Divisional Hurdle Rates - Randolph Corporation

1878 WordsNov 26, 20128 Pages
Introduction The Randolph Corporation is a multidivisional producer of electric sanders, sandpaper, industrial grinders and sharpeners, and coated ceramics. The Corporation also has a real estate development division. The diverse product lines of the company divide the corporation into four divisions, namely, real estate, ceramic coatings, equipment manufacturing and home products. The Randolph Corporation Stock performed below expectations recently, when compared to other player in the industry. The company’s main problem is believed to lie in the financial planning processes and in the risk consideration. To tackle these problems the assistant to the firm’s vice president suggests a target capital structure of 45% debt in every division…show more content…
Some modifications of the beta coefficient are the adjusted beta and the fundamental beta. The former tries to transform the historical beta closer to an average beta of 1.0. The latter seeks to incorporate information concerning the company to achieve a better estimate for beta. Moreover, beta values out of less-developed financial markets are not good estimates and therefore partly biased. Problems in estimating beta for divisions of a corporations could arise if the divisions are too small and therefore can be compared with less-developed financial markets. Hence, beta coefficients could be biased (Brigham & Daves, 2007). Thus we can suggest that beta values are very inconsistent and partly biased. Beta Value – Total Risk Analysis First, the beta value is known as an estimation for the market risk a corporation is faced to. Therefore, it is difficult to find beta for the total risk of the corporation. Total risk is actually measured by the variance or the standard deviation, respectively. So, if one tries to find beta for total risk, it is also possible to calculate the WACC or the hurdle rates for each division, respectively, because there is a high correlation between divisional betas and project’s betas. The latter can be estimated through a Monte Carlo analysis. The resulting estimates for the variance of the projects can be included in the following formula for beta: β_i=(σ_i/σ_M )*ρ_iM So

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