Experiments in online teaching: My Spring Classes and an Online Valuation Class

In my last two posts, I talked about the big picture, focusing on why I think MOOCs stumbled in the last year and the moat that gives universities their power to offer a "bundled product" at a premium price. In this one, I want to get back to the theme of experimentation and the future of online education.

Let me start by noting that there is far more that we are still learning about how to teach online. While MOOCs captured the public consciousness a few years ago, they did so more because of their numbers (of students) and less because of their effectiveness. A couple of years into this experiment, it is clear that there are problems: the drop out rates are astronomical, there are questions of effectiveness and even Sebastian Thrun, one of the earliest cheerleaders for the concept, seems to be having second thoughts.

This semester, I will be teaching my regular corporate finance and valuation MBA classes at the Stern School of Business at New York University, and like the last few semesters, I will be offering those classes on iTunes U and online for those of you who are interested.

Corporate Finance class: This is my big picture class in finance and sequentially comes ahead of the valuation class (though I don't think of it as a pre-requisite). It is  a business finance class that looks at the financial principles that should govern how we run businesses (small or large, private or public, developed or emerging). Here are your choices for taking it, if you are interested:
a. On my website: I will be posting all of the class webcasts, lecture notes and sundry material at the links below.
Link for the class: http://www.stern.nyu.edu/~adamodar/New_Home_Page/corpfin.html
Link for webcasts: http://www.stern.nyu.edu/~adamodar/New_Home_Page/webcastcfspr14.htm
There will be no protective gates around the class and you should be able to download the webcasts and other material.
b. On iTunes U: If you want a smoother experience, the same material will be posted on the iTunes U site in a public course (that anyone should be able to watch on an Apple device, if they have the iTunes U app, which is free)
Link for class: https://itunes.apple.com/us/course/id806212423
Classes start on February 3 and will go on until May 12, though the class will stay online for months afterwards.

Valuation class: This is a class about valuation, more valuation and still more valuation. As I describe, it is about valuing any type of asset or business, using any valuation technique and in any kind of setting. The choices for taking it are listed below:
a. On my website: All of the material for the class will be at the links below:
Link for the class: http://www.stern.nyu.edu/~adamodar/New_Home_Page/equity.html
Link for webcasts: http://www.stern.nyu.edu/~adamodar/New_Home_Page/webcasteqspr14.htm
b. On iTunes U: If you want a smoother experience, the same material will be posted on the iTunes U site in a public course (that anyone should be able to watch on an Apple device, if they have the iTunes U app, which is free).
Link for class: https://itunes.apple.com/us/course/id806212442
This class also starts on February 3 and lasts until May 12.

If you are interested in joining in, please do so. I would love to have you along for the ride. I know that many of you have tried to take these classes in the past and have had a difficult time making it past the first few sessions, and I entirely understand. Juggling family, friends, a full course schedule at your regular college and life's other challenges is difficult enough, without having to add two more 80-minute sessions each week, as well as all of the work that goes with these classes. If you can pull it off, I admire you, but if you don't have the time, I not only understand but I do have a offer for you that reflects four lessons that I have learned in my exposure to online learning.

1. Online learning is different from in-class learning: A classroom lecture of 80 minutes is long enough, but it is doable. An online lecture of 80 minutes is torturous. In fact, studies during the last two years suggest that an online lecture that lasts for more than ten minutes may very quickly end up losing its audience. Online classes have to be shorter, punchier and accompanied by fewer distractions than regular classes.
2. There is too little interaction: Online classes offer too little interaction, not only between faculty and students but also among students. Online classes need to find ways to increase interaction especially among students, not only to allow questions to be answered but to provoke discussion that can enhance learning.
3. There is limited or no feedback: Much as students like to complain about exams in their classes, it turns out that they miss not having them (as is the case in many online classes), since they provide tangible feedback on whether you are absorbing the material in the class. Online classes need to find ways to let students confirm that they are assimilating the key concepts of the class.
4. There is no hands-on experience: Ultimately, you learn by doing, not listening, and online classes seem to give short shrift to hands on experience. Online classes need to figure out ways of getting students to try what they learn in class on real world questions.

