Systematic risk

Systematic risk arises an account of the economy-wide uncertainties and the tendency of individual securities to move together with changes in the market. Also known as market risk.This is the risk can not be reduced through diversification.

Investor are exposed to market risk. Even when they hold well-diversified portfolio of securities systematic risk of the security.It can not be diversified because like other securities it also moves with the market.

As mention in paragraph systematic risk is not diversifiable. Investor do not pay any premium for diversifying total risk via reduction in non-systematic risk.They can do on their own, cheaply and quickly.

Add in the last of part example of systematic risk.

->The government changes the interest rate policy. The corporate tax rate increased.

->The government result to massive deficit financing.

->The RBI promulgates a restrictive credit policy.

->The government relaxes the foreign exchange contracts and announces full convertibility of the Indian rupee.

->The government withdrawal tax on dividends payment by companies.

->The government eliminates reduces the capital gain tax rate.

All securities have some systematic risk, whether bonds or stocks.I have systematic risk directly compasses interest rate risk, market risk,and inflation risk. In this discussion, however the emphasis will be on the systematic risk of common stock.

In this case, systematic risk is that part of the variability correlated with the variability of the stock market as a whole.

Measuring systematic risk.

A measure needed of this unavoidable systematic or nondiversifiable based on modern portfolio theory. The beta has emerged as such a measure. Beta’s usefulness as a measure of risk is briefly discussed here.

Beta is a relative measure of risk of an individual stock in relation to the overall market, as measure by the volatility of its returns by statistically relating the return for a security to the returns.

By statistically relating the returns for the stock market as whole (using a regression equation) it is possible to determine how the security’s returns move in relation to the market’s returns move  more( less) then the markets returns.

If the security’s returns move more(less) than the market’s returns. As  the latter changes, the security is said to be more (less) volatile than the market for example. A security whose returns rise or fall an average 15% when the market return rise or falls 10% is said to be volatile security.

Beta is the slope of the regression line relating a securities returns to those of the market. If the slope of this relationship for a particular security is a 45- degree angle. This means that for every 1% change in the market return, on average this security’s returns change 1%  if the line is higher, beta is higher,managing that the volatility( market risk) is greater

For Example, security A’s beta of 1.5 indicate that, on average security returns are 1.5 as volatile as market returns Both up and down. If the line is less steep than the 45 degree line beta is less than 1.0. This indicate that, on average, a stock’s returns have less volatility than the market as a whole. For example security c’s beta of 0.6 indicate that stock returns move up or down generally only 60% as much as the market as a whole.

The aggregate market has beta of 1.0. More volatile (risky) stock have betas small than 1.0 as a relative measure of risk, beta is very convenient if an investor is considering a particular stock and is informed that is beta 1.0,this investor can recognize immediately that the stock is very risky.

In relation to the average beta for all stock is 1.0 many brokerage houses and investment advisory services report betas as part of the total information given for individual stocks.

Estimating systematic risk

Betas are estimated from historical data, regressing for the individual security against the for some market index. As result, the usefulness of betas will depend on, among other factors, the volatility of the regression equation. Regardless of how good the fit it, however beta is an estimate subject to errors.

It is important to note that most calculated betas are ex post betas. What is actually needed in investment decision is an ex ante beta measuring expected volatility.

The common practice of many investor is simply to calculate the beta for a security and assume it will remain constant in the future . A risky assumption in the case of individual securities similar to standard deviations portfolio betas often are quite stable across time whereas individual security betas often are notoriously unstable.

However, this is not an unfavorable outcome for investors because the basic premise of portfolio theory is the necessity of holding a portfolio of securities rather than only on or a few securities.

Substantive evidence has been presented that betas tend to move toward 1.0 overtime. Betas substantially larger( smaller) than 1.0 should tend to be followed by betas that are lower, and closer to 1.0 .

Thus, forecasted betas should be closer to 1.0 thus, forecasted betas should be closer 1.0 than the estimates based solely on historical data would suggest. Several models have been advocated for adjusting betas for this tendency to ” regress toward the mean. As a result it is not unused to find ” adjusted ” betas rather than historical betas.





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