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, 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.

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