Thursday, October 6, 2016

Deutsche Bank: A Greek Tragedy at a German Institution?

This may be a stereotype, but the Germans are a precise people and while that precision often gets in the way of more creative pursuits (like cooking and valuation), it lends itself well to engineering and banking. For decades until the introduction of the Euro and the creation of the European Central Bank, there was no central bank in the world that matched the Bundesbank for solidity and reliability. Thus, investors and regulators around the world, I am sure, are looking at the travails of Deutsche Bank in the last few weeksand wondering how the world got turned upside down. I am sure that there are quite a few institutions in Greece, Spain, Portugal and Italy who are secretly enjoying watching a German entity be at the center of a market crisis. Talk about schadenfreude!

Deutsche Bank's Journey to Banking Hell
There are others who have told the story about how Deutsche Bank got into the troubles it is in, much more creatively and more fully than I will be able to do so. Consequently, I will stick with the numbers and start by tracing Deutsche Bank’s net income over the last 28 years, in conjunction with the return on equity generated each year.

If Deutsche Bank was reluctant to follow more daring competitors into risky businesses for much of the last century, it threw caution to the winds in the early part of the last decade, as it grew its investment banking and trading businesses and was rewarded handsomely with higher earnings from 2000 to 2007. Like almost every other bank on earth, the crisis in 2008 had a devastating impact on earnings at Deutsche, but the bank seemed to be on a recovery path in 2009, before it relapsed. Some of its recent problems reflect Deutsche’s well chronicled pain in investment banking, some come from its exposure to the EU problem zone (Greece, Spain, Portugal) and some from slow growth in the European economy. Whatever the reasons, in 2014 and 2015, Deutsche reported cumulative losses of close to $16 billion, leading to a management change, with a promise that things would turn around under new management. The other dimension where this crisis unfolded was in Deutsche’s regulatory capital, and as that number dropped in 2015, Deutsche Bank's troubles moved front and center. This is best seen in the graph below of regulatory capital (Tier 1 Capital) from 1998 to 2015, with the ratio of the Tier 1 capital to risk adjusted assets each year super imposed on the graph. 

The ratio of regulatory capital to risk adjusted assets at the end of 2015 was 14.65%, lower than it was in 2014, but much higher than capital ratios in the pre-2008 time-period. That said, with the tightening of regulatory capital constraints after the crisis, Deutsche was already viewed as being under-capitalized in late 2015, relative to other large banks early this year. The tipping point for the current crisis came from the decision by the US Department of Justice to levy a $14 billion fine on Deutsche Bank for transgressions related to the pricing of mortgage backed securities a decade ago. As rumors swirled in the last few weeks, Deutsche Bank found itself in the midst of a storm, since the perception that a bank is in trouble often precipitates more trouble, as rumors replace facts and regulators panic. The market has, not surprisingly, reacted to these stories by marking up the default risk in the bank and marking down the stock price, most strikingly over the last two weeks, but also over a much longer period. 

At close of trading on October 4, 2016, the stock was trading at $13.33 as share, yielding a market capitalization of $17.99 billion, down more than 80% from its pre-2008 levels and 50% from 2012 levels. Reflecting more immediate fears of default, the Deutsche CDS and CoCo bonds also have dropped in price, and not surprisingly, hedge funds sensing weakness have moved in to short the stock. 

Revaluing Deutsche Bank
When a stock is down more than 50% over a year, as Deutsche is, it is often irresistible to many contrarian investors, but knee jerk contrarian investing, i.e., investing in a stock just because it has dropped a lot, is a dangerous strategy. While it is true that Deutsche Banks has lost a large portion of its market capitalization in the last five years, it is also true that the fundamentals for the company have deteriorated, with lower earnings and hits to regulatory capital. To make an assessment of whether Deutsche is now “cheap”, you have to revalue the company with these new realities built in, to see if the market has over reacted, under reacted or reacted correctly to the news. (I will do the entire valuation in US dollars, simply for convenience, and it is straightforward to redo the entire analysis in Euros, if that is your preferred currency).

a. Profitability 
As you can see from the graph of Deutsche’s profits and return on equity, the last twelve months have delivered blow after blow to the company, but that drop has been a long time coming. The bank has had trouble finding a pathway to make sustainable profits, as it is torn between the desire of some at the bank to return to its commercial banking roots and the push by others to explore the more profitable aspects of trading and investment banking. The questions in valuation are not only about whether profits will bounce back but also what they will bounce back to. To make this judgment, I computed the returns on equity of all publicly traded banks globally and the distribution is below: 
Global Bank Data
I will assume that given the headwinds that Deutsche faces, it will not be able to improve its returns on equity to the industry median or even its own cost of equity in the near term. I will target a return on equity of 5.85%, at the 25th percentile of all banks, as Deutsche’s return on equity in year 5, and assume that the bank will be able to claw back to earning its cost of equity of 9.44% (see risk section below) in year 10. The estimated return on equity, with my estimates of common equity each year (see section of regulatory capital) deliver the following projected net income numbers. 
YearCommon EquityROEExpected Net Income
Base$64,609 -13.70%$(8,851)
1$71,161 -7.18%$(5,111)
2$72,754 -2.84%$(2,065)
3$74,372 0.06%$43
4$76,017 1.99%$1,512
5$77,688 5.85%$4,545
6$79,386 6.57%$5,214
7$81,111 7.29%$5,910
8$82,864 8.00%$6,632
9$84,644 8.72%$7,383
10$86,453 9.44%$8,161
Terminal Year$87,326 9.44%$8,244
I am assuming that the path back to profitability will be rocky, with losses expected for the next two years, before the company is able to turn its operations around. Note also that these expected losses are in addition to the $10 billion fine that I have estimated for the DOJ.

