Finbox Implied Equity Risk Premium Follow-Up

In this post, I want to follow up on the method to estimate the implied equity risk premium using the Finbox API function with an updated methodology, comparison with other market indices, and briefly discussing Damodaran’s numbers.

If you haven’t read my previous posts on the topic, feel free to check them out first:

  • Implied Equity Risk Premium Estimate Using Finbox (link)
  • S&P 500 Intrinsic Valuation Using Finbox (link)

Updated Methodology: Incorporating Net Income Growth Forecast

A key input for computing the implied equity risk premium is the earnings growth forecast for the next five years. The earnings growth serves as a base to estimate the potential dividends and buybacks firms can employ to return value to the shareholder in the coming years. The next five year growth is not a number you can find in a whitepaper or datasheet; it’s called a forecast for a reason.

In my previous article I proposed using Finbox’ Net Income Forecast CAGR 5Y (ni_proj_cagr_5y) as input for the earnings growth. The net income forecast is based on a bottom up estimate of growth for each of the S&P 500 firms. In total Finbox reports 6,283 estimates (April 4, 2020).

Finbox also offers a Net Income Growth Forecast (ni_proj_growth) metric which provides a forecast for the earnings growth in the next year. Incorporating this data in the model helps fine-tune the Year 1 growth. When discounting a series of cash flows, getting the “early money” right is important.

I kept the Year 5 earnings estimate consistent as to not dismiss the 5Y CAGR forecast input. For years 2 through 4, I split the difference between year 1 and 5 equally. The resulting calculation looks as follows:

Implied equity risk premium calculation on April 4, 2020
Implied equity risk premium calculation on April 4, 2020

The difference between the old methodology and new methodology is not that big: 6.64% (old) versus 6.61% (new).

Using Alternative Indices: STOXX 50, FTSE 250, CSI 100, S&P 100, Russell 1000

A question that comes up all the time when discussing the implied equity risk premium is: Why use the S&P 500 to calculate the risk premium? Why not any other index? What makes the S&P 500 so special that we can use it as the foundation to calculate the cost of equity in finance?

Implied equity risk premium tracker using the old methodology
Implied equity risk premium tracker using the old methodology

As Damodaran puts it in the 2020 edition of his paper on the equity risk premium: “Given its long history and wide following, the S&P 500 is a logical index to use to try out the implied equity risk premium measure”. In the section titled “Extensions of Implied Equity Risk Premium” (p110), Damodaran further expands on the topic of computing the equity risk premiums.

Out of curiosity, I used the same method on a couple of other well-known market indices. Below you can find the implied equity risk premiums as calculated on April 4, 2020.

  • CSI 100 (CN): 8.78% (RMB 21T total market cap)
  • FTSE 250 (UK): 8.81% (GBP 289B total market cap)
  • S&P 100 (US): 6.73% (USD 15.32T total market cap)
  • S&P 500 (US): 6.61% (USD 22.69T total market cap)
  • STOXX 50 (EU): 8.41% (EUR 2.35T total market cap)
  • Russell 1000 (US): 6.29% (USD 25.28T total market cap)

We can note two things.

First, the difference between the US stock market indices (S&P 100, S&P 500, Russell 1000) is not that large: 6.29% to 6.73% in favor of the larger market index. This can be explained by assuming the forward-looking estimate of the equity risk premium for small cap firms is -0.32% and for the large cap firms 0.12%.

Second, the difference between the US stock market indices and other indices is quite large (>2%).

This can potentially be explained by difference in risk-taking culture as “many companies and individuals in Europe have a cultural suspicion of risk-taking, entrepreneurialism and ‘Anglo-Saxon’ capital markets. Simply put, if you’re more risk averse you will demand a higher premium for investing in a more risky asset.

A second possible explanation is selection bias. Collectively, US companies are global leaders operating in a relatively free and open market with strong access to capital. The premium investors demand for a stake in a US company operating in this business environment is simply lower than for the same stake in any other market.

A third way to look at the difference is to consider that the markets may be overpriced (if the implied premium is too low) or underpriced (if the implied premium is too high). One could argue that the US and European equity market should be of equivalent risk, and therefore conclude that the European equity is underpriced (and may present an interesting investment opportunity).

Equity Risk Premium: Damodaran Versus Finbox API

Every month Damodaran updates the Implied Equity Risk Premium on his personal website. The Implied ERP on April 1, 2020, is 6.02%. Why are his numbers lower than the implied equity risk premium as computed using the Finbox API?

Damodaran's monthly implied equity risk premium update
Damodaran’s monthly implied equity risk premium update

Before we get into the number crunching, let’s state the obvious and say that these are extraordinary times of economic uncertainty due to (1) the global coronavirus pandemic and (2) associated economics of stoppage, (3) the credit & funding market dislocations, and (4) the oil price wars.

