Friday, January 12, 2018

January 2018 Data Update 3: Taxing Questions on Value

If you have read my prior posts on taxes, you already know my views on the US tax code, especially as it relates to corporate taxes. Without mincing words, the US corporate tax code, as it existed in 2017, was an abomination, a carry over from a prior century where the US was the center of the global economy and companies would do anything demanded of them, to preserve their US incorporation. I was therefore predisposed to favoring tax reform and Congress delivered its version towards the end of 2017. While the process was messy and partisan, it represents the most significant change in corporate taxation in the United States in the my lifetime, and as with all tax reform, it is a mix of the good, the bad and the ugly, with your political priors determining which one you believe dominates. No matter what you think about the tax reform package, there is the one thing that is not debatable: it will impact equity value and affect corporate behavior in the coming year. 

The 2017 Tax Reform: Key Changes
The tax reform package that passed Congress is more than a 1000 pages long and it is easy to get lost in the details. While it makes changes in individual, private business and corporate tax law, I will focus this post on the corporate tax law changes. In my view, there are four big changes embedded in this packet that deserve attention:
  1. Corporate Tax Rate: The federal corporate tax rate on the income that corporations generate ion the United States has been lowered from 35%, at the federal level, to 21%. This is the portion of the bill that attracted the most media attention, primarily because of the magnitude of the drop, bringing corporate taxes in the United States down to levels not seen in the country since the second world war.
  2. Treatment of Foreign Income: The other big change in corporate taxation that attracted less attention but my be just as consequential in the long term is that the US has now joined the rest of the world, replacing its global tax with a regional tax model. Put simply, until 2017, US companies were required to pay the US tax rate on all of their global income, though the differential tax on foreign income does not have to be paid, until repatriated to the US.  Starting in 2018, US companies will have to pay only the foreign taxes due on foreign income and will be free to bring the money back, when they want. There are two ancillary changes that the package makes to foreign income. First, it tries to clean up for past sins by imposing a one-time tax to un-trap cash that companies are holding in foreign locales. As I noted in this earlier post, the trapped cash is a predictable side effect of the global tax model, and not surprisingly, companies with global revenues have built up more than $2 trillion in foreign cash cash balances. The one-time tax rate will be 15.5% on cash invested in liquid assets and 8% on harder-to-sell assets. Second, the tax code also tries to put in disincentives for companies moving intangible assets to tax havens, by imposing a minimum tax rate of 13.1% (rising to 16.4% in 2025)  on excess profits (over and above a 10% cost of capital) earned in foreign subsidiaries. This seems to be specifically directed at technology and pharmaceutical companies that have found ways to create foreign subsidiaries for intangible assets.
  3. Limitation on Interest Deductibility: For the first time, the US tax code will put a limit on the deductibility of interest expenses, restricting it to 30% of the "adjusted taxable income" (with taxable income defined as EBITDA through 2022 and EBIT thereafter). To provide a cushion for companies that may have cyclical income, the lost (non-tax deductible) interest expense deductions can be carried forward and used in future years, with no expiration date.
  4. Capital Expensing: US companies will be allowed to deduct their investments in tangible assets in the year of the investment, for taxable income calculations, rather than have to depreciate it over time. This provision will remain intact until 2023 and be phased out by 2027.
The two best features of the tax reform package, in my view, are the changes in the taxation of foreign income and in the treatment of debt, and I will trace out the consequences for value in the next section. There are three features of the tax reform that I do not like. First, the package does little to reduce the complexity in the code, and in some cases, adds to that complexity. In particular, I don't like either the capital expensing rule change or the way in which it deals with intangible assets overseas. Second, I don't believe that tax codes are good instruments to do economic engineering and I don't think that the provisions that are in the changed code to encourage companies, especially in old-economy sectors, to reinvest more will make a significant difference. Third, by increasing the divergence in tax rates between individual income, pass-through business income and corporate income (the highest marginal federal tax rates will be 37%, 29.6% and 21% respectively), it is going to encourage tax gaming on the part of those who have a choice.

The Value Change
As I read the many assessments of how the tax reform bill will affect stock prices and values, I am reminded of the old parable of the seven blind men and the elephant, where each one after feeling a different part of the elephant's body gives a very different description of the animal. Analysts seem to be picking either one aspect of the tax code (lower tax rates, debt interest restrictions, foreign income taxation) or one dimension of value (cash flows, risk or growth) to arrive at a conclusion that reflects their political biases. Thus, I have seen supporters of the bill zero in on the drop in the tax rate from 35% to 21%, assume that this will increase after-tax income proportionately and extrapolate to a value increase of more than 20%. At the other end of the bias spectrum, there are pessimists who argue that the loss of the tax benefits from debt, from both lower tax rates and interest deductibility restrictions, will push up the after-tax cost of debt and capital for firms, and lower value. Both analyses are incomplete because they are focused on pieces of the valuation puzzle, rather than the entire valuation. The tax code, after all, affects every dimension of value, as can be seen in the picture below:
To assess the impact of tax reform on overall equity value, we have to move through each dimension of value. In making these assessments, I will focus on non-financial service firms, partly because the tax effects on debt and value are cleaner and more transparent.
  1. The Cash Flow Effect: The cash flows that a firm generates on operations are after taxes, but the relevant tax rate is not the statutory tax rate but the effective rate. It is true that the reduction of the statutory tax rate from 35% to 21%, will reduce taxes paid, but the reduction will be from the aggregated effective tax rate that companies paid in 2017, not the marginal rate. Based upon my estimates, in 2017, US non-financial service companies reported $330.8 billion in taxes on taxable income of $1,342.1 billion, translating into an effective tax rate of 25.19%. Since this tax rate includes state and local taxes and taxes on global income, these companies were paying an effective federal tax rate of closer to 23% on all of their taxable income in 2017. With the drop in the US corporate tax rate and the shift to a regional tax model, we would expect this tax rate to drop, but the magnitude of the decline is likely to be far smaller than optimists are assuming. My guess is that the effective tax rate next year will be about 20%, including state and local taxes, after the tax rate changes, resulting in an increase in after-tax operating earnings of approximately 6.67% [(1-.20)/(1-.2519)] in the next year. 
  2. The Cost of Capital Effect: The cost of capital is a weighted average of the cost of equity and the after-tax cost of debt. In computing the after-tax cost of debt, the tax rate that matters is the marginal tax rate on US income, since even companies that have low effective tax rates, like Apple, have found it in their best interests to borrow money in the US and set off interest expenses against their highest-taxed income. The marginal tax rate for a US company in 2017 was close to 38%, with state and local taxes added to the US federal tax rate of 35%. Moving that tax rate down to 24% (my estimate of the marginal corporate tax rate, with state and local taxes, in 2018) will increase the after-tax cost of debt. In 2017, US non-financial service firms collectively reported a debt to capital ratio, in market value terms, of 23.5% and faced a cost of equity of 7.85% and a pre-tax cost of debt of 3.91%. With a 38% marginal tax rate, that would have resulted in an after-tax cost of debt of 2.42% and a cost of capital of 6.57%. Keeping the pre-tax cost of debt and debt ratio fixed, and reducing the marginal tax rate to 24% will increase the cost of capital to 6.70%. 
  3. The Growth Effect: The growth effect is the trickiest one to assess, since the value of growth is a function of both how much companies reinvest but also how well they reinvest, measured as the return they earn on investments over and above their cost of capital. We do know that the incentive to reinvest has increased, especially at companies with physical and depreciable assets, because of the capital expensing provision and we also know that excess returns will change, as after-tax earnings and the cost of capital go up. In 2017, non-financial service companies in the US collectively reinvested 59.27% of their after-tax operating income back into their businesses and earned a return of 12.76% on their capital employed; the sustainable growth rate, if those numbers are maintained, is 7.56%. Increasing the return on capital to reflect the growth in after-tax earnings yields 13.65%, and assuming that reinvestment increases marginally to 65% of the after-tax earnings, because of the capital expensing rule change, yields an expected growth rate of 8.87%.
With these inputs in place, we can value US companies collectively, pre and post tax reform,  and the effect on firm value is captured in the table below:
Download spreadsheet
In making my estimates, I have assumed that the revenues and Note that this is the estimated increase in firm value, but equity value will rise proportionately, if the debt ratio remains unchanged. Does this mean that stock prices will rise 9.70% over the next year? No, and here is why. This tax reform package has been floating around for almost a year now and investors have had a chance to not only read it but incorporate its effects into prices. While the final package contained some surprises, the final version of the bill preserved the key ingredients that we introduced in April 2017. The strong returns posted by US stocks last year already include some of the value effects of the tax law. Note that this does not mean that the effects of the new tax code have already worked their way into prices since we still do not know how companies or the US economy will respond to the changes. This analysis is static, insofar as it does not allow for the changes in investing, financing and dividend behavior that we will see, as a consequence of the tax change. For instance, firms may decrease how much they borrow, since the tax benefit to debt has decreased, and that will lower debt ratios and change the cost of capital further.