b. Regulatory Capital 
Deutsche Bank’s has seen a drop in it Tier 1 capital ratios over time but it now faces the possibility of being further reduced as Deutsche Bank will have to draw on it to pay the US DOJ government fine. While the DOJ has asserted a fine of $14 billion, Deutsche will negotiate to reduce it to a lower number and it is assessing its expected payment to be closer to $6 billion. I have assumed a total capital drop of $ 10 billion, leaving me with and adjusted regulatory capital of $55.28 billion and a Tier 1 capital ratio of 12.41%. Over the next few years, the bank will come under pressure from both regulators and investors to increase its capitalization, but to what level? To make that judgment, I look at Tier 1 capital ratios across all publicly traded banks globally: 
Global Bank Data
I will assume that Deutsche Bank will try to increase its regulatory capital ratio to the average (13.74%) by next year and then push on towards the 75th percentile value of 15.67%. As the capital ratio grows, the firm will have to increase regulatory capital over the next few years and that can be seen in the table below: 

YearNet IncomeRisk-Adjusted AssetsTier 1 Capital/ Risk Adjusted AssetsTier 1 CapitalChange in Tier 1 CapitalFCFE = Net Income - Change in Tier 1
Base$(8,851)$445,570 12.41%$55,282
1$(5,111)$450,026 13.74%$61,834 $6,552 $(11,663)
2$(2,065)$454,526 13.95%$63,427 $1,593 $(3,658)
3$43 $459,071 14.17%$65,045 $1,619 $(1,576)
4$1,512 $463,662 14.38%$66,690 $1,645 $(133)
5$4,545 $468,299 14.60%$68,361 $1,671 $2,874
6$5,214 $472,982 14.81%$70,059 $1,698 $3,516
7$5,910 $477,711 15.03%$71,784 $1,725 $4,185
8$6,632 $482,488 15.24%$73,537 $1,753 $4,880
9$7,383 $487,313 15.46%$75,317 $1,780 $5,602
10$8,161 $492,186 15.67%$77,126 $1,809 $6,352
Terminal Year$8,244 $497,108 15.67%$77,897 $771 $7,472
The negative free cash flows to equity in the first three years will have to be covered with new capital that meets the Tier 1 capital criteria. By incorporating these negative free cash flows to equity in my valuation, I am in effect reducing my value per share today for future dilution, a point that I made in a different context when talking about cash burn

c. Risk
Rather than follow the well-trodden path of using risk free rates, betas and risk premiums, I am going to adopt a short cut that you can think of as a model-agnostic way of computing the cost of equity for a sector. To illustrate the process, consider the median bank in October 2016, trading at a price to book ratio of 1.06 and generating a return on equity of 9.91%. Since the median bank is likely to be mature, I will use a stable growth model to derive its price to book ratio: 
Plugging in the median bank’s numbers into this equation and using a nominal growth rate set equal to the risk free rate of 1.60% (in US dollars), I estimate a US $ cost of equity for the median bank to be 9.44% in 2016. 

Using the same approach, I arrive at estimates of 7.76% for the banks that are at the 25th percentile of risk and 10.20% for banks at the 75th percentile.  In valuing Deutsche Bank, I will start the valuation by assuming that the bank is at the 75th percentile of all banks in terms of risk and give it a cost of equity of 10.20%. As the bank finds its legs on profitability and improves its regulatory capital levels, I will assume that the cost of equity moves to the median of 9.44%. 

The Valuation 
Starting with net income from part a, adjusting for reinvestment in the form of regulatory capital in part b and adjusting for risk in part c, we obtain the following table of numbers for Deutsche Bank. 

YearFCFETerminal ValueCost of equity Cumulative Cost of EquityPV
5$2,874 10.20%1.6252$1,768.16
6$3,516 10.05%1.7885$1,965.99
7$4,185 9.90%1.9655$2,129.10
8$4,880 9.74%2.1570$2,262.34
9$5,602 9.59%2.3639$2,369.91
10$6,352 $87,317 9.44%2.5871$36,206.88
Total value of equity $31,838.74
Value per share =$22.97
Note that the big number as the terminal value in year 10 reflects the expectation that Deutsche will grow at the inflation rate (1% in US dollar terms) in perpetuity while earning its cost of equity. Note also that since the cost of equity is expected to change over time, the cumulated cost of equity has to be computed as the discount factor. The discounted present value of the cash flows is $31.84 billion, which when divided by the number of shares (1,386 million) yields a value of $22.97 per share. There is one final adjustment that I will make and it reflects the special peril that banks face, when in crisis mode. There is the possibility that the perception that the bank is in trouble could make it impossible to function normally and that the government will have to step in to bail it out (since the option of letting it default is not on the table). I may be over optimistic but I attach only a 10% chance to this occurring and assume that my equity will be completely wiped out, if it occurs. My adjusted value is: 
Expected Value per share = $22.97(.9) + $0.00 (.1) = $20.67 
Given my many assumptions, the value per share that I get for Deutsche Bank is $20.67. To illustrate how much the regulatory capital shortfall (and the resulting equity issues/dilution) and overhang of a catastrophic loss affect this value, I have deconstructed the value per share into its constituent effects: 

Unadjusted Equity Value =$33.63
- Dilution Effect from new equity issues$(10.66)
- Expected cost of equity wipeout$(2.30)
Value of equity per share today =$20.67

Note that the dilution effect, captured by taking the present value of the negative FCFE in the first four years, reduces the value of equity by 31.69% and the possibility of a catastrophic loss of equity lowers the value another 6.83%. The entire valuation is pictured below:
Download Spreadsheet
I know that you will disagree with some or perhaps all of my assumptions. To accommodate those differences, I have set up my valuation spreadsheet to allow for you to replace my assumptions with yours. If you are so inclined, please do enter your numbers into the shared Google spreadsheet that I have created for this purpose and let's get a crowd valuation going!

