# Skripsi Sampe Bab 3

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27-Mar-2015Category

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CHAPTER I INTRODUCTION 1.1 Background Theories of pricing model have been developed for years by many academicians. Each of those pricing model has different variables, considerations, and factors to be put into the models developed. Those pricing models have been used by academicians and practitioners in explaining, assesing, and defining the expected returns that assets can have in relevant with the risk that investors should consider when they want to conduct investments activities. The first model to be developed to explain returns of assets (especially stocks) is Capital Asset Pricing Model (known as CAPM), developed by Sharpe (1964), Lintner (1965), and Mossin (1966). This model is widely use because of its simplicity. After Capital Asset Pricing Model was being developed to explain asset return (usually stocks), many asset pricing models come up with different approaches to advance the explanation of expected assets return in relevant with different risk proxies that investors should consider when making a decissionabout investment activities. From those many assets pricing model, some of them are, Inter-temporal Capital Asset Pricing Model, developed by Merton (1973), The Arbitrage Pricing Model developed by Chen and Ross (1986), and Three factor model developed by Fama and French (1993). Different variables are being used by those pricing models to explain assets (stocks) return. Many researches and journals, compared two of them which are, the Capital Asset Pricing Model and Three Factor Model. The main reason is that, those two pricing models are generally applicable in different stock market circumstances across countries in the world, and in any economic conditions and characteristics that attached to a country being examined in the research.

The well-known prediction of CAPM is that, the expected excess return on an asset equals the beta of the asset times the expected excess return on the market portfolio, where the beta is the covariance of the assets return with the return on the market portfolio divided by the variance of the market return. John (2007) explained the simplicity of CAPM in explaining expected return on an asset. He explained that the expected rate of return on an asset is a function of the two components of required rate of return-the risk free rate and the risk premium. Thus,

Ki = Risk-free rate + Risk Premium = RF + [E(RM) RF]Equation 1.1

The use of only one risk factor in explaining expected return, makes this pricing model also being known as single factor model. Dhamodaran (2001) also explained CAPM with an analogy of an asset. He explained that in CAPM world, where all investors hold market portfolio, the risk to an investors individual asset will be the risk that this asset adds to the market portfolio. Intuitively, if an asset move independently in relevant with market portfolio, it will not add mcuh risk to the market portfolio. In other words, most of the risk in this asset is firm-specific and can be diversified. In contrast, if an asset tends to move up when the market portfolio moves up, and move down when market portfolio moves down, it will add risk to the market portfolio. It implies that this asset has more market risk and lessfirm specific risk. Statistically, this added risk is measured by the covariance of the asset with market portfolio. Under CAPM, investors adjust their risk preferences by using their allocation decission, whther they want to invest more in riskless assets or more in market portfolio.

Investors who are risk averse will choose to put more or even all their wealth to riskless assets. Conversely, investors who are risk taker will invest more, or even all of their wealth in market portfolio. Investors who invest their wealth in market portfolio and desired to bear more risk, would do so by borrowing at the riskless rate and investing in the market portfolio as anyone else. However some researches argue that the market beta itself is not sufficient to explain expected stock return. As quoted by Fama and French (1992); Basu (1977), shows that when common stocks are sorted on earning price ratio (E/P), future return of high E/P stock are higher than those predicted by CAPM. Moreover, Banz (1981), documented size effect, which revealed the statistical fact that stocks with low market value (market capitalization), earned higher return than what is predicted by CAPM; stocks with low market value have higher beta and higher average returns than those stocks with higher market value, but the difference is higher than those predicted by CAPM. Fama and French (1992), study the joint roles of market , size, E/P, leverage, and book to market equity in the cross section of average stock return. They find that used alone, or in combination with other variables, (the slope in the regression of a stocks return on a market return) has little information about average return. Used alone, size, E/P, leverage, and book-to-market equity seem to absorb the apparent roles of leverage and E/P in average return. Briefly, their research resulted in the statistical conclusion that, two empirically determined variables, size and book-to-market equity, do a good job in explaining the average returns. Thus, concerning other factors that might be able to explain stocks return, Fama and French (1993) developed a model called three factors model. This model is not only using the return of market portfolio to explain expected return, but also the other two factors, which are size and book-to market ratio. Mathematically, the model can be written as follow: E(Ri) - Rf =c + i (E(RM) Rf) + si E(SMB) + hi E(HML) +e

Fama and French three factors model captures the performance of stock portfolios grouped on size and the book-to-market ratio. Fama and French (1993,1996), have interpreted that their three factors model as evidence of risk premium or "distress premium. Small Stocks with high book-to-market ratios are firms that have performed poorly and are vulnerable to financial distress, and investors recognized a risk premium for this reason. Using the monthly stocks return data in NYSE, AMEX, and NASDAQ, from 1963 to 1991, Fama and French (1993) started their analysis by sorting stocks based on their size and their book-to-market ratio. They break the stocks based on size, into two groups, those stocks with small capitalization, and those stocks with big capitalization. Individually, they also break the stocks to be observed based on their book-to-market ratio, based on the breakpoints into three groups, those with low book-to-market ratio (30% of stocks), those with medium book-to-market ratio (40%), and those with high book-to-market ratio (30%). Their decision to break stocks into three groups on book-to-market ratio and only two groups on book-tomarket ratio, is based on their previous findings in Fama and French (1992), revealed that book-to-market equity has stronger role in average stock returns than size. Then six portfolios are formed based on the interception of the two size groups and the three book-to-market group, they are S/L, S/M, S/H, B/L, B/M, B/H (i.e S/L is portfolio consist of those stocks with small capitalization and low book-to-market ratio). The returns of those six portfolios are then being used as dependent variables. They use the excess market return (E(RM) Rf), which is the difference between the return on market portfolio, with risk free rate, as proxy for the market factor in stock return. To capture the size effect, they use the return of portfolio named under SMB (Small Minus Big). SMB meant to mimic risk factor in returns related to size. It is the difference (each month) between the simple averages of the return of the three small-stock portfolios (S/L, S/M, and S/H) and the simple average returns of three big-stock portfolios (B/L, B/M,

B/H). Thus, SMB is the difference between the returns on small and big stock portfolios with about the same weighted average book-to-market equity. To mimic capture the risk factor in returns related to book-to-market ratio, they use the return of portfolio named under HML (High Minus Low). It is the difference, each month, between the simple average of the returns on the two high book-to-market portfolios (S/H and B/H) with the simple average returns on the two low book-to-market portfolios (S/L and B/L). The two components are return on high and low book to market portfolio with about the same weighted average size. But, there also many research doubt about the strong relationship between book-tomarket ratio, and size toward return. Kothari, Shanken, and Sloan (1995), as quoted by Fama and French (1996), found that the relationship between book-to-market ratios toward return is relatively weak and not consistent with the findings of Fama and French (1992). The relationship between book-to-market ratio and return were partly caused by a certain bias on data. Bias on the data happened when there are data that cannot be obtain because the firms did not publish its financial reports, or the data from previous period are being used to fill the missing data that happen in the current period. There are also many explanations about size and book-to-market anomalies. Lakonishok, Shleifer, and Vishny (1994), Haugen (1995), and McKinlay (1995) , as quoted by Fama and French (1996), argue that the premium of financial distress is irrational. Three arguments justify it. First, it can express an over-reaction of the investors. Second argument is relative to the empirical observation of low stock return of firms with distress financial situation, but not necessarily during period of low rate of growth of GNP or of low returns of all stocks in the market. Lastly, diversified portfolios of stocks with, as well high as low, book-to-market ratio; have the same variance of return

From the discussion above it can be implied that the research about stock return and pr