Value Redistribution
While much of the discussion about the tax reform has been about its impact on the overall economy and equity values, the bigger effect of the changes to the code will be redistributive, with some sectors gaining and other losing. To identify the winners and the losers across sectors, we can use the same framework that we used to assess the value change and isolate the value effect on a sector to three variables:

VariableEffect on ValueProxy
Effective tax rateCompanies that are currently paying high effective tax rates (>23%) will benefit the most from the tax reform. Companies that are paying low effective tax rates under existing law may pay higher taxes, if their tax deductions /credit have been removed or restricted.Effective Tax Rate
Reinvestment in fixed assetsCompanies that invest large amounts in tangible assets (that are capitalized under existing law) will benefit the most from the capital expensing provision. Companies that invest in R&D or intangible assets, which are already expensed, will benefit less.Capital Expenditures as % of Sales
Debt RatioCompanies that have high debt ratios will see bigger increases in costs of capital, and value decreases, as the tax benefits from debt are reduced. Companies with little or no debt will see little change in the cost of capital.Debt/ (Debt + Equity), in market value terms
Put simply, companies (sectors) that are currently paying high effective tax rates, invest large amounts in tangible (depreciable) assets and have little or no debt will benefit the most from the tax code changes. Companies  (sectors) that are currently paying low effective tax rates, invest little or nothing in tangible (depreciable) assets and have high debt will be hurt the most by the tax code changes. To identify the sectors that will benefit the most or will be hurt the most by the tax reforms, I looked at effective tax rates, capital expenditures/sales and debt ratios across all non-financial service sectors in 2017 and used the market aggregate value as the comparison to identify which side of the divide (higher or lower than the market aggregate) each sector fell. The full list is at the link at the end of this post, but the sectors that delivered the benefit trifecta (high effective tax rate, high cap ex as a percent of sales and low debt ratio) and cost trifecta are listed below:
Download full sector spreadsheet
All the caveats apply, insofar as we are using effective tax rates and capital expenditures for one year (2017) to make the comparisons. There is one sector, real investment trusts (REITs) that showed up the loser trifecta but it's special tax treatment (where its income is not taxed, but passed through) led to its removal from the lists. Again, this should not be taken as an indication that the market will look favorably on the benefited sectors and punish the hurt sectors, since market prices have had time to adjust to the expected tax code changes. In a later post on how the pricing varies across the sectors, we will revisit this question.

Conclusion
It would be hubris to argue that we know what will happen over the next year, as a result of the tax code, but we know what we should be watching out for:
  1. Taxable income and tax rates:  Facing a more benign domestic tax environment, will companies be more expansive in their measurement of taxable income?  How much of this income will they pay out in effective taxes? 
  2. Capital Expenditures in tangible asset sectors: The capital expensing provision should make investing in depreciable assets more attractive, but will that be sufficient to induce companies to reinvest more? If so, how much?
  3. The Untrapping of Cash: How much of the trapped cash will companies bring back home, paying the one-time tax penalty? Will they reinvest this cash or return it (in the form of dividends and buybacks)?
  4. The Debt Shift: Will highly levered businesses react to the reduction in tax benefits from debt by retiring debt? What effects will a system-wide delevering have on bond default spreads?
On top of these company-level concerns are questions about how the economy will react to the tax changes, how much of the benefit will be redirected to employees and what effect there will be on interest rates. It is going to be an interesting year!

YouTube Video


Data/Spreadsheet Links
Data Update Posts
  1. January 2018 Data Update 1: Numbers don't lie, or do they?
  2. January 2018 Data Update 2: The Buoyancy of US Equities!
  3. January 2018 Data Update 3: Taxing Questions on Value
  4. January 2018 Data Update 4: The Currency Question
  5. January 2018 Data Update 5: Country Risk 
  6. January 2018 Data Update 6: Cost of Capital - A Global Update
  7. January 2018 Data Update 7: Growth and Value - Investment Returns
  8. January 2018 Data Update 8: Debt and Value
  9. January 2018 Data Update 9: The Cash Harvest - Dividend Policy
  10. January 2018 Data Update 10: The Pricing Prerogative

Tuesday, January 9, 2018

January 2017 Data Update 2: The Buoyancy of US Equities

If you were an investor in US stocks, 2017 was a very good year for you. Faced with a wall of macro economic and political worries, the US equity market proved more than up to the challenge and delivered good returns, proving the experts wrong again. Looking back at the year, the word that I used to describe US equities at the start of last year, which was "resilient", best described US stocks in 2017 as well. As we enter 2018 with US stocks at historical highs, worries remain, but stocks are on a healthier footing now, than a year ago, in terms of fundamentals. At the same time, the long promised surge in T.Bond rates that the Fed watchers promised us would happen in 2017 was nowhere to be seen, which raises interesting questions about whether we should waste our time listening to either stock market prognosticators and Fed watchers. But then again, without them, how would CNBC fill all its time?

The Year that Was
The best way that I can think of mapping out the year is to look at how stocks and bonds performed on a month by month basis through the entire year. In the table below, I look at returns on the S&P 500 and on bonds, through the year:

Start of monthS&P 500Price Appreciation in MonthT.Bond RateMonthly return
1-Jan-1722392.45%
1-Feb-1722791.79%2.47%0.03%
1-Mar-1723643.73%2.40%0.82%
1-Apr-172363-0.04%2.39%0.29%
1-May-1723840.89%2.30%1.00%
1-Jun-1724121.17%2.21%0.99%
1-Jul-1724230.46%2.30%-0.61%
1-Aug-1724701.94%2.30%0.19%
1-Sep-172418-2.11%2.12%1.80%
1-Oct-1725194.18%2.33%-1.68%
1-Nov-1725752.22%2.37%-0.16%
1-Dec-1726482.83%2.42%-0.24%
1-Jan-1826740.98%2.41%0.29%
Dividend Yield2.22%-
Total Return21.65%2.80%
The return on the S&P 500 for the year was 21.65%, with price appreciation accounting for 19.43% in returns and dividend yield representing the remaining 2.22%. In fact, the S&P 500 increased in ten of twelve months, with August representing the only significant down month; stocks were barely down in April. The T.Bond rate stayed within a tight bound for much of the year, with rates dropping to 2.12% at the start of September, from 2.45% at the start of the year, before rebounding to end the year little changed at 2.41%. Given that rates changed so little over the course of the year, the return on a 10-year T.Bond, with coupon and price change included, was 2.80%. 