Time for action or Excuse for inaction? 
At the current stock price of $13.33 (at close of trading on October 4), the stock looks undervalued by about 36%, given my estimated value, and I did buy the stock at the start of trading yesterday. Like everyone else in the market, I am uncertain, but waiting for the uncertainty to resolve itself is not a winning strategy. Either the uncertainty will be resolved (in good or bad ways) and everyone will have clarity on what Deutsche is worth, and the price and value will adjust, or the uncertainty will not resolve itself in the near future and you will be sitting on the side lines. For those of you who have been reading my blog over time, you know that I have played this game before, with mixed results. My bets on JP Morgan (after its massive trading loss in 2012) and Volkswagen (after the emissions scandal) paid off well but my investment in Valeant (after its multiple scandals) has lost me 15% so far (but I am still holding and hoping). I am hoping that my Deutsche Bank investment does better, but I strapped in for a rocky ride!

YouTube Videos


  1. My valuation of Deutsche Bank
  2. Global Banks - Data
  3. Google Shared Spreadsheet: Crowd Valuation of Deutsche Bank

Sunday, October 2, 2016

Venture Capital: It is a pricing, not a value, game!

Venture capitalists (VCs) don’t value companies, they price them! Before you explode, implode or respond with righteous indignation, this is not a critique of what venture capitalists do, but a recognition of reality. In fact, not only is pricing exactly what you should expect from VCs but it lies at the heart of what separates the elite from the average venture capitalist. I was reminded of this when I read a response from Scott Kupor of Andreessen Horowitz, to a Wall Street Journal article about Andreessen, that suggested that the returns earned by the firm on its funds were not as good as those earned at other elite funds. While Scott’s intent was to show that the Wall Street Journal reporter erred in trusting total returns as a measure of VC performance, I think that he, perhaps unintentionally, opened a Pandora’s box when he talked about how VCs attach numbers to companies and how these numbers get updated, and how we (investors, founders and VCs) should read them, as a consequence.

The WSJ versus the VC: A Recap
Let’s start with the Wall Street Journal article that triggered the Kupor response. With the provocative title of “Andreessen Horowitz’s returns trail venture capital elite”, it had all the ingredients for click bait, since a big name (Andreessen Horowitz) failing (“trail venture capital elite”) is always going to attract attention. I must confess that I fell for the bait and read the article and walked away unimpressed. In effect, Rolfe Winkler, the Journal reporter, took the three VC funds run by Andreessen and computed an IRR based upon the realized and unrealized gains at these funds. I have reproduced his graph below:

While the title of the story is technically correct, I am not sure that there is much of a story here. Even if you take the Journal’s estimates of returns at face value, if I were an investor in any of the three Andreessen funds, I would not be complaining about annual returns of 25%-42%, depending on the fund that I invested in. Arguing that I could have done better by investing in a fund in the top 5% of the VC universe would be the equivalent of claiming that Kevin Durant did not having a good NBA season last year, because Lebron James and Stephen Curry had better seasons.

In the hyper-competitive business of venture capital, though, the article must have drawn blood, since it drew Scott Kupor's attention and a response. Scott focused attention specifically on what he believed was the weakest link in the Journal article, the combining of realized and unrealized gains to estimate an internal rate of return. Unlike investments in public equities, where the unrealized returns are based upon observed market prices for traded stocks and can be converted to realized returns relatively painlessly, Scott noted that unrealized returns at venture capital funds are based upon estimates and that these estimates are themselves based upon opaque VC investments in other companies in the space and not easily monetized. Implicitly, he seemed to be saying that not only are unrealized returns at VC funds subject to estimation error, but also to bias, and should thus be viewed as softer than realized returns. I agree, though I think it is disingenuous to go on to argue that unrealized returns should not be considered when evaluating venture capital performance, since VCs seem to have qualms about using them in sales pitches when they serve their purpose.

The VC Game
The Kupor response has been picked in the VC space, with some commenters augmenting legitimate points about return measurement but many more using the WSJ article to restate their view that non-VC people should stop opining about the VC business, because they don’t understand how it works. Having been on the receiving end of this critique at times in the past, you would think I would know better than to butt in, but I just can’t help myself. I may not be qualified to talk about the inner workings of the venture capital business, but I do believe that I am on firmer ground on the specific topic of how VCs attach numbers to the companies that they invest in.

VCs price businesses, not value them!
I have made the distinction between value and price so many times before that I sound like a broken record, but I will make it again. You can value an asset, based upon its fundamentals (cash flows, growth and risk) or price it, based upon what others are paying for similar assets, and the two can yield different numbers.

