Market information and stock returns the nepalese evidence


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This is a Nepalese Stock Market research on the market information and its effects on stock price. More specifically, this study gauge the political effect, media effect, news coverage effect, determine the investors' priority prior to making investment decisions and finally and most importantly, the study provides the evidences that how long of historical data base are useful for investment decision making. I hope every one enjoy the research work.

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Market information and stock returns the nepalese evidence

  1. 1. 1 Chapter 1 INTRODUCTION1. 1 General BackgroundFrom the past decades, the financial market has been suffering from the unforeseen andsudden economic turbulences that have been directly or indirectly contributing for stockreturns movements. Identifying the factors affecting stock returns is not an easy task forthe financial economists, academicians and practitioners. To grasp some ideas through thesystematic procedure, the financial community felt the need of separate discipline so thatthe new discipline can solely deals with the management of financial assets. Theinvestment management and the portfolio theories are the outcomes of such efforts. Theevolution of investment management and the portfolio theory have long history. Thedevelopment of investment management can be traced chronologically through threedifferent phases (Francis, 1986). The first phase could be characterized as the speculativephase before 1929. During the 1930s investment management entered in its second phase,a phase of professionalism. Then, the investment industry began the process of upgradingits ethics, establishing standard practices and generating a good public image. As a result,the investment markets became safer places and the ordinary people also began to invest.Investors began to analyze the securities seriously before undertaking investments. Then,the investment community entered into its third phase, the scientific phase afterMarkowitz‘s study in 1952.Markowitz (1952) which is a single-period model and attempted to quantify the risk and itshowed that the risk in investment could be reduced through proper diversification ofinvestment which required the creation of a portfolio. The Markowitz study was extendedto CAPM in 1960s by Sharpe (1964), Lintner (1965) and Black (1972). The CAPMexplains the overall market performance that determines the stock returns. Then, theassets valuation models became the most popular area of study in Finance in developed,developing and the transitional economies. In other words, the history of development ofthe portfolio theories and its practices enter into the professionalism and scientific phase.The empirical evidences of Stattman (1980), Chan, (1991), Brav, (2000), Danieland Titman (2006) among others documented the book-to-market equity effects on stockreturns; earnings-to-price effects by Basu (1977), earning effects by Jafee, (1989),Fama and French (1995) and La Porta (1996) among others; Banz (1981), Vassalou andXing (2004) and Fama and French (2008) depicted the size effects, similarly, cash flows
  2. 2. 2effects by Berk, (1999) and Vuolteenaho (2002) among others are the major studiesthat documented the firm specific accounting variables are the major sources of stockreturns changes. Whereas in the later period, more focus was given towards thebehavioral aspects like investors‘ characteristics and behavioral issues and marketbehavior, news effects, media effects, etc. In sum, the recent focus has shifted towards theintangibles rather than the fundamental effects on stock returns. The studies on humanpsychology and behavioral issues, Einhorn, et al. (1978) documented that people havegreat confidence in their fallible judgment. Similarly, Einhorn (1980) conformed that theoverconfidence in judgment showed that the contribution of behavioral factors in stockreturns. Ikenberry, (1995), Odean (1999), Kaniel, (2008), Foucault, (2011),and Doskeland and Hvide (2011), among others, are the major studies documented thatinvestor behavior is the major aspect of stock returns movements. With these evidences,the general learning in the investment community is that the event that burst outexpectedly or unexpectedly that has significant impact on investors‘ mindset so that suchinformation plays crucial roles in individual investment decisions making, in totality oninvestment performance.After the evolution of the assets valuation models, there has been the considerable shift ofthe literature towards predicting returns and developing the forecasting tools andtechniques. But, there is lack of consensus upon single model, tools and procedures. Forinstance, Fama (1972) divided the stock returns into selectivity and risk, changes inexpected future dividends or expected future returns (Campbell, 1991), cash-flow newseffect (Vuolteenaho, 2002) and Daniel and Titman (2006) proved that stock return is afunction of tangible and intangible return. These empirical evidences focused towards thestock return decomposition which helps to identify the dimensions of returns. Nowadays,stock returns forecasting became the central issue in Finance and the numerous studieshave been articulated to scan the manifestations of returns. Moreover, the volatileeconomic environment also helps to justify these efforts. In the behavioral studies, DeLong, (1990) depicted that the overreaction of prices is due to news, price bubblesand expectations; sophisticated investors can earn superior returns by taking advantage ofunder-reaction and overreaction without bearing extra risk (Barbaris, et al., 1998) andasset prices are influenced by investor overconfidence (Daniel and Titman, 2000). Further,the analysis of intangible information is made by Sun and Wei (2011) documented thatinvestors are overly sensitive to intangible information when they need to make moresubjective judgments. Similarly, many investors consider purchasing only stocks that
  3. 3. 3have first caught their attention (Odean, 2008). These evidences suggest that theinvestment decisions are more than models and numbers so that the importance offinancial theories and behavior of the decision makers have been raised significantly. Ontop of the behavioral evidences, number of studies revealed that the existence ofrelationship of stock returns with, for instance, earnings, cash flows, dividends, returnsitself, market equity (size), book-to-market equity, leverage, etc. Size and book-to-marketequity provide a simple and powerful characterization of the cross-section of averagestock returns (Fama and French, 1992, Daniel and Titman, 1997) and on the contrary,Kothari, et al., (1995) documented the relationship between book-to-market equity andstock returns is weaker and less consistent.Similarly, under the branches of intangibles, the media and news events also effects onstock returns. The major evidences are: the media coverage, public relations and othermarketing activities could play an important causal role in creating and sustainingspeculative bubbles and fads among investors (Merton, 1987), similarly, Tetlock (2007)showed the media pessimism effect on stock trading, and Engelberg and Parsons (2011),among the others are major studies in media effects on stock returns. With the samefashion, the news events also affect the stock returns (Campbell and Hentschel (1992),Boyd, (2005), Zhang (2006) and Hirshleifer, (2009), among others).Apart from the voluminous studies in the developed and western economies, limitedstudies have been conducted in the developing and transitional economies like Nepal. Thepositive relation between stock returns and size where as inverse relation between returnsand market-to-book value (Pradhan, 1993), the positive relation of stock returns withearning yield and size whereas negative relation with book-to-market ratio and cash flowyield and book-to-market value (Pradhan and Balampaki, 2004). These studies providedthe evidences that book-to-market equity and size are the major determinant of stockreturns even if the capital market is inefficient in nature.The study of the stock returns and market information occupies an important place infinancial management. It has received much attention in recent years for identifying themarket signals to achieve relatively higher stock returns. The evidences on the stockreturns and market information indicate that this area is useful for financial decisionmaking process. More specifically, the insight from the analysis of stock returns andmarket information are useful to achieve the short-run stock returns while the marketbecame more volatile due to various influences like the news effect, political effect, the
  4. 4. 4fundamental information disclosure effect, etc. The momentum and trend in varyingcircumstances, magnitude and directions help to pretend the future development of stockmarket. In general, the market signals provide in-depth knowledge about the effects andranges of market information in different period of time. Thus, the market deserved theneed for extensive studies on market information and stock returns thus became animportant area of study in recent years. With this perspective, the study devoted to marketinformation and stock returns may be a rewarding one both for the academicians andpractitioners.1.2 Statement of the problemFinancial economists and investors have spent considerable time searching for investmentstrategies that could help to yield sustainably above the average returns but, the reliableone is yet to be found. Several studies have been attempted to identify the most importantand the consistent firm specific fundamental variables which help to explain the specificeffects on stock returns and price movements. For instance, earning yield effect of Basu(1977), size effect of Banz (1981), leverage effect of Bhandari (1988), book-to-marketeffect of Stattman (1980 ), joint effect of beta, size, leverage, book-to-market equity andearning yield of Fama and French (1992), book-to-market equity and cash flow yieldeffect of Chan, (1991) and the price-scaled variables: sales to price, cash flow toprice, earning to price and book to price ratios of Daniel and Titman (2006) are some ofthe major studies.Beyond the firm specific accounting variables as market information and its effect onstock returns, the intangible information effect like; the media effect, news event effect,political party led government, lag variable effects, past performance, stock marketbehavior and investors‘ sentiments, etc have also been contributing for the market pricemovements. Some field evidences showed that news events lead some investors to reactmore quickly. Among others, past long-term losers have outperformed past long-termwinners (―long-term reversal,‖ De Bondt and Thaler (1985)), past short-term winnershave outperformed past short-term losers (―momentum,‖ Jagadeesh and Titman (1993)),high book-to-market-equity firms (―book-to-market anomaly,‖ Rosenberg, (1985)),controlling for other characteristics, firms with higher profitability have earned higheraverage stock returns (Haugen and Baker (1996)), high-leverage firms have historicallyoutperformed low-leverage firms low-leverage firms (Bhandari‘s (1988) ―leverageeffect‖), are some major evidences. From the different stand point in Finance literature,financial economists have puzzled over the two observations. First, over the long horizons,