For the last few months, I have wrestled with how best to create an online class that tries (and perhaps fails) to overcome these problems. My first experiment was with my investment philosophies iTunes U class, tied to my book, that I posted on a few months ago. My second experiment is now ready to go and I would love to have your feedback on what parts of it work and which ones don't. It is my valuation class, restructured and redesigned for an online audience, with the following components. You can find it on iTunes U by going to the following link:
Online valuation class: https://itunes.apple.com/us/course/id780803998
If you have an iPad, this should be easy to do. If you have an Android, you will need to download an app that allows you to access iTunes U courses.  If you do try this class, you will find the following changes.

1. Less is more: I compressed each of my MBA classes (80 minutes) into a 10-15 minute session. Thus, this class is composed of 25 sessions, averaging around 15 minutes each. I tried to get the core of each class into the shorter session. You can be the judge!
2. Easier on the eye? Stern was kind enough to provide me with a professional cameraman and editor for the sessions and I think they are much more watchable. My thanks go to Kristen Sosulski, Brian O'Hagan and David Schumacher for making these videos look great, though I retain responsibility for anything stupid that was said during any of them.
3. Post class tests and solutions: Like the investment philosophy class, each session in this class comes with a post class test and solution to allow you to test your understanding of that session.
4. Discussion boards: Kipin Hall is a business started by some very bright young people at NYU that offers a discussion board online. I have added a link to each session, with a discussion forum for that session. You can use it to ask questions about the material that someone else taking the class may be able to answer or which I may, from time to time, be able to provide input on.You can also use it to chat with others in the class, post links about the topic or in any other creative way that you want. You will need to register the first time you use the discussion board, and if you any questions or issues, you can contact Kipin Hall at info@kipinhall.com. 
5. In-practice webcasts: Since you learn valuation by doing, I have added number of in-practice webcasts on practical questions ranging from how you read a 10K to how you adjust earnings for leases or compute a cost of debt. You can use this to take the material from the class and value companies.
6. Blog post valuations: In an ongoing part of the class, I plan to take the weekly company valuations that I do this semester in my regular class and do short blog posts on how I approached the valuation, accompanied by my spreadsheet containing the valuation.

I am not ready to give up on online learning yet. If they have not worked well so far, it is not because they can never work but because we have much to learn about how people learn online and what works and what does not. I plan to keep trying and with your help, I hope to get better over time.

The barbarians are at the gate! Of universities, moats and disruption!

In my last post, I attempted to break down the bundled product that comprises a college education into its component parts, and closed by arguing that the future of universities rests on their ability to preserve the competitive advantages that have allowed them to get premium prices for these bundles and that of online education entrepreneurs on their capacity to find chinks in the university armor. 

In this one, I would like to look at the competitive advantages that colleges/universities have on each component and how close (or distant) the online threat is on each of them. Borrowing from the terminology of value investing, universities have moats around their “educational castles” and the online barbarians (at least as seen by the members of the educational establishment) are trying to breach the establishment. Since so much of this debate comes from one side of this divide or the other,  I decided that it would be good to try to look at both sides. In the table below, I take a look at each piece of the bundle, what colleges/universities bring as a competitive advantage on that piece and the challenges faced by online disruptors.

The University Moat and the Online Challenge

Bundled item	The “University” Moat is deepest at	The Online Challenge
Screening	More selective” schools that have reputations based on long histories and tradition. It is also self-perpetuating, since your selectivity allows them to attract the best students who burnish their reputations further.  In softer disciplines, where it is difficult, if not impossible, for an outsider to observe output or make judgments on quality.	Online entities have a "chicken & egg" problem, since they need good reputations to be selective and need to be selective to generate those reputations.  However, they may have a much better chance of breaking through  (a) if they can team up with an entity that has a reputation (a university like Stanford/MIT or a pure screener like the College Board) or (b) in areas where the skill sets of graduates are measurable and observable. (Engineering, software coding etc.) (c) in disciplines where there is a common certification exam (accounting, law).
Structuring	Colleges that help students create customized study or degree programs, built around their interests and objectives.	Online education is currently chaotic when it comes to structuring. While course offerings proliferate, guidance for novices on structuring & sequencing these courses is limited or non-existent.
Classes	Colleges that offer classes that are well taught by “star” faculty and built around interaction, group learning, individualized feedback and informative grading systems (that measure learning and not attendance/memorization) have an edge.	Online classes are often too passive, focused on delivering content and mechanized testing/grading. Creating more interactive, dynamic online classes as well as hybrid variations, which are online much of the time, but have in-person meeting components, may help bridge the gap.
The Network	Colleges that create networks among students that continue long after they graduate, augmented by small group networks such as sororities/ fraternities and campus clubs/activities.	Fostering close networks when your interactions are all online is more difficult ( but as Facebook and Linkedin's success show, it is not impossible) and serendipitous contact (like the ones you have on the college green with strangers) is very limited.
Career Advice/ Placement	Colleges that provide career guidance early in college life, followed by access to good placement services (with exclusive and privileged access to prized employers) .	Getting employers to trust your “products” as much as they trust established institutions (colleges & universities) will take time, though it should be easier in professions where the proof of competence can be tested.
Entertainment	Colleges with strong sports teams and cultural activities on campus.	Entertainment options online are getting richer but it will be difficult to match the real thing. Online universities don't have basketball teams or play bowl games.
Education	Colleges that try to students how to learn & prepare them for life.	Same challenge, but magnified because you are restricted to do this online.