In public investing, I have argued that this plays out in whether you choose to play the value game (invest in assets where the price < value and hope that the market corrects) or the pricing game (where you trade assets, buying at a lower price and hoping to sell at a higher).  I would be glad to be offered evidence to the contrary but based upon the many VC "valuations" that I have seen, VCs almost always play the pricing game, when attaching numbers to companies, and there are four ways in which they seem to do it:
  1. Recent pricing of the same company: In the most limited version of this game, a prospective or existing investor in a private business looks at what investors in the most recent prior round have priced the company to gauge whether they are getting a reasonable price. Thus, for an Uber, this would imply that a pricing close to the $62.5 billion that the Saudi Sovereign fund priced the company at, when it invested $3.5 billion in June 2016, will become your benchmark for a reasonable price, if you are investing close to that date. The dangers in doing this are numerous and include not only the possibility of a pricing mistake (a new investor who over or under prices the company) spiraling up and down the chain, but also the problems with extrapolating to the value of a company from a VC investment in it.
  2. Pricing of “similar” private companies: In a slightly more expanded version of this process, you would look at what investors are paying for similar companies in the “same space” (with all of the subjective judgments of what comprises “similar” and “same space”), scale this price to revenues, or lacking that, a common metric for that space, and price your company. Staying in the ride sharing space, you could price Lyft, based upon the most recent Uber transaction, by scaling the pricing of the company to its revenues (relative to Uber) or to rides or number of cities served.
  3. Pricing of public companies, with post-value adjustments: In the rare cases where a private business has enough operating substance today, in the form of revenues or even earnings, in a space where there are public companies, you could use the pricing of public companies as your basis for pricing private businesses. Thus, if your private business is in the gaming business and has $100 million in revenues and publicly traded companies in that business trade at 2.5 times revenues, your estimated value would be $250 million. That value, though, assumes that you are liquid (as publicly companies tend to be) and held by investors who can spread their risks (across portfolios). Consequently, a discount for lack of liquidity and perhaps diversification is applied, though the magnitude (20%, 30% or more) is one of the tougher numbers to estimate and justify in practice.
  4. Forward pricing: The problem with young start-ups is that operating metrics (even raw ones like riders, users or downloads) are often either non-existent or too small to be base a pricing. To get numbers of any substance, you often have to forecast out the metrics two, three or five years out and then apply a pricing multiple to these numbers. The forecasted metric can be earnings, or if that still is ephermal, it can be revenues, and the pricing multiple can be obtained not just from private transactions but from the public market (by looking at companies that have gone public). That forward value has to be brought back to today and to do so, venture capitalists use a target rate of return. While this target rate of return plays the same mechanical role that a discount rate in a DCF does, that is where the resemblance ends. Unlike a discount rate, a number designed to incorporate the risk in the expected cash flows for a going concern, a target rate of return incorporates not just conventional going-concern risk but also survival risk (since many young companies don’t make it) and the fear of dilution (a logical consequence of the cash burn at young companies), while also playing role as a negotiating tool. Even the occasional VC intrinsic value (taking the form of a DCF) is a forward pricing in disguise, with the terminal value being estimated using a multiple on that year's earnings or revenues.

At the time of a VC investment, the VC wants to push today’s pricing for the company lower, so that he or she can get a greater share of the equity for a given investment in the company. Subsequent to the investment, the VC will want the pricing to go higher for two reasons. First, it makes the unrealized returns on the VC portfolio a much more attractive number. Second, it also means that any subsequent equity capital raised will dilute the VC’s ownership stake less. If you reading this as a criticism of how venture capitalists attach numbers to companies, you are misreading it because I think that this is exactly what venture capitalists should be doing, given how success is measured in the business. This is a business where success is measured less on the quality of the companies that you build (in terms of the cash flows and profits they generate) and more on the price you paid to get into the business and the price at which you exit this business, with that exit coming from either an IPO or a sale. Consequently, how much you are willing to pay for something becomes a process of judging what you will get when you exit and working backwards.

But Venture Capitalists have a data problem
It is not just venture capitalists who play the pricing game. As I have argued before, most investors in public markets (including many who call themselves value investors) are also in the pricing game, though they use pricing metrics of longer standing (from PE to EV/EBITDA) and have larger samples of public traded firms as comparable firms. The challenges with adapting this pricing game to venture capital investments are primarily statistical:
  1. Small Samples: If your pricing is based upon other private company investments, your sample sizes will tend to be much smaller, if you are a VC than if you a public company investor. Thus, as an investor in a publicly traded oil company, I can draw on 351 publicly traded firms in the US or even the 1029 publicly traded companies globally, when making relative value or pricing judgments. A VC investor pricing a ride sharing company is drawing on a sample of less than ten ride sharing firms globally.
  2. With Infrequent Updating: The small sample problem is exacerbated by the fact that unlike public companies, where trading is frequent and prices get updated for most of the companies in my sample almost continuously, private company transactions are few and far between. In many ways, the VC pricing problem is closer to the real estate pricing than conventional stock pricing, where you have to price a property based upon similar properties that have sold in the recent past.
  3. And Opaque transactions: There is a third problem that makes VC pricing complicated. Unlike public equities, where a share of stock is (for the most part) like any other share of stock and the total market value is the share price times number of shares outstanding, extrapolating from a VC investment for a share in a company to the overall value of equity can be and often is complicated. Why? As I noted in an earlier post on unicorn valuations, the VC investment at each stage of capital-raising is structured differently, with a myriad of options embedded in it, some designed for protection (against dilution and future equity rounds) and some for opportunity (allowing future investments at favorable prices). As I noted in that post, a start-up with a "true" value of $750 million can structure an investment, where the VC pays $50 million (instead of $37.5 million) for 5% of the company, by adding enough optionality to the investment. I may be misreading Scott's section on using option pricing to price VC investments, but if I am reading it right, I think Scott is saying that Andreessen uses option pricing models to clean up for the add-on options in VC investments to get to the fair value. Put differently, Andreessen would put a value of $750 million on this company rather than the $1 billion that you would get from extrapolating from the $50 million for 5%.
I am sure that nothing that I have said here is new to venture capitalists, founders and those close to the VC process, but it is the subtle differences that throw off those whose primary experience is in the public markets. That is one reason that public investors should take the numbers that are often bandied about as valuations of private companies (like Palantir, Uber and Airbnb) with a grain of salt.  It is also why I think that public investors like mutual funds and university endowment funds should either tread lightly or not all in the space. Even within the VC business, it is sometimes easy, especially in buoyant times to forget how much the entire pricing edifice rests as much on momentum and mood, as it does on the underlying fundamentals.