  5. 5. 5future stock returns are inversely related to the past performance. Second, stock returnsare positively related to price-scaled variables; earning yield, cash flow yield, book-to-market equity, etc.The De Bondt and Thaler (1985, 1987) and, LSV (1994) studies argued that the reversaland book-to-market effects are a result of investor overreaction to the firm‘ pastperformance. In contrast, Fama and French (1995, 1996) argued that, since pastperformance is likely to be negatively associated with changes in systematic risk, highbook-to-market firms are likely to be riskier and hence require higher expected returns. Informer studies, investors overreact to the information contained in accounting growthrates, and later studies shows that the increased risk and return of high book-to-marketfirm is the result of distress brought about by poor past performance. Thus, the studyinitiates to explain the differences that exist in the previous studies.The sound returns on investments visibly attract the initial investment. The returnscomprise the dividend plus the capital gains. The future prospects and the marketopportunities also help to determine the level of investment either in terms of equity ordebts. The relationship developed by Van Rooij, et al. (2007) is a significant associationbetween financial literacy and investment decisions. Even though, the financial crisisoccurred in 2008 it has heightened the institutional as well as individual investors‘awareness in the field of financial decision making. The literacy and the technologicaladvancement contribute to score the timely and quality information. The evidencesuggested that there is an association between stockholding and computer and Internet use(Bogan, 2006). On the other hand, Lusardi and Mitchell (2006) revealed that the negativeassociation between planning for retirement and financial education. These evidences alsosuggest that the additional factors – investor awareness, financial education and thefinancial literacy that contributes to the stock market movement also play as marketreactors.Now, it is important to realize that stock return is a function of multiple interacting factorsin the capital market. It has been gradually influencing by the defined and undefinedfactors. The information available in the market could be disseminated by themanagement or could be developed through the end of invisible sources. The magnitudesof the information that incorporated in stock prices are determined by the nature and formof the capital market. Along with the information effect, the variation in stock prices canalso be affected by the future prospects and the other unseen factors. Thus, the study
  6. 6. 6helps to enhance the knowledge by decomposing the stock returns and marketinformation. There are a number of ways to decompose the information that influence thestock prices. For instance, Fama (1972) segregate the stock returns into selectivity andrisk; Campbell (1991) decompose the stock returns into a component that reflectsinformation about cash flows, and a second component that reflects information aboutdiscount rates; Daniel and Titman (2006) decompose the returns into tangible andintangible returns. Similarly, the study decomposes the information into two components;the first one is firm‘s past and current performance that is described in its financialstatements are treated as tangible information which is relatively concrete and, which isby definition orthogonal to the tangible information is refer to as intangible information.More specifically, the financial indicators that can be generated from the financialstatement of the enterprises are categorized into tangible parts and the other informationwhich is not tangible and orthogonal to the tangible information is categorized intointangible parts. In light of the separation of market information into two components, thestudy also decompose the stock returns into tangible return –which is associated with pastperformance or supported by the tangible information and intangible return – which isunrelated to past performance of the firm itself or backed by the intangible information.The decomposition results might be a useful procedure to grasp the far sights in thecapital market so that one can perform well than others.The study deals with the following issues:o What is the relationship between past tangible information and future returns?o Is there relationship between past intangible returns and future returns?o Is there association between the fundamentals to price scaled variables with the future returns?o Do the stock prices overreact to the past performance?o What is the most predictable fundamental accounting growth measure in stock exchange?o How long the past fundamentals help to predict the market returns?o What are the news effects on stock returns? What is the bad news effect? What is the good news effect? and what is the informational news effect?o Does the political leadership influence on Nepalese stock market? What are the effects of NC led government? CPN-UML led government? King led government? and, UCPN(M) led government?
  7. 7. 7o What are the opinions of Nepalese stock investors on investment alternatives, decision making, market prices and stock returns?o What are the factors affecting investment decision making in equity investment?, and,o What are the opinions of stock investors on various issues like stock returns, fundamental measures, mutual funds, central depository system, portfolio management services, credit rating agencies, sources of investment funds, rate of interest, the trading behavior on different conditions, and on the various emerging issues in stock market performance?1.3 Objectives of the studyThe basic objective of the study is to analyze the market information and stock returns inNepalese stock market. The following are the specific objectives of the study:o To evaluate the relationship between stock returns and fundamental measures.o To determine the news effects – bad news, good news and informational news, on stock returns.o To examine the political leadership effects on stock returns.o To determine the factors affecting stock investment in Nepalese stock market.o To examine the investor opinions on various such as investor education and personality type, preferences, trading behavior and practices, sources of funds for investment, risk perception, level of investor awareness, investor reactions and judgments on previous findings of the similar studies.1.4 HypothesesIn order to achieve the above objectives, the study attempts to test the followinghypotheses related to the market information and stock returns in Nepal.o There is significant relationship between the past tangible returns and future returns.o There is significant relationship between the past intangible returns and future returns.o The firm specific variables have strong relationship with its stock returns.o There is significant relationship between stock returns and news coverage.o There is significant relationship between political leadership and stock market returns.1.5 Organization of the studyThe study is organized in five chapters. The overall background of the study, statement ofthe problem, issues of the study, basic and specific objectives, and the hypotheses havebeen included in first chapter. The conceptual framework and review of some major
  8. 8. 8studies in the field of market information and stock returns have been summarized inchapter two. The review of literature section has been divided into nine categoriesexcluding review of Nepalese context. These nine parts has been organized as perseparate variable in chronological order and the concluding remarks of the review sectionhave been presented at the end of the chapter. Subsequently, research methodology of thestudy has been presented in third chapter which describes the research design, nature andsources of data, selection of the sample enterprises, sector-wise distribution of the listedenterprises, population and sample for primary and secondary database, the methods ofdata analysis are broadly divided into two subsections – secondary data analysis andprimary data analysis. Besides the descriptive statistics, correlation matrix analysis,portfolio formation, regression analysis, Kolmogorov-Smirnov test, stock returnsdecomposition, the test of significance, etc, are the major analysis under the section of thesecondary data analysis. Further, the primary data analysis includes the descriptivestatistics of demographic variables along with percentage, frequency distribution, simpleand cross table analysis, mean score analysis, the test of association – chi-square test, andthe factor analysis which includes: Cronbach‘s Alfa test, the correlation matrix analysis,anti-image correlation matrix – the measure of sampling adequacy (MSA), Kaiser-Meyer-Olkin and Bartletts Test, the initial and rotated solution for factor analysis, and the screeplot are used. The concluding remarks have been shown in the final sector of chapter four.Finally, in chapter five, the summary and the conclusions of the study along with therecommendations for the stakeholders of Nepalese capital market have been presented.
  9. 9. 9 Chapter 2 REVIEW OF LITERATUREThe chapter contains the review of literature on market information and stock returnswhich is organized into four sections. The conceptual framework has been presented inthe first sector. The second part includes the review of major empirical studies on stockreturns and market information. The related studies in Nepalese context have beenpresented in the third section. Finally, the forth section has been devoted for concludingremarks.2.1 Conceptual frameworkEarly from the twentieth century, the financial literature focuses towards the assetsvaluation which intends to identify the real values of the assets. The valuation works forthe assets like tangible and intangible financial assets, and for the liabilities. The marketinformation which is considered as a weapon for market volatility influences thevaluations models significantly time and again. For many reasons in finance, assetsvaluation is at the heart of financial economics and especially for the corporate finance.Thus, the market information is considered as one the most important factor thatincorporates many things at the same time and that influence the securities pricesregularly. Among the financial securities, common stock is a most popular and the mostpracticed financial assets in most of the economies. The exchange of equity is possible atthe organized stock exchanges or over-the-counter market which is based on the free flowof demand and supply assuming that the equilibrium market price.The security prices depend upon number of interacting factors. Some of them aremeasurable by nature. For instance, the firm specific accounting variables, the macro-economic indicators, etc and the other qualitative factors are difficult to measure such asinvestors‘ psychology, selective investment behavior, attitude and perception, the politics,etc. The classification of these interacting variables in terms of their measurement can betermed as tangible and intangible variables, respectively. Regarding the investment infinancial securities like common stocks, bonds, and the financial derivatives: options,swap, futures, forward, etc, the tangible and intangible variables plays the crucial roles indecision making process as well as for the investment performance.
