Operating Leverage

Joachim Kuczynski, 01 November 2025

Net Income

With the abbreviations \mu … net income, S … sales, F … fix expenses, V … variable expenses, A … depreciation and amortization, T … taxes, I … interests for debt and X … tax shield we can define net income by:

(1)   \begin{equation*}\mu=S-F-V-A-T-I+X\end{equation*}

Let r_D be the interest rate for debt and r_t be the incremental tax rate. We assume that we get full tax shield of X=Dr_Dr_t. Taxes T are paid on EBIT, that means T=(S-F-V-A ) r_t. Z=equity+debt is the asset or enterprise value and d is the debt ratio, d=D/Z. Substituting that in the previous expression we obtain:

(2)   \begin{equation*}\mu=(S-F-V-A)(1-r_t)-dZr_D+dZr_Dr_t\end{equation*}

Summarizing the terms leads to:

(3)   \begin{equation*}\mu=(S-F-V-A-dZr_D)(1-r_t)\end{equation*}

Beta of a weighted sum is the weighted sum of the components’ betas, shown in the post “Portfolio Beta”. Thus we get an equation for the betas:

(4)   \begin{equation*}\mu\beta_\mu=(S\beta_S-F\beta_F-V\beta_V-A\beta_A-dZr_D\beta_D)(1-r_t)\end{equation*}

We assume that fix expenses (F), depreciation, amortization (A) and debt (D) have no correlation to the market return rate, \beta_F=0, \beta_A=0, \beta_D=0. Variable expenses should have the same correlation to market development as sales, that gives \beta_V=\beta_S. We obtain:

(5)   \begin{equation*}\mu \beta_\mu=\left( S-V \right) \left( 1-r_t \right) \beta_S\end{equation*}

Substituting \mu=\left( S-F-V-A -dZr_D \right) \left( 1-r_t \right) leads to:

(6)   \begin{equation*}\beta_\mu= \frac{ S-V }{ S-F-V-A -dZr_D }\beta_S\end{equation*}

Rearranging the terms shows:

(7)   \begin{equation*}\beta_\mu=\left( 1+ \frac{ F+A+dZr_D }{ S-F-V-A -dZr_D } \right) \beta_S\end{equation*}

Return on Equity

Return on equity measures relative equity increase. It is defined by:

(8)   \begin{equation*}\text{ROE}=\frac{\text{net income}}{\text{equity}}=\frac{\mu}{(1-d)Z}\end{equation*}

With the substitution of \mu we obtain:

(9)   \begin{equation*}\text{ROE}=\frac{\left( S-F-V-A-dZr_D \right)(1-r_t) }{(1-d)Z}\end{equation*}

We want to link the beta of ROE to the beta of net income. We take the definition of \beta with its bilinearity of covariance and get:

(10)   \begin{equation*}\beta_{\text{ROE}}=\frac{cov(r_\frac{\mu}{E}, r_m)}{var(r_m)}=\frac{\frac{1}{E}cov(r_\mu, r_m)}{var(r_m)}=\frac{1}{E}\beta_\mu=\frac{1}{(1-d)Z}\beta_\mu\end{equation*}

Hence we get \beta_{\text{ROE}} as function of \beta_S:

(11)   \begin{equation*}\beta_{\text{ROE}}=\left(\frac{ S-V }{ S-F-V-A -dZr_D}\right)\frac{1}{(1-d)Z}\beta_S\end{equation*}

(12)   \begin{equation*}\beta_{\text{ROE}}=\left( 1+ \frac{ F+A+dZr_D }{ S-F-V-A -dZr_D}\right)\frac{1}{(1-d)Z}\beta_S\end{equation*}

This is the relationship of the ROE beta and the sales beta. It depends on several variables, but especially on fixed expenses F+A+dZr_D.