With Predictable Consequences
So, let’s see. VCs price companies and that pricing is often based upon really small samples with infrequently updated and tough-to-read data. The consequences are predictable.
  1. The pricing estimates will have more noise (error) attached to them. The pricing that I obtain for Lyft, based upon the pricing of Uber, Didi Chuxing and GrabTaxi, will have a larger band around the estimate and there is a greater chance that I will be wrong. 
  2. The pricing will be more subjective, since you have the freedom to choose your comparable firms and often can use discretion to adjust for the infrequent data updating and the complexity of equity investments. While that may seem to just be a restatement of the first critique, there is also a much greater potential for bias to enter into the process. Not surprisingly, therefore, not all VC returns are created equal, especially when it comes to the unrealized portion, with more aggressive VCs reporting “higher” returns than less aggressive VCs. That is perhaps the point being made by Scott about realized versus unrealized returns.
  3. The pricing will lag the market: It is a well-established fact that the capital coming into the VC business ebbs and flows across time, with the number of transactions increasing in up markets and dropping in down markets. When there is a severe correction (say, just after the dot-com bust), transactions can come to a standstill, making repricing difficult, if not impossible. If VCs hold off on full repricing until transactions pick up again, there can be a significant lag between when prices drop at young companies and those price drops getting reflected in returns at VC firms.
  4. There is a price feedback loop: Since VC pricing is based upon small samples with infrequent transactions, it is susceptible to feedback loops, where one badly priced transaction (in either direction) can trigger many more badly priced transactions. 
  5. And a time horizon issue: The lack of liquidity and small samples that get in the way of pricing holdings also introduce a constraint into the pricing game. Unlike public market investors, where the pricing game can be played in minutes or even fractions of a minute on liquid stocks, private market pricing requires patience and more of it, the younger a company is. Put differently, winning at the VC pricing game may require that you take a position in a young start up and bide your time until you build it up and find someone who will find it attractive enough to offer you a much higher price for it. This is perhaps what Scott was talking about, in his response, when he talked about this being VC investing being a "long" game.
There is one final point that also needs to be made. Much as we like to talk about the VC market and the public market as separate, populated by different species, they are linked at the hip. To the extent that a venture capitalist has to plot an exit, either in an initial public offering or by selling to a publicity traded company, if the public market catches a cold, the venture capital market will get pneumonia, though the diagnosis may come much later.
The VC Edge
If I were to summarize the entire post in a couple of sentences, here is what it would say. Venture capitalists price the companies they invest in, base that pricing on small samples of opaque transactions and the pricing is therefore more likely to be wrong and lag reality. That sounds pretty damning, but I think that these features work to the advantage of venture capitalists, or at least the very best among them. That may sound contradictory, but here is my basis for making that statement.
  1. The average VC does better than the average public market active investor: Both VC and public market investors play the pricing game, with the latter having the advantage of more and better data, but over time, venture capitalists seem to deliver better results than public market investors, as seen in the graph below. These are raw returns and I do realize that you have to adjust for risk, but some of the biggest risks in venture capital (failure risk) have already been incorporated into long term returns. 
    Source: Cambridge Associates
  2. The Elite: The most successful VCs not only earn higher returns than the top public market investors but that there seems to be more consistency in the VC business, insofar as the best of the VCs are able to generate higher returns across longer time periods. That would suggest that venture capitalists bring more durable competitive advantages to the investing game than public market investors.
How do I reconcile my argument that the VC pricing game is inherently more error-prone and noisy with the fact that VCs seem to make money at it? I think that the very factors that make it so difficult to price and profit of a VC investment are what allow VCs collectively to earn excess returns and the very best VCs to set themselves apart from the rest. In particular, the best in the business set themselves apart from the rest on three dimensions:
  1. They are better pricers (relatively): As Scott notes in his piece, the price that you can attach to a VC investment can vary widely across investors and he uses the example of how Andreessen's option pricing approach can yield a lower pricing for the same company than an alternative approach. While all of these prices are undoubtedly wrong (because they are estimates), some of them are less wrong than others. Repeating a statement that I have made before, you don't have to be right to make money, you just have to be less wrong than everyone else and the chances of you doing that are greater in the VC pricing game.  
  2. They can influence the pricing game: Unlike public market investors, who for the most part can observe company metrics but not change them, venture capitalists can take a more active role in the companies that they invest in, from informally advising managers to more formal roles as board members, helping these companies decide what metrics to focus on, how to improve these metrics and how (and when) to cash in on them (from an IPO or a sale).
  3. They have better timing: The pricing game is all about timing, and the VC pricing game is more emphatically so. To be successful, you not only have to time your entry into a business right but even more critically, time your exit from it. 
If you are an investor in a VC fund, therefore, you should of course look at both realized returns and unrealized returns, but you should also look at how the fund measures its unrealized returns and how it has generated its returns. A realized return that comes primarily from one big hit is clearly less indicative of skill than a return that reflects multiple hits over longer time periods. After all, if separating luck from skill is difficult in the public marketplace, it can become even more so in the venture capital business.

YouTube Video

Wednesday, September 14, 2016

Fairness Opinions: Fix them or Flush them!

My post on the Tesla/SCTY deal about the ineptitude and laziness that Lazard and Evercore brought to the valuation process did not win me any friends in the banking M&A world. Not surprisingly, it drew some pushback, not so much from bankers, but from journalists and lawyers, taking me to task for not understanding the context for these valuations. As Matt Levine notes in his Bloomberg column, where he cites my post, "a fairness opinion is not a real valuation, not a pure effort to estimate the value of a company from first principles and independent research" (Trust me. No one is setting the bar that high. I was looking for biased efforts using flawed principles and haphazard research and these valuation could not even pass that standard)  and that "they (Lazard and Evercore) are just bankers; their expertise is in pitching and sourcing and negotiating and executing deals -- and in plugging in discount rates into preset spreadsheets -- not in knowing the future". (Bingo! So why are they doing these fairness opinions and charging millions of dollars for doing something that they are not good at doing? And there is a difference between knowing the future, which no one does, and estimating the future, which is the essence of valuation.) If Matt is right, the problems run deeper than the bankers in this deal, raising questions about what the purpose of a   "fairness opinion" is and whether it has outlived its usefulness (assuming that it was useful at some point).

