CHAPTER II LITERATURE REVIEW

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1 CHAPTER II LITERATURE REVIEW II.1. Risk II.1.1. Risk Definition According Brigham and Houston (2004, p170), Risk is refers to the chance that some unfavorable event will occur (a hazard, a peril, exposure to loss or injury). If you invest in speculative stocks (or really, any stock), you are taking a risk in the hope of having an appreciable return. In general, the definition of risk is always associated with negative image. Although according to Damodaran (2001, p150), Risk, as we see it, refers to the likelihood that we will receive a return on an investment that is different from the return we expected to make. Thus, risk includes not only the bad outcomes, that is, returns that are lower than expected, but alsso good outcomes, that is, returns that are higher than expected. Furthermore, Damodaran explained that: Risk is a mix of danger, and opportunity. In financial terms, we term the danger to be risk and the opportunity to be expected return. So in any investment, we will convert the danger into opportunity. In other words, in general, the investment risk is associated with the possibility to have the return on investment that is not in line with expectation, the higher expected return on investment, the higher the risk. 6

2 7 II.1.2. Risk Measurement In investment activities, both financial investments such as stocks and bonds, as well as real estate such as land and building, in general there are two things that should be considered, i.e. risk and return. Risk is a variability of actual return compared to expected return. Standard deviation is a proxy that is used to estimate what is the possibility of the actual return being different with expected return. II.1.3. Type of Risks Keown, Martin, Petty, Scott (2005, p193), We can divide the total risk in two types of risk : (1) firm specific or company-unique risk and (2) market-related risk. Company-unique risk might also be called diversifiable risk, because it can be diversified away. This diversified risk is the result factors that are unique to the particular firm. Market risk is non diversifiable risk; it cannot be eliminated, no matter how much we diversify. Bodie, Kane, Marcus (2005, p224), The risk that remains even after extensive diversification is called market risk, risk that is attributable to market wide risk sources. Such risk is also called systematic risk, or non diversifiable risk. In contrast, the risk that can be eliminated by diversification is called unique risk, firm specific risk, non systematic risk, or diversifiable risk.

3 8 II Systematic Risk (Beta) Systematic risk or undiversified risk is also called as market risk. This risk has relationship with the market condition in general, for example the change in macroeconomic condition, interest rate risk, political risk, inflation risk, foreign exchange risk and market risk. These risks affect to all companies and therefore can t be eliminated with diversification. Parameter used to estimate systematic risk is beta. According to Houston and Brigham (2004, p189) Beta coefficient, a measure of market risk, which is the extend to which the returns on a given stock move with the stock market. Scott, Martin, Petty, and Keown (2005, p199) define beta as Beta, a measure of the relationship between an investment s return and the market s returns. This is a measure of the investment s non diversifiable risk. Beta is used to calculate the return on investment in stocks and compared with market return. Beta is also used to measure the sensitivity of individual stocks return with the market return in general. In summary, it can be concluded that: Company with beta = 1, indicates that the risk of investment equal to average market risk. The stock price fluctuate in line with the market fluctuation. Company with beta > 1, indicates the risk of investment is higher than the average market risk. Company with beta < 1, indicates the risk of investment is lower than the average market risk.

4 9 It can be concluded that beta is a tool to measure volatility of systematic risk of stocks. Beta of stocks can be measured using historical data as well as subjective estimation. Historical beta can be calculated using historical data from market, i.e stock return and market return. Systematically, according to Bodie (2005, p166), beta can be calculated using the following formula: X = Market Return (Rm) Y = Stock Return (Ri) N = number of observation β = Stock Beta II Unsystematic risk Unsystematic risk or diversified risk is a risk that applied only a single stock or a small group of stocks. Unsystematic risk is risk that can be eliminated by way of diversification. Standard deviation is a risk that all investors have to face, i.e a risk that actual return vary from the expected return. The higher the standard deviation, the higher variability of the expected return.

5 10 Figure 2.1 Relationship between Systematic Risk and Unsystematic Risk The above illustration explains the relationship between systematic risk and unsystematic risk. Both risks are illustrated as total risk which is the sum of systematic risk and unsystematic risk. Total risk represents the risk level of investment in general. II.2. Stock Return Risk is highly correlated with return because investors expect return equal to the risk of their investment. According to Brigham (1999, p192), the definition of return is measure the financial performance of an investment. In this research, return is the considered as a proxy to measure the financial performance of a company. Horne and Wachovic (1998, p26) define return as follow Return as benefit which related with owner that includes cash dividend last year which is paid, together with market cost appreciation or capital gain which is realization in the end of the