I know that I am probably being simplistic in some of my assessments, but the key is to get this conversation started. 

Last year, I gave this talk at a few schools about the future of education, and I tried an experiment, making one half of the audience play the role of the university (and giving them the job of defending the moat) and the other half of the audience the role of online disruptors. I created worksheets for each group to try to get them to be specific about gauging the state of the moat at their institutions and potential challenges. If you are interested, the links to each side are below:

1. Worksheet for the University side (on how to make the moat deeper) (Download as pdf file)
2. Worksheet for the Online disruptor side (on how to get across the moat) (Download as pdf file)

If your sympathies lie with the university side or your future depends upon it's survival (because you are a faculty member or administrator), you can see that keeping the education monopoly will require work and changes in the way universities are structured. Lifetime tenure, a low teaching load and research freedom may all be viewed as inalienable rights by university faculty today (at least at the top research schools) but they will all have to be reexamined in light of the competition. 

If you are an online education entrepreneur, this exercise will be a reality check. Universities will not cede their power easily and have the means to make it difficult for online disruptors to challenge them, since they not only get to define what comprises education but are backed up by licensing/accreditation bodies that have bought into the system. . To wean consumers away from traditional universities, online educators have to think broader, be more creative and use guerilla warfare where necessary. 

I believe that change is coming to education but that it will come in stages and be under-the-surface. The first to feel the heat (if they have not already) will be colleges that have loose or non-existent screens, mechanized degree programs, content-heavy but learning-light classes and nonexistent networks. As they fall prey to online or alternative education systems, it is an open question as to how schools further up the food chain will react. I won’t claim to know the mindset of faculty/administrators at the top schools but my interactions with them suggest that many of them will, for the most part, resist change (especially if it inconveniences them) and argue that there is no chance that their civilized citadels will fall to the barbarians. But they are fooling themselves, since the disruptors have the luxury of being able to experiment, with nothing to lose, until they find the weapons that work. It is only a matter of time!

The MOOC stumble: Lessons from Napster and the Music Business!

I have been a long time proponent of online education and have been offering webcasts of my classes since 2001. However, I was a little skeptical about the news stories that appeared a couple of years ago about Massive Open Online Courses (MOOCs) being the next "big thing" in education. If a class were only about delivering content, a MOOC may do the job, but a good class should be (though it often is not) more than that. It has to foster hands-on experience, interaction, excitement and "aha'" moments, and MOOCs (including mine) have not paid enough attention to these pieces. Thus, as the initial buzz about MOOCs has faded, we are discovering the achilles heels of online classes: high drop out rates and poor retention of knowledge. It is therefore not a surprise to read stories like this one about the failures of and financial troubles faced by MOOCs.

As is often the case, some journalists and analysts are over reacting to these news stories to conclude that online education is a failed venture. Some of the more reactionary university administrators and faculty are gleeful and are ready to go back to what they have done for decades: take students for granted and cater to the other interest groups that feed at the higher education trough. That would be a mistake, analogous to music companies reacting to the demise of Napster more than a decade ago by going back to their old modes of business (selling CDs through music stores), only to be swept away by Apple iTunes a few years later. The MOOC model represented the first serious foray of online entities into education and like Napster, it failed because it not only came with flaws but because it's promoters failed to fully understand the business it was trying to disrupt.