Putting 2017 in perspective, adding the 2017 returns for stocks, T.Bonds and T.Bills to the historical data yields the following historical annual average returns for the three asset classes:
Download historical returns spreadsheet
For devotees of mean reversion (and I am not one), this table becomes the basis for estimating equity risk premiums, with the geometric average returns pointing to an equity risk premium of 4.77% over the 10-year T.Bond rate, i.e., the difference between the geometric average return on stocks (9.65%) and the geometric average return on bonds (4.88%).

When stocks have as good a year as they did in 2017, you would normally expect the fundamentals to weaken, at least relative to prices, but stocks ended the year in a healthier state than at the start. That can be seen by comparing the earnings, dividends and cash returned in 2017, by the S&P 500 companies, relative to 2016:


20162017% Change for year10-Year Average
Earnings106.26124.9417.58%93.00
Dividends45.749.738.82%32.76
Dividends + Buybacks108.02109.891.73%82.28
Payout Ratio43.01%39.80%42.05%
Cash Return Ratio101.66%87.95%89.35%
Note that earnings almost kept track with stock prices for the year, but the change is in the cash returned, where you saw a leveling off in the buyback boom. While that would normally be a negative for stocks, the draw back in buybacks left stocks looking healthier by reducing the cash returned as a percent of earnings from an unsustainable 101.66% in 2016 to 87.95% in 2017. 

To evaluate whether the T.Bond rate is at a level that can be justified by fundamentals, I fall back on an approach that I have used before, where I compare the T.Bond rate to an intrinsic risk free rate that I compute by adding the inflation rate for the year to real growth rate in the economy (GDP real growth rate). While those numbers are still not final for 2017, using the most recent values for both allows for an update of my intrinsic interest rate chart:
Download spreadsheet with data
The intrinsic risk free rate, using the estimated numbers as of January 1, 2018, is 4.50%, 2.09% higher than the US treasury bond rate of 2.41%, suggesting that there will be upward pressure on the US treasury bond rate over the next year.

Looking Forward
While it is tempting to continue to dissect last year's numbers, it is healthier to turn our attention to the future. It is why I have increasingly moved away from using historical risk premiums, like the 4.77% premium that I computed by looking at the 1928-2017 return table, and towards implied equity risk premiums, where I back out what investors are demanding as a premium for investing in stocks by looking at how much they pay for stocks and what they expect to generate as cash flows. (Think of it as an IRR for stocks, analogous to the yield to maturity on a bond). At the start of 2018, putting this approach into play, I estimated an equity risk premium of 5.08% for the S&P 500:
Download spreadsheet
It is instructive to look at how the inputs have changed since the start of 2017, when my estimate of the implied ERP was 5.69%. The S&P 500 has risen 19.43%, while cash returned has remained stable; the drop in buybacks has been offset by an increase in dividends. Analysts have become more optimistic about future earnings growth, partly because US companies had a healthy earnings year and partly because of the expected drop in corporate tax rates.  It is true that there are judgment calls that I had to make in estimating the implied premium, including using the analyst estimates of earnings growth for the S&P 500 (7.05%), but the resulting error pales in comparison to the standard error in the historical risk premium estimate. 

While I take this implied equity risk premium as a market price for risk, and will use it in my individual company valuations in January 2018, there are some who like playing the market timing game. If you are so inclined, the question that you are asking is whether 5.08% is a high, low or reasonable number. If you believe that the current implied premium is too low (high), you also have to believe that stocks are over priced (under priced), and to help you make that judgment, I have graphed the implied equity risk premium for the S&P 500 from 1960 to 2017 in the graph below:
Historical Implied ERP spreadsheet
There is a reason why those who are intent on claiming that the market is in a bubble have a tough sell. Unlike the end of 1999, when implied equity risk premiums were at historical lows (close to 2%), the current implied ERP is well within the bounds of historic norms. It is only if you read this graph, in conjunction with the earlier one on risk free rates, that you should be concerned, since one reason that the premium is at 5.08% is because the US treasury bond rate is 2.41%. If the T.Bond rate moves towards 4.50%, and nothing else changes, the implied ERP will drop below comfort levels. 

Worried about Equities? 
There has never been a time in the last three decades where I have felt sanguine about equity markets and I am thankful for that, since that is a sure sign of denial about the risk that is always under the surface, with stocks. That said, my worries shift from year to year and in this new year, I will continue to watch how the changing tax code will play out in both earnings and cash flows, since both are likely to be significantly affected, the former, because a lower tax rate should raise after-tax earnings, and the latter, because of the release of hundreds of billions of trapped cash. My macro crystal ball is always hazy but I expect T. Bond rates to rise, but if those higher rates go with a more robust economy, the market will take it in stride. There is the very real possibility that the economy stumbles, while rates rise, in which case US equities will be hard pressed to repeat their 2017 performance next year.

YouTube Video


Data Links
  1. Historical Returns on Stocks, Bonds and Bills: 1928-2017
  2. T.Bond and Intrinsic Interest Rates: 1960-2017
  3. Implied Equity Risk Premium, S&P 500 (Jan 1, 2018)
  4. Historical Implied Equity Risk Premiums, 1960-2017
Data Update Posts
  1. January 2018 Data Update 1: Numbers don't lie, or do they?
  2. January 2018 Data Update 2: The Buoyancy of US Equities!
  3. January 2018 Data Update 3: Taxing Questions on Value
  4. January 2018 Data Update 4: The Currency Question
  5. January 2018 Data Update 5: Country Risk 
  6. January 2018 Data Update 6: Cost of Capital - A Global Update
  7. January 2018 Data Update 7: Growth and Value - Investment Returns
  8. January 2018 Data Update 8: Debt and Value
  9. January 2018 Data Update 9: The Cash Harvest - Dividend Policy
  10. January 2018 Data Update 10: The Pricing Prerogative




Friday, January 5, 2018

January 2018 Data Update 1: Numbers don't lie, or do they?

Every year, since 1992, I have spent the first week of my year, paying homage to the numbers gods. I collect raw accounting and market data from a variety of raw data providers, and I am grateful to all of them for making my life easier, and I summarize the data on many dimensions, by geography, by industry and by market capitalization. That summarized data, for the start of 2018, can be found on my website, as can the archived data from prior years

The What?
My dataset includes every publicly traded firm that has a market price available for it, in my raw dataset, and at the start of 2018, it included 43,848 firms, up from the 42,678 firms at the start of 2017. To the question of why I don't restrict myself to just the biggest, the most liquid or the most heavily followed firms, my answer is a statistical one. Any decision that I make on screening the data or sampling will create biases that will color my results, and while I will not claim to be bias-free (no one is), I would prefer to not initiate it with my sampling.

There are 135 countries that are represented in the data, though many have only a handful of firms that are incorporated there. That said, it is worth noting that while the companies are classified by country of incorporation, many have operations in multiple countries. I have classified my firms into five "big" groups: the United States, Europe (EU, UK), Emerging Markets, Japan and Australia/Canada/New Zealand. The pie chart below provides the breakdown:
Download spreadsheet
Since the emerging market grouping includes firms from Asia, Latin America, Africa and Eurasia, I also have the data for sub-groups including India, China, Small Asia (other than India, China and Japan), Latin America, Africa & MidEast and Russia/Eurasia. That is pictured in the second pie chart above.

