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Industry Beta Approach

Guide to Understanding the Industry Beta (β) Approach

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Industry Beta Approach

In This Article
  • What are the steps to calculate the industry beta?
  • What are the benefits of using the industry beta approach?
  • What are some of the drawbacks to using the observed beta?
  • How do differences in the capital structure (debt/equity ratio) impact beta?

Industry Beta Approach Overview

Beta (β) is a metric that represents the sensitivity of a security or portfolio to systematic risk, i.e. the relative volatility compared to the broader market (S&P 500).

However, beta is under constant criticism from industry practitioners based on the notion that it is a flawed measure of risk.

The process of calculating beta is by running a regression model that compares a stock’s historical returns to the market benchmark returns (e.g. S&P 500) for a specified time span.

The slope of the regression line represents the beta of the company – but there are several issues:

  • “Backward Looking”: The calculation of beta using historical data is one major drawback to the metric, as past performance is an imperfect indicator of future performance.
  • Constant Capital Structure: A company’s capital structure is a critical factor in determining a company’s volatility, yet the inevitable changes in the debt-to-equity ratio are not reflected in beta (e.g. the component weights adjust as companies mature and new developments within the markets emerge).
  • Neglected Business Adjustments: The historical beta captures business risk across a specified period (i.e. over the regression model), which can be misleading especially if the company had implemented significant changes in its business model, target customer profile, end market targets, etc.
  • Large Standard Error: The regression model used to calculate beta is highly sensitive to the assumptions used, e.g. company-specific events can distort the implied market correlation.

Benefits to the Industry Beta Approach

The limitations to the beta calculation – namely those related to the capital structure – explains why the industry beta may be used.

The regression model is based on the historical data (and capital structure weights), as opposed to the current debt-to-equity mix, which would be more accurate in projecting future performance and volatility.

As an alternative, the industry beta approach calculates a company’s beta by integrating an aspect of “comps” to determine its future volatility.

The implied assumption here is that the target company’s business risk will gradually converge to be on par with that of its peer group over the long term, i.e. the performance of comparable companies is more indicative of the company’s future performance than the company’s own historical performance.

In practice, however, both the observed beta and industry beta are calculated side-by-side as a sanity check.

The benefits are that any company-specific noise is eliminated, which refers to eliminating distorting events that could’ve potentially caused the correlation in its historical beta to be misleading.

Therefore, the industry beta – i.e. the peer-group derived beta – is a “normalized” figure because it takes the average of the unlevered betas of comparable businesses, which is then re-levered at the target capital structure of the company being valued.

In addition, private companies do not have a readily-available beta, so the industry beta approach must be used in the case of valuing private companies.

Industry Beta Approach Calculation

Levered and unlevered beta are two different types of beta (β), with the distinction being related to the inclusion or removal of the impact of debt in the capital structure.

  • Levered Beta → Inclusive of Capital Structure (D/E) Effects
  • Unlevered Beta → Absence of Capital Structure (D/E) Effects

The process of calculating the industry beta is a three-step process:

  1. Peer Group: First, comparable companies to the target company are compiled. These companies should operate in the same (or similar) industry as the target, with similarities in the revenue model, target customer profile, end market served, risks, etc.
  2. De-Lever Beta: Next, since differences in capital structure can distort the observed beta of companies (i.e. more leverage → more volatility), the effects of debt must be removed by calculating the unlevered beta of all the companies in the peer group. The reason we cannot just take the average of the raw betas is that those figures include the effects of debt, making it paramount to de-lever the peer group’s collective betas.
      • De-Levered Beta = Levered Beta / [1 + (1 – Tax Rate) * (Debt / Equity)]
  3. Re-Lever Beta: Finally, the average of the unlevered betas will be applied to the target company’s optimal target structure, which is a subjective judgment call based on the company’s current capital structure and the capital structure of comparable companies, among other factors.
      • Re-Levered Beta = Unlevered Beta * [1 + (1 – Tax Rate) * (Debt / Equity)]

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