It is also worth noting that the failure of MOOCs really rests on your definition of the word "fail".  My corporate finance MOOC, offered on iTunes U, YouTube and online last spring had 50,000+ people registered in it. By my count (and it is unofficial), about 10% of them have finished the class, as of now, and a significant portion took more than a year, and another 5% or 10% may get around to completing the class in the next few months. While that represents only 15% to 20% of the overall total, that works out to 7500-10000 people taking the class, a number that I would find impossible to reach in  a physical classroom, even over many years. If that represents failure, I will take it!

One reason for the inability of MOOCs to penetrate the education market is that they started with the faulty premise that the core of what you get for the college tuition that you pay is classroom content. As my third child went off to college last year, I had a chance to revisit the question of what it is that you get in return for that check you write out to the educational institution of your choice. The first thing to note is that universities operate like cable companies (and other monopolistic entities) and force you to buy a "bundled product", whether you want the individual pieces or not. The second is that classes are only a piece, and perhaps not even the most critical piece, of the "education" bundle. As I see it, here are the ingredients of the bundle:

1. Screening: It can be argued that the most value-added day of your education at a selective school (say an Ivy League, Stanford, MIT or Caltech in the US or the equivalents in other countries) is the day that you receive your admissions letter from the school. The rest is purely academic (in the truest sense of the word), since the fact that you were able to make it through the screen becomes the most noticed part of your education. 
2. Structuring: For better or worse, universities have been able to define the content of an education for centuries. This includes not only a specification of how long it takes to get a degree (in terms of time and courses) but also the breakdown of courses into required or core classes and the sequencing of electives thereafter. 
3. Classes: Within the course structure are classes, delivered by faculty (generally exclusive to that university) in restricted settings (physical classrooms) owned by the university and with an infrastructure of exams, tests and grades that affirms to outsiders that students have taken and mastered the content in these classes. Students in these classes learn from interactions (usually live) with the faculty and other students and can get help from tutors or teaching assistants for these classes. In special cases, students that have an intense interest in a topic may be get mentoring and advice from faculty who are (presumably) experts on that topic.
4. Networking: Even those of you who have been victimized by the "old boy (or old girl)" network have to admit that it works remarkably well at taking care of those who are lucky enough to be part of it. The networks that are created when you are a student at an educational institution may provide you with job openings, employment options and business opportunities later in life. This can be augmented by smaller networks also created by sub-groups (fraternities & sororities, clubs) at schools.
5. Career advice: Recognizing the economic imperatives that most students face in terms of getting employment after their education, universities have invested (some more than others) in providing both career advice and placement services. 
6. Entertainment: While this may sound irreverent, it is reality that a portion of the college experience is entertainment. Whether it be going to football games at Alabama or Notre Dame, enjoying a concert on campus or just people-watching on Sproul Plaza on Berkeley, you don't realize how much fun you have in college, until you graduate (and get into the real world, where such entertainment is more difficult to find, more expensive and expose you to more danger). At the risk of sounding cynical, I would also include as part of entertainment, the semester abroad programs that schools love to tout as a "bargain educational experience in exotic foreign locales" , since there is generally more fun to be had in your semester abroad in Spain/France/Brazil/Italy than learning.
7. Education: There is a final fuzzy component that universities claim to aspire to deliver, though there is no way of measuring whether they deliver on the promise. "Send your 18-year old to us", they say, "and and we will turn them into educated people".  A Harvard panel defined educated people as those who “leave school with a deep understanding of themselves and how they fit into the world and have learned how solve complex problems, be creative & entrepreneurial, manage themselves and to be life long learners". Well, good luck with that!!!

There are undoubtedly other bits and pieces that I am not including in the bundle, ranging from on-campus food/housing (which is now a requirement and not an option at most schools) to an implicit belief (misplaced or not) on the part of some foreign students that getting an undergraduate degree at a US university will improve their odds of being able to work and live in the United States. (If I have missed pieces of your specific college bundle, please do let me know and I will add it in).