Fairness Opinions: The Rationale
What is a fairness opinion? I am not a lawyer and I don't play intend to play one here, but it is perhaps best to revert back to the legal definition of the term. In an excellent article on the topic, Steven Davidoff defines a fairness opinion as an "opinion provided by an outsider that a transaction meets a threshold level of fairness from a financial perspective". Implicit in this definition are the assumptions that the outsider is qualified to pass this judgment and that there is some reasonable standard for fairness.  In corporate control transactions (acquisition, leveraged buyout etc.), as practiced today, the fairness opinion is delivered (orally) to the board at the time of the transaction, and that presentation is usually followed by a written letter that summarizes the transaction terms and the appraiser's assumptions and attests that the price paid is "fair from a financial point of view". That certainly sounds like something we should all favor, especially in deals that have obvious conflicts of interest, such as management-led leveraged buyouts or transactions like the Tesla/Solar City deal, where the interests of Elon Musk and the rest of Tesla 's stockholders may diverge.

Note that while fairness opinions have become part and parcel of most corporate control transactions, they are not required either by regulation or law. As with so much of business law, especially relating to acquisitions, the basis for fairness opinions and their surge in usage can be traced back to Delaware Court judgments. In Smith vs Van Gorkom, a 1985 case, the court ruled against the board of directors of Trans Union Corporation, who voted for a leveraged buyout, and specifically took them to task for the absence of a fairness opinion from an independent appraiser. In effect, the case carved out a safe harbor for the companies by noting that “the liability could have been avoided had the directors elicited a fairness opinion from anyone in a position to know the firm’s value”.  I am sure that the judges who wrote these words did so with the best of intentions, expecting fairness opinions to become the bulwark against self-dealing in mergers and acquisitions. In the decades since, through a combination of bad banking practices, the nature of the legal process and confusion about the word "fairness", fairness opinions, in my view, have not just lost their power to protect those that they were intended to but have become a shield used by managers and boards of directors against serious questions being raised about deals. 

Fairness Opinions: Current Practice?
There are appraisers who take their mission seriously and evaluate the fairness of transactions in their opinions, but the Tesla/Solar City valuations reflect not only how far we have strayed from the original idea of fairness but also how much bankers have lowered the bar on what constitutes acceptable practice.  Consider the process that Lazard and Evercore used by  to arrive at their fairness opinions in the Tesla/Solar City deal, and if Matt is right, they are not alone:

What about this process is fair, if bankers are allowed to concoct discount rates, and how is it an opinion, if the numbers are supplied by management? And who exactly is protected if the end result is a range of values so large that any price that is paid can be justified?  And finally, if the contention is that the bankers were just using professional judgment, in what way is it professional to argue that Tesla will become the global economy (as Evercore is doing in its valuation)? 

To the extent that what you see in the Tesla/Solar City deal is more the rule than the exception, I would argue that fairness opinions are doing more harm than good. By checking off a legally required box, they have become a way in which a board of directors buy immunization against legal consequences. By providing the illusion of oversight and an independent assessment, they are making shareholders too sanguine that their rights are being protected. Finally, this is a process where the worst (and least) scrupulous appraisers, over time, will drive out the best (and most principled) ones, because managers (and boards that do their bidding) will shop around until they find someone who will attest to the fairness of their deal, no matter how unfair it is. My interest in the process is therefore as much professional, as it is personal. I believe the valuation practices that we see in many fairness opinions are horrendous and are spilling over into the other valuation practices.

It is true that there are cases, where courts have been willing to challenge the "fairness" of fairness opinions, but they have been infrequent and  reserved for situations where there is an egregious conflict of interest. In an unusual twist, in a recent case involving the management buyout of Dell at $13.75 by Michael Dell and Silver Lake, Delaware Vice Chancellor Travis Lester ruled that the company should have been priced at $17.62, effectively throwing out the fairness opinion backing the deal. While the good news in Chancellor Lester's ruling is that he was willing to take on fairness opinions, the bad news is that he might have picked the wrong case to make his stand and the wrong basis (that markets are short term and under price companies after they have made big investments) for challenging fairness opinions.

Fish or Cut Bait?
Given that the fairness opinion, as practiced now, is more travesty than protection and an expensive one at that, the first option is to remove it from the acquisition valuation process. That will put the onus back on judges to decide whether shareholder interests are being protected in transactions. Given how difficult it is to change established legal practice, I don't think that this will happen. The second is to keep the fairness opinion and give it teeth. This will require two ingredients to work, judges that are willing to put fairness opinions to the test and punishment for those who consistently violate those fairness principles.

A Judicial Check
Many judges have allowed bankers to browbeat them into accepting the unacceptable in valuation, using the argument that what they are doing is standard practice and somehow professional valuation.  As someone who wanders across multiple valuation terrain, I am convinced that the valuation practices in fairness opinions are not just beyond the pale, they are unprofessional. To those judges, who would argue that they don't have the training or the tools to detect bad practices, I will make my pro bono contribution in the form of a questionnaire with flags (ranging from red for danger to green for acceptable) that may help them separate the good valuations from the bad ones.

