Betas & Valuation
Betas & Valuation
Author: Joris Kersten MSc/ Owner Kersten Corporate Finance
Kersten Corporate Finance: M&A advisory + Business Valuations + Valuation Training
Source used: Morgan Stanley Investment Management, Counterpoint Global Insights: Cost of Capital – A practical guide to measuring opportunity cost. 2023. M.J. Mauboussin & D. Callahan.
Introduction
In this blog series I will talk about “the cost of capital” for valuation.
This is the 3rd article in this sequence.
The first one was about “the cost of debt” (23rd June 2023), you can find it on the link below:
And the second one was about “the equity risk premium” (26th June 2023), you can find it on the link below:
This third one is about Betas & Valuation !
Beta & popularity
CAPM (the capital asset pricing model) is very popular among practitioners.
But the concept of “Beta” has been challenged on both empirical & intellectual grounds.
The empirical problem is that beta does not predict expected returns the way it should.
Specifically, stocks with low betas generate higher returns than the model predicts.
And stocks with high betas deliver lower returns than the model predicts.
And the intellectual issue is that “volatility” is a poor way to measure risk.
Value investors generally define risk as potential permanent loss of capital.
And they argue that the volatility of asset prices does a poor job on capturing that risk.
The measure Beta
Beta measures the return of an individual security relative to the return on the market index.
It reflects the “financial elasticity”.
You calculate a historical beta by doing a regression analysis with the market’s total returns as the independent variable (X-axis).
And the asset’s total returns as the dependent variable (Y-axis).
And now the slope of the best fit line is the beta.
The slope of the regression line is the rise (up or down) over the run (left to right).
And the beta is 1.0 for a security that goes up and down the same as the market.
The beta is 2.0 for a security that goes up and down at a percentage twice that of the market.
So this security is considered riskier than the market.
And the beta is 0.5 if the security goes up and down at a rate that is one half of the market’s percentage.
So this security then is less risky than the market.
Measuring Beta
Similar to the ERP (equity risk premium), beta should be a measure that looks forward.
But this is unobservable.
Therefor we have to examine historical relationships and make some adjustments to remove some “noise”.
In order to calculate beta a few judgements have to be made, like:
1.??????Which index to compare to;
2.??????How far back in history to go;
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3.??????Measurement history (e.g. daily, weekly, monthly, quarterly or at a yearly basis).
The S&P 500 is a sensible index for investors in the United States.
And the benefit of going back further in time is that there is more data, and the regression result is more reliable.
The drawback is that the company may over time has changed its:
·??????Business model;
·??????Business mix,
·??????Level of financial leverage;
·??????Or the company simply may have matured.
A longer time period to measure beta is better for companies with stable business models and stable capital structures.
And you can consider a shorter time period if you notice that the beta changes materially during the period you measure.
At last, more frequent measures create more data.
But a good place to start with measuring beta is by monthly returns over 60 months (5 years).
Industry beta
You can improve beta by using an industry beta rather than the beta of an individual company.
The rationale is that “business risk” (the variability of the cash flows), is the same for all companies within an industry.
For an industry beta you need to take three steps:
1.??????Unlever the industry company betas;
2.??????Calculate the average unlevered beta for the industry;
3.??????Relever the beta for the specific company.
A company’s beta combines business risk + financial risk.
We want to measure business risk first, so we need to remove the effect from “financial leverage” from the industry betas.
The formula is:
Beta unlevered = Beta levered / ( 1 + D / E * ( 1 -/- Tc ) )
Then calculate the average unlevered beta for the industry.
And the trick is here to define “the industry”.
Ideally, it is a group of companies:
1.??????With similar business risk because they are exposed to the same markets;
2.??????That create comparable products;
3.??????That deal with similar customers.
And the average can be weighted by market capitalisation.
And taking the “median” helps to check for outliers that might distort the average.
Unlevering betas isolates the “business risk”, but we still need to set back the “financial risk”.
This is done by using the target company’s "expected long term capital structure".
And the formula to relever beta is:
Beta levered = Beta unlevered * ( 1 + D / E * ( 1 -/- Tc ) )
And this levered beta can then be used for your specific target company.
At last, the motivation to calculate an industry beta is to come up with a (more) accurate and (more) stable estimate of a company’s risk.
This was it for this week, see you next week again !!
Best regards, Joris Kersten
Source used: Morgan Stanley Investment Management, Counterpoint Global Insights: Cost of Capital – A practical guide to measuring opportunity cost. 2023. M.J. Mauboussin & D. Callahan.