The value of this bundle and its components will clearly vary from school to school. With some highly ranked, research universities (that I will leave unnamed), the screening, networking and career advice may be the predominant parts, with classes a distant fourth. That is perhaps the admission that Wharton was making when it put a large chunk of its first-yar MBA classes online, for free. With small, teaching oriented colleges, the tilt may be towards classes and structuring (with customized programs), with small but very strong networks, as a bonus. Of course, you could end up at a college that is not particularly selective, has a one-size fits all for coursework, indifferent faculty/content-heavy classes, weak networks and little or no career advice/placement and unwatchable sports teams. If so, I hope that you are not paying $50,000/year for an education, because you certainly are not getting your money's worth.

If you are or were a consumer of the education bundle, some introspection may be called for. If your college education was in the past, was it worth the money you paid for it and the time you spent acquiring it? If so, what part of the bundle has paid off the most? Was it the screening, the class content, the connections (network), the entertainment value or that unquantifiable secret ingredient (personal growth)? If you or your child is in college right now, ask the same questions about your ongoing experience. In particular, are there parts of this bundle that you are paying for that you have no use for? The one thing you cannot do is assume that the threat has passed, just because an immediate threat (MOOCs) may have dissipated.

If you are a faculty member or a college administrator, you have to ask the same questions and your future may ride on the answers. In particular, you have to look at what it is that you offer (as a college or university) that makes your education bundle unique, different and difficult to replicate (either online or in another institution). If you are an online education entrepreneur, your task is to figure out ways to unbundle the product and probe its weakest points. That will be the subject of a companion post.

Numbers Time! Data update for 2014

In 1992, I had just finished a spreadsheet that contained the average PE ratios for companies in different sectors in the United States. There was little of substance in it, but I decided that since I had it, I might as well share it. I posted that spreadsheet for students in my class to download and made it available to others who visited my website (more hopeful thinking than an actual plan, since there were relatively few people looking for data online). Each year since, I have added to the data collection, initially expanding my list of data items for US companies, and in the last decade, adding to the collection by looking at non-US companies. It is my first task each year and it takes up the first week of the year, and I just uploaded the data today for the 2014 update. 

I never imagined that my initial foray into data sharing that started with one spreadsheet of a single statistic would expand to cover 285 spreadsheets in 2014, with more than a thousand data items and that my universe of stocks would include 40,906 listed companies in 131 markets.

While you can find them all by going to the data section on my website, I won’t bore you with the details in this post, but focus instead on the what, why and what next of data.

The “what”: It starts with raw data!

In the last three decades, we have witnessed a revolution in data access that we need to step back to appreciate. In the 1980s, unless you worked at a university or an investment bank, your access to data was not just limited but often non-existent. I remember trekking to the library (yes, the place with real books and reference stacks and the Dewey decimal system) to review Value Line summary sheets for individual companies and the industry averages that S&P published at the start of every year. I had access to Compustat through the university but it was accounting-focused (with very few market numbers) and dated. 

The first glimmers of the data revolution were in the 1990s and for me, it began with Value Line offering an electronic version of the data, delivered on a CD every month by mail. That was the basis for my first data updates and Value Line data remains my base for US data, more because of my familiarity with it and its history than any special characteristics. In fact, there are databases that have richer detail, not just in terms of having more data items for US companies, but in bringing in listings in other markets. My decision to expand my data updates from US to global companies was triggered by my access to Bloomberg terminals that were installed at the Stern School of Business about a decade ago. About five years ago, I started tapping into Capital IQ, an S&P product, that is one of the more comprehensive databases for global companies today. In addition to accounting data, it includes market data and corporate governance data on individual companies and an easy interface for screening and downloading data.

My focus in data analysis is to consolidate the data into a form where it not only less overwhelming but also more usable in valuation and corporate finance endeavors. To that effect, I compute averages on key statistics (profitability measures, risk measures and financial leverage measures) across industries and geographical groupings. I also use the raw data to put my spin on corporate finance measures (cost of capital, excess returns) for individual companies.

The why: It is purely self-interest!

While I am gratified that there are some out there who use my data in their analyses, I want to be clear that there is very little that is altruistic about my efforts. So, in case you are curious, here are the reasons why I think that the week that I spend at the start of each year is well spent.