Within each geographic group, I break the companies down into 94 industry groupings and the numbers in each grouping are summarized at this link. While some would prefer a finer breakdown, I prefer this coarser grouping because it allows for larger sample sizes, especially as I go to sub-groups. Finally, I compute a range of numbers for each grouping, reflecting my corporate finance biases, and classify them into risk, profitability, leverage and cash return measures in the table below:


Risk MeasuresCost of FundingPricing Multiples
1.     Beta1.     Cost of Equity1.     PE &PEG
2.     Standard deviation in stock price2.     Cost of Debt2.     Price to Book
3.     Standard deviation in operating income3.     Cost of Capital3.     EV/EBIT, EV/EBITDA and EV/EBITDA
4.     High-Low Price Risk Measure4.     EV/Sales and Price/Sales
ProfitabilityFinancial LeverageCash Flow Add-ons
1.     Net Profit Margin1.     D/E ratio & Debt/Capital (book & market) (with lease effect)1.     Cap Ex & Net Cap Ex
2.     Operating Margin2.     Debt/EBITDA2.     Non-cash Working Capital as % of Revenue
3.     EBITDA, EBIT and EBITDAR&D Margins3.     Interest Coverage Ratios3.     Sales/Invested Capital
ReturnsDividend PolicyRisk Premiums
1.     Return on Equity1.     Dividend Payout & Yield1.     Equity Risk Premiums (by country)
2.     Return on Capital2.     Dividends/FCFE & (Dividends + Buybacks)/ FCFE2.     US equity returns (historical)
3.     ROE - Cost of Equity
4.     ROIC - Cost of Capital
The links in the table will lead you to the html versions of the US data, but you can find the excel versions of this data and for the other groupings on my webpage. Since I report more than 150 data items, you may have to work to find what you are looking for but it (or a close variant) should be available somewhere on the site. Since there can be variations on how metrics are computed (like EV/EBITDA or even PE), I summarize my definitions at this link.

The Why?
Much as I would like to claim that my data sharing is driven by altruism and making the world a better place, the reasons are more prosaic. I do this for myself. I enjoy analyzing the data for many reasons:
  1. Perspective: As our access to data increases, partly because of increased information disclosure on the part of firms, and partly because technology has made it easier to download data, it is ironic that we are more likely to develop tunnel vision now than before we had access to this data. When valuing individual companies, I find that knowing the industry and geographic averages gives me perspective on the numbers that I use for the company. Thus, when valuing Indofoods, an Indonesian food processing company, I can look at typical profit margins for food processing companies in South East Asia, in making my estimates for inputs, and compare my valuation to the pricing of other South East Asian food companies, when I am done.
  2. Rules of Thumb: Investing is full of rules of thumb that we devised in a different time for a different market, but still are used by investors, often without question. The notion that a stock that trades at a PEG ratio less than one or at a price less than its book value is cheap is deeply engrained in value investing books, but is it true? Looking at the cross sectional distributions of PEG and Price to Book ratios across all companies should give us the answer and allow us to eliminate the rules of thumb that no longer work.
  3. Curiosity: There are questions that all of us have about companies that the numbers can help answer. Do US companies pay less in taxes than their foreign counterparts? Does growth create or destroy value at companies? The answers to these questions are in the numbers and I find that they provide an antidote to experts who try to pass off opinions as facts.
  4. Trends and Shifts: Companies change over time, albeit slowly, and these changes have consequences not just for investors, but for governments, taxpayers and workers. One reason that I do not make jarring changes in the way that I classify and report my numbers is to see how these numbers change over time.
In the next two weeks, I will try to summarize what I learn from the data about corporate investment, financing and dividend policy in a series of posts that I have tentatively listed at the end of this post, starting with an update on US equities (and risk premiums) and ending with the a look at market pricing multiples at the end of 2017. Along the way, I will grapple with the rise of crypto currencies and what they might or might not mean for valuation. The motivations for creating these datasets are selfish but I find it pointless to keep them to myself. After all, there is no secret sauce in this data that will lead me to riches, and nothing that someone else with access to the raw data could not generate themselves. If, in the process, a few people are able to use my data in their analyses, I consider them deposits in my "good karma" bank.

The Quirks
Each year that I update the data, there are four challenges that await me. The first relates to data timing, where I try to put myself in the shoes of an investor making investment choices on January 2, 2018. The second is how best to deal with missing data, par for the course since my dataset includes some very small companies in under developed markets. The third is to clean up after the accountants, who are not always consistent in their rules across sectors and geographies. The fourth and final challenge is to find and correct mistakes in the data.
  1. Timing: All of the data that I have used in my analysis was collected after the close of trading on the last trading day of 2017 (December 29 for most markets) and reflects the most updated data, as of that day. That said, it is worth noting that not all data gets updated at the same rate, with market-set numbers (risk free rate, stock prices, risk premiums) being as of close of trading at the end of the year, but accounting numbers reflecting the most recent financial reports (from October, November and December of 2017). The accounting numbers that I use to compute my financial and pricing ratios are therefore trailing 12-month numbers, if they are updated every quarter, or even 2016 numbers, if they are not updated. 
  2. Missing Data: Information disclosure requirements vary widely across markets and since my dataset spans all markets, there are some items that are available in some markets and not in others. Rather than eliminate companies with missing data, which will both decimate and bias my sample, I keep them in the sample and deal with them the best that I can.  For instance, US companies report stock based compensation as an expense item but many non-US companies do not. I report stock based compensation as a percent of total revenues in every market but they are close to reality only in the US data.
  3. Accounting inconsistencies: I have argued in prior posts that accountants are inconsistent in their treatment of capital expenditures and debt across companies, treating the biggest capital expenditures (R&D) at technology and pharmaceutical companies as operating expenses and ignoring the primary debt (leases) at retail and restaurant companies. Rather than wait for accounting rules to come to their senses, which may take decades, I have capitalized both R&D and lease commitments for all companies and that has consequences for my earnings, invested capital and debt numbers.
  4. Data mistakes: Working with a spreadsheet with 43,848 companies and 150 data items, I am sure that there are mistakes that have found their way into my summaries, notwithstanding my attempts to catch them. Some of these mistakes are mine but some reflect errors in the raw data. The datasets that are least likely to be affected by mistakes are the US and Global dataset, where I have a combination of the law of large numbers and good disclosure backing me up. Needless to say, if you do find mistakes, please draw my attention to them.
The Caveats
If you find my data useful in your investing, valuation or corporate finance analysis, you are welcome to partake of it. That said, as a number cruncher who both loves numbers and views them with caution, here are a few things to keep in mind.
  1. Numbers ≠ Facts: While the numbers, once reported, look precise, they are not facts. Thus, when you look at the debt ratios that I report for a sector, it is worth emphasizing that I have capitalized lease commitments and added them to all interest bearing debt (short and long term) to arrive at total debt, yielding a different number than what you may see on a different service. I have tried to be as transparent as I can in making my estimates but they reflect my judgment calls. 
  2. Past is not always prologue: There are some numbers where I report historical trend lines and averages. That is not because I am a die-hard believer in mean reversion,  the  driving force in many investment philosophies. I believe that knowing history is useful in investing, but trusting it to repeat itself is dangerous.
  3. Just because everyone does it does not make it right: As you look at the datasets, you will see patterns in investment, financing and dividend policy in sectors. Some sectors, such as telecommunications, are more debt funded than others, say pharmaceuticals, and other pay more dividends (utilities) than others (technology). While there are often good reasons for these differences, there are also bad ones, with inertial on top of that list. The reality is that there are established corporate finance policies in many sectors that no longer make sense, because the sectors have changed fundamentally over time.
As you browse through the numbers, you will notice that I report almost no numbers at the company level. While I do have that data, I am constrained from sharing that data, because I risk stepping on the toes and the legal rights of my raw data providers. 

Conclusion
At the end of my data week, I am both exhilarated and exhausted, exhilarated because I can now analyze the data and exhausted because even a number cruncher can get tired of working with numbers. There is information in this data but it will take more care than I have given it so far, but I have the rest of the year to spend looking for those nuggets. 

