Why one risk input can materially change the value of a business

In 2020, a Delaware appraisal dispute turned on a seemingly small detail in a valuation model: the equity beta used to calculate the company's cost of equity.

In Manichaean Capital v. SourceHOV Holdings, experts on both sides disagreed over how beta should be calculated. The Delaware Court of Chancery rejected the company's expert's approach, and the court's decision ultimately put the methodology behind the beta under scrutiny. The case is important because it demonstrates a basic valuation principle: a number in a financial model does not become defensible simply because the model looks sophisticated.

Beta often looks like a small decimal tucked between other assumptions. But it feeds into the cost of equity, which influences the discount rate and, ultimately, the present value assigned to future cash flows.

That makes the real question less about finding 'the beta' and more about asking: **How was the beta derived, and can the methodology withstand scrutiny?**

Why Beta Matters

Beta measures the sensitivity of a security's returns to movements in the broader market. In the Capital Asset Pricing Model (CAPM), it is used to estimate the equity risk component of the cost of equity.

The relationship is commonly expressed as:

Cost of Equity = Risk-Free Rate + Beta × Equity Risk Premium

If beta rises, the equity risk component rises. A higher cost of equity can increase the discount rate used in a valuation and reduce the present value of future cash flows. If beta falls, the opposite can occur.

The effect compounds across a discounted cash flow model. A change that looks small at the input level can become meaningful when applied to years of projected cash flows.

For example, if the risk-free rate and equity risk premium remain unchanged, moving from a beta of 1.05 to 1.25 increases the equity risk component by 0.20 × the equity risk premium. Whether that materially changes value depends on the rest of the model, but the direction is clear: the beta assumption affects the cost of capital and therefore valuation.

The Problem: Most Private Companies Don't Have a Beta

A public company's beta can be estimated from historical share-price data by regressing its returns against a market index. But private companies, subsidiaries, divisions and closely held businesses do not have a traded share price from which to calculate a direct regression beta.

So beta has to be built rather than observed.

That is where the bottom-up approach becomes useful. Instead of asking what the private company itself traded at in the past, the analyst looks at publicly traded companies that operate in comparable businesses, estimates their underlying business risk, removes the effect of their capital structures, and then adjusts that risk for the company being valued.

Aswath Damodaran's valuation materials describe bottom-up beta as a process based on comparable businesses, unlevering their betas, weighting the underlying business risks and then relevering for the subject company's financial leverage. citeturn0search0turn0search2

Step 1: Build the Right Peer Set

The first judgment is arguably the most important: which companies are actually comparable?

Industry labels alone are not enough. A useful peer set should consider business mix, geography, customer base, growth stage, operating characteristics and size.

Imagine a private SaaS company with recurring enterprise revenue. Using a broad technology peer set could introduce businesses with very different economics—hardware manufacturers, semiconductor companies, consumer internet platforms or early-stage businesses.

The calculation may still produce a precise-looking number. But precision does not make the underlying comparison appropriate.

A weak peer set can therefore distort every step that follows.

Step 2: Unlever the Comparable Betas

Observed equity beta reflects both operating risk and financial leverage. A highly leveraged company can have a different equity beta from a company operating in the same industry with much less debt.

Unlevering attempts to remove the effect of the comparable company's capital structure so that the analysis focuses more directly on the risk of the underlying business.

A commonly used relationship is:

Unlevered Beta = Levered Beta ÷ [1 + (1 − Tax Rate) × Debt/Equity]

The resulting unlevered beta can then be used as a cleaner measure of business or asset risk. Damodaran notes that averaging across comparable firms can reduce some of the noise found in individual regression betas. citeturn0search2

Step 3: Relever for the Company Being Valued

Once an appropriate unlevered beta has been established, the analyst adjusts it for the capital structure of the subject company.

A simplified Hamada-style relationship is:

Levered Beta = Unlevered Beta × [1 + (1 − Tax Rate) × Debt/Equity]

This matters because two businesses with similar operating risk can have different equity risk if their leverage differs.