Historically, the US equity risk premium averages around 4.5% (source: Damodaran’s Implied ERP (annual) from 1960 to Current) with peaks over 7% only occurring a handful of times in March 2009 (7.68%), April 2009 (7.01%), October 2011 (7.64%), January 2012 (7.32%), February 2012 (7.04%), and June 2012 (7.28%) (Source: Damodaran’s Implied ERP by month for previous months). The increased risk premiums were marked by market crashes: the financial crisis of 2007-08 and the European sovereign debt crisis of 2010.

Damodaran historical implied premium for US equity market between 1960 and 2019
Historical implied premium for US equity market between 1960 and 2019 (source: Damodaran)

Returning to the number crunching, a key difference between the two methods is the choice of inputs.

InputDamodaranFinbox API
Cash flowDividend + buybacksDividend + buybacks – stock issuances
GrowthTop down forecastBottom up forecast
Payout RatioSustainableSustainable
Difference in inputs to compute implied equity risk premium

In particular, the growth forecast is different. Damodaran’s analyst-acquired bottom-up estimate is 6.42% whereas the top-down estimate is 3.18%. Bottom-up estimates tend to over-estimate the growth as analysts focus in on specific firms and may not fully take into account the macro-environment. Sadly, there are no top-down estimates available through the Finbox API so the bottom-up forecast (weighted by net income) is the only option we have.

Also, the timing of the computation plays a role. Between March 12, 2020, and April 4, 2020, we tracked the implied equity risk premium using the old methodology resulting in an average of 6.75%, with minimum of 6.29% and maximum of 7.49%. Damodaran’s 6.52% falls within the range we’re seeing using Finbox.

Lastly, one of the limitations of the implied equity risk premium during a crisis is that while the index level and risk free rate are current, the earnings and cash flow numbers are stale. The trailing twelve months earnings will eventually come down as firms release their Q1 and Q2 reports. The index level has already “priced in” lower earnings whereas our model may not.

One way to work around this problem is to make the earnings growth forecast as current as possible. While Finbox updates the metric at least once a day for the most recent changes in analyst forecasts, they are still dependent on timely analyst forecasts.

Another workaround is by manual intervention and overriding the Finbox input with your own estimate of earnings growth. Matching Damodaran’s inputs (dividends + buybacks as cash flow choice, Year 1 earnings growth of -30%, 5Y CAGR of 1.47%, Adjusted expected cash payout of 87.86%) yields a lower, covid-adjusted implied equity risk premium of 5.54%.

Covid-adjusted implied equity risk premium using Finbox API

At the end of the day, it’s up to everyone to determine which method they feel most comfortable with.

DateIERPS&P 500RiskfreeMarket CapEarningsDividendsBuybacksIssuancesCash to EquityNet Cash to EquityY1 Growth FC
Sust. Payout
7/55.32% $2,848.42
5/55.37% $2,842.74
2/55.45% $2,830.71
28/45.35% $2,878.48
25/45.45% $2,836.74
24/45.55% $2,797.80
22/45.76% $2,736.56

27/36.29%$2,630.07 0.85%$23,968,209

Implied Equity Risk Premium Estimate Using Finbox

We can estimate the implied equity risk premium used for estimating the cost of equity in corporate finance and valuation using the Finbox API service.

Equity Risk Premium

Simply put, the equity risk premium is the price of risk in equity markets. It captures the premium investors demand to invest in equity over a risk-free safe haven investment such as treasury bills. It can also be understood as the expected return on equity compared to the expected return on risk-free assets. Estimating the premium plays an important role in estimating the cost of equity and cost of capital in corporate finance and valuation.

Most equity risk premium estimates are backwards looking historical risk premium estimates based on the historical performance of stocks. As Damodaran points out in his lengthy paper on equity risk premiums (Equity Risk Premiums (ERP): Determinants, Estimation and Implications – The 2019 Edition), historical risk premiums carry an inherent bias towards the user’s preference of time window, type of average, and the chosen risk-free rate. Even for the most data-rich estimates, the standard error is still significant and thus the statistical value low.

Comparison of historical equity risk premium estimates (Mr. Aswath Damodaran)
Comparison of historical equity risk premium estimates (Mr. Aswath Damodaran)

The implied equity risk premium is a forward-looking method of estimating equity risk premiums. The idea is as follows:

“If you know the price paid for an asset and have estimates of the expected cash flows on the asset, you can estimate the IRR of these cash flows. If you paid the price, this is what you have priced the asset to earn (as an expected return). If you assume that stocks are correctly priced in the aggregate and you can estimate the expected cashflows from buying stocks, you can estimate the expected rate of return on stocks by finding that discount rate that makes the present value equal to the price paid.”

Mr. Aswath Damodaran
Example of an implied equity risk premium calculation by Mr. Damodaran
Example of an implied equity risk premium calculation by Mr. Damodaran

Every month Damodaran updates the Implied ERP on his NYU Stern website. I urge you to read through the many teaching materials available on his website to get a better understanding of the mechanics of the implied equity risk premium.

Finbox Inc

Finbox Inc ( ) is a Chicago-based online toolbox for investment and financial professionals that covers over 95,000 companies worldwide through their partnership with Standard & Poor’s Market Intelligence. I found this platform late 2018 and signed up for a membership in June 2019. I personally use their powerful stock screener to identify potential investment targets and pull relevant financial data into excel spreadsheets using their Excel spreadsheet add-on. Here you can find a complete list of supported API metrics.