  10. 10. 10The investment is the postponement of current spending for the future purpose with theexpectation of financial benefits as the compensations for the investor‘s sacrifice. Ingeneral, to satisfy the long-term commitment of the funds, the stock returns should beacceptable or at least equal to market compensation. If it is deviated from the benchmarklevel, there would be a problem of withdrawal of long-term commitment of funds or thatcould create a problem of mispricing of the securities. The expectation of stock returnsmight be different, among the other factors, one of them could be the expected futuredividends or it could be the expected future returns (dividends plus capital gain). Inpractice, the framework of stock return can be conceptualized as follows: Demand and Supply Productivity Financial Statements Market Competition Efficiency Relative Business Strength of the Firm Stock returns Figure 2.1 Conceptual framework of stock returnsThe stock returns framework in Figure 2.1 indicates that the financial statements replicatethe demand and supply, and the market competition as well as the productivity andefficiency on the other hand. The financial statements strengthen the business strength ofthe firm so as the direct relationship with stock returns. On top of that, the change ofdividend news; the change in expected returns with the change in expected dividends; aninnovation in the expected return today might have the implications for distance future;and also shocks in expected future dividends might have been the correlational effect onshare prices . Thus, the stock prices have the significant effects of quantitative or thetangible as well as qualitative or the intangible information, which is popularly known asmarket information.In finance, the basic question that has been stimulated voluminous research and became aheated debate is: what moves the stock price or the stock returns? Some studies have beentrying to identify the factors by using stock returns decomposition. In case of the stock
  11. 11. 11returns decomposition it is the process of splitting the total stock returns into differentparts for instance, returns for selectivity and returns for timing, expected future dividendsand expected future returns, cash flow expectations and discount rates, tangible andintangible returns, etc. Some other studies use the fundamental variables to determine thefactors affecting stock returns. Moreover, the risk and return trade-off is a primitivetheory of stock return movements.The study based on the quantitative and qualitative approach, use some accountingvariables: stock price, annual yield, numbers of common stock outstanding, book value ofequity, earnings, sales and cash-flow for the analysis. Further, the news headlines –positive news, negative news and informational news, and political leadership effects isproposed for the proxies of intangible information for stock returns. It is also assumedthat the log price-per-share is equal to the log returns i.e. as price increases, returnincreases. A cross-sectional regression of 5-year log returns on firm specific growthmeasures – book value, earnings, cash-flow, and sales growth or all of these will performto calculate the expected log (Pt). For a given firm at a given point in time, the expectedlog (Pt) is the summation of the firm‘s expected log price at t conditional on log (Pt-5) andits unanticipated fundamental growth between t-5 and t. The study defined that a givenfirm‘s tangible return illustrated by the dashed line in the figure, and its intangible returnis the residual. In other words, the tangible return as the past 5-year stock return thatwould be expected based solely on the past fundamental growth measures. The intangiblereturn is then the part of the past return that remains unexplained and presumably is theresult of an investors‘ response to information which is not contained in the accountinggrowth measures. The framework is presented in Figure 2.2 as follows: Log (Pt) Intangible Return Total Return Log (Pˆ) Tangible Return Log(Pt-5) Log (Pt-5) t-5 t Figure 2.2 - Graphical presentation shows the breakdown of a firm’s past return into tangible and intangible returns.
  12. 12. 12After the description of the variables used, if it is assumed in a close system, theinteraction of tangible and intangible information with the tangible returns and intangiblereturns can be conceptualized and presented in Figure 2.3 as follows: Tangible Information Intangible Information Market Information LEADS Total Stock Returns Tangible Returns Intangible Returns Figure 2.3 Conceptual Framework of market information and stock returns (the broader perspective)The market information comprises the tangible information and the intangibles. Similarlythe total stock return is made up of the tangible returns and the intangible return, whereasthere is direct relationship between tangible components and the intangible components.In sum, the total stock returns moves as on the market information within the closesystem.More specifically, the relationship of the tangibles and intangibles can also be presentedwith its interacting components. The cluster as well as the interaction of thesecomponents can be presented in Figure 2.4 as below: Cash B/M Flow Equity Earnings Tangible / Market
  13. 13. 13Since, the tangibles are the quantifiable variables such as book-to-market equity, cashflow, earnings, size or the number of common stock outstanding, lagged stock returns, etcwhich has the direct linkage with the tangible stock return and a major contribution forthe total market information so as to the stock price movements. Secondly, the qualitativeor the intangible variables generate the intangible information which has the directrelation with intangible returns. The components of intangibles include behavioral issuesand it is very difficult the grasp the consistent signals of such components, such as: socialand individual values, individual and group psychology, sentiments, overconfidence,overreactions and under-reactions, news effects (events), media effects, market reactions,market behaviors, investors behavior, etc. These components contribute the remainingpart of the market information that has uncovered by the tangibles.With these stated interrelationship between and among the firm specific variables and theexternal variables, it is clear that there is direct relationship between the tangible
  14. 14. 14 information and tangible return, intangible information and intangible return, further, the market information comprises the tangible and intangible information, similarly, the total stock returns made up of the tangible returns and the intangible returns. Thus, there is the interrelationship between the market information and total stock returns in a close system approach. The most popular traditional relationship between risk and return can be explained by the risk-return trade-off principles. With the same notion, when the news effect is incorporated with this primitive approach, it can be described as: regular information flow in Figure 2.5 (a) and its effect on risk and returns, and irregular information flow and its effect on risk and returns is presented in Figure 2.6 (b) and Figure 2.7 (c) respectively. More specifically, the irregular news flow can be divided into good news and bad news. The relationship between news events, risk and returns can be presented as follows: Regular Information Flow (a) Irregular Information Flow (b) & (c) Good News Events Return Return Return Bad News EventsRf Rf Rf Risk Risk Risk Figure 2.5 (a) Normal Figure 2.6 (b) Bad News Figure 2.7 (c) Good News The traditional risk-return trade-off describes the positive relation between risk and return i.e. as risk increases, return also increases and vis-à-vis. When introducing the news effects, assuming that risk is constant, bad news serve as a negative stimulus to the market so as the market perceive it negatively whereas good news contribute as positive stimulus to the market so as the market take it positively. Therefore, the conceptual relationship between risk and return with news events indicate that bad news leads to market slash and inversely - the good news leads the market growth. 2.2 Review of Major Empirical Studies The review of major empirical studies on market information and stock returns has been organized into nine categories excluding the Nepalese studies. The studies are categorized
  15. 15. 15based on their qualitative and quantitative nature. The grouping under each category ismanaged as per the time period and based on their similarities. The major classificationsof the selected studies are as follows: a) Fundamental effects on stock returns i) Book-to-market effects ii) Cash flow and earnings effects iii) Size effects b) Stock return analysis, return decomposition and methodology effects i) Stock return analysis ii) Stock return decomposition and methodology effects c) Investors’ behavior studies i) Studies before 2000 ii) Studies during 2000s d) Studies related to initial public offerings (IPOs) e) Studies on stock market behavior i) Studies prior 1990 ii) Studies 1990 onwards f) Market reactions to tangible and intangible information i) Studies on intangible information till 2000 ii) Studies on intangible information between 2000 and 2010 iii) Studies on tangible information before 1990 iv) Studies on tangible information during 1990s v) Studies on tangible information 2000 onwards g) Studies related to media effects h) News events effects on stock returns i) Studies related to investors overconfidence i) Studies before 2000 iii) Studies 2000 onwardsa) Review of major studies on fundamental effects on stock returns