For a private company, the analyst may need to consider whether current leverage or a normalized/target capital structure is more appropriate. The choice should reflect the valuation context and the evidence available. citeturn0search2turn0search10

A Simple Example

Consider a private company operating in a single industry.

Suppose the selected comparable companies produce an average unlevered beta of 0.90.

If the subject company's normalized debt-to-equity ratio is 0.50 and the applicable tax rate is 25%, a simplified relevering calculation gives:

0.90 × [1 + (1 − 0.25) × 0.50] = 1.2375

The resulting beta is approximately 1.24.

This is not a universal answer or a substitute for a full valuation analysis. It simply illustrates why a private company's beta is not something that should be copied from a database. It is constructed from the risk of comparable businesses and the financing profile of the company being valued.

Why the Choice of Data Matters

Even after selecting comparable companies, several methodological choices can affect the result.

These include the period used to estimate beta, return frequency, statistical reliability, treatment of thinly traded securities, outliers, leverage measurement and tax assumptions.

A two-year weekly beta can differ from a five-year monthly beta. A thinly traded stock may produce a noisy estimate. A company that has materially changed its business mix may have a historical beta that no longer reflects its current operations.

Damodaran specifically notes that regression betas can have significant standard errors and that bottom-up betas can be more useful because they average across companies and can reflect a company's current business mix and financial leverage. citeturn0search0turn0search11

Case Study: Manichaean Capital v. SourceHOV

The SourceHOV appraisal dispute shows why methodology matters in practice.

The Delaware Court of Chancery determined SourceHOV's fair value at the time of the merger at $4,591 per share. The valuation dispute involved multiple inputs, including the treatment of beta and capital structure assumptions. The court's opinion shows how the competing cost-of-capital approaches produced materially different results and why the court examined the underlying methodology rather than accepting a model simply because it contained familiar valuation formulas. citeturn0search7turn0search13

That is the broader lesson: in a contested valuation, the question is not whether a beta looks reasonable in isolation. The question is whether the evidence and methodology support it.

When Beta Can Become Especially Important

Beta deserves closer attention when:

• The company is private and has no observable market beta.

• The business has changed significantly over the historical period.

• The company operates across multiple business lines.

• Comparable companies have very different leverage.

• The selected peer group is small or heterogeneous.

• The valuation is being used in a transaction, dispute, financial reporting exercise or other setting where assumptions may be challenged.

• The valuation is highly sensitive to the discount rate.

Beta Is Not the Same as Total Business Risk

Beta should also not be treated as a complete measure of all risk in a business.

It captures a particular dimension of systematic equity risk used within the chosen cost-of-capital framework. Company-specific risks may require separate consideration depending on the valuation methodology and circumstances.

This distinction matters because simply increasing beta to compensate for every perceived risk can double-count risk or make the model internally inconsistent.

A disciplined valuation identifies where a risk belongs in the model and avoids adjusting multiple inputs for the same underlying issue.

How Clybourne Applies This

Clybourne derives beta on a bottom-up basis from a set of comparable listed companies, unlevering and then relevering the result to the subject company's capital structure.

The objective is to reflect market-based business risk rather than relying on a generic database beta that may not represent the company's current business mix or financing profile.

The process also creates an audit trail: the peer set, assumptions, leverage adjustment and resulting beta can each be examined rather than treating beta as an unexplained input.

That matters because a defensible valuation is not simply about producing a number. It is about being able to explain how the number was built.

The Bottom Line

Beta may look like one small decimal in a valuation model. It isn't a small decision.

For private companies, beta has to be constructed through a chain of judgments: which businesses are comparable, how their betas are measured, how leverage is removed, how the risk is weighted and how the result is adjusted for the subject company's capital structure.

Two analysts can therefore reach different beta estimates without either simply making up a number. What matters is whether the methodology is appropriate, transparent and supported by evidence.

The better question is not:

**“What beta should we use?”**

It is:

**“What beta does the evidence support—and can we defend how we got there?”**