YouTube Video


Links
    1. January 2018 Data Update 1: Numbers don't lie, or do they?
    2. January 2018 Data Update 2: The Buoyancy of US Equities!
    3. January 2018 Data Update 3: A New Tax Code - Value Consequences? 
    4. January 2018 Data Update 4: The Currency Question
    5. January 2018 Data Update 5: Country Risk 
    6. January 2018 Data Update 6: Cost of Capital - A Global Update
    7. January 2018 Data Update 7: Growth and Value - Investment Returns
    8. January 2018 Data Update 8: Debt and Value
    9. January 2018 Data Update 9: The Cash Harvest - Dividend Policy
    10. January 2018 Data Update 10: The Pricing Prerogative

Friday, October 27, 2017

Bitcoin Backlash: Back to the Drawing Board?

My last post on Bitcoin got me some push back and I am glad that it did. I would rather be read, and disagreed with, than not read at all. I have been told that I know very little about crypto currencies and that I have much to learn, and I agree. The crux of the disagreements though lay in my classifying Bitcoin as a currency, not as an asset or as a commodity. Since this classification is central to how you should think about investing versus trading, and value versus price, and goes well beyond Bitcoin, I decided to dig deeper into the classification and provide even more ammunition for those who disagree with me to tell me how wrong I am.

Classifying Investment: The What and the Why
We are products of our own world views, and mine, for better or worse, are built around my interest in valuation. It is that perspective that led me to classifying investments into cash flow generating assets, commodities, currencies and collectibles. To value an investment, I need that investment to generate future cashflows (at least on an expected basis) and that was my basis for separating cash flow generating assets (which range the spectrum from a bond to a stock to a business) from the rest.

The pushback that I got did not surprised me, partly because my definition may be at odds with the definitions used by other entities. Accountants, for instance, classify items as assets that I think are pure fiction, such as goodwill. There are others who argue that any investment on which you can make money is an asset, broadening it to include just about everything from baseball cards to government bonds. In fact, crypto currencies have been at the center of many of these disagreements, with the SEC recently deciding to treat ICOs as securities (and thus assets) and the Korean central bank categorizing Bitcoin as a commodity. Since the judgment made by these entities have regulatory and tax consequences, I am sure that they will be debated, discussed and disagreed with.  

Why Bitcoin is a currency and not an asset..
One reason that people are uncomfortable drawing the line between currency, commodity and asset is that the line can sometimes shift quickly. Take the US dollar, for instance. Its primary purpose is to serve as a medium of exchange and as a store of value, and it is thus a currency. However, you can lend US dollars to a business or individual and generate interest income. That is true, but it is not the currency that is then the asset, but the loan that you make with it, or the bond that is denominated in it. Building further, if I create a bank that takes in deposits in dollars (and pays an interest rate on them) and lends out those dollars as loans, I have a business and that business is an asset. I can value the loan and the bond based upon the interest rate you earn and the default risk that you face, or the bank, based upon the interest rate spread it earns and the risk of default that it faces on its collective portfolio, but I cannot value the US dollar.

Can I construct investments denominated in Bitcoin or another crypto currency that earn me interest or a return? Of course, but I can do that in any currency, and it is in fact one of the functions of a currency. That does not make Bitcoin an asset! You can already see that the question of whether Initial Coin Offerings (ICO) are currencies or assets becomes trickier, because an ICO can be constructed to give you a share of the ownership in a business (and the cash flows from that business), making it more of an asset than a currency (thus giving credence to the SEC's view that it is a security). The lack of standardization in ICO structures, though, makes it difficult to generalize, since loosely put, an ICO can be constructed to be anything from a donation (at least, according to Kathleen Breitman at Tezos) to quasi common stock (without the voting rights).

A few of you have pointed to the networking benefits that might create value for Bitcoin, but I am afraid that I don't see that as a basis for assigning value to it. A network can become an asset, but only when you can make money off the network. The value of Facebook to me, as an investor, is not that I am part of the Facebook network (I am not, since I have not posted on Facebook in almost three years) but that I get a share of the money made from selling advertising to those on the network. Unless you can trace monetary benefits to being part of the Bitcoin network, there is no value to being part of the network. (Visa and MasterCard are assets, not because they have wide networks and are accepted globally, but because every time they are used, they make 1-2% of the transaction value.) To the argument that Bitcoin miners can make money as the network expands, that value is for providing a service, not for holding Bitcoin.

Why Bitcoin is more currency than commodity
The essence of a currency is that its primary uses are as a medium of exchange or as a store of value. The key to a commodity is that it is an input into a process that has a utilitarian function. Oil and coal are clearly commodities, since they derive their value from the fact that they can be used to produce energy. It is true, as with currencies, that you can create an asset based upon a commodity. A share of an oil well is an asset not because you like or even need oil, it is because you hope to sell the oil to generate cash flows. It is also true that gold is a commodity, but as I noted in the prior post, I think it is more currency than commodity, because the quantity of gold that we have on the face of the earth vastly exceeds whatever utilitarian needs it might serve. It is shiny, durable, makes beautiful jewelry and has some industrial uses, but if that is all we valued gold for, it would be worth a lot less than it is trading for, and there would be less of it around. 

The question with Bitcoin then becomes whether it can become (or perhaps already is) like gold. Here is my test: If tomorrow, humanity collectively decided to abandon its attachment to gold as a value store, would its price go to zero? I don't think so, because it does have uses and while its price will drop, it will be priced based on those uses. Applying the same test to Bitcoin, I am left nonplussed about what value to attach to a digital currency if at the end, no one uses it in transactions, it has no aesthetic value and it produces nothing utilitarian.

A Commodity Argument for Crypto Currencies (but perhaps not for Bitcoin)
Some of you have pointed to Bitcoin's scarcity (created by the hard cap on production) and the fact that time and energy are spent on its production. Scarcity is neither a sufficient nor even a necessary condition for something to be a commodity. Sand is a scarce resource but it is not a commodity because I cannot think of a good use for it; so is bull manure, but that is a discussion for another time and day. The fact that time and energy went into the production of Bitcoin cannot be used to justify paying for it unless you can show that it is necessary for something that does create utility or value.   If, as argued by someone who commented on my last post, Bitcoin is a synthetic commodity, I can see that it is synthetic but what conceivable use does it have that makes it a commodity? Therein lies an opening for a “crypto currency as commodity” defense, though it works better for crypto currencies like Ethereum than it does for Bitcoin, and it require three building blocks: 
  1. Block Chains and Smart Contracts will create large disruptions in businesses: You have to believe that block chains and the smart contracts that emerge from them will replace conventional contracts in many businesses, and that will generate cash flows to the contract providers. Your argument can be based upon either economic (that the transactions costs willl be lower) or security (that the contracts will be more secure) rationales.
  2. Crypto Currencies are the lubricants for smart contracting: The discussion of block chains and crypto currency have become entangled into one discussion, but it is worth remembering that block chains predate crypto currencies and can work with fiat currencies. Thus, you will have to argue that crypto currencies are a necessary ingredient to make smart contracts work efficiently, and that the demand for them will then rise as smart contracting expands. 
  3. “Your” crypto currency will be one of the winners: Even if you can make the first two legs of this argument, it remains an argument for growth in digital or crypto currencies, not an argument for a specific one. To seal the deal, you will have to explain why your crypto currency of choice (Bitcoin, Ethereum etc.) will become the winner or at least one of the winners in the smart contracting currency race, perhaps because it has the “best technology” for smart contracting or has the most buy in by the institutional players in the game.
I think that the first leg of this argument will be easy to make, the second leg a little more difficult and the third leg will need the most convincing. Even if you can show, based upon today's technology, that you have the "best" smart contracting currency, how do you build barriers to entry that prevent you being pre-empted by another innovation or technology down the road? 

Conclusion
The game is still early, and there is much that we do not know about crypto currencies. I remain willing to learn both from people who know more than I do (and there are many out there) as well as events on the ground. As you listen to arguments for or against crypto currencies, my only advice is that you go back to basics about the needs that they are filling and that you ask questions about their long term staying power. I think it is also time for us to separate arguments about block chains/smart contracts from arguments about crypto currencies, since you can have one without the other, and to differentiate between crypto currencies, rather than defend them or abandon them all, as a bundle. To me, Bitcoin, Ethereum, Ripple and  ICOs are different enough from each other, not only in structure but also in terms of end game, that they need to be assessed independently.

