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What return do share prices imply?

Claryss measures the unlevered return of an equity universeA group of listed companies: a specified market, a market segment, or a mirror of an equity fund. Figures are computed on the companies Claryss covers., above the risk-free rate:

The Market-Implied
Excess Return

Inferred bottom-up from share prices, consensus estimates, reported financial statements and risk-free rates. Measured using standard valuation techniques in a new combination, an Excess Return (ER) has these properties:

  • Comparable over time, despite changing risk-free rates
  • Comparable across different capital structures
  • Can be read across asset classes
  • Point-in-time; no regressions
  • No assumed asset beta
  • No assumed equity risk premium

Addressing investors’ questions

Tactical Asset Allocation, portfolio beta positioning, fund comparison, and the discovery of a company’s cost of equity all ask what return share prices imply. For example:

What reward is there for holding US equities? How to build up a coherent cost of equity based on unlevered market-implied valuation factors? How do US triple B corporate bonds compare to US equities, on a single axis? What premium, if any, do Asia-Pacific small caps carry over large caps, today and historically? How did the valuation of Japanese stocks develop over time, and against US equities, across changing risk-free rates, and corrected for differences in leverage?

Like the promised yield-spread on a bond

The promised yield-spread on a corporate bond is the compensation for all the risks associated with investing in the bond, in excess of a risk-free rate. Claryss ports this concept to the valuation of equity universes.

ER differs in that dividends are not promised, but projected, and ER removes one risk, that of financial leverage, making it comparable across capital structures.

Putting that leverage back gives the Levered Excess Return, ERL.

Like corporate bond spreads, ER and ERL are incomplete valuation metrics: neither shows whether its excess return is adequate compensation for the risks it covers.

Claryss measures; you judge.

A live sample of Claryss output

Claryss offers account holders a free sample of subscriber output. The equity universe selected is a fund mirrorFund mirror
An equity universe whose members are taken from the holdings a fund reports in its regulatory filings. Claryss uses the equity composition only, never the fund’s returns, costs or currency hedges, and includes only holdings inside Claryss coverage, so a mirror holds fewer companies than the fund it is named after. The composition is the one last filed and is held fixed across the history shown. of the iShares Core S&P 500 ETF. The ER and the ERL are presented alongside the Price/Earningst+2Price/Earningst+2 (P/Et+2)
The share price divided by the consensus earnings per share estimate for the second fiscal year ahead. ratio and are produced by the same method as the subscriber valuation reports.

Accounts available only to professional clients in eligible jurisdictions. Claryss is not affiliated with, sponsored by, or endorsed by BlackRock or iShares.

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What ER and ERL represent

Take a company’s share price. Combine it with reported financial statements and consensus analyst estimates. There is exactly one return that makes that price consistent with these point-in-time inputs. Claryss solves for it, taking only the part above the risk-free rate, and removes the effect of the company’s financial leverage. That is the Company-specific Excess Return, ERc.

The Excess Return of an equity universe, ER, summarises the ERc of its constituents into one robust figure. It is inferred from what the market is pricing; it is not a Claryss forecast. A single rules-based cash flow projection engine extends consensus estimates into dividend projections, applied systematically to every company on any date; no company-specific judgment enters at any step.

Re-levering each constituent's ERc on its own leverage and aggregating the results gives the Levered Excess Return, or ERL. The ERL of a broad listed-equity universe can be read as an approximation of the Capital Asset Pricing Model's Equity Risk Premium, under assumptions and limitations explained in an article on Claryss Platform.

Why not simply use a multiple

Price/Earnings (P/E) ratios are quick, observable and familiar. ER keeps that observability. It differs from a multiple in four respects.

Cash flow oriented. A multiple compresses years of expected cash flows into a single year's accounting subtotal. ER is derived from point-in-time share prices and multi-year projected cash flows, so expectations beyond that single year enter the measure directly instead of being left out.

Consistent across interest rate environments. The same P/E reads differently when the risk-free rate is 1% or 4%, and the multiple itself does not show which environment produced it. ER is measured as a spread over the prevailing risk-free rate, so a change in the rate environment does not distort comparisons over time or across markets.

Neutral to differences in leverage. Two companies with the same operations but different debt levels can trade at different P/E multiples for capital-structure reasons alone. ER removes the effect of financial leverage, so the comparison can be about the business itself.

Comparable across asset classes. A P/E cannot be set against a bond yield. ER and ERL are expressed as returns over the risk-free rate, similar to how bonds are quoted, so Excess Returns allow equity valuation to be read together with spreads of other asset classes.

These corrections are material rather than cosmetic. Multiples nonetheless remain the common reference point, which is why Claryss Platform presents ER and ERL together with P/Et+2.

Is there a premium for size

Textbooks treat the size premium as a levered constant to add in a cost of equity build-up. Such premia are based on historical, levered equity returns.

Claryss differs from that approach in two respects: unlevered instead of levered, and point-in-time instead of historical.

Claryss infers an unlevered premium for size that can be re-levered to the subject company's actual capital structure in its cost of equity build-up, instead of an added constant.

The size premium itself is available as a point-in-time measurement to take, both unlevered and levered: split an equity universe into buckets by unlevered enterprise value, compute each bucket's ER and ERL, and that universe's own pricing of that size bucket at that date can be read.

