- Weighted Average Cost of Capital (WACC)
- Methods of Calculating Weights in WACC
- Applications of Cost of Capital
- Weighted Average Cost of Capital (WACC) - Practical Example and Issues
- Calculating Cost of Debt: YTM and Debt-Rating Approach
- Issues in Estimating Cost of Debt
- Estimating the Cost of Preferred Stock
- Estimating the Cost of Common Stock
- Calculating Beta Using Market Model Regression (Slope)
- Calculating Beta Using Pure Play Method
- Estimating the Country Risk (Country Equity Premium)
- Marginal Cost of Capital (MCC) Schedule
- Flotation Costs and WACC

# Methods of Calculating Weights in WACC

From the perspective of an investment analyst, the weights used in the calculation of WACC should be calculated on the basis of target capital structure that the firm expects to achieve. However, since it’s difficult to find out the company’s target capital structure, the analysts will use the current capital structure of the company as a proxy for their target capital structure. In doing so, they will current capital structure based on the market values of each component.

Let’s say the market values of a firm’s capital are: Debt outstanding – $4 million, Preferred - $1 million, and Equity - $5 million.

Total capital is $10 million.

With this information we can calculate the weight of each component

**W _{d} = 4/10 = 0.40**

**W _{p} = 1/10 = 0.10**

**W _{e} = 5/10 = 0.50**

The analyst may also use any other information available to him while determining the weights. For example, if he notices that the firm has been consistently issuing more debt year after year, he may use a higher weight for the debt component. He the analyst believes that the firm’s current capital structure is not a good indicator of its target capital structure then he can also use the average capital structure of the industry.

### You may find these interesting

#### Related Downloads

#### Related Quizzes

## Free Guides - Getting Started with R and Python

Enter your name and email address below and we will email you the guides for R programming and Python.