YouTube Video


Past Blog Posts on Crypto Currencies

Tuesday, October 24, 2017

The Bitcoin Boom: Asset, Currency, Commodity or Collectible?

As I have noted with my earlier posts on crypto currencies, in general, and bitcoin, in particular, I find myself disagreeing with both its most virulent critics and its strongest proponents.  Unlike Jamie Dimon, I don't believe that bitcoin is a fraud and that people who are "stupid enough to buy it" will pay a price for that stupidity. Unlike its biggest cheerleaders, I don't believe that crypto currencies are now or ever will be an asset class or that these currencies can change fundamental truths about risk, investing and management. The reason for the divide, though, is that the two sides seem to disagree fundamentally on what bitcoin is, and at  the risk of raising hackles all the way around, I will argue that bitcoin is not an asset, but a currency, and as such, you cannot value it or invest in it. You can only price it and trade it.

Assets, Commodities, Currencies and Collectibles
Not everything can be valued, but almost everything can be priced. To understand the distinction between value and price, let me start by positing that every investment that I will look at has to fall into one of the following four groupings:
  1. Cash Generating Asset: An asset generates or is expected to generate cash flows in the future. A business that you own is definitely an asset, as is a claim on the cash flows on that business. Those claims can be either contractually set (bonds or debt), residual (equity or stock) or even contingent (options). What assets share in common is that these cash flows can be valued, and assets with high cash flows and less risk should be valued more than assets with lower cash flows and more risk. At the same time, assets can also be priced, relative to each other, by scaling the price that you pay to a common metric. With stocks, this takes the form of comparing pricing multiples (PE ratio, EV/EBITDA, Price to Book or Value/Sales) across similar companies to form pricing judgments of which stocks are cheap and which ones are expensive.
  2. Commodity: A commodity derives its value from its use as raw material to meet a fundamental need, whether it be energy, food or shelter. While that value can be estimated by looking at the demand for and supply of the commodity, there are long lag and lead times in both that make that valuation process much more difficult than for an asset. Consequently, commodities tend to be priced, often relative to their own history, with normalized oil, coal wheat or iron ore prices being computed by averaging prices across long cycles.
  3. Currency: A currency is a medium of exchange that you use to denominate cash flows and is a store of purchasing power, if you choose to not invest. Standing alone, currencies have no cash flows and  cannot be valued, but they can be priced against other currencies. In the long term, currencies that are accepted more widely as a medium of exchange and that hold their purchasing power better over time should see their prices rise, relative to currencies that don't have those characteristics. In the short term, though, other forces including governments trying to manipulate exchange rates can dominate. Using a more conventional currency example, you can see this in a graph of the US $ against seven fiat currencies, where over the long term (1995-2017), you can see the Swiss Franc and the Chinese Yuan increasing in price, relative to the $, and the Mexican Peso, Brazilian Real, Indian Rupee and British Pound, dropping in price, again relative to the $.
  4. Collectible: A collectible has no cash flows and is not a medium of exchange but it can sometimes have aesthetic value (as is the case with a master painting or a sculpture) or an emotional attachment (a baseball card or team jersey). A collectible cannot be valued since it too generates no cash flows but it can be priced, based upon how other people perceive its desirability and the scarcity of the collectible.  
Viewed through this prism, Gold is clearly not a cash flow generating asset, but is it a commodity? Since gold's value has little to do with its utilitarian functions and more to do with its longstanding function as a store of value, especially during crises or when you lose faith in paper currencies, it is more currency than commodity. Real estate is an asset, even if it takes the form of a personal home, because you would have had to pay rental expenses (a cash flow), in its absence. Private equity and hedge funds are forms of investing in assets, currencies, commodities or collectibles, and are not separate asset classes. 

Investing versus Trading
The key is that cash generating assets can be both valued and priced, commodities can be priced much more easily than valued, and currencies and collectibles can only be priced. So what? I have written before about the divide between investing and trading and it is worth revisiting that contrast. To invest in something, you need to assess its value, compare to the price, and then act on that comparison, buying if the price is less than value and selling if it is greater. Trading is a much simpler exercise, where you price something, make a judgment on whether that price will go up or down in the next time period and then make a pricing bet. While you can be successful at either, the skill sets and tool kits that you use are different for investing and trading, and what makes for a good investor is different from the ingredients needed for good trading. The table below captures the difference between trading (the pricing game) and investing (the value game).

The Pricing Game
The Value Game
Underlying philosophy
The price is the only real number that you can act on. No one knows what the value of an asset is and estimating it is of little use.
Every asset has a fair or true value. You can estimate that value, albeit with error, and price has to converge on value (eventually).
To play the game
You try to guess which direction the price will move in the next period(s) and trade ahead of the movement. To win the game, you have to be right more often than wrong about direction and to exit before the winds shift.
You try to estimate the value of an asset, and if it is under(over) value, you buy (sell) the asset. To win the game, you have to be right about value (for the most part) and the market price has to move to that value
Key drivers
Price is determined by demand & supply, which in turn are affected by mood and momentum.
Value is determined by cash flows, growth and risk.
Information effect
Incremental information (news, stories, rumors) that shifts the mood will move the price, even if it has no real consequences for long term value.
Only information that alter cash flows, growth and risk in a material way can affect value.
Tools of the game (1) Technical indicators, (2) Price Charts (3) Investor Psychology (1) Ratio analysis, (2) DCF Valuation (3) Accounting Research
Time horizon
Can be very short term (minutes) to mildly short term (weeks, months).
Long term
Key skill
Be able to gauge market mood/momentum shifts earlier than the rest of the market.
Be able to “value” assets, given uncertainty.
Key personality traits
      (1) Market amnesia (2) Quick Acting (3) Gambling Instincts
      (1) Faith in “value” (2) Faith in markets (3) Patience (4) Immunity from peer pressure
Biggest Danger(s)
Momentum shifts can occur quickly, wiping out months of profits in a few hours.
The price may not converge on value, even if your value is “right”.
Added bonus
Capacity to move prices (with lots of money and lots of followers).
Can provide the catalyst that can move price to value.
Most Delusional Player
A trader who thinks he is trading based on value.
A value investor who thinks he can reason with markets.

As I see it, you can play either the value or pricing game well, but being delusional about the game you are playing, and using the wrong tools or bringing the wrong skill set to that game, is a recipe for disaster.