  16. 16. 16The review of fundamental effects on stock returns is organized into four sub-sectioncomprising – book-to-market effects, cash flow effects, earning effects and size effects.The review covers the major studies on respective variables during 1981 to 2008.i) Review of major studies on book-to-market effectsThe book-to-market effects on stock returns from the period 1991 to 2006 have beenpresented in the Table 2.1 below: Table 2.1: Review of major studies on book-to-market effectsStudy Major findingsChan, (1991) The book to market ratio and cash flow yield has the most significant positive impact on expected returns.Davis (1994) Book-to-market equity, earnings yield, and cash flow yield have significant explanatory power with respect to the cross-section of realized stock returns and, there was a strong January seasonal in the explanatory power of book-to-market equity, earning yield and cash flow yield.Brav, (2000) Underperformance is concentrated primarily in small issuing firms with low book- to-market ratios.Daniel and Titman Book-to-market equity ratio, a good proxy for intangible return forecasts returns. A(2006) composite equity issuance measure, also as an intangible information independently forecasts the future returns.The study analyzed the cross-sectional differences of Japanese stocks returns to theunderlying behavior of the variables: earnings yield, size, book-to-market ratio, and cashflow yield, Chan, (1991). Seemingly Unrelated Regression (SUR) model and Fama-Mac-Beth (1973) methodology are applied on comprehensive, high-quality monthly dataset of stocks listed on the Tokyo Stock Exchange (TSE) that extends from 1971 to 1988.The sample includes both manufacturing and nonmanufacturing firms, companies fromboth sections of the Tokyo Stock Exchange, and also delisted securities. The findingsrevealed the univariate analysis of stock returns and fundamental variables indicated thathigh earnings yield stocks outperform low earnings yield stocks; small stocks achievedsubstantially higher returns than large stocks; the firms with large positive book-to-market equity ratio earned high premium than firms with low; and positive book-to-market equity. Further, cash flows yield is found to have positive relation with stockreturns. However regression analysis produced striking results: the earning yield effectwas not significant across the different regressions models and it was not even significantwhen earning yield was the only independent variables. Firm size, in general, issignificant with an unexpected sign meaning that large companies in Japan tend tooutperform small companies. The performance of book-to-market equity is statisticallyand economically the most important among the four variables investigated. Although,the study confirmed the existence of size effect after adjusting for market risk and other
  17. 17. 17fundamental variables, the statistical significant of the size variable is sensitive to thespecification of the model. Of the four variables investigated, though, it is hardest todisentangle the effect of earnings yield variable. In sum, the book to market ratio and cashflow yield has the most significant positive impact on expected returns.The 100 firms listed in the Moody‘s Industrial Manual which is free from thesurvivorship bias and four fundamental variables: book-to-market equity, cash flow yield,earning yield and historical sales growth as primary focus of the study (Davis, 1994).Stock returns, stock prices and market values of equity were derived from the CRSPmonthly file. The study uses the Fama-MacBeth (1973) cross-sectional regression modelto determine the explanatory power of realized returns from 1940 to the early 1960s, thepre-COMPUSTAT era. The findings of the study includes: significant relationshipbetween book-to-market equity and subsequent returns, cash flow yield has explanatorypower with respect to subsequent realized returns when book-to-market equity andhistorical sales growth are held constant, earning yield has also explanatory power topredict subsequent returns, insignificant explanatory power for beta to predict returns,weak relationship between sales growth and returns, and there is significance of log book-to-market, earning to price, and cash flow to price with returns mostly in January. Thus,the study concluded that book-to-market equity, earnings yield, and cash flow yield havesignificant explanatory power with respect to the cross-section of realized stock returnsand there was a strong January seasonal in the explanatory power of book-to-marketequity, earning yield and cash flow yield.Brav, (2000) examined whether a distinct equity issuer underperformance anomalyexists is the major focus of the study. Sample of initial public offering (IPO) and seasonedequity offering (SEO) of the firms from 1975 to 1992 derived from CRSP for NYSE,ASE and NASDAQ. The sample included 4526 offerings made by 2772 firms. The studyfound that underperformance is concentrated primarily in small issuing firms with lowbook-to-market ratios. SEO firms that underperform these standard benchmarks havetime series returns that covary with factor returns constructed from non-issuing firms. Thestudy concluded that the stock returns following equity issues reflect a more pervasivereturn pattern in broader set of publicly traded companies.Book-to-market equity ratio forecasts stock returns because it is a good proxy forintangible returns. Further, composite equity issuance measure, which is related tointangible returns, independently forecasts returns (Daniel and Titman, 2006). The book-
  18. 18. 18to-market effect is often interpreted as evidence of high expected returns on stocks ofdistressed firms with poor past performance. The study also found that while a stock‘sfuture return is unrelated to the firm‘s past accounting-based performance, it is stronglynegatively related to the intangible return, the component of its past return that isorthogonal to the firm‘s past performance. Other findings of the study are: stock returnsover a relatively long horizon (5 years) should be closely linked to concurrentfundamental performance; there is a strong positive relation between intangible returnsand future fundamental performance measures i.e. a firm‘s intangible returns reflects, atleast partial information to its future growth prospects, there is no evidence of any linkbetween past tangible information and future return; there is strong negative relationbetween past tangible returns and future returns; future returns are unrelated to internallyfunded growth in sales; future returns are strongly negatively associated with growth thatis financed by the share issuance; composite share issuance variable is significantlynegatively related to future returns; the strong intangible return and issuance effects thatcannot explain the existence of mispricing; low book-to-market firms have both higherfuture accounting growth rates and lower future returns; negative correlation between thelagged book-to-market ratio and book-return; and the composite share issuance measureis strongly negatively related to future returns.ii) Review of major studies on cash flow and earnings effectsThe cash flow is considered as the fundamental variable and the variation in cash flowmight be the causes of changes in the stock returns. The major previous studies on cashflow from 1999 to 2002 have been presented in Table 2.2 as follows:An analysis on optimal investment, growth options and security returns is conducted byBerk, (1999). The interest of the study is the individual firm. The random evolutionof the firm‘s collection of projects determines how its risk and return change over time. Inthe study, the partial equilibrium model gives the tractability to focus on the dynamics forthe relative risks of individual firms. The study found that as a consequence of optimalinvestment choices, a firm‘s assets and growth options change in predictable ways. In thestudy, the dynamic model imparts predictability to changes in a firm‘s systematic risk,and its expected returns. Simulations showed that the model Table 2.2: Review of major studies on cash flow and earnings effects Study Major findings Berk, (1999) The valuation of the cash flows that result from the investment decision making by the individual firms, along with the firm‘s opinions to grow in the future, leads to dynamics for conditional expected returns.
  19. 19. 19Vuolteenaho Firm-level stock returns are mainly driven by cash-flow news.(2002)Jafee, (1989) A significant relation between returns and earnings only in the month of January and, the size effect was negative only in January.Fama and French There are market, size, and BE/ME factors in earnings like those in returns.(1995)La Porta (1996) Earnings growth is the only variable with the significant explanatory power in explaining stock returns.simultaneously reproduces: the time-series relation between the book-to-market ratio andasset returns; the cross-sectional relation between book-to-market ratio, market value, andreturns, contrarian effects at short horizons; momentum effects at longer horizons and theinverse relation between interest rates and the market risk premium. The study simulated20,000 months of data for 50 firms and restrict the attention to firms that have reached asteady state distribution for the number of ongoing projects by dropping the first 200observations. In addition to dynamic and simulation models, FM regression models,varying types of frequency distributions are used for the analysis. The findings of thestudy concluded that the valuation of the cash flows that result from the investmentdecision making by the individual firms, along with the firm‘s opinions to grow in thefuture, leads to dynamics for conditional expected returns. The model of expected returnsin the study helps explain a number of the important features of the cross-sectional andtime-series behavior of stock returns, and the biases that might be induced by the modelthat ignores these dynamics. On the other hand, the simulation results showed that themodel can reproduce simultaneously several important cross-sectional and time-seriesbehaviors that studies have documented for stock returns, including the explanatorypower of book-to-market value, and interest rates, and the success of contrarian andmomentum strategies at different horizons.Vuolteenaho (2002) conducted a study on firm-level returns, where author use a vectorautoregressive model (VAR) to decompose an individual firm‘s stock returns into twocomponents: changes in cash-flow expectations i.e. cash-flow news and changes indiscount rates i.e. expected-return news. By definition, a firm‘s stock returns are drivenby shocks to expected cash flows (cash-flow news) and/or shocks to discount rates(expected-return news). Substantial studies have been done to measure the relativeimportance of cash-flow and expected-return news for aggregate portfolio returns, butvirtually no evidence on the relative importance of these components at the firm level.The basic data for the study derived from the CRSP-COMPUSTAT intersection, from1954 to 1996. CRSP monthly stock file contains the data of monthly prices, sharesoutstanding, dividends, and returns for NYSE, AMEX, and NASDAQ stocks,