1. Anchor Angst: Behavioral economists, starting with Kahnemann and Tversky, have noted that investors and analysts look for anchors, starting points for making judgments, when making decision. They also noted that these anchors are often either skewed (by an investor's own experiences and history) or based on fiction, leading to bad decisions. So, what is a low PE ratio in today’s market or a high revenue multiple? Rather than make those judgments based on bad information, I find it useful to look at the data each year and let it inform my assessments. It is this theme that I used for my update last year, where I used one of my favorite books/movies, Moneyball, to illustrate the power of data.
2. It is a time saver: This may seem like an odd claim to make, after I have spent a week collecting and processing the data, but I am convinced that the net effect of my efforts during the last week will be a time saving over the course of the year.  As some of you are aware, I not only teach a valuation class but I also value companies frequently, both in the context of the class and to satisfy my curiosity. While the starting data for my valuations comes from the company’s financial statements, the key inputs in valuation are often industry-wide risk and profitability measures. The industry averages that I computed this week will often be the numbers that I return to over and over again, during the course of this year.
3. Go global: It is easy to talk “global” but it remains true that we are most comfortable with staying “local”. This is not only true for investors, who continue to have a home bias in investing (over investing in their domestic markets) but it also applies to businesses and academics. In fact, much of finance research, while paying lip service to the global market, continues to have a US focus. One reason that I have extended and deepened my analysis of global companies over time is to fill in the empty spots in my knowledge on listed companies in many of the smaller markets. It is telling that 80% of the time that I spent in the last week was on non-US data, a significant jump from the cursory efforts I made a decade ago when I started reporting global numbers.

The what next: Caveat emptor!

If you do decide to download and use any of the data on my website and use it, here are a few things that I hope that you will keep in mind:

1. Data can be subjective: Contrary to the widely held view that numbers are objective, the statistics that you will see in my datasets reflect my judgments and points of view, some of which you may agree with, but some that you may disagree with, perhaps vehemently. Thus, my estimates of equity risk premiums for individual countries are largely based upon sovereign ratings and CDS spreads, both bond market measures of default risk. Similarly, my estimates of costs of capital for individual companies are built on my estimates of relative risk (beta) for these companies, which are in turn estimated from the sectors that they operate in and their policies on debt.
2.  Bludgeon, not scalpel: One of the key differences between analyzing one company and trying to assess tens of thousands of companies is that you cannot have too much nuance in the estimation approaches that you use for the latter. For example, for an individual company, I will try to estimate the cost of debt, based on an actual or synthetic bond rating. With multitudes of companies, I use a much looser approximation, where I tie the cost of debt to the variability in the stock price. Bottom line: If you are valuing an individual company, go to the source (the annual report and financial filings) and not the line data that you see for that company on my data set. If you are analyzing an entire sector, you can use my approximated data in your analysis.
3. There will be mistakes in the raw data: I am incredibly grateful to Value Line, Bloomberg and S&P for giving me access to the raw data on companies, but it is also true that there is potential for human error at the date input stage. While I run my own tests to try and catch data input errors , I will miss a few. Thus, if you do find a company in my data base that has a return on equity of 20,000% or a PE ratio of 0.1, odds are that there is something wrong in the raw data of the company. 
4.  The outlier conundrum: Even if the raw data is accurate, the ratios and multiples computed from that data can sometimes yield absurd values. Thus, the PE ratio for a company with earnings fading towards zero can converge on infinity. With individual companies, you notice these absurdities and either adjust for them or look for alternative statistics. With large samples, though, that oversight is again difficult and while I could have arbitrarily set limits (ignore PE ratios greater than 200, for instance), I was reluctant to put my imprint on the data. So, if you see strange numbers for some statistics, it is what came out of the data.
5. The law of large numbers is your ally: The other side of large samples is a positive one, since the advantage of having very large samples is that the outliers have less of an impact on your statistics. Thus, I am comforted by knowing that I have hundreds of firms in each sector, when I compute my averages and that strange numbers on the part of a few companies will have only a small impact on the averages.

I know that there is little earth-shattering that I have said about what I learned from the 2014 data update, but I think those lessons will be better covered in a series of posts that I plan to make in the next  couple of weeks.

P.S: As always, there are dozens of links and data sets in my data page and I am sure that I have screwed up on some of them. If you find any missing links or have issues with the data, please let me know and I will fix them as soon as I can. 

A good year ends, but what's next for stocks?

