiple R
0.352516
R Square
0.124268
Adjusted R
Square
-0.75146
Standard Error
26.83832
Observations
7
ANOVA
df
Regression
Residual
Total
Intercept
X Variable 1
X Variable 2
X Variable 3
3
3
6
SS
MS
F
306.6331 102.211 0.141902
2160.886 720.2954
2467.519
Coefficients
-30.1711
1.621505
74.85935
1.632156
Standard
Error
t Stat
P-value
83.81569 -0.35997 0.742719
9.853195 0.164566 0.879749
405.48 0.184619 0.865303
46.5931 0.03503 0.974256
49
Significance
F
0.928469
Lower 95%
-296.91
-29.7358
-1215.56
-146.648
Upper
95%
236.5678
32.97877
1365.278
149.9122