January 2017 Information Update 4: Province Opportunity Update

In my concluding post, I pointed to currency confusion equally i of the side effects of globalization. In this one, I volition fence that equally companies too investors globalize,  investors too analysts conduct maintain no pick but to larn how to bargain alongside the ease of the world, both inwards terms of risk too pricing. One argue that I accept a detailed facial expression at province risk too pricing numbers every yr is that my valuations too corporate finance ease so heavily on them. 

Why province risk matters
It seems to me an intuitive suggestion that a company’s value too pricing tin terminate depend upon the geography of its business. Put simply, cash flows generated inwards riskier countries should hold upwards worth less than equivalent cash flows generated inwards safer ones but in that location are ii follow upwards propositions worth emphasizing:

1. Operation, non incorporation: I believe that it is where a companionship operates that determines its risk exposure, non precisely where it is incorporated. Thus, you lot tin terminate conduct maintain U.S. of A. of America companies similar Coca Cola (through its revenues) too Exxon Mobil (from its oil reserves) alongside substantial emerging marketplace exposure too emerging marketplace companies similar Tata Consulting Services too Embraer alongside pregnant developed marketplace exposure. In fact, what nosotros human face upwards inwards valuation increasingly are global companies that through the accident of history hap to hold upwards incorporated inwards different countries.
2. Company, Country too Global Risks: Not all province risk is created equal, peculiarly equally you lot are facial expression at that risk equally a diversified investor. Some province risk tin terminate hold upwards isolated to private companies too is thus averaged out equally you lot diversify fifty-fifty across companies inwards that country. Still other province risk is country-specific too tin terminate hold upwards mitigated equally your portfolio includes companies from across the globe. There is, however, increasingly a component division of province risk that is global, where fifty-fifty a global investor remains exposed to the risk too to a greater extent than so inwards roughly countries than others. The argue that nosotros depict this distinction is that risks that tin terminate hold upwards diversified away volition touching alone the expected cash flows; that adjustment effectively takes the shape of taking into trouble organization human relationship the likelihood too cash menses consequences of the risk occurring when computing the expected cash flow. The risks that are non diversifiable volition touching both the expected cash flows too likewise the discount rates, alongside the agency of adjustment unremarkably taking the shape of higher risk premiums for equity too debt. That may audio similar double counting but it is not, since the expected cash flows are adjusted for the likelihood of bad scenarios too their consequences too the discount charge per unit of measurement adjustment is to need a premium for beingness exposed to that risk:
   
   If you lot brand the supposition that all province risk is diversifiable, you lot acquire inwards at the determination that you lot don't need to adapt discount rates for province risk, a defensible declaration when correlations across countries were real depression (as inwards the 1980s) but non whatsoever more.

Thus, dealing alongside province risk correctly becomes a fundamental ingredient of both corporate finance, where multinational companies drive to mensurate hurdle rates too returns on projects inwards different countries too inwards valuation, where investors drive to attach values or prices to the same companies inwards fiscal markets. 

Country Default Risk

Since I conduct maintain had extended posts on province risk before, I volition non repeat much of what I conduct maintain said earlier too instead focus this transportation service on precisely updating the numbers. Simply put, the virtually easily accessible measures of province risk tend to hold upwards measures of default risk:

1. Sovereign Ratings: Ratings agencies similar S&P, Moody’s too Fitch attach sovereign ratings to countries, where they mensurate the default risk inwards regime borrowing precisely equally they create for private companies. These ratings agencies oftentimes likewise furnish split ratings for local currency too unusual currency borrowings yesteryear the same government. The film below summarizes ratings yesteryear country, inwards Jan 2017, too the linked spreadsheet contains the same data.

   

   Link to alive version of map

2. Government Bond Default Spreads: When a regime issues bonds inwards a unusual currency, that are traded, the involvement charge per unit of measurement on those bonds tin terminate hold upwards compared to the risk costless charge per unit of measurement inwards a bond issued inwards the same currency to acquire inwards at measures of default risk for the government. In much of Latin America, for instance, where countries has US-dollar denominated bonds, comparison the rates on those bonds to the U.S. of A. of America T.Bond charge per unit of measurement (of equivalent maturity) provides a snapshot of default risk. The tabular array below summarizes regime bond default spreads equally of Jan 1, 2017, for Latin American countries alongside U.S. of A. of America dollar denominated bonds:
3. Sovereign CDS Spreads: This mensurate of default risk is of to a greater extent than recent vintage too is a market-determined number. It is, roughly speaking, a mensurate of how much you lot would conduct maintain to pay, on an annual basis, to insure yourself against province default too dissimilar ratings tin terminate motility chop-chop inwards reply to political or economical developments inwards a country, making them both to a greater extent than timely too to a greater extent than volatile measures of province risk. In Jan 2017, sovereign CDS spreads were available for 64 countries too you lot tin terminate encounter them inwards the film below too download them equally a spreadsheet at this link.

   

   Link to alive version of the map

Country Equity Risk

There are many who role province default spreads equally a proxy for the additional risk that you lot would need for investing inwards equity inwards that country, adding it on to a base of operations equity risk premium (ERP) that they conduct maintain estimated for a mature marketplace (usually the US).

ERP for Country Influenza A virus subtype H5N1 = ERP for U.S. of A. of America + Default Spread for Country A

The limitation of the approach is that in that location are non alone are equities affected yesteryear a broader ready of risks than purely default risk but that fifty-fifty default tin terminate conduct maintain a larger impact on equities inwards a province than its bonds, since equity investors are the residuum claimants of cash flows.

There are broader measures of province risk, taking the shape of province risk scores that contain political, economical too legal risks, that are estimated yesteryear entities, roughly world (like the World Bank) too roughly private (like PRS too the Economist). The showtime is that they tend to hold upwards unstandardized, inwards the feel that each service that measures province risk has its ain scoring mechanism, alongside World Bank scores going from depression to high equally province risk increases too PRS going from high to low. The instant is that they are subjective, alongside variations inwards the factors considered too the weights attached to each. That said, in that location is information inwards looking at how the scores vary across fourth dimension too across countries, alongside the film below capturing PRS scores yesteryear province inwards Jan 2017. The numbers are likewise available inwards the linked spreadsheet.

Link to alive map

I conduct maintain my ain idiosyncratic agency of estimating the province risk premiums that builds off the province default spreads. I role a ratio of marketplace volatility, contention that default spreads need to hold upwards scaled to reverberate the higher volatility of equities inwards a market, relative to regime bonds inwards that market. 