As an exceptionally good year for stocks comes to an end, the talk of stock market bubbles fills the air.  Among others, Robert Shiller warns us, that based upon his market measure of value, that we are in "bubble" territory and almost  every acquaintance that I have starts off by asking me whether I think that US equities are ready to pop. I have great respect for Shiller, but I also know that the market is bigger than any of us, Nobel prize winners or not. As the the new year begins, and we all turn our attention to the state of our portfolios, I am sure that this discussion will only get louder. You may be accuse me of being "chicken" but I am loath to get into this guessing game, since market timing is not my strength. However, the scattered nature of the debate, where each side (bubble or no bubble) finds something in the market that supports its thesis reminds me of the story about the blind men who are allowed to touch an elephant and come to very different conclusions about what it looks like. Perhaps, the only contribution I can make to this discussion is to provide a framework that can be used to make sense of the different perspectives on the future of stocks and at lease provide some perspective on how investors can look at the same numbers and come to such different conclusions.

Standard Pricing Metrics: In the eye of the beholder?

Most of the arguments about whether we are in bubble territory still are built around the standard metrics, where equity multiples are compared across time and markets. In fact, a surprisingly large number of arguments, pro and con, are based on the PE ratio, with variants on earnings used by each side to make its case.  Those who remain optimistic about the market focus on trailing or forward earnings and note that the trailing and forward PEs, while high can be explained by low interest rates. Those who are pessimistic about markets either make their comparisons to the historic averages for the PE ratio for the market or argue that earnings for the market are high today (in both absolute levels and stated as a percent of revenues) and are ripe for adjustment. Thus, it is no surprise that those who use cyclically-adjusted PE (CAPE) are sounding alarm bells about the market.

Valuing the market

Like any other investment, the value of a market is determined by cash flows, growth (level and quality) and risk in stocks. Consider an investor who buys the equity index. That investor can lay to claim to all cash paid out by the companies in the index, composed of both dividends and stock buybacks. If we forecast out these composite cash flows, the value of the index in intrinsic terms can be stated as a function of the following variables:

Holding all else constant, higher base-year cash flows and higher growth rates lead to higher values for equities, whereas higher risk free rates and equity risk premiums result in lower values for equities.

The status quo

Given these drivers of equities, where do we stand right now? The S&P 500 starts the year (2014) at 1848.36, up almost 30% from it's level of 1426.19, a year prior. While that jump in stock prices makes most investors wary, it is also worth noting that the cash paid out to equity investors in the twelve months leading into the start of 2014 amounted to 84.16, up 21.16% from the cash flows to equity in the twelve months leading into the start of 2013. As the economy strengthened over 2013, the US treasury bond rate also climbed from 1.76% at the start of 2013 to 3.04% at the close of trading on December 31, 2013.  To estimate the cash flows in future years, we used the estimates of earnings from analysts who track the aggregate earnings on the S&P 500 (top down estimates), resulting in an earnings growth rate of 4.28% a year for the next five years, which we also assume to be the growth rate in the cash flows paid out to equity investors (thus keeping the payout stable at 84.13% of earnings). As a final input, we set the growth rate in cash flows beyond year 5 at 3.04%, set equal to the risk free rate.

The simplest way to bring these numbers together is to look for a discount rate that will make the present value of the cash flows (i.e., the intrinsic value of the index) equal to the traded value of 1848.36. That discount rate works out to be 8.00% and can be viewed as the expected return on equities, given my estimates of cash flows. Netting out the risk free rate from that number yields an implied equity risk premium of 4.96%.

Are we in a bubble?

One way to evaluate whether stocks are collectively misplaced is to compare the implied equity risk premium today to what you believe is a reasonable value. That "reasonable value" is clearly up for discussion but to provide some perspective, I have reproduced the implied equity risk premiums for the S&P 500 from 1961 to 2013 in the figure below.

The equity risk premium of 4.96% is clearly down from its crisis peaks (6% or higher), but it is still higher than the average of 4.04% from 1961-2013 and slightly above the average of 4.90%, from 2004-2013. Market optimists would point out that unlike the market peak in early 2000, when the implied equity risk premium of 2.00% was well below the historic norms, the equity risk premium today is at acceptable or even above acceptable levels. Market pessimists, though, will note the equity risk premium in September 2008 was also just above the historic norms and that it provided little protection against the ensuing crash.