Releveraging Equity Return Rate and WACC

An equity investor wants to know which return rate market provides at the same risk (volatility) level as our investigated investment. The WACC after taxes of the appropriate market portfolio is given by:

(13)   \begin{equation*}\text{WACC'}=d'r_D'\left( 1-r_t' \right)+(1-d')r_{E'}\end{equation*}

I indicate all market portfolio parameters with a line on the top. r_{E'} ist the required return rate of an incremental equity investor. This is the return rate of the completely diversified market portfolio of the appropriate industry segment. The Capital Asset Pricing Model (CAPM) states that r_{E'} can be approximated by a linear function of \beta_{E'} by a given market return rate r_m:

(14)   \begin{equation*}r_{E'}=r_f+\beta_{E'}\left( r_m-r_f \right); \beta_{E'}=\frac{cov(r_{E'},r_m)}{var(r_m)}\end{equation*}

\beta_{E'} is the average equity \beta of an market portfolio representing the investigated investment. It is based on an averaged financial and operating leverage of the market portfolio. If these parameters do not match capital and cost structure of the considered investment, you have to “releverage” \beta_{E'}.

Operating leverage: We have a look at the relationship of \beta_{E'} and \beta_{S'}:

(15)   \begin{equation*}\beta_{\text{E'}}=\left(\frac{ S-V' }{ S'-F'-V'-A' -d'Z'r_D'}\right)\frac{1}{(1-d')Z'}\beta_{S'}\end{equation*}

\beta_{E'} is provided by an official data collection in most cases. With the other data from the market portfolio we can calculate \beta_{S'}:

(16)   \begin{equation*}\beta_{\text{S'}}=\left(\frac{ S'-F'-V'-A' -d'Z'r_{D'} }{S'-V'}\right)(1-d')Z'\beta_{E'}\end{equation*}

\beta_{S'} is the linear approximated change of sales because of a change in market return rate r_m. \beta_{S'} does not depend on F, V, Z, D, d and r_D. \beta_{S'} is the same for all combinations of these parameters, that means \beta_S=\beta_{S'}. Now we take the parameters of the investment, to which we want to adjusted \beta_E. With the \beta_{S'} from the previous equation we obtain the adjusted \beta_E:

(17)   \begin{equation*}\beta_{\text{E}}=\left(\frac{ S-V }{ S-F-V-A-dZr_D}\right)\frac{1}{(1-d)Z}\beta_S\end{equation*}

With this \beta_E we can calculate the new equity return rate r_E:

(18)   \begin{equation*}r_E=r_f+\beta_E\left( r_m-r_f \right)\end{equation*}

After the releveraging process we get the releveraged WACC with the appropriate r_E:

(19)   \begin{equation*}\text{WACC}=dr_D\left( 1-r_t \right)+(1-d)r_E\end{equation*}

Portfolio Beta

Joachim Kuczynski, 12 September 2025

Beta (\beta) measures the sensitivity (covariance) of an asset’s return to the market return. If you have multiple assets in a portfolio, the betas don’t simply add up. Rather they are weighted by their values in the portfolio. This is what I want to prove in this post.

A portfolio beta \beta_p is defined by:

    \[\beta_p=\frac{cov(r_p,r_m)}{var(r_m)}\]

r_m is the market return rate. The return rate of a portfolio, r_p, is the weighted average of its components’ return rates:

    \[r_p=\sum_{i=1}^{n}\alpha_ir_i\]

\alpha_i stands for the relative value share of asset i in the portfolio. The covariance of two random variables is bilinear. Hence we get:

    \[cov(r_p, r_m)=cov(\sum_{i=1}^{n}\alpha_ir_i,r_m)=\sum_{i=1}^{n}\alpha_icov(r_p, r_m)\]

Inserting that into the definition of \beta_p leads to the final result:

    \[\beta_p=\frac{\sum_{i=1}^{n}\alpha_icov(r_p, r_m)}{var(r_m)}=\sum_{i=1}^{n}\alpha_i\beta_i\]

This proves that \beta_p of a portfolio with n assets is the weighted average of its components, weighted by their relative value share in the portfolio.

Consent Management Platform by Real Cookie Banner