Since the volatility ratio tin terminate hold upwards both hard to acquire at a province bird too volatile, peculiarly if the regime bond is illiquid, I compute volatilities inwards an emerging marketplace equity index too an emerging marketplace regime bond index too role the resulting ratio equally a constant that I apply globally to acquire inwards at equity risk premiums for private countries. In Jan 2017, I started my estimates alongside a 5.69% equity risk premium for mature markets (set equal to the implied premium on Jan 1, 2017, for the S&P 500) too so used a combination of default spreads for countries too a ratio of 1.23 for relative equity marketplace volatility (from the index volatilities) to acquire inwards at equity risk premiums for private countries.

For countries that had both sovereign CDS spreads too sovereign ratings, I was able to acquire different measures of equity risk premium using either. For countries that had alone a sovereign rating, I used the default spread based on that rating to gauge equity risk premiums (see lookup tabular array here). For those countries that likewise had sovereign CDS spreads, I computed alternate measures of equity risk premiums using those spreads. Finally, for those frontier countries (mostly inwards the Middle East too Africa) that were neither rated nor had sovereign CDS spreads, I used their PRS scores to attach real stone oil measures of equity risk premiums (by looking at other rated countries alongside similar PRS scores). The film below summarizes equity risk premiums yesteryear province too the link volition arrive at you lot the same information inwards a spreadsheet.

Link to alive map

Closing

The i prediction that nosotros tin terminate likewise safely brand for adjacent yr is that precisely equally nosotros conduct maintain each yr since 2008, in that location volition hold upwards at to the lowest degree i too mayhap fifty-fifty ii major shocks to the global economical system, precipitated yesteryear politics or yesteryear economic science or both. Those shocks touching all markets globally, but to different degrees too it behooves us to non alone hold upwards aware of the impact afterward they hap but hold upwards proactive too start edifice inwards the expectation that they volition hap into our required returns too values.

YouTube Video


Datasets

1. Sovereign Ratings yesteryear Country, S&P too Moody's on Jan 1, 2017
2. Sovereign CDS spreads (ten-year) on Jan 1, 2017
3. Political Risk Services (PRS) scores yesteryear country, Jan 1, 2017
4. Equity Risk Premiums too Country Risk Premiums yesteryear province on Jan 1, 2017

Data 2017 Posts

1. Data Update 1: The Promise too Perils of Big Data
2. Data Update 2: The Resilience of U.S. of A. of America Equities
3. Data Update 3: Cracking the Currency Code - Jan 2017
4. Data Update 4: Country Risk too Pricing, Jan 2017
5. Data Update 5: Influenza A virus subtype H5N1 Taxing Year Ahead?
6. Data Update 6: The Cost of Capital inwards Jan 2017
7. Data Update 7: Profitability, Excess Returns too Corporate Governance- Jan 2017
8. Data Update 8: The Debt Trade off inwards Jan 2017
9. Data Update 9: Dividends too Buybacks inwards 2017
10. Data Update 10: The Pricing Game

January 2017 Information Update 6: A Toll Of Working Capital Alphabetic Quality Update!

I withdraw hold described the cost of uppercase every bit the Swiss Army knife of finance, a number that shows upward inward thence many dissimilar places inward corporate fiscal in addition to analysis in addition to valuation in addition to inward thence many dissimilar contexts, that it is slowly to mangle in addition to misunderstand. In this post, my objective is simple. I volition start amongst a description of the sequence that I role to instruct to a cost of uppercase for companies inward Jan 2017, but the volume of the post service volition locomote describing what the cost of uppercase looks similar at the start of 2017 for companies some the world.

The Cost of Capital: Hurdle Rate, Opportunity Cost in addition to Discount Rate
As I motility from corporate finance to valuation to investment philosophies, the 1 number that seems to present upward inward almost every aspect of analysis is the cost of capital. In corporate finance, it is the hurdle charge per unit of measurement that determines whether companies should brand novel investments, the optimizer for financing mix in addition to the divining rod for how much to provide to stockholders inward dividends in addition to buybacks. In valuation, it is the discount charge per unit of measurement inward discounted cash catamenia valuations in addition to the determinants of enterprise value multiples (of EBITDA in addition to sales).

It is perchance because it is used inward thence many dissimilar contexts past times such varied sub-groups that it remains a vastly misunderstood in addition to misused number. If yous are interested inward reading to a greater extent than close the cost of capital, yous may desire to try this newspaper that I withdraw hold on the topic (it is non technical or theoretical).

The Cost of Capital Calculation

The cost of uppercase is the weighted average of the costs of equity in addition to debt for a business. While entire books withdraw hold been written on the measuring questions, I volition hold it simple.

1. The cost of equity is the charge per unit of measurement of provide that the marginal investors, i.e., the investors who are most influential at setting your marketplace price, are demanding to invest inward equity inward your business. To instruct to that number, yous demand 3 inputs, a jeopardy costless charge per unit of measurement to instruct started, a mensurate of how risky your equity is, from the perspective of the marginal investors, in addition to a cost for taking that risk.

Cost of Equity = Risk Free Risk + Relative Risk Measure * Price of Risk

In the rarefied basis of the uppercase property pricing model, yous assume that the marginal investor is diversified, beta measures relative jeopardy in addition to the equity jeopardy premium is the cost of risk, yielding a cost of equity.

2. The cost of debt is the charge per unit of measurement at which yous tin laissez passer on notice borrow money, long term in addition to today. It is non a historic cost of borrowing, nor tin laissez passer on notice it locomote influenced past times decisions on changing debt maturity. It tin laissez passer on notice locomote computed past times adding a credit or default spread to the jeopardy costless charge per unit of measurement but it does come, inward many markets, amongst a taxation create goodness which is captured past times netting it out of your cost.

After-tax Cost of Debt = (Risk Free Rate + Default Spread) (1- Marginal Tax Rate)

The default spread tin laissez passer on notice sometimes locomote observed, if the society issues long term bonds, sometimes easily estimated, if the society has a bond rating in addition to yous trust that rating, in addition to sometimes requires to a greater extent than work, if yous withdraw hold to justice default jeopardy yourself.

3. The weights on debt in addition to equity should locomote based upon marketplace values, non volume values, in addition to tin laissez passer on notice modify over time, every bit your society changes.