What is Bitcoin?
The first step towards a serious debate on bitcoin then has to be deciding whether it is an asset, a currency, a commodity or collectible. Bitcoin is not an asset, since it does not generate cash flows standing alone for those who hold it (until you sell it).  It is not a commodity, because it is not raw material that can be used in the production of something useful. The only exception that I can think off is that if it becomes a necessary component of smart contracts, it could take on the role of a commodity; that may be ethereum's saving grace, since it has been marketed less as a currency and more as a smart contracting lubricant.  The choice then becomes whether it is a currency or a collectible, with its supporters tilting towards the former and its detractors the latter. I argued in my last post that Bitcoin is a currency, but it is not a good one yet, insofar as it has only limited acceptance as a medium of exchange and it is too volatile to be a store of value. Looking forward, there are three possible paths that I see for Bitcoin as a currency, from best case to worst case.
  1. The Global Digital Currency: In the best case scenario, Bitcoin gains wide acceptance in transactions across the world, becoming a widely used global digital currency. For this to happen, it has to become more stable (relative to other currencies), central banks and governments around the world have to accept its use (or at least not actively try to impede it) and the aura of mystery around it has to fade. If that happens, it could compete with fiat currencies and given the algorithm set limits on its creation, its high price could be justified.
  2. Gold for Millennials: In this scenario, Bitcoin becomes a haven for those who do not trust central banks, governments and fiat currencies. In short, it takes on the role that gold has, historically, for those who have lost trust in or fear centralized authority. It is interesting that the language of Bitcoin is filled with mining terminology, since it suggests that intentionally or otherwise, the creators of Bitcoin shared this vision. In fact, the hard cap on Bitcoin of 21 million is more compatible with this scenario than the first one. If this scenario unfolds, and Bitcoin shows the same staying power as gold, it will behave like gold does, rising during crises and dropping in more sanguine time periods.  
  3. The 21st Century Tulip Bulb: In this, the worst case scenario, Bitcoin is like a shooting star, attracting more money as it soars, from those who see it as a source of easy profits, but just as quickly flares out as these traders move on to something new and different (which could be a different and better designed digital currency), leaving Bitcoin holders with memories of what might have been. If this happens, Bitcoin could very well become the equivalent of Tulip Bulbs, a speculative asset that saw its prices soar in the sixteen hundreds in Holland, before collapsing in the aftermath.
I would be lying if I said that I knew which of these scenarios will unfold, but they are all still plausible scenarios. If you are trading in Bitcoin, you may very well not care, since your time horizon may be in minutes and hours, not weeks, months or years. If you have a longer term interest in Bitcoin, though, your focus should be less on the noise of day-to-day price movements and more on advancements on its use as a currency. Note also that you could be a pessimist on Bitcoin and other crypto currencies but be an optimist about the underlying technology, especially block chain, and its potential for disruption.

Reality Checks
Combining the section where I classified investments into assets, commodities, currencies and collectibles with the one where I argued that Bitcoin is a "young" currency allows me to draw the following conclusions:
  1. Bitcoin is not an asset class: To those who are carving out a portion of their portfolios for Bitcoin, be clear about why you are doing it. It is not because you want to a diversified portfolio and hold all asset classes, it is because you want to use your trading skills on Bitcoin to supercharge your portfolio returns. Lest you view this as a swipe at cryptocurrencies, I would hasten to add that fiat currencies (like the US dollar, Euro or Yen) are not asset classes either.
  2. You cannot value Bitcoin, you can only price it: This follows from the acceptance that Bitcoin is a currency, not an asset or a commodity. Any one who claims to value Bitcoin either has a very different definition of value than I do or is just making up stuff as he or she goes along.
  3. It will be judged as a currency: In the long term, the price that you attach to Bitcoin will depend on how well it will performs as a currency. If it is accepted widely as a medium of exchange and is stable enough to be a store of value, it should command a high price. If it becomes gold-like, a fringe currency that investors flee to during crises, its price will be lower. Worse, if it is a transient currency that loses all purchasing power, as it is replaced by something new and different, it will crash and burn.
  4. You don't invest in Bitcoin, you trade it: Since you cannot value Bitcoin, you don't have a critical ingredient that you need to be an investor. You can trade Bitcoin and become wealthy doing so, but it is because you are a good trader.
  5. Good trader ingredients: To be a successful trader in Bitcoin, you need to recognize that moves in its price will have little do with fundamentals, everything to do with mood and momentum and big price shifts can happen on incremental information.
Would I buy Bitcoin at $6,100? No, but not for the reasons that you think. It is not because I believe that it is over valued, since I cannot make that judgment without valuing it and as I noted before, it cannot be valued. It is because I am not and never have been a good trader and, as a consequence, my pricing judgments are suspect. If you have good trading instincts, you should play the pricing game, as long as you recognize that it is a game, where you can win millions or lose millions, based upon your calls on momentum. If you win millions, I wish you the best! If you lose millions, please don't let paranoia lead you to blame the establishment, banks and governments for why you lost. Come easy, go easy!

YouTube Video


Past Blog Posts on Crypto Currencies

Tuesday, October 17, 2017

Deconstructing Amazon Prime: Loss Leader or Value Creator?


Update (October 17, 2017): One of the things that I enjoy most about posting my valuations online is the feedback and how much I can use that feedback loop to improve my valuation. There are three changes that I have made to my Amazon valuation, though the end number that I get is not that different. First, as many Prime members outside the US have pointed out, the cost of Amazon Prime is less than $99/year in many countries, ranging from $22/year in Italy to just over $50/year in Germany to only $8/year in India. That lower annual cost will bring down the value of a member (existing and new). To allow for that, I have replaced the $99 annual fee that I had used in my valuation with $93.78, a  weighted average of the fees, allowing for the one quarter of Prime customers in the US who have monthly subscriptions (and pay more) and the 20% of customers outside the US (my estimate), who pay, on average, about $50/year.  Second, as some of you have noted, my operating margin was computed prior to just shipping costs and that I am double counting the customer service and media costs, which should also be added back. That increases my operating margin to 12.11% from 9.19% and I will assume that it improves to 13% over time. Third, and this was entirely my mistake, my value per existing member did not factor in the drop out rate and that has been fixed. 

I am an Amazon Prime member and have been one for a long time, and I am completely hooked. Not only do I (and my family) use Amazon Prime for items ranging from tissue paper to big screen televisions, but it has become my go-to for every possession that I need in my working and personal life. In fact, I know (and am completely at peace with the fact) that it has subtly affected my buying, as I substitute slightly more expensive Prime items for non-Prime equivalents, even when I shop on Amazon. It is not just the absence of shipping costs that draws me to Prime, but the reliability of delivery and the ease of return. In short, it makes shopping painless. As I tally how much we save each year because of Prime and weigh it against the $99 that we pay for it, I am convinced that we are getting far more value from it than what we pay, and that leads to an interesting follow up. If many of the 85 million other Prime members in October 2017 are getting the same bargain that we are, is this not an indication that Amazon has not just under priced Prime, but is perhaps selling it below cost? As someone who has wrestled with valuing Amazon over the last 20 years, I have learned never to under estimate the company. In this post, I would like to take the process I used to value a user at Uber and apply it to value not just a Prime member to Amazon but the collective value of Amazon Prime to the company.

The Growth of Amazon Prime
Amazon introduced Prime in 2005 and the service was slow to take off. At the end of 2011, only about 4% of Amazon customers were Prime members. In the years since, though, the service has seen explosive growth:
In fact, the jump in members in the last three years is particularly impressive, given how much bigger the base has become. In 2016, the company added almost 20 million new members and is on pace to add a similar number this year. In October 2017, the company’s mammoth Prime user base meant that almost 60% of all US households had memberships, suggesting that a non-Prime member is more the exception than the rule for Amazon’s US operations. Growth has been slower outside the US, slowed both by competitive/regulatory pressures and logistical challenges.

The Economics of Amazon Prime
To understand how Amazon Prime works, let’s break down the mechanics. Any one (in the countries where Prime is offered) can become a Prime member, either on a monthly or an annual basis. In the US, in 2017, the annual fee for membership was $99, as it has been for the last few years, and the monthly fee was $10.99. With 85 million members, that translates into a total revenue for the company of over $8.5 billion; the monthly members pay more but there is a portion of the membership (including students) who get discounted memberships. The other benefit for Amazon, though, comes from the fact that Amazon Prime members spend more on Amazon than non-Prime members. While the exact numbers are known only to Amazon, the most recently leaked reports suggest that the typical Prime member spends approximately $1,300/year on Amazon products, as opposed to the $700 spent by a non-Prime member. While it seems obvious, then, that Prime membership leads to more spending ($600, if you believe these two numbers), the statisticians will raise red flags about sampling bias since the true incremental revenue is unobservable; it is the difference between what the existing Prime members are spending ($1300/year) and what those same members would have spent, if they did not have Prime memberships. That is a reasonable point, but there is clearly a Prime impact, where Prime members choose Prime items over less expensive non-Prime offerings on Amazon, just as I do.