Who is paying you to do this valuation and how much? Is any of the payment contingent on the deal happening? (FINRA rule 2290 mandates disclosure on these)
Payment reflects reasonable payment for valuation services rendered and none of the payment is contingent on outcome
Payment is disproportionately large, relative to valuation services provided, and/or a large portion of it is contingent on deal occurring.
Where are you getting the cash flows that you are using in this valuation?
Appraiser estimates revenues, operating margins and cash flows, with input from management on investment and growth plans.
Cash flows supplied by management/ board of company.
Are the cash flows internally consistent?
1.     Currency: Cash flows & discount rate are in same currency, with same inflation assumptions.
2.     Claim holders: Cash flows are to equity (firm) and discount rate is cost of equity (capital).
3.     Operations: Reinvestment, growth and risk assumptions matched up.
No internal consistency tests run and/or DCF littered with inconsistencies, in currency and/or assumptions.
-       High growth + Low reinvestment
-       Low growth + High reinvestment
-       High inflation in cash flows + Low inflation in discount rate
What discount rate are you using in your valuation?
A cost of equity (capital) that starts with a sector average and is within the bounds of what is reasonable for the sector and the market.
A cost of equity (capital) that falls outside the normal range for a sector, with no credible explanation for difference.
How are you applying closure in your valuation?
A terminal value that is estimated with a perpetual growth rate < growth rate of the economy and reinvestment & risk to match.
A terminal value based upon a perpetual growth rate > economy or a multiple (of earnings or revenues) that is not consistent with a healthy, mature firm.
What valuation garnishes have you applied?
A large dose of premiums (control, synergy etc.) pushing up value or a mess of discounts (illiquidity, small size etc.) pushing down value.
What does your final judgment in value look like?
A distribution of values, with a base case value and distributional statistics.
A range of values so large that any price can be justified.

If this sounds like too much work, there are four changes that courts can incorporate into the practice of fairness opinions that will make an immediate difference:
  1. Deal makers should not be deal analysts: It should go without saying that a deal making banker cannot be trusted to opine on the fairness of the deal, but the reason that I am saying it is that it does happen. I would go further and argue that deal makers should get entirely out of the fairness opinion business, since the banker who is asked to opine on the fairness of someone else's deal today will have to worry about his or her future deals being opined on by others.
  2. No deal-contingent fees: If bias is the biggest enemy of good valuation, there is no simpler way to introduce bias into fairness opinions than to tie appraisal fees to whether the deal goes through. I cannot think of a single good reason for this practice and lots of bad consequences. It should be banished.
  3. Valuing and Pricing: I think that appraisers should spend more time on pricing and less on valuation, since their focus is on whether the "price is fair" rather than on whether the transaction makes sense. That will require that appraisers be forced to justify their use of multiples (both in terms of the specific multiple used, as well as the value for that multiple) and their choice of comparable firms. If appraisers decide to go the valuation route, they should take ownership of the cash flows, use reasonable discount rates and not muddy up the waters with arbitrary premiums and discounts. And please, no more terminal values estimated from EBITDA multiples!
  4. Distributions, not ranges: In my experience, using a range of value for a publicly traded stock to determine whether a price is fair is useless. It is analogous to asking, "Is it possible that this price is fair?", a question not worth asking, since the answer is almost always "yes". Instead, the question that should be asked and answered is "Is it plausible that this price is a fair one?"  To answer this question, the appraiser has to replace the range of values with a distribution, where rather than treat all possible prices as equally likely, the appraiser specifies a probability distribution. To illustrate, I valued Apple in May 2016 and derived a distribution of its values:

Let's assume that I had been asked to opine on whether a $160 stock price is a fair one for Apple. If I had presented this valuation as a range for Apple's value from $80.81 to $415.63, my answer would have to be yes, since it falls within the range. With a distribution, though, you can see that a $160 price falls at the 92nd percentile, possible, but neither plausible, nor probable.  To those who argue that this is too complex and requires more work, I would assume that this is at the minimum what you should be delivering, if you are being paid millions of dollars for an appraisal.

The most disquieting aspect of the acquisition business is the absence of consequences for bad behavior, for any of the parties involved, as I noted in the aftermath of the disastrous HP/Autonomy merger. Thus, managers who overpay for a target are allowed to use the excuse of "we could not have seen that coming" and the deal makers who aided and abetted them in the process certainly don't return the advisory fees, for even the most abysmal advice. I think while mistakes are certainly part of business, bias and tilting the scales of fairness are not and there have to be consequences:
  1. For the appraisers: If the fairness opinion is to have any heft, the courts should reject fairness opinions that don't meet the fairness test and remove the bankers involved  from the transaction, forcing them to return all fees paid. I would go further and create a Hall of Shame for those who are repeat offenders, with perhaps even a public listing of their most extreme offenses. 
  2. For directors and managers: The boards of directors and the top management of the firms involved should also face sanctions, with any resulting fines or fees coming out of the pockets of directors and managers, rather than the shareholders involved.
I know that your reaction to these punitive suggestions is that they will have a chilling effect on deal making. Good! I believe that much as strategists, managers and bankers like to tell us otherwise, there are more bad deals than good ones and that shareholders in companies collectively will only gain from crimping the process.

YouTube Video

  1. The Fairness Questionnaire (as a word file, which you are free to add to or adapt)

Tuesday, September 6, 2016

Keystone Kop Valuations: Lazard, Evercore and the TSLA/SCTY Deal

It is get easy to get outraged by events around you, but I have learned, through hard experience, that writing when outraged is dangerous. After all, once you have climbed onto your high horse, it is easy to find fault with others and wallow in self-righteousness. It is for that reason that I have deliberately avoided taking issue with investment banking valuations of specific companies, much as I may disagree with the practices used in many of them. I understand that bankers make money on transactions and that their valuations are more sales tools than assessments of fair value and that asking them to pay attention to valuation first principles may be asking too much. Once in a while, though, I do come across a valuation so egregiously bad that I cannot restrain myself and reading through the prospectus filed by Tesla for their Solar City acquisition/merger was such an occasion. My first reaction as I read through the descriptions of how the bankers in this deal (Evercore for Tesla and Lazard for Solar City) valued the two companies was "You must be kidding me!".