Stress Testing the Market

The assessment of the equity risk premium above is a function of the risk free rate and my estimates of expected cash flows and growth. Since all of these can and will change over 2014, it is prudent to evaluate which of these variables pose the greatest threat to equity investors.

1. Risk free rate

While the US T.Bond rate has rebounded from its historic lows, it remains well below its norm, as indicated in the figure below:

While there are many who attribute the low rates in the last few years primarily through quantitative easing by central banks, I remain a skeptic and believe that low economic growth was a much bigger contributor. In fact, as economic growth rebounded in 2013, interest rates rose, and if expectations of continued growth in 2014 come to fruition, I believe that rates will continue to risk, no matter what the Fed decides to do.  While that rise in rates may seem like an unmitigated negative for stocks, the net effect on stocks will be a function of whether the economic growth also translates into higher earnings/cash flow growth. It is only if interest rates rise at a much steeper rate than earnings growth rates increases that stocks will be hurt.

2. Equity Risk Premium

While the equity risk premium today is not low, relative to historic standards, the last five years have taught us that market crises can render historic norms useless. Thus, there is always the possibility that 2014 could bring a macro crisis that could cause equity risk premiums to revert back to 2009-levels. In the following table, I estimate the intrinsic value for the S&P 500 at different equity risk premiums.

If, in fact, we saw a reversal back to the 6.4% equity risk premiums that we observed after the crash, the index would be valued at 1418, making it over valued by about 30% today.

3. Cash flows

It is clear that US companies returned to their pre-crisis buyback behavior in 2013 and there are some who wonder whether these cash flows are sustainable. To answer that question, we looked at dividends and buybacks from 2001 to 2013 in the figure below, and compare them to the earnings on the index each year.

Are US companies returning too much cash to investors? It is true that the 84.13% of earnings paid out in dividends and buybacks in 2013 was higher than the average of 79.96% from 2004-2013, but the difference is not large.  The bigger danger to cash flows to equity is a collapse in earnings. In fact, using the CAPE rule book, we estimated the inflation-adjusted earnings on the index each year from 2004 to 2013 and computed a ten-year average of these earnings of 82.64. Applying the average payout ratio of 79.96% to these earnings results in a much lower cash flow to equity of 66.08. Using those cash flows, with an equity risk premium of 4.90%, results in an intrinsic value for the index of 1467.89, about 20.6% lower than the index level on January 1, 2014. Thus, it is no surprise that those analysts who use PE ratios based on average earnings over time come to the conclusion that stocks are over priced.

4. Growth Rates

The use of analyst estimates of growth can make some of you uneasy, since analysts can sometimes get caught up in the mood of the moment and share in the "irrational exuberance" of the market. While using top down estimates (as opposed to the estimates of growth in earnings for individual companies), provides some insulation, there is a secondary test that we can use to judge the sustainability of the predicted growth rate. In particular, when the return on equity is stable, the expected growth in earnings is a product of the retention ratio (1- payout ratio) and the return on equity:

Sustainable growth rate = (1 - Payout ratio) (Return on equity)

Using the 84.13% payout ratio and the return on equity of 15.790% generated by the market in 2013, we estimate an expected growth rate in earnings of 2.67%, lower than the analyst estimate of 4.28%. Substituting in this growth rate lowers the value of the index to 1741, making it over valued by about 6%, at its current level.

Try it yourself

I know that you will probably have your own combination of fears and hopes. To help convert those into an intrinsic value for the index, I have the spreadsheet that I used in my analysis for download. When you open the spreadsheet, you will be given a chance to set your combination of the risk free rate, equity risk premium, cash flows and growth and see the effect on value. The spreadsheet also has historical data on risk free rates and equity risk premiums embedded as worksheets.

Bottom Line

As I look at the fundamentals and the possibilities for 2014, I am wary but no more so than in most other years. There are always scenarios where the intrinsic value of the index will drop and the biggest dangers, as I see them, come from either a global crisis that blindsides markets or from a precipitous drop in expected earnings.  Can I guarantee that these scenarios will not unfold? Of course not, and that is precisely why I would require an equity risk premium for investing in stocks and will continue to diversify across asset classes and markets. You may very well come to a different conclusion, and whatever it is, I wish you only success in the coming year, even if it comes at my expense. Happy New Year!

End of the year (2014) data update posts

1. A good year ends, but what's next for stocks?