Since I desire to compute the cost of uppercase for every 1 of the 42,668 firms that comprised this year’s sample, I had to brand some simplifying (and perchance fifty-fifty simplistic) assumptions, some of which were necessitated past times the size of my sample in addition to some past times information limitations. I withdraw hold summarized them inward the motion painting below.

I withdraw hold computed the costs of uppercase for all companies inward US of America dollar terms, non for parochial reasons, since converting to some other currency is small (as I noted inward my post service on peachy the currency code) but to allow for consolidation in addition to comparison.

The costs of uppercase that I compute for private companies withdraw hold 2 shortcomings, driven primarily past times information limitations. The get-go is that the beta that I role for a society comes from the line organisation that it is categorized in, rather than a weighted average of the multiple businesses that it may operate in. The minute is that I withdraw hold attached the equity jeopardy premium of the province of incorporation rather than a weighted average of the ERPs of the countries inward which a society operates; I had to create this since the revenue breakdowns past times province were either non available for many companies or inward every bit good hard a shape to locomote with. If yous desire to compute the cost of uppercase for a society using my data, I withdraw hold a spreadsheet that yous tin laissez passer on notice role that volition allow yous intermission out of these bounds, allowing yous to compute a beta across multiple businesses in addition to an equity jeopardy premium across many countries/regions.

Differences across Geographies

The get-go comparing I brand is inward the costs of uppercase across dissimilar countries in addition to regions. The motion painting below shows cost of uppercase past times province in addition to yous tin laissez passer on notice download the information inward a spreadsheet at this link.

Link to alive map

Given that these are all US-dollar based costs of capital, the differences across countries tin laissez passer on notice locomote attributed to 4 factors:

1. Country risk: Country jeopardy shows upward inward 2 places inward the cost of uppercase calculation, the equity jeopardy premium for the society (which is gear upward equal to the equity jeopardy premium of the province it is in) in addition to an additional default spread inward the cost of debt. 
2. Industry concentration: Since my mensurate of relative jeopardy comes from looking at the global beta for the sector inward which a society operates, the cost of uppercase for a province volition reverberate the breakdown of industries inward that country. Thus, the cost of uppercase for Peru, a province amongst a disproportionately large number of natural resources companies, volition reverberate the beta of mining in addition to natural resources companies.
3. Marginal taxation rate: To the extent that a higher marginal taxation charge per unit of measurement lowers the after-tax cost of debt, belongings all else constant, countries amongst higher marginal taxation rates volition withdraw hold lower after-tax costs of debt in addition to perchance lower costs of capital.
4. Debt ratio: Twinned amongst the marginal taxation rate, inward computing how much a society is beingness helped past times the taxation create goodness of debt, is the amount of debt that the society uses, amongst higher debt ratios oft translating into lower costs of capital.

Differences across Industry Groups

I side past times side plough to manufacture groupings in addition to differences inward cost of uppercase across them. In the tabular array below, I listing the 10 (non-financial service) manufacture groupings globally, amongst the highest costs of capital, in addition to the ten, amongst the lowest, at the start of 2017.

Spreadsheet amongst all industries

The ground for excluding fiscal service companies is simple. For banks, insurance companies in addition to investment banks, the alone hurdle charge per unit of measurement that has relevance is a cost of equity, since debt is to a greater extent than raw textile than a rootage of uppercase for these firms. You tin laissez passer on notice download the entire manufacture listing (with Global, European, Emerging Market in addition to Australia/Canada worksheets) at this link, but 1 time again at that topographic point are alone a few reasons for the differences:

1. Business risk: Some businesses are clearly to a greater extent than risky than others in addition to I am using my sector betas to capture the differences inward risk. 
2. Leverage differences: Companies inward some sectors borrow to a greater extent than than others, amongst mixed effects on the cost of capital. The resulting higher debt to equity ratios force upward sector betas more, leading to higher costs of equity. That, though, is to a greater extent than than partially offset past times the create goodness of raising financing at the after-tax cost of debt, a create create relative to equity.
3. Country exposure: Some manufacture groupings withdraw hold geographic concentrations in addition to to the extent that those concentrations are inward countries amongst real depression or real high risk, relative to the remainder of the world, your cost of uppercase volition locomote skewed depression or high.

Distributional Perspective

I withdraw hold long argued that analysts pass far every bit good much fourth dimension on tweaking in addition to finessing costs of uppercase inward valuation in addition to non plenty on estimating earnings in addition to cash flows, in addition to I base of operations my declaration on a real uncomplicated fact. The distribution of costs of uppercase for publicly traded companies is a tight one, amongst a large proportion of companies falling inward a real narrow range. Rather than beak inward abstractions, consider the histogram of costs of uppercase for US of America in addition to global companies at the start of 2017:

The median US of America $ cost of uppercase for a US of America society is 7.22%, 50% of all US of America companies withdraw hold costs of uppercase betwixt 5.69% in addition to 8.14%, in addition to 80% withdraw hold costs of uppercase betwixt 4.59% in addition to 8.87%. If yous expand the distribution to include all global stocks, your distribution widens but non past times every bit much every bit yous mightiness think. The median US of America $ cost of uppercase for a global society is 8.03%, one-half of all global companies withdraw hold costs of uppercase betwixt 6.88% in addition to 9.15% in addition to 90% of all companies globally withdraw hold costs of uppercase betwixt 5.63% in addition to 10.68%. In other words, yous don't withdraw hold a lot of leeway to motility your cost of uppercase for publicly traded firms. It is truthful that every bit yous convey inward other currencies into the mix, yous tin laissez passer on notice brand the differences larger, but every bit I noted in my post service on currencies, it is because of differences inward inflation. You may desire to pay withdraw heed to these distributions the side past times side fourth dimension that yous encounter an analyst using a 20% US$ cost of uppercase to value a "risky" society or a 3% US$ cost of uppercase for a "safe" company, since neither number looks defensible, given the distribution.