The biggest cost, by far, to Amazon is the shipping cost that the company now bears on Prime items. In 2016, the company reported net shipping subsidy costs of $7.2 billion (in the footnotes to the 10K) and assuming that almost all of these costs were related to servicing the 60 million members that Amazon had in 2016 leads to a per-member shipping cost of close to $120/ member. The other free services that Amazon offers its Prime members also create costs, though those costs are embedded in larger company-wide items and are more difficult to separate out. 
There is one final component of cost that we would like to know, but have to guess at and that is the cost to Amazon of acquiring a new member. That promotional/marketing cost is part of the total marketing cost of $7,233 million that Amazon reported in 2016 and we will assume that this cost is $100/member; in 2016, this would have translated into a total cost of $2 billion to acquire 20 million new members, leaving the remaining $5.2 billion in marketing costs as conventional advertising/marketing cost.  Pulling all these numbers, real and imagined, into a picture, here is what we get as the economics of an Amazon Prime member.

The closing statistic that is worth emphasizing here is that once someone becomes an Amazon Prime member, they tend to stay as members with an annual renewal rate of 96%.

The Value of an Existing Prime Member
Using the numbers from the previous section as a starting point, we are on our way to valuing an existing Prime member. To get to that value, we have to make some estimates for the future that reflect how the base numbers will evolve over time:
  1. Renewal Rate: We will assume that annual renewal rates will stay high, at 96%, since the subscription model and the dependence on free shipping makes dropping the service difficult to do. 
  2. Incremental Revenue/ Member Growth: As Amazon looks for new products and services to sell its Prime members, we will assume that the company’s legendary marketing skills will work and that the incremental revenue (which we estimated to be $600 and attributed entirely to Prime membership) will grow 10% a year for the next five years. That growth rate will scale down to the inflation rate (1.50%) in year 10, but that cumulated effect will result in incremental sales of $1,275/member in 2027. 
  3. Operating Margins on revenues: To estimate the operating margin on revenues, I started with Amazon's operating margin but then added back the shipping, customer service and Prime media acquisition costs, since I treat them as separate costs. The resulting margin is 12.11%.
  4. Shipping Costs: The biggest cost to Amazon is shipping and much of what the company seems to be doing both in terms of new investments (in distribution centers, trucks and drop off locations) and acquisitions (Whole Foods) seems to be designed to keep these costs in check. We will assume that shipping costs will grow 3% a year for the next five years (well below the incremental revenue growth), before settling into growing at the inflation rate thereafter. 
  5. Customer Service Costs: The cost of Prime member customer service will increase 5% a year for the next 5 years and the inflation rate thereafter.
  6. Risk and Cost of Capital: I will assume that Amazon’s overall cost of capital applies as the right risk adjusted rate to use on all of its member valuations, since they partake in its entire product line. That cost of capital, in October 2017, given a US treasury bond rate of 2.35% was 8.00%.
With those assumptions in place, we can estimate the value of a Prime member:
With our estimates, the value per prime member is approximately $486 and the total value of 85 million prime members is $41.3 billion.  While you may view this value as built on a mountain of guesstimates, and you would be right, the analysis does provide guidance on the drivers of Prime member value. The two biggest are:
  1. Growth in incremental revenues: Getting Amazon Prime members to buy more products and services is key to their value and it should be no surprise to see stories like this one. As revenue growth climbs from 10% to 15%, for instance, the value of an existing member becomes $744 and the value of member base increases almost 65%.
  2. Keeping shipping costs contained: The key to extracting value from Prime members is checking shipping costs. To illustrate, if shipping costs grow at the same rate as incremental revenues do, the value per member collapses to $71.50. 
Viewing Prime members through this prism makes it easier to explain the Whole Foods acquisition, by Amazon, for about $14 billion. Rather than think of it as Amazon’s entrĂ©e into a low-margin, intensely competitive grocery business, it would make more sense to view it as an acquisition of a distribution system (of 460 Whole Foods stores, in prime locations) that will reduce shipping costs in the future, while also providing a new menu of products/services that can be offered to Prime members. That is bad news for a whole host of other players in the market but that is a story for another day.

The Value of a New Member
To get from the value of an existing member to that of a new member, you need to have a measure of how much Amazon is spending to acquire new members. As I noted earlier, the company is opaque on this issue, though I would hazard a guess that it is a much more onerous number outside the United States. If you work with my guess of $100/new member as the base year number, we need only one more estimate to get to the value of new members and that is the growth in the membership base. Given the success that the company has shown on this front in the last five years, we will assume a growth rate of 15% for the next five years (which will bring Prime membership to 155 million in 2022). Given that large base, we will scale growth down to 5% a year from years 6-10 and to 2.25% a year thereafter.
Download spreadsheet
Again, with our estimates, the value of new Prime Members is approximately $53.9 billion and that number, in addition to being sensitive to our estimates of growth in members, magnifies the effects of incremental revenue and shipping cost growth that affected the value of an existing member. Thus, setting shipping costs to grow at the same rate as incremental revenues makes the value of new members a negative number, suggesting that growth will become value destructive if shipping costs are not brought under control.

The Corporate Drag
While it is tempting to stop and add the value of existing members and new members to arrive at the value of Amazon Prime, you would be missing a significant cost that we will term the corporate drag. To feed its ambitions with Prime, Amazon is spending far more on media content (books, movies, TV shows) than it would otherwise have and those costs will continue to grow with Prime. Earlier, we assume that 10% of the company’s current technology/media costs are attributable to Prime, yielding a base year cost of $1,609 million. We will assume that these costs will grow with the number of Prime members, yielding the following value for future costs:
Download spreadsheet
In effect, we will lower the value of Amazon Prime by $32.8 billion to reflect these additional costs. Note that though I treat this cost as a drag, it is not wasted, since it is the additional media that is being offered as a sweetener for existing Prime members to stay on and new ones to join.

The Value of Amazon Prime
Now that we have valued Amazon Prime’s existing members, its new members and the corporate drag, it is a matter of bringing them all together into a consolidated value. In our judgment, Amazon Prime is worth $62.2 billion to Amazon:   

CategoryValue/Cost todayDetails
Value of Existing Members$41,334.69Value of 85 million members @$486/each
Value of New Members$52,792.78Value of new members added
- PV of Corporate Expenses$32,845.63 Value of additional media/tecnology costs
Value of Prime Membership$61,281.83Overall value of Amazon Prime
I know that I have made a multitude of assumptions along the way to get to this value and that you may disagree with many of them. As always, you can download my spreadsheet and make the changes that you think need to be made. If you work at Amazon or view yourself as an expert on Amazon (I am not), your numbers should be much better than mine, and I would hope that your valuation will reflect the better information. While I have made a few optimistic assumptions to get to the value of Amazon Prime, I believe that there is an additional value that I have not counted in. Amazon is building a base of loyal, intense members that it can draw on to promote whatever its next product or service is, whether it be in retailing, technology, entertainment or cloud computing. That value is what you could call a real option, though those words are used far too frequently in places where they should not be, and that real option may be Amazon’s ultimate wild card.

Conclusion
I have long described Amazon as a Field of Dreams company, one that goes for higher revenues first and then thinks about ways of converting those revenues into profits; if you build it, they will come. In coining this description, I am not being derisive but arguing that the market's willingness to be patient with the company is largely a the result of the consistency with Jeff Bezos has told the same story for the company, since 1997, and acted in accordance with it. Amazon Prime symbolizes how Amazon plays the long game, an investment that has taken a decade to bear fruit, but one that will be the foundation on which Amazon launches into new businesses. I know that there are many companies that model themselves after Amazon, but unless these "Amazon Wannabes" can match its narrative consistency and long time horizon, it will remain a one of a kind.

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Attachments
  1. Amazon Prime Valuation
  2. Amazon 10K (2016)
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