Because equity market capitalisation is itself a function of debt, grouping on it would carry leverage back into the comparison; unlevered enterprise value does not. The spread this yields is therefore not an unlevered restatement of the documented size premium: it is formed on a different grouping variable.

The factor size serves as an example; it can be applied to other factors as well, like sector and country. Claryss does not assume the existence of any factor premium; it shows when a spread is present and when it is not. Whether a premium is present for size right now is a question our platform answers to subscribers for several equity universes; the live series are shown there.

For cost-of-equity assignments the ER outcomes allow for a coherent approach to size adjustments: the ER can serve as an unlevered baseline, to which unlevered factor premia can be added before re-levering the result to the target company's capital structure. The coherence argument, and its contrast with the conventional build-up where a levered size premium is added as a final step, is set out in more detail in the working paper 'A Beta-Free, Market-Implied Excess Return
for Point-in-Time Equity Valuation'.

Where do equities stand against corporate bonds

Corporate bond spreads and ERL are both excess returns over the risk-free rate. That shared basis lets Tactical Asset Allocation professionals chart their development on a single, cross-asset axis: the market-implied excess return on equities and the spreads of BBB, BB and B rated corporate debt, each read against its own history.

The same basis allows a change of reference rate: subtracting a rating category's spread from ERL expresses the return on equities as an excess return over the yield of that rating category, say BBB, instead of over the risk-free yield.

Is ER just an inverted P/E

If ER were a repackaged earnings yield, one would be recoverable from the other. It is not. The two are positively related, as you would expect of two return measures built from the same prices, but the earnings yield accounts for under half the cross-sectional variation in ER. The rest comes from the parts of the valuation the multiple does not take into account.

Example output. Each point is one universe-level observation at a point in time. Excess Return against the two-year-forward earnings yield; the multiple is inverted so both are expressed as returns. R² = 0.45. Universe and axis scales undisclosed.

What can I use Excess Returns for

Tactical Asset Allocation

Compare the valuation of sectors, styles, size segments, countries, regions on a consistent basis over time; both on an unlevered and a levered basis, surviving changes in the risk-free rates. ERL can also be charted against corporate bond spreads, showing the valuation of equities and credits on a single axis.

Portfolio beta positioning

Investment mandates often allow managers to vary the portfolio’s sensitivity to the equity market, the portfolio beta. ER provides a valuation-based input for such positioning.

Fund comparison, beyond past performance

Complement past performance of fund-based equity universes (fund mirrors) with the ER and ERL implied by today's prices.

Analyse the valuation of preselected sub-segments within a fund mirror, such as sector or size.

Compare fund mirrors, today and through the served history.

Note: Coverage excludes the Financial sector and REITs, so a mirror may well deviate from its fund.

A beta-free cost of equity build-up

Derive a point-in-time, unlevered market-implied cost of equity from an equity universe filled with peers of the subject company at the valuation date, with no beta estimated at any step. Use ER to estimate unlevered valuation factors that apply to the subject company, such as for size, sector or country. Constituent concentration limits do apply.

What subscribers receive

Equity universes on Claryss Platform come in preselected sets, arranged into four subscription packages:
- North America
- Developed Europe
- Developed Asia-Pacific, and
- Developed Global

North America

The packages differ in scope, not in method: every constituent is measured the same way at every date. Each universe shows ER and ERL alongside P/Et+2 in a downloadable report. Some reports include comparisons between equity universes.

Platform coverage is confined to developed markets and the valuation metrics are aggregated from over 6,000 listed entities. The details of the subscription packages are available on platform.claryss.com, together with Explainer articles that set out how the figures are derived.

The dark side of consistency

Consistency and scale are what Claryss' method buys. The price is a reduced degree of company-specific adaptability.

  • Adjustments are bounded by data. Company-level adjustments are limited to what standardised data can support. Insights gained from management engagement or in-depth company analysis are not reflected.
  • Coverage has a boundary. ER can be inferred only where consensus EBITDA estimates exist, and there is a substantial number of listed entities for which no consensus estimates are available, or their availability varies over time. Financial-sector companies, including banks and insurers, and REITs are excluded: for financials, leverage is part of the operating model rather than a financing choice. It is challenging to envisage a single projection layer to cover both financial companies and non-financial companies at the same time.
  • Consensus has a horizon. Estimates typically extend only a few years ahead. Risks and opportunities beyond that horizon, particularly long-term or qualitative ones, may not be fully captured in the resulting Excess Returns.
  • Inputs move at different speeds. Prices adjust faster than consensus estimates, so ER can temporarily overstate or understate the market-implied return until estimates catch up, and any systematic bias in consensus estimates carries through to its level and to every aggregate built from it.
  • The leverage adjustment is a convention. Removing debt from the return uses a tax-adjusted relation that treats debt as close to risk-free. For highly levered or distressed issuers this is least defensible, and alternative conventions would shift the figure (further detailed in the working paper).

Our story

Claryss grew out of a career spent on different angles on corporate cash flows: advising on mergers and acquisitions, investing in corporate bonds, standard setting and investor engagement. Automating cash-flow projections for thousands of companies led its founder, Martijn Bos, to a realisation: the cost of equity does not have to be built up from rather judgmental regression betas and premium tables. It can be inferred, company by company and date by date, directly from the share price, the financial statements and consensus estimates, by running a dividend discount model in reverse. Today the measurement runs across developed markets and over time.

Where to go from here

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The method, its assumptions, its limitations, and how it fits into existing literature.

Working paper

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