Cost of Capital Maxims
I intend that nosotros non alone pass every bit good much fourth dimension on estimating costs of uppercase inward valuation but nosotros also misunderstand what it is designed to measure. At the jeopardy of repeating myself, hither are 4 suggestions that I withdraw hold on the cost of capital:

1. Don't brand the cost of uppercase the receptacle of all your hopes in addition to fears: Many analysts withdraw hold to view the regulation that riskier firms should withdraw hold higher costs of uppercase (or discount rates) but thence continue to intuit what that discount charge per unit of measurement should locomote for company, given how risky they intend it is.  In the process, they oft contain risks that don't belong inward discount rates in addition to attach prices for those risks that reverberate their gut responses rather than what the marketplace is paying.
2. Focus on cash flows, non discount rates: When your valuations instruct awry, it is almost never because of the mistakes that yous made on the discount charge per unit of measurement in addition to almost ever because of errors inward your estimates of cash flows (with growth, margins in addition to reinvestment). 
3. Spend less fourth dimension on estimating discount rates: It follows thence that when yous withdraw hold a express amount of fourth dimension that yous tin laissez passer on notice pass on a valuation (and who does not?), that fourth dimension is amend spent on assessing cash flows than inward fine tuning the discount rate.
4. An approximation plant well : When I am inward a hurry to value a company, I role my distributional statistics (see graph above) to instruct started. Thus, if I am valuing an average jeopardy society inward US of America dollars, I volition start off using an 8% cost of uppercase (the global median is 8.03%) in addition to consummate my valuation amongst that number, in addition to if I nonetheless withdraw hold time, I volition come upward dorsum in addition to tweak the cost of capital. If it is real risky firm, I volition start off amongst a 10.68% cost of uppercase (the 90th percentile) in addition to gain revisit that number, if I withdraw hold the time.

All inward all, if your let on yourself obsessing close the minutiae of discount rates inward a valuation, it is perchance because yous desire to avoid the large questions that brand valuation interesting in addition to challenging at the same time.

YouTube Video

Paper on the cost of capital

1. The Cost of Capital: The Swiss Army Knife of Finance

Spreadsheets

1. Cost of Capital Calculator for private company

Datasets

1. Cost of Capital (US$), past times Country - Jan 2017
2. Cost of Capital (US$), past times Industry - Jan 2017
3. US $ Cost of Capital - Percentiles for US of America in addition to Global companies

Data 2017 Posts

1. Data Update 1: The Promise in addition to Perils of Big Data
2. Data Update 2: The Resilience of US of America Equities
3. Data Update 3: Cracking the Currency Code - Jan 2017
4. Data Update 4: Country Risk in addition to Pricing, Jan 2017
5. Data Update 5: Influenza A virus subtype H5N1 Taxing Year Ahead?
6. Data Update 6: The Cost of Capital inward Jan 2017
7. Data Update 7: Profitability, Excess Returns in addition to Corporate Governance- Jan 2017
8. Data Update 8: The Debt Trade off inward Jan 2017
9. Data Update 9: Dividends in addition to Buybacks inward 2017
10. Data Update 10: The Pricing Game

January 2017 Information Update 8: The Nighttime As Well As Low-Cal Sides Of Debt

There is no aspect of corporate finance where morality plays a bigger utilisation than  the determination of how much to borrow. That should come upwards every bit no surprise. For generations, almost every religion has inveighed against debt, amongst roughly seeking outright bans too others strongly urging followers to "neither a borrower nor a lender be", too perchance amongst proficient reason. History is filled amongst instances of human beings, caught upwards inwards the mood of the moment, borrowing coin too so finding themselves destitute inwards bad times. That said, in that location is no denying that the determination of whether to borrow money, too if so how much to borrow, has popular off a critical business office of running a business.

The merchandise off on debt

In corporate finance, the tidings of debt begins amongst an examine of the merchandise offs on using debt, instead of equity, to finance operations. I take maintain described debt every bit a double-edged sword before, too running out of analogies, I am going to force on Star Wars framing, too utter well-nigh the lite side (benefits) of debt too the nighttime side (costs) of debt. In the course of educational activity of the discussion, I wishing to separate the illusory benefits too costs of debt from the existent benefits too costs, partly because I come across them mixed upwards inwards do all the time.

In terms of the real factors that drive the merchandise off, debt creates ii benefits. The biggest comes from the contention inwards the taxation code, which allows involvement expenses to last taxation deductible too cash flows to equity to last not. The secondary produce goodness is that debt tin operate every bit a disciplinary mechanism, amongst the dependent of having to brand debt payments restraining managers from taking genuinely abysmal projects. These benefits take maintain to last offset against ii large costs, the get-go too biggest beingness the increased likelihood of distress too the 2nd beingness the potential for disagreements betwixt lenders too equity investors well-nigh the hereafter of the draw solid (and how it plays out every bit debt covenants). All of these factors demo upwards inwards the cash flows too adventure assessment of a business. There are all the same illusory factors that tin last distracting. On the produce goodness side, in that location are roughly who fighting that debt is proficient because it tin force upwards your provide on equity or quest to the fact that the cost of debt is lower than the cost of equity. Both statements are to a greater extent than oft than non right, but the flaw inwards reasoning inwards both is that they assume that every bit y'all borrow to a greater extent than money, your cost of equity volition rest unchanged, too it volition not. In fact, inwards the absence of debt too distress, the positive too negative effects volition offset each other, leading to no value change. On the cost side, debt detractors volition banknote that the involvement expenses associated amongst debt volition lower cyberspace income, ignoring the fact that the lower cyberspace income is right away beingness earned on a lower equity base. If the declaration is that debt volition increment default adventure too the cost of debt, it is worth pointing out that fifty-fifty at the higher cost, debt is soundless cheaper than equity. Finally, in that location are transient factors that come upwards from marketplace position frictions, where if your equity is mis-priced or the involvement charge per unit of measurement on your debt is laid every bit good depression or high (given your default risk), y'all (as the company) may take maintain payoff of the friction, using to a greater extent than debt if equity is nether priced too debt carries every bit good depression an involvement charge per unit of measurement too less debt if equity is over priced too debt carries every bit good high a rate. This, of course, volition ask CFOs of companies to embark on that most unsafe of expeditions, of judging marketplace position assessments of their value too risk. The motion-picture demo below brings together all of the elements:

As nosotros debate why companies borrow coin too how it affects their value, it is proficient to last clear eyed well-nigh how debt changes value. It is almost alone because of the taxation produce goodness that it is endowed with, too if y'all take maintain that taxation produce goodness away, the reasons for borrowing rapidly dissipate.

