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Risk and Return.

Risk and Return. Risk and Uncertainty. Risk and returns are two sides of the investment coin. Risk is associated with the possibility of not realizing return or realizing less return than expected.

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Risk and Return.

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  1. Risk and Return. • Risk and Uncertainty. • Risk and returns are two sides of the investment coin. • Risk is associated with the possibility of not realizing return or realizing less return than expected. • The degree of risk varies on the basis of the features of the assets, investment instruments, the mode of investment, the issuer of securities etc. • Thus, risk of an investment is the variance associated with its returns. • The objective of risk management is not elimination of risk but proper assessment of the risk and deciding whether it is worth taking or not.

  2. Risk and uncertainty. • Risk refers to a situation where the decision maker knows the possible consequence of a decision and their related likelihoods. • Uncertainty involves a situation, about which the likelihood of possible outcome is not known. • Uncertainty cannot be quantified whereas risk can be quantified of the likelihood of future outcomes. • The degree of risk depends upon the features of assets, investment instruments, mode of investments etc.sss

  3. Causes of Risks. • Wrong method of investment. • Wrong timing of investment. • Wrong quantity of investment. • Interest rate risk. • Nature of investment instruments. • Nature of industry in which the company is operating. • Creditworthiness of the issuer. • Maturity period. • Terms of lending. • National and International factors. • Natural calamities etc.

  4. Types of Risk. • Systematic risk. • Systematic risk refers to that portion of variation in return caused by factors that affect the price of all securities. • The systematic risk cannot be avoided. It relates to economic trends which affect the whole market. • The systematic risk cannot be eliminated by diversification of portfolio, because every share/bond is influenced by general market trend.

  5. Cont- • Unsystematic risk. • Unsystematic risk refers to that portion of the risk which is caused due to factors unique or unrelated to a firm or industry. • This risk is a company’s specific risk and can be controlled if proper measures are taken. • As it is unique to a particular firm or industry it is caused by factors like labour unrest, management policies, shortage of power, recession in a particular industry, consumer preferences etc.

  6. Risk and Expected return. • There is a positive relationship between the amount of risk assumed and the amount of expected return. Greater the risk, the larger the expected return and the larger the chances of substantial loss. • Investment which carry low risk such as high grade bonds will offer a lower expected rate of return than those which carry high risk such as equity stock of a new company. • A rational investor would have some degree of risk aversion, he would accept the risk only if he is adequately compensated for it. • One of the most difficult problems for an investor is to estimate the highest level of risk he is able to assume. Any such estimate is essentially subjective, although attempts to quantify the willingness of an investor to assume various levels of risk can be made.

  7. Measurement of Risk. • Risk is associated with the variability in the likelihood of its outcomes. If the returns of an asset have no variability, it has no risk. • There are different ways to measure variability of returns or the risk associated with an asset. • The behavioural view of risk can be obtained by using: • (i) sensitivity analysis or the range method. • (ii) probability distribution. • The quantitative or statistical measures of risk include: • (i) standard deviation • (ii) coefficient of variation.

  8. Sensitivity or range analysis. • Where different returns from an asset are possible under different circumstances, more than one forecast of the future returns may be made. • These returns may regarded as ‘ optimistic’, ‘most likely’ and ‘pessimistic’. • The range of the returns is the difference between the highest possible rate of return and the lowest possible rate of return. • According to this measure, an asset having greater range is said to be more risky than the one having lesser range.

  9. Cont- • The following example illustrate the sensitivity analysis. • asset A asset B • Initial cash outlay Rs 100 lakhs Rs 100 lakhs • Rate of return %: • Pessimistic 10 6 • Most likely 12 12 • Optimistic 14 18 • Range (highest –lowest • possible return) 4 12 • We can say that Asset B having greater range of returns is more risky.

  10. Probability Distribution. • The risk associated with an asset can be measured more accurately by the use of probability distribution than the range analysis as the range is based on only two extreme values. The probability of an event represents the chances of its occurrence. • For instance, if the chance of an event taking place is 3 out of 5, it can be said to have 60% chance or 0.60 probability.

  11. Cont- • The expected rate of return for any asset is the weighted average of all possible returns multiplied by their respective probabilities. This can be represented as below: • E ( R) = n/sigma Pi*Ri • Where E( R) = expected return • n= No of possible outcomes • Pi=probability associated with ith possible out come. • Ri= Rate of return for the ith possible outcome.

  12. Cont- • The expected rate of return for assets A and B is presented in the following example. • Possible prob. Rate of return expected/retur • Outcome Pi Ri(%) E( R) = Pi*Ri • 1 0.25 10 2.5 • 2 0.50 12 6.0 • 3 0.25 14 3.5 • total = 12.00.

  13. Cont- • Expected return for asset B. • Possible Prob. ROR Expected return • outcome Pi Ri E (R)= Pi*Ri • 1 0.25 6 1.50 • 2 0.50 12 6.00 • 3 0.25 18 4.50 • total = 12.00

  14. Standard Deviation. • Standard deviation is the most common quantitative measure of risk of an asset. Unlike the range, it considered every possible event and weight equal to its probability is assigned to each event. • In this method the deviations are squared making all values positive. Then the weighted average of these figures is taken, using probabilities on weights. The result is termed as variance. It is converted to the original units by taking the square root. The result is termed as standard deviation. • SD= formul

  15. Cont- • S= Standard deviation • n= No of possible outcomes • Ri= Rate of return from the ith possible outcomes • E( R)= Expected return • Pi = Possibility associated with the ith possible outcomes. • Note—the greater the standard deviation of return an asset, the greater is the risk of the asset. Thus, the investor usually prefers investments with higher rate of return and lower standard deviation.

  16. Standard deviation measure of risk. • For asset A. • P/O ROR E(R ) d =Ri-E( R) (d)2 Prob Pi*d • 1 10 12 -2 4 0.25 1.00 • 2 12 12 0 0 0.50 0.00 • 3 14 12 2 4 0.25 1.00 • total = 2.00 • SD= under root of 2.00= 1.414.

  17. Standard deviation measure of risk. • For asset B. • P/O ROR E(R ) d =Ri-E( R) (d)2 Prob Pi*d • 1 6 12 -6 36 0.25 9.00 • 2 12 12 0 0 0.50 0.00 • 3 18 12 6 36 0.25 9.00 • total = 18.00 • SD= under root of18.00=4.243 • Note– it is clear from the above that asset B is more risky as the SD of asset is greater than that of asset A.

  18. Coefficient of Variation. • Standard deviation is an absolute measure of dispersion and it may give misleading results if the alternative assets differ in size of expected returns. In such a case, coefficient of variation may be used as a better measure of risk . • Coefficient of variation is a relative measure of dispersion in which risk per unit of expected return is calculated as: • CV= SD/ Mean or Sd/ E( R).

  19. Cont- • Coefficient of variation of assets of A and B. • C V of A = 1.414/12= 0.1178 • C V of B = 4.243/12= 0.3536 • As the coefficient of variation of asset B is more , it can be said to be more risky as compared to asset A.ssssss

  20. Question. • Star Computer System Ltd has forecasted returns on its share with the following probability distribution: • Return(%) Prob. • -20 0.05 • -10 0.05 • -5 0.10 • 5 0.10 • 10 0.15 • 18 0.25 • 20 0.25 • 30 0.05 • Calculate the expected return, variance and SD for returns for Star computer system Ltd.

  21. Cont- • E (R)= R1*P+ R2*P2+R3*P3--------- • Variance of returns • (Sd )2= (R1-E(R))2*p1+(R2-E(R))2*p2----- • S d = under root of variance.

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