  20. 20. 20COMPUSTAT contains the relevant accounting information for the most publicly tradedU.S. stocks and the study, in addition, used rolled-over one month Treasury-bill returns asrisk-free rate. Based on the VAR and Campbell‘s (1991) return-decompositionframework enable the study to decompose the firm-level stock returns into cash-flow andexpected-return news and to estimate how important these two sources of stock variationare for an individual firm. In addition, the study measure whether positive cash-flow newsis typically associated with an increase or decrease in expected returns. The findings ofthe study includes - the information about future cash flows is the dominant factor drivingfirm-level stock returns, cash-flow news is positively correlated with expected returns fora typical stock. Finally, it is appeared that while cash-flow information is largely firmspecific, expected-return information is predominantly driven by systematic,macroeconomic components. In sum, VAR yields three main results. First, firm-levelstock returns are mainly driven by cash-flow news. For a typical stock, the variance ofcash-flow news is more than twice that of the expected-return news. Second, the expectedreturns and cash flows are positively correlated for a typical small stock. Third, expected-return-news series are highly correlated across firms, while cash-flow news can largely bediversified away in aggregate portfolios.The study uses the CRSP monthly stock return data for relatively a longer period from1951 to 1986 and from the ―back data‖ versions from 1950-1966 periods. Jafee, evaluated the relation between size and earnings yield effects on stock returns.Over the entire period, the study reported a significant relationship earnings and stockreturns only in the month of January, while it is observed a significant relation during allmonths of the sub-period 1969-1986. Conversely, the size effect is found significantlynegative only in January in the overall period and in both sub-periods.Fama and French (1995) analyzed whether the behavior of stock prices in relation to sizeand book-to market-equity (BE/ME) reflects the behavior of earnings. The study focusedon six portfolios, formed yearly from a simple sort of firms in to two group on marketequity and another simple sort into three groups on book-to-market equity. Further, it isstudy attempted to provide an economic foundation for empirical relations betweenaverage stock returns and size, and average stock returns and book-to-market equityobserved in Fama and French (1992). Consistent with rational pricing, high BE/MEsignals persistent poor earnings and low BE/ME signals strong earnings. Moreover, stockprices forecast the reversion of earnings growth observed after firms are ranked on sizeand BE/ME. The evidence that size and book to market equity proxy for sensitivity to risk
  21. 21. 21factors in returns is consistent with a rational pricing story for the role of size and BE/MEin average returns. Specifically, the analysis of whether the behavior of stock prices, inrelation to size and book-to-market equity, is consistent with the behavior of earnings. Ina nutshell, low BE/ME, a high stock price relative to book value, is typical of firms withhigh average returns on capital (growth stocks), whereas high BE/ME is typical of firmsthat are relatively distressed. Size is also related to profitability, controlling for BE/ME,small stocks tend to have lower earnings on book equity than do big stocks. The testscenter on six portfolios formed on ranked values of size and BE/ME for individual stocksi.e. profitability, earnings, profitability in chronological time, earnings/price ratios,earnings growth rates, and stock returns. Then, the overall analysis examines the linksbetween returns and these common factors in earnings and established that the level ofearnings is related to size and BE/ME. The study is based on the data from 1963 to 1992of NYSE, AMEX and NADSAQ. Information was abstracted from the CRSP. Groups areformed based on the breakpoints for the bottom 30 percent (Low), middle 40 percent(Medium), and top 30 percent (High) of the ranked values of BE/ME for NYSE stocksand do not consider the negative BE firms. Thus, the overall relationship of variablesamong the portfolios, analysis of regression results suggest that there are market, size, andBE/ME factors in earnings like those in returns.Further, La Porta (1996) examined whether investors make the systematic mistakes thatare consistence with the errors in expectation hypothesis when growth in earnings. Thestudy employed CRSP monthly returns files of the listed companies of NYSE and AMEX.Annual portfolio returns are constructed by compounding monthly returns. The regressionresults reported that earnings growth as the only variable with the significant explanatorypower. The study revealed that the earnings growth is the only significant variable inmultivariate regression when it is combined with size, book-to-market equity, and cashflow to price ratio. The regression results confirmed the role of the expected rate ofearnings growth in explaining stock returns. The findings are based on multivariateregression models which reported the negative relation of expected returns with book-to-market equity, size and earnings growth and positive relation with cash-flow yield. Whenstock were sorted by expected growth rate in earnings, it is shown that low earningsgrowth stock beat high earnings growth stock by twenty percentage points. The studyfurther documented that there is no evidence that low earnings growth stocks are morerisky than high earnings growth stocks. When portfolios were formed on the basis of
  22. 22. 22expected growth rate in earnings, the results indicated that low earnings growth stockshave significantly lower standard deviations and betas than high earning growth stocks.iii) Review of major studies on size effectsThe size is defined as the market value of common stock outstanding and it is also calledas fundamental variable for stock returns. The major studies including some seminalworks have been presented in Table 2.3 below. The review of size effect on stock returnscovers the period 1981 to 2008. Table 2.3: Review of major studies on size effectsStudy Major findingsBanz (1981) Small firms, on average, have significantly larger risks adjusted returns than large firms.Fama and Size (ME) and book-to-market equity (BE/ME) provide a simple and powerfulFrench (1992) characterization of the cross-section of average stock returns.Fama and Portfolios constructed to mimic risk factors related to size and BE/ME addFrench (1993) substantially to the variation in stock returns explained by a market portfolio.Daniel and There is no evidence of a separate distress factor and, it is characteristics (size &Titman (1997) book-to-market) rather than factor loadings that determine expected returns.Daniel, In equilibrium, there is ability of fundamental/price ratios and market value to(2001) forecast stock returns, and the domination of beta by these variables.Vassalou and Both the size and book-to-market effects can be views as default effects which are inXing (2004) sum the case of size effect.Fama and The anomalous returns associated with net stock issues, accruals, and momentum areFrench (2008) pervasive; they show up in all size groups (micro, small, and big) in cross-section, and they are also strong in sorts, at least in the extremes.The relationship between total market value of equity and common stock returns isexamined by Banz (1981). The study covered the observations from 1926 to 1975, andincluded all common stocks listed in the NYSE. Data were derived from monthly returnsfile of the CRSP, University of Chicago. Using pooled cross-sectional and time seriesregression, the study reported that small NYSE firms, on average, have significantlylarger risks adjusted returns than large NYSE firms. The evidence suggested that theCAPM is not correctly specified. However, the size is not linear in the market protectionbut is most pronounced for the smallest firms in the sample. The effect is not very stablethrough time. An analysis of the ten year sub-period showed substantial differences in themagnitude of the coefficient of the size factor. Finally, the study concluded that there isno theoretical foundation for such an effect, and it is not confirmed whether the factor issize itself or whether size is just a proxy for one or more true but unknown factorscorrelated with size. Therefore, the study reasoned that it is possible, however to offersome conjectures and even discuss some factors for which size is suspected to proxy.
  23. 23. 23The observations starting from July 1963 to December 1990, Fama and French (1992)conducted a analysis on the cross-section of expected stock returns. In area of portfoliomanagement several studies have been undertaken to specify the characteristics of stockreturns. Among the others, CAPM is the most popular model uses a single factor, beta, tocompare a portfolio with the market as a whole. Then, some research findings showedcontradictory results in the literature of finance with CAPM. The motivation of thisresearch is guided by such evidences. The purpose of the study is to evaluate joint roles ofmarket beta, size, earning yield, leverage, and Book to Market Equity in the cross sectionof average stock returns on NYSE, AMEX, and NASDAQ stocks. The study capture thecross-sectional variation in average stock returns associated with size (ME) and book-to-market equity. Sample included are all non-financial firms listed in NYSE, AMEX andNASDAQ and accounting information were collected from CRSP and COMPUSTATdatabase. Fama and MacBeth (1973) regression is used for the analysis. The studyrevealed strong relationship between the average stock returns and size, but there was noreliable relation between average returns and beta. When the stock returns is sorted basedon earnings yield, a familiar U-shape relation is observed. The relation between averagereturns and book-to-market equity is strongly positive. The FM regressions alsoconfirmed the importance of book-to-market equity in explaining the cross section ofaverage stock returns. This book to market equity relation is found stronger than the sizeeffects when both size and book-to-market equity were included in multivariateregressions. The author reported book-to-market equity is consistently the most powerfulfactor explaining the cross-section of average stock returns, whereas size effect was foundweaker. Based on the regression results and analysis of portfolios, the study concludedthat size and book-to-market equity provide a simple and powerful characterization of thecross-section of average stock returns.The common five risk factors for stocks and bonds returns are idenified by Fama andFrench (1993). Three factors: an overall market factors, factor related to firm size andbook-to-market equity are the stock market related factors. For instance if the portfilosconstructed on mimic risk factors related to size and BE/ME, capture a strong commonvariation in returns as the evidence that size and book-to-market equity indeed proxy forsensitivity to common risk factors in stock returns. Other two bond market factors: defaultrisks, and factor related to maturity, are the bond risk factors. Stock returns have sharedvariation due to the stock market factors, and which are linked to the bond returns throughshared variation in the bond market factors. Mostly the bond market factors capture the