The Cross Sectional Distribution 

Before nosotros embark on an examine of debt loads across companies, let's start past times looking at 3 unlike measures of fiscal leverage:

1. Debt to Capital = Debt/ (Debt + Equity): This is a mensurate of how much of the upper-case alphabetic quality inwards a fellowship comes from debt. It tin last measured every bit accountants come across value (with volume values for debt too equity) or every bit the marketplace position sees it (with marketplace position values for debt too equity).
2. Debt to Equity = Debt/Equity: This is a unopen variant of debt to capital, amongst debt stated every bit a percent of equity, over again inwards volume value or marketplace position value terms.
3. Debt to EBITDA = Debt/EBITDA: This measures how much debt a fellowship has relative to the cash it generates from operations, before taxes too upper-case alphabetic quality expenditures.

In computing my total debt for the 42,668 companies inwards my sample, I include all involvement bearing debt (short term, every bit good every bit long term) every bit good every bit the introduce value of lease commitments (which I process every bit debt, too which accountants volition start treating every bit debt inwards 2018 or 2019).  I volition start past times looking at the distribution of debt to upper-case alphabetic quality ratios, inwards both volume too marketplace position terms, across all companies:

Influenza A virus subtype H5N1 large per centum of firms, to a greater extent than than 25% inwards the US too almost 20% globally, take maintain no debt. Regionally, on a marketplace position debt to upper-case alphabetic quality ratio, Eastern Europe(with Russia) too Latin America are the most highly levered regions of the world, but inwards terms of debt every bit a multiple of EBITDA, Canadian too Chinese companies take maintain the highest debt burden.

I follow upwards past times looking at debt to upper-case alphabetic quality ratios for companies, past times country, inwards the motion-picture demo below too the statistics for all 4 measures of leverage in this spreadsheet.

Link to alive map

Latin America too Eastern Europe rest the most indebted portion inwards the world, amongst almost every province inwards each portion having debt ratios of 30% or higher inwards marketplace position value terms too oft 50% or higher inwards volume value terms. While roughly of this tin last attributed to the driblet inwards commodity prices over the terminal few years, I intend that 1 argue is that many Latin American companies are hooked on a combination of high (and oft unsustainable) dividends too a wishing for command (manifested inwards an unwillingness to dilute equity ownership). The same factors explicate why many Middle Eastern companies, where in that location is no taxation produce goodness from debt, popular off along to borrow money.

Industry Differences

You would expression companies inwards unlike sectors to take maintain rattling unlike policies on fiscal leverage, too most of the differences take maintain to produce amongst where they autumn on the debt merchandise off. In the tabular array below, I listing the most highly levered too lightly levered non-financial service sectors inwards the United States, inwards terms of marketplace position debt to upper-case alphabetic quality ratios.

Spreadsheet amongst debt ratios, past times sector

There are few surprises on this list, every bit y'all come across technology scientific discipline sectors (software, online retail, semiconductor, semiconductor equipment too electronics) on the least-levered listing too upper-case alphabetic quality intensive sectors (power, trucking, telecom) on the most-levered list. It is interesting that integrated oil/gas companies are amidst the to the lowest degree levered sectors but oil/gas distribution is on the most levered list. If y'all wishing to come across the total listing of industries, non merely for the U.S. but also for other regions of the world, try this spreadsheet.

Closing

In my before post on taxes, I noted that 2017 is probable to last a twelvemonth of change, at to the lowest degree for the US taxation code too almost every version of taxation reform that is beingness talked well-nigh volition trim the marginal taxation charge per unit of measurement too thence the taxation benefits of debt. In fact, in that location are roughly versions where the entire taxation produce goodness of debt volition last removed. While I believe that this volition last healthier inwards the long term for businesses, it volition last a seismic shift that volition take maintain massive effects non merely on corporate borrowing but on the corporate bond market. I am non certain that nosotros (as investors too companies) are laid for that large a change. So, small-scale steps agency from the condition quo, which is skewed strongly towards borrowers, may last all that y'all tin expression to see!

YouTube Video

Spreadsheets

1. Capital Structure Optimizer
2. APV Spreadsheet

Datasets

1. Debt Ratios, past times country
2. Debt Ratios, past times industry

Data 2017 Posts

1. Data Update 1: The Promise too Perils of Big Data
2. Data Update 2: The Resilience of US Equities
3. Data Update 3: Cracking the Currency Code - Jan 2017
4. Data Update 4: Country Risk too Pricing, Jan 2017
5. Data Update 5: Influenza A virus subtype H5N1 Taxing Year Ahead?
6. Data Update 6: The Cost of Capital inwards Jan 2017
7. Data Update 7: Profitability, Excess Returns too Corporate Governance- Jan 2017
8. Data Update 8: The Debt Trade off inwards Jan 2017
9. Data Update 9: Dividends too Buybacks inwards 2017
10. Data Update 10: The Pricing Game

January 2017 Information Update 7: Profitability, Excess Returns In Addition To Governance

If asked to depict a successful business, most people volition say yous that it is 1 that makes coin together with that is non an unreasonable starting point, but it is non a practiced ending point. For a trouble concern to endure a success, it is non precisely plenty that it makes coin but that it makes plenty coin to compensate the owners for the working capital missive of the alphabet that they guide maintain invested inward it, the opportunity that they are exposed to together with the fourth dimension that they guide maintain to hold off to larn their coin back. That, inward a nutshell, is how nosotros define investment success inward corporate finance together with inward this post, I would similar to purpose that perspective to mensurate whether publicly traded companies are successful.

Measuring Investment Returns

The commencement pace towards measurement investment success is measurement the supply that companies brand on their investments. This step, though seemingly simple, is fraught alongside difficulties. First, corporate measures of profits are non only historical (as opposed to time to come expectations) but are also skewed past times accounting discretion together with exercise together with year-to-year volatility. Second, to mensurate the working capital missive of the alphabet that a fellowship has invested inward its existing investments, yous oft guide maintain laid out alongside what is shown equally working capital missive of the alphabet invested inward a residual sheet, implicitly assuming that majority value is a practiced proxy for working capital missive of the alphabet invested. Notwithstanding these concerns, analysts oft compute a supply on invested working capital missive of the alphabet (ROIC) equally a mensurate of investment supply earned past times a company:

This uncomplicated computation has croak corporate finance’s most widely computed together with used ratio together with spell I compute it together with purpose it inward a multifariousness of contexts, I do together with then alongside the recognition that it comes alongside flaws, some of which tin endure fatal. In the context of reporting this statistic at the start of concluding year, I reported my ROIC caveats inward a picture:

Put simply, it would endure unfair of me to tar a immature fellowship similar Tesla equally a failure because it has a negative supply on invested capital, together with unsafe for me to stance HP equally a fellowship that has made practiced investments, because it has a high ROIC, since is only due to the fact that it has written off almost $16 billion of mistakes, reducing its invested working capital missive of the alphabet together with inflating its ROIC. I compute the supply on invested working capital missive of the alphabet at the start of 2017 for each fellowship inward my world fellowship sample of 42,668 firms, using the next judgments inward my estimation:

I do brand adjustments to operating income together with invested working capital missive of the alphabet that reverberate my stance that accounting miscategorizes R&D together with operating leases. I am soundless using a bludgeon rather than a scalpel hither together with  the returns on invested working capital missive of the alphabet for some companies volition endure off, either because the concluding year’s operating income was abnormally high or depression and/or accountants guide maintain managed to plow the invested working capital missive of the alphabet at this fellowship into a set out that has fiddling to do alongside what is invested inward projects. That said, I guide maintain the police force of large numbers equally my ally.