6 11 year. According to Jones (2000, p124) return is yield and capital gain (loss). Yield, is cash flow paid to shareholder periodically (in form of dividend). Capital gain (loss), is a gap between purchase price of a stock and its sale price. This statement is supported by Corrado and Jordan (2000, p5) that Return from investment security is cash flow and capital gain/loss. Based on above statements, it can be concluded that stock return is capital gain or loss that is obtained by investors as a result of their investment decision. Dividend is a portion of company s profit that is distributed to shareholders during a specific period. Capital gain or loss during a specific period is a gap between beginning price and ending price. If the price at the end of period is higher than the price at the beginning of period, then investor will have capital gain, while on the contrary, the investor will experience capital loss. II.2.1. Type of Return According to Jogiyanto (2003, p109) stock return can be divided into two types: (1) A Realized gain, which represents the return that has been realized. (2) Expected return, which represents return that investor is expected to have in the future. Based on definition, stock return is a yield of an investment that is measured by calculating the gap between current stock price compared to stock price from the last period and ignoring the dividend factors.

7 12 The formula to calculate stock return is presented below: Ri = Stock Return P t = Stock price at t period P t-1 = Stock price at t-1 period Whilst, the market return is calculated using the following formula: Rm = Market return JCI t = Jakarta Composite Index at t period JCI t-1 = Jakarta Composite Index at t-1 period II.3. Capital Asset Pricing Model (CAPM) In Scott, Martin, Petty, and Keown (2005, p205) The capital asset pricing model is an equation that equates the expected rate of return on a stock to the riskfree rate plus a risk premium for the stock s systematic risk. The CAPM provides an intuitive approach for thinking about the return that an investor should require on an investment, given the asset s systematic or market risk. CAPM Equation: k j = k rf + β j (k m - k rf ) k j = the appropriate required rate of return for the j th security

8 13 k rf k m β = risk-free rate = expected return for the market = asset s systematic risk However, according to Faerber (2007, p58) the beta coefficient does not provide a foolproof way to measure the market risk because of the following four factors: The beta coefficient for a company s stock varies if you use different measure of the market The beta coefficient for a company s stock varies if you use different time frames. The risk-return relationship may differ from that predicted by the theory. Lowrisk stocks have earned higher returns than expected, and high-risk stocks have earned lower returns than expected. Relationships between stock prices and market prices change and do not always reflect past relationship. II.3.1. Relationship between Risk and Return According to Fardiansyah (2002, p48), beta is defined as a measurement of a stock sensitivity to market risk or the measurement of contribution of a stock to market risk. By investing in various stocks (portfolio), investors can choose stocks based on their risk appetite. Logically, the higher risk, the higher the return. An investor with high risk appetite will choose stocks with high beta and will be compensated with higher return on investment. On the contrary, an investor with low risk appetite

9 14 will choose stocks with low beta and will be compensated with low return on investment. Several research have studied the relationship between beta and return. Damodaran (2002, p77) summarized: Fama and French (1992) examined the relationship between betas and returns between 1963 and 1990 and concluded that there is no relationship. These results have been contested on three fronts. First, Amihud, Christensen, and Mendelson (1992) used the same data, performed different statistical tests, and showed that differences in betas did in fact explain differences in returns during the time period. Second, Kothari and Shanken (1995) estimated betas using annual data instead of the shorter intervals used in many tests, and concluded that betas do explain a significant proportion of the differences in returns during the time period. Third, Chan and Lakonishok (1993) looked at a much longer time series of returns from 1926 to 1991 and found that the positive relationship between betas and returns broke down only in the period after They also found that betas are a useful guide to risk in extreme market conditions, with the riskiest firms (the 10 percent with highest betas) performing far worse than the market as a whole in the 10 worst month for the market between 1926 and II.4. Debt to Equity Ratio According to Ross, Westerfield, Randolph (2002, p80), Debt to Equity ratio is a proxy to estimate level of leverage of a company. A company with high Debt to Equity ratio may provide higher return to its shareholder, in line with the risk that is faced by the company compared to other company with lower Debt to Equity ratio.

10 15 According to Werner, Jones (2004, p480), Debt to Equity Ratio shows a proportional relationship between debt and equity. The lower Debt to Equity ratio means that total debt is relatively lower compared to total equity. Debt to Equity ratio of a company must be evaluated from few perspectives, such as (1) the Debt to Equity Ratio of comparable companies, (2) At which business stage the company is in (new companies tend to have more debt), (3) Company s policy that considers the optimum level of debt financing. II.4.1. Relationship between Debt to Equity Ratio and Stock Returns According to Bhandari (1988), a natural proxy for the risk of common equity of a firm is that firm s debt/equity ratio (DER). An increase in the DER of a firm increases the risk of its common equity, measuring risk in any reasonable way. Though it does not follow that, cross-sectionally, the common equity of a higher DER firm always has higher risk since the firm-level risk may varies, DER is expected to be positively correlated to the risk of common equity across firms. Therefore, DER proposed to be an additional variable to explain the expected common stock returns. II.5. Leverage According to De Medeiros, Lustosa, and Dantas (2006), the concept of leverage derives from the idea of lever in physic, which is associated with the