  24. 24. 24common variation in bond returns, except for low-grade corporates. Most importantly,these common risk factors seem to explain average returns on stocks and bonds. On theother hand, variables that have no special standing in asset pricing theory shows reliablepower to explain the cross-section of average returns. The list of empirically determinedaverage stock returns variables includes size (ME, stock price times number of shares),leverage, earning price ratio (E/P), and book-to-market equity (the ratio of the book valueof a firm‘s common stock, BE to its market value, ME). The study employed the time-series regression approach of Black, (1972). Monthly returns on stocks and bonds areregressed on the returns to a market portfolio of stocks and mimicking portfolios for size,book-to-market equity, and term-structure risk factors in returns. The time-seriesregression slopes are factor loadings that are unlike size or book-to-market equity have aclear interpretation as risk-factor sensitivities for bonds as well as for stocks. Thus, Famaand French (1993) confirm that portfolios constructed to mimic risk factors related to sizeand BE/ME add substantially to the variation in stock returns explained by a marketportfolio. Moreover, a three-factor asset-pricing model that includes a market factor andrisk factors related to size and BE/ME seems to capture the cross-section of averagereturns on U.S. stocks.There is now considerable evidence that the cross-sectional pattern of stock returns can beexplained by characteristics such as size, leverage, past returns, dividend-yield, earnings-to-price ratios, and book-to-market ratios (Fama and French, 1993). The study argued thatthe association between these characteristics and returns arise because the characteristicsare proxies for non-diversifiable factor risk. Whereas, Fama and French (1992, 1996)examine all of these variables simultaneously and concluded that with the exception ofthe momentum strategy described by Jegadeesh and Titman (1993) the cross-sectionalvariation in expected returns can be explained by only two of these characteristics, sizeand book-to-market. Firm sizes and book-to-market ratios are both highly correlated withthe average returns of common stocks. In contrast, the evidence of the study indicates thatthe return premia on small capitalization and high book-to-market stocks does not arisebecause of the co-movements of these stocks with pervasive factors. It is thecharacteristics rather than the covariance structure of returns that appear to explain thecross-sectional variations in stock returns. The study focus on the factor portfoliossuggested by Fama and French (1993) and draw the conclusion that factor loadingsmeasured with respect to the various macro factors used by Chan, (1985), Chen,, and Jagannathan and Wang (1996) also failed to explain the stock returns once
  25. 25. 25characteristics are taken into account. Thus, implying different forms of regressionmodels, portfolios analysis and analysis of factor loadings, Daniel and Titman (1997)demonstrated two major things: First, there is no evidence of a separate distress factor.Most of the co-movement of high book-to-market stocks is not due to distressed stocksbeing exposed to a unique distress factor, but rather, because stocks with similar factorsensitivities tend to become distressed at the same time. Second evidence suggests that itis characteristics (size & book-to-market) rather than factor loadings that determineexpected returns. It shows that factor loadings do not explain the high returns associatedwith small and high book-to-market stocks beyond the extent to which they act as proxiesfor these characteristics.Daniel, (2001) offered a model in which asset prices reflect both covariance risk andmisperceptions of firms‘ prospects, and in which arbitrageurs‘ trade against mispricing.The classical theory of security market equilibrium is based on the interaction of fullyrational optimizing investors. Several important studies have been explored alternatives tothe premise of full rationality in recent years. One approach model market misevaluationas a consequence of noise or positive feedback trades. Another approach analyzes howindividuals form mistaken beliefs or optimize incorrectly, and derives the resulting tradesand misevaluation. The objective of the study is to offer a theory of asset pricing in whichthe cross section of expected security returns is determined by risk and investormisevaluation. In equilibrium, expected returns are linearly related to both risk andmispricing measures e.g., fundamental/price ratios. With many securities, mispricing ofidiosyncratic value components diminishes but systematic mispricing does not. Thetheory offer untested empirical implications about volume, volatility, fundamental/priceratios and mean returns which is consistent with several empirical findings. Thus, thestudy included that the ability of fundamental/price ratios and market value to forecaststock returns, and the domination of beta by these variables.A firm is said to be default when it fails to service its debt obligations. Therefore, defaultrisk induces lenders to require from borrowers a spread over the risk-free rate of interest.This spread is an increasing function of the probability of default of the individual firm.Vassalou and Xing (2004) estimated the default likelihood indicators (DLI) for individualfirms using equity beta. The main purpose of the study is to address the issue thatinvestors are still known very little about how default risk affects equity returns. The DLIare nonlinear functions of the default probabilities of the individual firms and arecalculated using the contingent claims methodology of Black and Scholes (1973) and
  26. 26. 26Merton (1974). The study used the COMPUSTAT file of all firms for the analysis startingfrom January 1971 to December 1999. The major findings of the study are: the measureof default risk contains very different information from the commonly used aggregatedefault spreads which is default risk, intimately related to the size and book-to-marketcharacteristics of a firm. It shows that both effects are intimately related to default risk.Small firms earn higher returns than big firms, only if they also have higher default risk.Similarly, value stocks earn higher returns than growth stocks, if their risk of default ishigh. In addition, high-default-risk firms earn higher returns than low default risk firms,only if they are small in size and/or high book-to-market equity. In all other cases, there isno significant difference in the returns of high and low default risk stocks. With thesefindings the study concluded that both the size and book-to-market effects can be viewsas default effects which is in sum the case of size effect.In a study of dissecting anomalies, Fama and French (2008) considered the patterns ofaverage stock returns which do not explained by CAPM. Two approaches were used toidentify anomalies: sorts of returns on anomaly variables, and regressions, in the spirit ofFama and MacBeth (1973) to explain the cross-section of average returns. The datacollection started from at the end of each June 1963 to end with 2005. NYSE, Amex, andNASDAQ stocks were allocated into three size groups - microcaps (tiny), small stocks,and big stocks. The breakpoints are the 20th and 50th percentiles of end-of-June marketcap for NYSE stocks. The findings of the study includes: as the previous work found thatnet stock issues, accruals, momentum, profitability, and asset growth are associated withanomalous average returns. Smilarly, the study explored the pervasiveness of these returnanomalies via sorts and cross-section regressions estimated separately on microcaps,small stocks, and big stocks. The book-to-market ratio, net stock issues, accruals, andprofitability all produce average regression slopes that are indistinguishable across sizegroups. The measured net of the effects of size and B/M, the equal- and value-weightabnormal hedge portfolio returns associated with momentum, net stock issues, andaccruals are strong for all size groups (and thus pervasive). There is a more serious stainon the net stock issues anomaly. The regression results showed that, at least for 1963 to2005, each of the anomaly variables seems to have unique information about futurereturns. All the anomaly variables are at least rough proxies for expected cash flows.Finally, the study commonly interprets the average returns associated with anomalyvariables as evidence of market inefficiency. In sum, the anomalous returns associatedwith net stock issues, accruals, and momentum are pervasive; they show up in all size
  27. 27. 27groups (micro, small, and big) in cross-section regressions, and they are also strong insorts, at least in the extremes. The asset growth and profitability anomalies are less robust.There is an asset growth anomaly in average returns on microcaps and small stocks, but itis absent for big stocks. Among profitable firms, higher profitability tends to beassociated with abnormally high returns, but there is little evidence that unprofitable firmshave unusually low returns.b) Review of major studies on stock returns analysis, return decomposition andmethodology effectsThe financial investment focus towards the returns in terms of shareholders wealthmaximization or simply, on financial returns. The returns on investment is not an isolatedterms, it is relative and interrelated with multiple factors including its own behavior. Thissection includes the major studies on stock returns which help to analyze the stock returnsin depth. The stock return analysis along with its decomposition and the methodologicaleffects for the period 1972 to 2008 have been presented herein first and second sub-section respectively.i) Review of major studies on stock returnsThe level of market efficiency is formed based on the speed of adjustment of newinformation. Among the others, the market information is one that causes the stockreturns. The market would be consistent if there is strong form of efficiency but the strongform of efficiency is imaginary so that the stock returns moves ups and downs as per theinformation as well as on the basis of time being. Table 2.4 shows the major studies onstock returns analysis.Rendleman (1982) aimed to reexamine the previous study (Reinganums study)which indicates that abnormal returns could not be earned unexpected quarterly earningsinformation, and documented precisely the response of stock prices to earningsannouncements. The study used a very large sample of stocks and daily returns whichrepresents the most complete and detailed analysis of quarterly earnings. The majorfindings of the study is contrary to those of the earlier study and showed that abnormalreturns could have been earned almost any time during the 1970s. The analysis alsoindicated that risk adjustments matter little in this type of work. Finally, the study foundroughly 50 percent of the adjustment of stock returns to unexpected quarterly earningsoccurs over a 90-day period after the earnings are announced.