Measuring Excess Returns

If the mensurate of investment success is that yous are earning to a greater extent than on your working capital missive of the alphabet invested than yous could guide maintain made elsewhere, inward an investment of equivalent risk, yous tin run across why the cost of working capital missive of the alphabet becomes the other one-half of the excess supply equation. The cost of working capital missive of the alphabet is mensurate of what investors tin generate inward the marketplace on investments of equivalent risk. Thus, a fellowship that tin consistently generate returns on its invested working capital missive of the alphabet that move past times its cost of working capital missive of the alphabet is creating value, 1 that generates returns equal to the cost of working capital missive of the alphabet is running inward house together with 1 that generates returns that are less than the cost of capital, it is destroying value. Of course, this comparing tin endure done exclusively on an equity basis, using the cost of equity equally the required charge per unit of measurement together with the supply on equity equally a mensurate of return:

In general, specially when comparing large numbers of stocks across many sectors, the working capital missive of the alphabet comparing is a to a greater extent than reliable 1 than the equity comparison. My halt results for the working capital missive of the alphabet comparing are summarized inward the pic below, where I intermission my global companies into 3 broad groups. The first, value creators, includes companies that earn a supply on invested working capital missive of the alphabet that is at to the lowest degree 2% greater than the cost of capital, the second, value zeros, includes companies that earn inside 2% (within my estimation error) of their cost of working capital missive of the alphabet inward either administration together with the third, value destroyers, that earn a supply on invested working capital missive of the alphabet that is 2% lower than the cost of working capital missive of the alphabet or worse. 

The world marketplace house globally, at to the lowest degree at the start of 2017, has to a greater extent than value destroyers than value creators, at to the lowest degree based upon 2016 trailing returns on capital. The practiced tidings is that at that spot are almost 6000 companies that are super value creators, earning returns on working capital missive of the alphabet that earn 10% higher than the cost of working capital missive of the alphabet or more. The bad tidings is that the value destroying grouping has almost 20,000 firms (about 63% of all firms) inward it together with a large subset of these companies are stuck inward their value destructive ways, non only continuing to rest invested inward bad businesses, but investing to a greater extent than capital.

If yous are wary because the returns computed used the most recent 12 months of data, yous are correct be. To counter that, I also computed a ten-year average ROIC (for those companies alongside 10 years of historical information or more) together with that set out compared to the cost of capital. As yous would await alongside the selection bias, the results are much to a greater extent than favorable, alongside almost 77% of firms earning to a greater extent than than their cost of capital, but fifty-fifty over this much longer fourth dimension period, 23% of the firms earned less than the cost of capital. Finally, if yous are doing this for an private company, yous tin purpose much to a greater extent than finesse inward your computation together with use this spreadsheet to brand your ain adjustments to the number.

Regional together with Sector Differences
If yous bring my numbers, a 3rd of all companies are destroying value, a 3rd are running inward house together with a 3rd are creating value, but are at that spot differences across countries? I respond that enquiry past times computing the excess returns, past times country, inward the pic below:

Link to alive map

Just a annotation on caution on reading the numbers. Some of the countries inward my sample, similar Republic of Mali together with Republic of Kazakhstan guide maintain really few companies listed together with the numbers should taken alongside a grain of salt. Breaking out the excess returns past times broad regional groupings, hither is what I get:

Spreadsheet alongside province data

Finally, I took a facial expression at excess returns past times sector, both globally together with for unlike regions of the world, comparing returns on working capital missive of the alphabet on an aggregated dry soil to the cost of capital. Focusing on non-financial service sectors, the sectors that delivered the most negative together with most positive excess returns (ROIC - Cost of Capital) are listed below:

Spreadsheet alongside sector data

Many of the sectors that delivered the worst returns inward 2016 were inward the natural resources sectors, together with depressed commodity prices tin endure fingered equally the culprit. Among the best performing sectors are many alongside depression working capital missive of the alphabet intensity together with service businesses, though tobacco tops the listing alongside the highest supply spread, partly because the large buybacks/dividends inward the sector guide maintain shrunk the working capital missive of the alphabet invested inward the sector.

For investors, looking at this listing of practiced together with bad businesses inward 2017, I would offering a alarm most extrapolating to investing choices. The correlation betwixt trouble concern character together with investment returns is tenuous, at best, together with hither is why. To the extent that the marketplace is pricing inward investment character into stock prices, at that spot is a really existent possibility that the companies inward the worst businesses may offering the best investment opportunities, if markets guide maintain over reacted to investment performance, together with the companies inward the best businesses may endure the ones to avoid, if the marketplace has pushed upward prices equally good much. There is, however, a corporate governance lesson worth heeding. Notwithstanding claims to the contrary, at that spot are many companies where managers left to their ain devices, volition uncovering ways to pass investor coin badly together with demand to endure held to account.

What next?

I am non surprised, equally some mightiness be, past times the numbers above. In many companies, intermission fifty-fifty is defined equally making coin together with profitable projects are considered to endure pulling their weight, fifty-fifty if those profits don’t mensurate upward to option investments. Influenza A virus subtype H5N1 large set out of companies, if set on the spot, volition non fifty-fifty able to say yous how much working capital missive of the alphabet they guide maintain invested inward existing assets, either because the investments occurred way inward the past times or because of the way they are accounted for. It is non only investors who comport the cost of these piteous investments but the economic scheme overall, since to a greater extent than working capital missive of the alphabet invested inward bad businesses agency less working capital missive of the alphabet available for novel together with peradventure much ameliorate businesses, something to squall back most the adjacent fourth dimension yous read a rant against stock buybacks or dividends.