For the purpose of estimating the implied equity risk premium, I use Finbox’ API services primarily to pull in data of the companies included in the S&P 500.

Data Gathering

To estimate the implied equity risk premium of a mature market, we need the following data inputs:

  • Mature market index: S&P 500 (Yahoo Finance)
  • Long-term risk-free rate: 10Y US bond yield (Wikipedia)
  • Company information (Finbox API)
    • Current market capitalization (marketcap)
    • Dividends paid LTM (total_div_paid_cf)
    • Stock buybacks LTM (common_rep)
    • Stock issues LTM (common_issues)
    • Net income LTM (ni)
    • Book value of equity FY (total_equity)
S&P500 company data provided by API service
S&P500 company data provided by API service

To estimate the current premium, we want to use the most up to date information available. That’s why for most metrics we use the last twelve months data points.

Dividend and Buyback Computation

After gathering the raw data, we normalize by weighing the current S&P 500 index against the S&P 500 total market capitalization.

From raw data to index unit adjusted data points

At the moment of writing, March 22, 2020, the index units adjusted data points are:

  • Earnings: $142.92
  • Dividends: $57.44
  • Buybacks: $81.50
  • Issuances: $138.94
  • Cash to Equity: $138.95 (dividends + buybacks)
  • Net Cash to Equity: $129.52 (dividends + buybacks – issuances)

Estimating Implied Equity Risk Premium

To estimate the intrinsic value of the S&P500 index, we only need a couple of inputs:

  • Current level of the index
  • Expected earnings growth for the next 5 years (top-down analyst forecast provided by Finbox)
  • Expected earnings growth in terminal year (equal to the long-term risk-free rate)
  • Expected returns to equity for the next 5 years (net cash to equity)
  • Expected returns to equity in terminal year (sustainable payout ratio)
  • Discount rate (implied equity risk premium)

The current level of the index is a single data point anyone can find in a matter of seconds.

The expected growth in earnings is a bit more difficult as we’re trying to predict future cash flows. In Damodaran’s worksheets you’ll find several options to determine your choice of growth rate though he seems to prefer a top-down analyst forecast of the S&P 500 index level. Following this idea, I rely on Finbox’ Net Income Forecast CAGR 5Y (ni_proj_cagr_5y) as main growth input.

Net income growth forecast by finbox as foundation for expected growth
Net income growth forecast by Finbox API

The forecast data is sourced from Standard & Poor’s aggregate of forecasts by various brokers and equity research institutions. Finbox’ Data Explorer allows you to check how many analysts contribute to the forecast of a specific stock. For example, Apple’s net income forecast is based on 73 estimates. While not all companies are covered equally (or accurately for that matter), the sample size of total estimates for all S&P 500 companies should give us a solid base as growth input.

As terminal growth rate we choose the risk-free rate (US 10Y gov’t bond yield).

To estimate expected returns, I slightly diverge from Damodaran’s preferred choice and opt to include dividends, stock buybacks as well as stock issuances (Net Cash to Equity). I feel it’s a more fair representation of return to all shareholders (existing and new). To estimate the returns between year 1 and year 5, I draw upon what Damodaran calls the sustainable payout level. The sustainable payout is computed using the stable growth rate and the trailing 12-month ROE and equal to 1 – g/ ROE. The payout ratio is adjusted over the next 5 years in linear increments to this value.

Once all this is set up, we’re ready to solve for the equity risk premium using Excel’s built-in Goal Seek function.

Example of estimating the implied equity risk premium using excel goal seek function
Example of estimating the implied equity risk premium using excel goal seek function

On March 22, 2020, my estimate for the implied equity risk premium is 7.18%. For your reference, you can compare this number with the implied equity risk premium published by Damodaran on his website at any time (5.77% for March 2020).

Conclusive Thoughts and Spreadsheets

I don’t think there’s a fundamental difference between the method for estimating the implied equity risk premium outlined in this blog post and the method used by Damodaran. However, the API service provided by Finbox facilitates gathering relevant data. Also, it offers a larger sample size of analysts for the top-down S&P 500 earnings growth forecast. Lastly, with the latest updated company and analyst information we can calculate the implied equity risk premium on a daily basis.

The value of this “instant” data point remains to be seen. Does it really matter to have the absolute latest information? Is having today’s estimate more useful than relying on Damodaran’s monthly ERP update? I’m not entirely sure so I’ll leave that up to you to decide. In case you’re also a Finbox user, I will link my spreadsheets below, so you open them and play around with them yourself.

To end this blog post, I would like to express my gratitude to Mr. Aswath Damodaran for his generous attitude towards teaching and sharing information. I don’t have the opportunity to join his classes at NYU Stern, but I do have access to his study materials and classroom via the online videos and webcasts. I highly recommend you to check those out if you want to learn more about corporate finance and valuation. While you’re at it, also check out his YouTube channel and blog for more content and insights.