11 16 achievement of a final outcome that is more than proportional to the force employed. In the economic and financial environment of firms, two types of leverage stand out: the operating (related to the asset s structure) and the financial (related to the capital structure) leverage. In business terminology, high leverage means that a small change in sales will result a significant change in operating income. Horne and Wachoviz (1998, p425) define leverage as the use of fixed cost in an attempt to increase (to lever up) profitability. II.5.1.Degree of Operating Leverage Garrison and Noreen (2003) define operating leverage as the degree of response of earnings to changes on sales revenues. It expresses the possibility of a more than proportional increase on operating earnings with respect to a raise on sales, working as an amplifier. Dugan and Shriver (1992) present a more dynamic concept, in which operating leverage is a function of the fixed costs and reflects the degree of change on the structure of production costs of a given firm, replacing fixed by variable costs. In short, it reflects the operating earnings uncertainty with respect to the sales uncertainty. Thus, operating leverage is an instrument used for the management of fixed costs, and its optimization is obtained through the increase in volume. When a company incurs in high fixed operating costs, an increase on sales revenues results in a relatively higher change in operating earnings. In this condition, managers strive for

12 17 maximization of the utilization of the installed capacity (fixed structure) of the firm, represented by costs and fixed expenses. One of the factor affect the business risk of a company can be examined from how much is the proportion of fixed cost element in the company s cost structure. If the fixed cost element is significant, a small change in sales will results in a large change in ROE and vice versa as cited from Houston and Brigham (2004, p482), In business terminology, a high degree of operating leverage, other factors held constant, implies that a relatively small changes in sales results in a large change in ROE. Degree of Operating Leverage is a function of a company s capital structure, fixed cost and total cost. As been mentioned by Damodaran (2001, p202): A firm that has fixed costs relative to total costs is said to have high operating leverage. A firm with high operating leverage will also have higher variability in operating income than would a firm producing a similar product with low operating leverage. Other things remaining equal, the higher variance in operating income will lead to a higher beta of the firm with the high operating leverage. According to De Medeiros, Lustosa, and Dantas (2006), since the degree of operating leverage is an accounting measure associated to business risk, one might suppose that it is related to the systematic risk of stock, i.e. the beta (β) from the Capital Asset Pricing Model (CAPM), which also a risk measure but determined by the market. Rubinstein (1973) develops an equation to express expected stock returns and demonstrates that the premium for the operating risk is the product of four

13 18 factors, among them the degree of operating leverage, which is captured by the margin of contribution. The relationship between systematic risk and operating leverage is also put by Lev (1974), who concludes that when the degree of operating leverage increases (decreases), the volatility of stock returns also increases (decreases). The evidence on the association between these variables is supported by Gahlon (1981), who shows that instabilities observed in firm s betas might be explained by changes on the DOL and by sales variability. Moyer, McGuigan, and Kretlow (1981) also associate risk to operating leverage, demonstrating this relationship based on the following rationale; if the DOL is the firm s earning response to changes on the sales level, the higher the DOL of a firm is, the higher the change on the operating earnings for a given change on sales will be Hence, cateris paribus, the higher the DOL of a firm is, the higher the operating risk level will be. In practice, the risk of installed capacity becomes perceptible when instead of an increase on the revenues volume, a decrease is observed. In this case, the operating leverage mechanism acts inversely, amplifying losses. For a high DOL structure, a growth on revenues may result in high operating gains, in the same way that reductions on revenues may lead to large operating losses. % % According to Scott, Martin, Petty, and Keown (2005, p519), Operating leverage is the responsiveness of the firm s EBIT to fluctuations in sales. DOL equation based on sales:

14 19 % % If the variable cost data is available, the following formula can be used: To use the above formula, variable cost information must be available to calculate the operating leverage. However, if such data is not available and only the income statement that is available, the following formula can be used: Scott, Martin, Petty, and Keown (2005, p522) mentioned, The three versions of the operating leverage measure all produce the same result. Data availability will sometimes dictate which formulation can be applied. The crucial consideration, though, is that you grasp what the measurement tells you. II.5.2. Relationship between Degree of Operating Leverage and Stock Returns According to Martikainen (1993), considering the association between operating leverage and systematic risk of stocks, between risk and stock returns, and between the systematic risk and stock returns, it should be logical to infer an association between the degree of operating leverage and stock returns. Besides, considering the positive theoretical relationship between systematic risk and

15 20 operating leverage, one should expect a positive relation between stock returns and operating leverage for a given firm.

Lecture 5. Return and Risk: The Capital Asset Pricing Model

Lecture 5. Return and Risk: The Capital Asset Pricing Model Lecture 5 Return and Risk: The Capital Asset Pricing Model Outline 1 Individual Securities 2 Expected Return, Variance, and Covariance 3 The Return and Risk for Portfolios 4 The Efficient Set for Two Assets