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Spreadsheet

1. ROIC Calculator

Datasets

1. Excess Returns, past times Country- Jan 2017
2. Excess Returns, past times Industry - Jan 2017

Data 2017 Posts

1. Data Update 1: The Promise together with Perils of Big Data
2. Data Update 2: The Resilience of U.S. Equities
3. Data Update 3: Cracking the Currency Code - Jan 2017
4. Data Update 4: Country Risk together with Pricing, Jan 2017
5. Data Update 5: Influenza A virus subtype H5N1 Taxing Year Ahead?
6. Data Update 6: The Cost of Capital inward Jan 2017
7. Data Update 7: Profitability, Excess Returns together with Corporate Governance- Jan 2017
8. Data Update 8: The Debt Trade off inward Jan 2017
9. Data Update 9: Dividends together with Buybacks inward 2017
10. Data Update 10: The Pricing Game

January 2017 Information Update 1: The Hope Too Perils Of Big Data!

Each year, for the concluding 25 years, I receive got spent the showtime calendar week playing Moneyball, amongst fiscal data. I assemble accounting in addition to marketplace information on all publicly traded companies, listed globally, in addition to and thus attempt to extract whatever lessons that I tin from the data, to utilization inwards investing, corporate finance in addition to valuation for the residuum of the year. I study the data, classified yesteryear manufacture grouping in addition to yesteryear country, on my website, inwards the promise that others mightiness let out it useful. While, similar concluding year, I volition hold out summarizing what I run into inwards the information inwards a serial of posts over the residuum of January, I decided to utilization this 1 to both furnish approximately perspective in addition to cautionary notes non only on my information but on numbers, inwards general.

The Number Cruncher's Delusions
In an before transportation service on narrative in addition to numbers, I confessed that I am to a greater extent than naturally a release cruncher than a story teller in addition to that I receive got learned through experience that focusing alone on the numbers tin atomic number 82 you lot astray inwards valuation in addition to investing. In fact, as you lot read my posts on what the numbers expect similar at the start of 2017, it is as good worth noting that I am, similar all release crunchers, susceptible to iii delusions almost data:

1. Numbers are precise: I say, only one-half jokingly, that when a release cruncher is inwards doubt, his or her reaction is to add together to a greater extent than decimals, inwards the promise that making a release expect to a greater extent than precise volition expire far so. The truth is that numbers are only as precise as the procedure that delivers them in addition to inwards business, that makes them imprecise. Thus, when you lot peruse the returns on uppercase or costs of uppercase that I volition hold out estimating in addition to reporting for both companies in addition to manufacture groups, delight exercise recognize that the quondam is an accounting number, where discretionary choices on expensing in addition to depreciation tin interpret into large changes inwards returns on capital, in addition to the latter is marketplace number, making it non only a moving target (as involvement rates in addition to adventure premiums change) but as good a locomote of my estimation choices as good as estimation fault inwards estimating adventure premiums in addition to adventure parameters. 
2. Numbers are objective: One of the resentments that release crunchers receive got almost story tellers is that the latter indulge inwards flights of fancy in addition to are unashamed almost bringing their biases into their stories in addition to through them into pricing in addition to investing. The problem, though, is that numbers tin hold out simply as biased as stories, amongst the caveat that it is easier to enshroud biases amongst numbers. To laissez passer on 1 example, 1 of the datasets that I volition hold out updating has revenue enhancement rates paid yesteryear US companies inwards 2016 in addition to I furnish iii measures of effective revenue enhancement rates, ranging from a uncomplicated average of effective revenue enhancement rates across all companies inwards a sector, yielding the lowest values, to a weighted average effective revenue enhancement charge per unit of measurement that is computed only across money-making firms, which yields much higher values. If you lot are dead-set on making a instance that US companies don't pay their fair part inwards taxes, you lot volition study only the showtime release in addition to non cite the rest, whereas if you lot desire to demo that US companies pay their fair part in addition to to a greater extent than inwards taxes, you lot volition expire amongst the latter. It is for this argue that I volition non claim to hold out unbiased (since no 1 is) but I volition attempt to furnish multiple measures of widely used variables in addition to exit it to you lot to create upwards one's heed which 1 best fits your preconceptions. 
3. Numbers set you lot inwards control: It is human nature to attempt to hold out inwards command in addition to numbers serve us well, inwards that pursuit. As inwards other aspects of life, nosotros seem to mean value that attaching a release to a volatile or uncontrollable variable brings it nether control. So, at the adventure of stating the obvious, permit me tell that mensuration your render on invested uppercase is non going to plough bad projects into proficient ones, simply as estimating your involvement coverage ratio is non going to expire far easier for you lot to brand your involvement payments. 

Don't acquire me wrong! I remain, at heart, a release cruncher but I receive got a to a greater extent than complicated, in addition to healthier, human relationship amongst information than I used to have. My organized religious belief inwards information has been tempered yesteryear my experiences amongst data, in addition to peculiarly thus amongst the ease amongst which I receive got seen it bent to reverberate the agenda of the user. I trust numbers, but only afterward I verify them, in addition to I promise that you lot volition exercise the same amongst the information that you lot let out on my site.

A Big Data Skeptic

It is my experience amongst information that brand me skeptical almost ii of the hottest concepts inwards business, large information in addition to information analytics, at to the lowest degree as a footing for making money. It is truthful that companies are collecting to a greater extent than information than e'er before on almost every aspect of our lives, amongst the intent of using that information to brand to a greater extent than coin off us. In a capitalist society, I rest doubtful that large information volition hold out monetized, for iii reasons.

1. Data is non information: Not all information is created equal. Data that is based on what you lot exercise is worth a lot to a greater extent than than what you lot tell volition do; a tweet that you lot are bullish on Apple, Twitter or the entire marketplace is less useful information than a tape of you lot buying Apple, Twitter or the entire market. This is a indicate worth remembering as the rush is on to contain social media information (from Twitter in addition to Facebook) amongst fiscal information to create super information bases. In addition, as nosotros collect in addition to shop to a greater extent than data, it is worth noting that information is non information. In fact, if information analytics does its job, converting information to information volition rest its focus, rather than generating neat looking graphs in addition to obscure statistics. 
2. If everyone has it (data), no 1 has it: For information to receive got value, you lot receive got to approximately storey of exclusivity inwards access to that information or a proprietary border on processing that data. It is 1 of the reasons that investors receive got been unable, for the most part, to convert increased access to fiscal information into investing profits.
3. Not all information is actionable: , To convert that information to profits, you lot bespeak to hold out able to let out a means to monetize whatever information border you lot receive got acquired. For companies that offering products in addition to services, this volition accept the shape of modifying existing products/services or coming upwards amongst novel products/services to what you lot receive got learned from the data.

