Sectoral beta coefficient as a stable measure of risk
R. Levy's research in the 1970s. proved that for any share its beta-coefficient is not sustainable in time and therefore can not serve as an accurate estimate of future risk. Nevertheless, the beta portfolio, consisting of even 10 randomly selected shares, is fairly stable and, therefore, can be viewed as an acceptable measure of portfolio risk.
Another interesting observation: the beta coefficient shows a largely sectoral reaction to macroeconomic shifts (changes in the business cycle, inflationary outbursts, etc.). Companies of consumer industries (B2B), energy companies have a beta coefficient of less than one. Cyclic companies that are sensitive to the business cycle and consumer preferences (car manufacturers, manufacturers of sophisticated home appliances, developers) have beta-coefficient values greater than one (at the level of 1.2-1.4). Even higher values of the beta coefficient are shown by high-tech companies, which are highly uncertain about the persistence of demand for products (online stores, Internet search engines, sophisticated ultramodern equipment manufacturers).
Ibbotson Associates , to address the instability of the beta factor for individual companies, uses the industry-level reception.
Adoption of the industry beta-coefficient - replacement of the actual (raw) beta-factor in CAPM with the adjusted, calculated as industry-specific.
Distortions on the actual beta-factor companies are usually recorded in cases where there were restructuring processes during the period on which the regression analysis was built. Estimated actual the value of the beta coefficient from past data will not reflect the current and future level of systematic risk, as the shift in the structure of assets used, the direction of cash flows inevitably generated in the past fluctuations in profits, stock prices and ultimately changed the average level and yield volatility. Another motive for using the industry level is the evaluation of closed companies for which there are no stock quotes and the regression method is not applicable at all. In addition, this method can be recommended for open companies with low stock liquidity (when their prices do not reflect the true processes of supply and demand formation). Instead of virtual beta in the CAPM design there appears the beta of the industry portfolio.
Research by Ibbotson Associates shows that the beta values of companies are more volatile than industry levels, so the systematic risk inherent in a particular company can be fairly well approximated by the industry beta coefficient.
Recommended algorithm for the investor:
- determine the company's industry affiliation;
- for the directories to find the average sectoral value of the beta coefficient or the beta coefficient of the portfolio made up of companies in this sector (the sector of the economy);
- clear sectoral beta-factor from the effect of financial leverage. This is a typical, mandatory correction that analysts use. You can often see more detailed approaches to the accounting of specific characteristics of companies. For example, adjustments are made for the size, for the time horizon of the proposed investment;
- to adjust the industry beta-factor taking into account the capital structure of the analyzed company - "To put the financial risk on beta";
- the corrected value is applied to CAPM.
Ibbotson Associates , with a certain periodicity (every six months), compiles directories (tables) on sectoral beta coefficients according to the standard industry classification classification (SIC ) . As part of this classification, the company is a specific industry, if more than 75% of its revenue falls on the relevant activity. In addition, the Ibbotson Associates tables are detailed taking into account the size of the companies (the smaller the size, the higher the beta value, all other things being equal), the median value of the industry beta, the beta-factor with debt financing and ; cleaned values ( unlevered beta). The corrected beta-factor values are also indicated to exclude distortions related to the presence of a large number of integrated companies (in which the shares of other areas of activity are large). Other specialized companies refine the industry-level algorithm for sectoral sectors (in fact, regression analysis of the sub-sector to the market portfolio). The goal is to highlight the individual risks of the sub-sector and to calculate the measure of their systematic risk. In practice, analysts often take the industry level as the basis for assessing the profitability of segments within the industry, or in the absence of the analyzed sector (industry) in specialized tables take the value of the beta coefficient at the level of unity (as market risk).
In some cases, a formula is used for the weighted average values from the actual and branch values of the beta coefficient. The higher the error value in the regression equation, the more important the industry coefficient becomes.
Also We Can Offer!
- Argumentative essay
- Best college essays
- Buy custom essays online
- Buy essay online
- Cheap essay
- Cheap essay writing service
- Cheap writing service
- College essay
- College essay introduction
- College essay writing service
- Compare and contrast essay
- Custom essay
- Custom essay writing service
- Custom essays writing services
- Death penalty essay
- Do my essay
- Essay about love
- Essay about yourself
- Essay help
- Essay writing help
- Essay writing service reviews
- Essays online
- Fast food essay
- George orwell essays
- Human rights essay
- Narrative essay
- Pay to write essay
- Personal essay for college
- Personal narrative essay
- Persuasive writing
- Write my essay
- Write my essay for me cheap
- Writing a scholarship essay