  28. 28. 28 Table 2.4: Review of major studies on stock returnsStudy Major findingsRendleman, Abnormal returns could have been earned almost any time. The analysis also(1982) indicated that risk adjustments matter little in this type of work.Poterba and Positive autocorrelation in returns over short horizons and negative autocorrelationSummers (1988) over longer horizons, although random-walk price behavior cannot be rejected at conventional statistical levels. With this, the conclusion is substantial movements in required returns are needed to account for the correlation patterns.Kothari, The relationship between book-to-market equity and returns is weaker and less(1995) consistent.Fama and French Except for the continuation of short-term returns, the anomalies largely disappear.(1996b)Fama and French Survivor bias does not explain the relation between book-to-market equity and(1996a) average returns and, beta alone cannot explain average returns.Fama and French The costs of equity for industries are imprecise.(1997)Devas, The value premium in average stock returns in US is robust.(2000)Asness Within-industry momentum has predictive power for the firm‘s stock return beyond(2000) that captured by across-industry momentum.Fama and French The average stock return on the last half-century is a lot higher than expected in(2002) US.Malmendier and Overconfident CEOs over-estimate their ability to generate returns.Tate (2008)The transitory components in stock prices are investigated by Poterba and Summers(1988). After showing that statistical tests have little power to detect persistent deviationsbetween market prices and fundamental values, the study considered whether prices aremean-reverting. The study is based on the data from the United States and 17 othercountries. The point estimates of the empirical work explain the positive autocorrelationin returns over short horizons and negative autocorrelation over longer horizons,although random-walk price behavior cannot be rejected at conventional statistical levels.The authorities indicated that substantial movements in required returns are needed toaccount for the correlation patterns. The study also discussed with persistent, buttransitory, disparities between prices and fundamental values.A study by Kothari, (1995) examined whether beta explains cross-sectional variancein average returns over the post-1940 periods as well as the longer post-1926 period, andwhether book-to-market equity captures cross-sectional variations in average returns overa longer 1947 to 1987 period. The authors noted that the relationship between book-to-market equity and returns is weaker and less consistent than that in Fama and French(1992). They claimed that past book-to-market results using COMPUSTAT data areaffected by a selection bias and provide indirect evidence. Using an alternative datasources from standard poor‘s industry level from 1947 to 1987, the authors have notedthat book-to-market is at best weakly related to average stocks returns. The study
  29. 29. 29presented evidence that average returns do indeed reflects sustainable compensation forbeta risk, provided that betas are measured at the annual interval. Finally, the authorsclaimed that the failure of a significant relation between book-to-market equity andreturns to emerge the standards poor‘s industry portfolios poses a serious challenge tobook-to-market equity ―empirical asset pricing model‖.The study is based on previous work that average returns on common stocks are related tofirm characteristics like size, earnings/price, cash flow/price, book-to-market equity, pastsales growth, long-term past returns, and short-term past returns, Fama and French(1996b). Because these patterns on average returns apparently are not explained by theCAPM, they are called anomalies. The three-factor time series regression models inFama and French (1993), the 25 Fama and French (1993) Size-BE/ME Portfolios ofvalue-weighted NYSE, AMEX and NASD stocks, excess return portfolios were formedbased on Lakonishok, (LSV 1994) using COMPUSTAT accounting data, LSVdouble-sort portfolios, portfolios formed on past returns, one-factor CAPM excess-returnregressions and alike rigorous models and procedures were used for the analysis for the30 years of data covering 1964 to 1993. Fama and French (1993) found that the three-factor risk-return relation is a good model for the returns on portfolios formed on size andbook-to-market equity. The study that also explained the strong patterns in returnsobserved when portfolios are formed on earnings/price, cash flow/price, and sales growth,variables recommended by Lakonishok, (1994) and others. The three-factor risk-return relation also captures the reversal of long-term returns documented by DeBondtand Thaler (1985). Thus, portfolios formed on E/P, C/P, sales growth, and long-term pastreturns do not uncover dimensions of risk and expected return beyond those required toexplain the returns on portfolios formed on size and BE/ME. The three-factor risk-returnrelation is, however, just a model. It surely does not explain expected returns on allsecurities and portfolios. The study found that cannot explain the continuation of short-term returns documented by Jegadeesh and Titman (1993) and Asness (1994). Thus, thestudy concluded, except for the continuation of short-term returns, the anomalies largelydisappear in a three-factor model. The results are consistent with rational ICAPM or APTasset pricing, but also consider irrational pricing and data problems as possibleexplanations.Fama and French (1996a) revealed that survivor bias does not explain the relationbetween book-to-market equity and average returns. The study used COMPUSTAT datafrom the period 1928 to 1993. The portfolios in June of each year were formed using
  30. 30. 30betas on the NYSE value-weight market portfolio estimated with two to five years of pastmonthly returns. The result showed that the average monthly and annual post formationsreturns initially increased with post formation betas, but relation between average returnsand beta was rather flat from fourth to tenth beta deciles. However, the authors have alsoexplained that univariate beta regressions leave an unexplained size effect. In theportfolios formed on size and beta, the average beta premiums form univariateregressions of return on beta underestimated the positive relation between beta andaverage returns produced by size sort and overestimated the relation between beta andaverage returns produced by beta sort. Therefore, result suggested that beta alone cannotexplain average returns.The study estimated that costs of equity for industries are imprecise, Fama and French(1997). The standard errors of more than three percent per year are typical for both theCAPM and the three-factor model of Fama and French (1993). The study found thatthese large standard errors are the result of uncertainty about true factor risk premiumsand imprecise estimates of the loadings of industries on the risk factors. Thus, theestimates of the cost of equity for firms and projects are surely even less precise.The study documented that the value premium in U.S. stock returns is robust (Devas,,2000). The positive relationship between average returns and book-to-market equity andthe three-factor risk model explains the value premium better than the hypothesis that thebook-to-market characteristic is compensated irrespective of risk loadings. The study isbased on data from 1929 to 1997, derived from Moody‘s industrial manuals andCOMPUSTAT. Sample firms were selected from the NYSE, AMEX and NASDAQindustrials and non-industrials. Fama and French (1993) three-factor asset pricing modeland characteristics model are employed. The findings showed that the value premium inaverage stock returns is robust. The three-factor model explains the value premium betterthan the characteristics model. Finally, when portfolios are formed from independentsorts of stocks on size and BE/ME, the three-factor model is rejected. Based on theseresults, the study concluded that the three-factor model is just a model and thus anincomplete description of expected returns.Within-industry momentum has predictive power for the firm‘s stock returns beyond thatcaptured by across-industry momentum and a significant short-term (one month) industrymomentum effect which remains strongly significant when restrict the sample to only themost liquid firms (Asness, 2000). The study considered the sample of all firms listed
  31. 31. 31on the NYSE, AMEX, and NASDAQ stock exchanges from July 1963 throughDecember 1998 and the necessary financial data were retrieved from COMPUSTATdatabase. Fama-MacBeth regression model and its modified models along with two-waysorts of portfolios and descriptive statistics are employed for the analysis. Originallyestablished by Fama and French (1997), sample firms are categorized into 48 industries.To explore the better proxies for the information about future returns contained in firmcharacteristics such as size, book-to-market equity, cash flow-to-price, percent change inemployees, and various past returns measure were obtained by breaking theseexplanatory variables into two industry-related components. The first component is thedifference between firms‘ own characteristics and the average characteristics of theirindustries i.e. within-industry variables and, the second is average characteristics of firms‘industries i.e. across-industry variables. In conclusion, the study provided the better wayof sorting stocks and primarily, within-industry and across-industry variables are betterable to explain the cross-section of expected stock returns than risk proxies in the morecommon market-wide form.A study is designed to estimate the equity premium using dividend and earnings growthrates to measure the expected rate of capital gain, Fama and French (2002). The equitypremium is the difference between the expected returns on the market portfolio ofcommon stocks and the risk-free interest rate. Dividends and earnings are used to estimatethe expected stock returns. The explanation of the model used is: the average stock returnis the average dividend yield plus the average rate of capital gain. The CRSP value-weighted portfolio of NYSE, AMEX and NASDAQ stocks from 1951 to 2000 are usedfor the analysis. The results estimates the dividend growth rates for 1951 to 2000, 2.55percent and earnings growth rates 4.32 percent, are much lower than the equity premiumproduced by the average stock return, 7.43 percent. The evidence suggests that the highaverage return for 1951 to 2000 is due to a decline in discount rates that produces a largeunexpected capital gain. Thus, the main conclusion is that the average stock returns on thelast half-century is a lot higher than expected.A study analyzes the top level overconfidence on acquisition and its impact on market orthe market reaction. Does CEO‘s overconfidence help to explain merger decisions? is thefocus of Malmendier and Tate (2008). Generally, overconfident CEOs over-estimatetheir ability to generate returns. As a result, they overpay for target companies andundertake value-destroying mergers. The effects are strongest if they have access tointernal financing. The study tests these predictions using two proxies for overconfidence:
  32. 32. 32CEOs‘ personal over-investment in their company and their press portrayal. The resultshows that the odds of making an acquisition are 65percent higher if the CEO isclassified as overconfident. The effect is largest if the merger is diversifying and does notrequire external financing. The market reaction at merger announcement is significantlymore negative than for non-overconfident CEOs. The study considered alternativeinterpretations including inside information, signaling, and risk tolerance while analyzingthe relationship.ii) Review of major studies on stock return decomposition and methodology effectsIn principle, decomposition is to make a complex problem into simple. It helps to get thethinking straight into simpler way with a logical reasoning and come out with a potentialsolution for the complex issue. The decomposition approach in other words, is an attemptto obtain relatively simple interpretation for the complex issues. With the decompositionprinciple, one can identify the factors affecting stock returns. Apart from identifying thefactors contributing for stock returns, the methodology used for the study is also a majorcontributor for stock return anomalies. Table 2.5 shows the major studies in stock returnsdecomposition and the methodology effects as follows: Table 2.5: Review of major studies on stock returns decomposition & methodology effectsStudy Major findingsFama (1972) Return on a portfolio can be subdivided into two parts: the return from security selection (selectivity) and the return from bearing risk (risk).Campbell (1991) Unexpected stock returns associated with changes in expected future dividends or expected future returns.Fama (1998) Anomalies can be due to methodology, most long-term return anomalies tend to disappear with reasonable changes in technique used for the analysis and the anomaly is stronger for small stocks.The evaluation of the investment performance is the crucial issue in investmentmanagement. Number of studies has been conducted on the similar topics. Among others,Fama (1972) suggested the methods for evaluating investment performance. The previousworks are concerned with measuring performance into two dimensions, return and risk.The study suggested somewhat finer breakdowns of the investment performance. Thegoal of the performance measure itself is just to test how good the portfolio manager is atsecurity analysis. That is, does the portfolio manager show any ability to uncoverinformation about individual securities that is not already implicit in their prices? Thebasic notion underlying the methods of performance evaluation is presented, and thereturns on managed portfolios can be judged relative to those of "naively selected"
  33. 33. 33portfolios with similar levels of risk. Both the measure of risk and the definition of anaively selected portfolio were obtained from modern capital market theory. Theconclusions of the study are: the stock returns on a portfolio can be subdivided into twoparts: the return from security selection (selectivity) and the return from bearing risk(risk). The return from selectivity is defined as the difference between the return on themanaged portfolio and the return on a naively selected portfolio with the same level ofmarket risk.What moves the stock returns? To get the ideas on this voluminous research question andthe heated debate issue, Campbell (1991) conducted a study on variance decompositionfor stock returns. The study present a simple way to break stock market movements intotwo components; one which is associated with changes in rational expectations of futurereturns is "news about future returns", and one which is not is called the "news aboutfuture dividends". The approaches and tools used for the analysis are; arbitrary correlationapproach between the two components which is important in practice, regression analysisto describe the evolution through time of the forecasting variables, vector autoregressive(VAR) system used to calculate the impact that an innovation in the expected return willhave on the stock price, contemporaneous regression approach regresses stock returns oncontemporaneous innovations to variables which might plausibly affect the stock market,univariate time-series approach studies the autocorrelation function of stock returns. Thestudy shows that unexpected stock returns must be associated with changes in expectedfuture dividends or expected future returns. A vector autoregressive method is used tobreakdown the unexpected stock returns into two components. In U.S. monthly data ofNYSE retrieved from CRSP from 1927 to 1988, one-third of the variance of unexpectedreturns is attributed to the variance of changing expected dividends, one-third to thevariance of changing expected returns, and one-third to the covariance of the twocomponents. Changing expected returns have a large effect on stock prices because theyare persistent: a 1 percent innovation in the expected return is associated with a 4 or 5percent capital loss. Changes in expected returns are negatively correlated with changesin expected dividends, increasing the stock market reaction to dividend news. In theperiod 1952-88, changing expected returns account for a larger fraction of stock returnvariation than they do in the period 1927-51.Consistent with the market efficiency hypothesis that the anomalies are chance results,apparent overreaction to information is about as common as underreaction, and post-event continuation of pre-event abnormal returns is about as frequent as post-event
  34. 34. 34reversal (Fama, 1998). Most important, consistent with the market efficiency predictionthat apparent anomalies can be due to methodology, most long-term return anomaliestend to disappear with reasonable changes in technique used for the analysis. The three-factor model of Fama and French (1993) is employed to estimate the portfolios abnormalreturns, it showed that the three-factor model is not a perfect story for average returnsand considered as the bad-model. The bad-model problem can produce spuriousanomalies in event studies. All methods for estimating abnormal returns are subject tobad-model problems, and no method is likely to minimize bad-model problems for allclasses of events. The study provides the important general message from the initialpublic offerings and seasoned equity offerings results is one caution: two approaches thatseem closely related i.e. both attempt to control for variation in average returns related tosize and BE/ME, can produce much different estimates of long-term abnormal returns.The anomalies are largely limited to small stocks because small stocks always poseproblems in tests of asset pricing models, so that they are prime candidates for bad-modelproblems in tests of market efficiency on long-term returns. Thus, the anomaly isstronger for small stocks.c) Review of major studies on investor behaviorThe heated issue in financial literature is the behavioral effects on stock returns. Thefinancial literature explained that there are numerous qualitative factors that contribute forstock market movements. The quantitative factors that can be measured but theirsignificance is questionable because of historic nature. The behavioral factors on the otherhand, significantly influence the stock movements. At the same time, it is very difficult toarticulate the level of its influences. The major studies on investor behavior have beenpresented in this section. The study period range from 1994 to 2011.i) Review of major studies on investor behavior before 2000This sub-section focuses on the review of value strategies versus glamour strategies withinvestor behavior, information processing, news and events responses, etc. Table 2.6presents the review of major studies on investor behavior before 2000 as follows:Lakonishok, (1994) conducted a study on the most debatable, value strategies,glamour strategies, investors‘ extrapolation and risk which have attracted academicattention as well. The value strategies call for buying stocks that have low prices relativeto earnings, dividends, book assets, or other measures of fundamental value. For manyyears, scholars and investment professionals have argued that value strategies outperform
  35. 35. 35the market. While there are some agreements that value strategies produce higher returns,but the interpretation of why they do so is more controversial. The objective of the studyis to shed further light on the two potential dimensions for why value strategies work. Table 2.6: Review of major studies on investor behavior before 2000Study Major findingsLakonishok, Value strategies yield higher returns than glamour strategies because these (1994) exploit the suboptimal behavior of the typical investor and not because these strategies are fundamentally riskier.Ikenberry et The market responds mistakenly in initial phase of information and appeared to ignoreal. (1995) much of the information conveyed through repurchase announcement.Barberis, In a variety of markets, sophisticated investors can earn superior returns by (1998) advantage of under-reaction and overreaction without bearing extra risk.Klibanoff, News events lead some investors to react more (1998)Odean The trading volume of a particular class of investors, those with discount brokerage(1999) accounts, is excessive. These investors trade excessively in the sense that their returns are, on average, reduced through trading.First, the study examines more closely the predictions of the contrarian model. Second,value strategies that bet against those investors who extrapolate past performance too farinto the future produce superior returns. Variables employed for the study are: pastperformance is measured using information on past growth in sales, earnings, and cashflow, and expected performance is measured by multiples of price to current earnings,and cash flows. The sample period covered from the end of April 1963 to the end of April1990. The sources of data are CRSP and COMPUSTAT, of NYSE and AMEX firms. Theresults could potentially suffer from the Look-ahead or survivorship bias (Banz and Breen,1986) and Kothari,, 1992) but methodology used is different from those in otherrecent studies in ways that should mitigate this bias by First, do not use those returns toevaluate strategies which appear such bias. Second, study only NYSE and AMEX firms.Finally, report results for the largest 50 percent of firms on the NYSE and AMEX. Theselection bias is less serious among these larger firms (La Porta, 1993). Couple of simplestatistical tools; average, percentage, standard deviation along with rigorous portfolioanalysis and FM regression models is used for the analysis. The study provides that valuestrategies (high B/M) yield higher returns because these strategies exploit the suboptimalbehavior of the typical investor and not because these strategies are fundamentally riskier.A total of 1239 open market share repurchases announced between January 1980 andDecember 1990 by firms whose shares traded on the NYSE, ASE, or NASDAQ isconsidered as the sample of the study, (Ikenberry, 1995). For the performance
  36. 36. 36measurement, the study used the CAR approach and the buy-and-hold approach. Thelong-run firm performance following open market share repurchase announcementindicated that the average abnormal four year buy-and-hold return measured after theinitial announcement is 12.1 percent where as the average market response to theannouncement of an open market share repurchase is 3.5 percent. For value stocks,companies more likely to be repurchasing shares because of undervaluation, the averageabnormal return is 45.3 percent. For repurchases announced by glamour stocks, whereundervaluation is less likely to be an important motive, no positive drift in abnormalreturn is observed. Thus, at least with respect to value stocks, the market errs in its initialresponse and appears to ignore much of the information conveyed through repurchaseannouncement.The motivation of the study is the recent empirical researches in Finance which have beenuncovered two families of pervasive regularities: underreaction of stock prices to newssuch as earnings announcements, and overreaction of stock prices to a series of good orbad news. For example, the underreaction evidence shows that over horizons of perhapsone to twelve months security prices underreact to news. In an effort to fill this gap,Barberis, (1998) propose a model of investor sentiment. As a consequence, news isincorporated only slowly into prices, which tend to exhibit positive autocorrelations overthese horizons. A related way to make this point is to say that current good news haspower in predicting positive returns in the future. The overreaction evidence shows thatover longer horizons of perhaps three to five years, security prices overreact to consistentpatterns of news pointing in the same direction. That is, securities that have had a longrecord of good news tend to become overpriced and have low average returns afterwards.Put differently, securities with strings of good performance, however measured, receiveextremely high valuations. This effort presents a parsimonious model of investorsentiment, or of how investors form beliefs, which is consistent with the empiricalfindings. The model is based on psychological evidence and produces both under-reactionand overreaction for a wide range of parameter values. The existence of this modelchallenge to the efficient markets theory because it suggests that in a variety of markets,sophisticated investors can earn superior returns by taking advantage of under-reactionand overreaction without bearing extra risk.In an effort to investigate the investors‘ reactions to salient news, Klibanoff, (1998)conducted a study on ‗investor reaction to salient news in closed-end country funds.‘Panel data on prices and net asset values are used to test whether dramatic country-