As you lot expect at these iii factors, it is slowly to run into why Netflix in addition to Amazon receive got expire illustrative examples for the benefits of large data. They acquire to detect us (as consumers) inwards action, Amazon watching what nosotros purchase in addition to Netflix observing what nosotros scout on our devices, in addition to that information is non only proprietary but tin hold out used to non only modify production offerings but to as good nudge us to human activity inwards ways that volition hold out beneficial to the companies. By the same token, you lot tin as good run into why using large information as an investing wages will, at best, furnish a transitory advantage, in addition to why I experience no qualms almost sharing my data. 

Data Details

If you lot direct to utilization whatsoever of my data, it behooves me to accept you lot through the procedure yesteryear which I collect in addition to analyze the information in addition to offering approximately cautionary notes along the way. 

1. Raw Data: The showtime pace inwards the procedure is collecting the raw information in addition to I am deeply thankful to the information services that allow me to exercise this. I utilization S&P Capital IQ, Bloomberg in addition to a host of specialized services (Moody's, PRS etc.). For company-specific data, the only criteria that I utilization for including a companionship is that it has to receive got a non-zero marketplace capitalization, yielding a total of 42678 firms on Jan 1, 2017. The information collected is as of Jan 1, 2017, amongst marketplace information (stock prices, marketplace capitalization in addition to involvement rates) existence as of that information but accounting information reflecting the most recent twelve months (which would hold out through September 30, 2016 for calendar yr companies). 
2. Classification: I kind out these companies showtime yesteryear geographic grouping into 5 groups - the United States, Japan, Developed Europe (including the European Union in addition to Switzerland), Emerging Markets (including Eastern Europe, Asia, Africa in addition to Latin America) in addition to Australia/New Zealand/Canada, a somewhat arbitrary grouping that I am stuck amongst because of history.
   
   I as good kind out firms into 96 manufacture groups, built loosely on raw service industrial grouping in addition to SIC codes. The release of firms inwards each manufacture group, broken downwards farther yesteryear geographic grouping, tin hold out constitute at this link and you lot tin let out the companies inwards each manufacture grouping at this link.
3. Key numbers: I to a greater extent than oftentimes than non don't study much macroeconomic information (interest rates, inflation, gross domestic product growth etc.), since in that location are much ameliorate sources for the data, amongst my favorite remaining FRED (the Federal Reserve information site inwards St. Louis). I update equity adventure premiums non only for the US but for much of the globe at the start of every year in addition to volition update them in 1 lawsuit again inwards July 2017. Using the companionship data, I study on dozens of metrics at the manufacture grouping in addition to geographic levels on profitability, cost of capital, relative adventure in addition to valuation ratios in addition to you lot tin let out the entire listing here.
4. Computational details: One of the lessons that I receive got learned from wrestling amongst the information is that computing fifty-fifty uncomplicated statistics requires making choices, which, inwards turn, tin hold out affected yesteryear your biases. Just to furnish an example, to compute the PE ratio for US steel companies, I tin accept a uncomplicated average of the PE ratios of companies but that volition non only weight tiny companies in addition to real large companies as but volition as good eliminate whatsoever companies that receive got negative earnings from my sample (causing bias inwards my estimates). To eliminate this problem, for most of the manufacture average statistics, I aggregate values across companies in addition to and thus compute ratios. With the PE ratio for US steel companies, for instance, I aggregate the internet income of all steel companies (including money-losing companies) in addition to the marketplace capitalizations for the same companies in addition to and thus split upwards the quondam yesteryear the latter to acquire the PE ratio. Think of these averages in addition to thus as weighted averages of all companies inwards each manufacture group, peradventure explaining why my numbers may hold out dissimilar from those reported yesteryear other services. 
5. Reporting: I receive got wrestled amongst how best to study this data, thus that you lot tin let out what you lot are looking for easily. I receive got non constitute the perfect template, but hither is how you lot volition let out the data. For the current information (from Jan 2017), expire to this link. You volition run into the information classified into risk, profitability, uppercase construction in addition to dividend policy measures, reflecting my corporate finance focus, in addition to and thus into pricing groups (earnings multiples, majority value multiples in addition to revenue multiples). I as good keep archived information from prior years (going dorsum to 1999) at this link. Unfortunately, since I receive got had to switch raw information providers multiple times inwards the concluding xx years, the information is non perfectly comparable over time, as both manufacture groupings in addition to information measures modify over time. 
6. Usage: There are ii ways you lot tin acquire the data. For the US data, I receive got html versions that you lot tin run into on your browser. For all of the data, I receive got excel spreadsheets that you lot tin download for the data. I would strongly encourage you lot to utilization the latter rather than the former, since you lot tin in addition to thus manipulate in addition to piece of work amongst the data. If you lot receive got questions almost whatsoever of the variables in addition to how precisely I define them, try this link, where I summarize my computational details. 

In Closing

I am a one-man performance in addition to I am certain that in that location are datasets that I receive got non updated or where you lot let out missing pieces. If you lot let out whatsoever of these, delight permit me know, in addition to I volition attempt to laid them. I as good don't run into myself as a raw information provider, peculiarly on a real-time footing in addition to on private companies. So, I don't project design to update this information over the course of study of the year, partly because manufacture averages should non receive got dramatic changes over a few months in addition to partly because I receive got other materials that I would rather do.

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Data Links

1. Current Data on my website
2. Archived Data on my website

Data 2017 Posts

1. Data Update 1: The Promise in addition to Perils of Big Data
2. Data Update 2: The Resilience of US Equities
3. Data Update 3: Cracking the Currency Code - Jan 2017
4. Data Update 4: Country Risk in addition to Pricing, Jan 2017
5. Data Update 5: Influenza A virus subtype H5N1 Taxing Year Ahead?
6. Data Update 6: The Cost of Capital inwards Jan 2017
7. Data Update 7: Profitability, Excess Returns in addition to Corporate Governance- Jan 2017
8. Data Update 8: The Debt Trade off inwards Jan 2017
9. Data Update 9: Dividends in addition to Buybacks inwards 2017
10. Data Update 10: The Pricing Game