The Tesla/Solar City Deal
In June 2016, Tesla announced that it intended to acquire Solar City in a stock swap, a surprise to almost everyone involved, except for Elon Musk. By August 1, the specifics of the deal had been ironed out and the broad contours of the deal are captured in the picture below:

At the time of the deal, Mr. Musk contended that the deal made sense for stockholders in both companies, arguing that it was a "no-brainer" that would allow Tesla to expand its reach and become a clean energy company. While Mr. Musk has a history of big claims and perhaps the smarts and charisma to deliver on them, this deal attracted attention because of its optics. Mr. Musk was the lead stockholder in both companies and CEO of Tesla and his cousin, Lyndon Rive, was the CEO of Solar City. Even Mr. Musk's strongest supporters could not contest the notion that he was in effective control at both companies, creating, at the very least. the potential for conflicts of interests. Those questions have not gone away in the months since and the market concerns have been reflected in the trend lines in the stock prices of the two companies, with Solar City down about 24% and Tesla's stock price dropping about 8%.

The board of directors at Tesla has recognized the potential for a legal backlash and as this New York Times article suggests, they have been careful to create at least the appearance of an open process, with Tesla's board hiring Evercore Partners, an investment bank, to review the deal and Solar City's board calling in Lazard as their deal assessor. Conspicuously missing is Goldman Sachs, the investment banker on Tesla's recent stock offering, but more about that later.

The Banking Challenge in a Friendly Merger
In any friendly merger, the bankers on the two sides of the deal face, what at first sight, looks like an impossible challenge. The banker for the acquiring company has to convince the stockholders of the acquiring company that they are getting a good deal, i.e., that they are acquiring the target company at a price, which while higher that the prevailing market price, is lower than the fair value for the company. At the same time, the banker for the target company has to convince the stockholders of the target company that they too are getting a good deal, i.e., that they are being acquired at is higher than their fair value. If you are a reasonably clever banking team, you discover very quickly that the only way you can straddle this divide is by bringing in what I call the two magic merger words, synergy and control. Synergy in particular is magical because it allows both sides to declare victory and control adds to the allure because it comes with the promise of unspecified changes that will be made at the target company and a 20% premium:

In the Tesla/Solar City deal, the bankers faced a particularly difficult challenge. Finding synergy in this merger of an electric car company and a solar cell company, one of which (Tesla) has brand name draw and potentially high margins and the other of which is a commodity business (Solar City) with pencil thin margins) is tough to do. Arguing that the companies will be better managed as one company is tricky when both companies have effectively been controlled by the same person(Musk) before the merger. In fact, it is far easier to make the case for reverse synergy here, since adding a debt-laden company with a questionable operating business (Solar City) to one that has promise but will need cash to deliver seems to be asking for trouble. The bankers could of course have come back and told the management of both companies (or just Elon Musk) that the deal does not make sense and especially so for the stockholders of Tesla but who can blame them for not doing so? After all, they are paid based upon whether the deal gets done and if asked to justify themselves, they would argue that Musk would have found other bankers who would have gone along. Consequently, I am not surprised that both banks found value in the deal and managed to justify it.

The Valuations
It is with this perspective in mind that I opened up the prospectus, expecting to see two bankers doing what I call Kabuki valuations, elaborately constructed DCFs where the final result is never in doubt, but you play with the numbers to make it look like you were valuing the company. Put differently, I was willing to cut a lot of slack on specifics, but what I found failed even the minimal tests of adequacy in valuation. Summarizing what the banks did, at least based upon the prospectus (lest I am accused of making up stuff):
Tesla Prospectus
Conveniently, these number provide backing for the Musk acquisition story, with Evercore reassuring Tesla stockholders that they are getting a good deal and Lazard doing the same with Solar City stockholders, while shamelessly setting value ranges so wide that they get legal cover, in case they get sued.  Note also not only how much money paid to these bankers for their skills at plugging in discount rates into spreadsheets but that both bankers get an additional payoff, if the merger goes through, with Evercore pocketing an extra $5.25 million and Lazard getting 0.4% of the equity value of Solar City.  There are many parts of these valuations that I can take issue with, but in the interests of fairness, I will start with what I term run-of-the-mill banking malpractice, i.e., bad practices that many bankers are guilty of.
  1. No internal checks for consistency: There is almost a cavalier disregard for the connection between growth, risk and reinvestment. Thus, when both banks use ranges of growth for their perpetual value estimates, it looks like neither adjusts the cash flows as growth rates change. (Thus, when Lazard moves its perpetual growth rate for Solar City from 1.5% to 3%, it looks like the cash flow stays unchanged, a version of magical growth that can happen only on a spreadsheet).
  2. Discount Rates: Both companies pay lip service to standard estimation technology (with talk of the CAPM and cost of capital), and I will give both bankers the benefit of the doubt and attribute the differences in their costs of capital to estimation differences, rather than to bias.  The bigger question, though, is why the discount rates don't change as you move through time to 2021, where both Tesla and Solar City are described as slower growth, money making companies.
  3. Pricing and Valuation: I have posted extensively on the difference between pricing an asset/business and valuing it and how mixing the two can yield a incoherent mishmash. Both investment banks move back and forth between intrinsic valuation (in their use of cash flows from 2016-2020) and pricing, with Lazard estimating the terminal value of Tesla using a multiple of EBITDA. (See my post on dysfunctional DCFS, in general, and Trojan Horse DCFs, in particular).
There are two aspects of these valuations that are the over-the-top, even by banking valuation standards:
  1. Outsourcing of cash flows: It looks like both bankers used cash flow forecasts provided to them by the management. In the case of Tesla, the expected cash flows for 2016-2020 were generated by Goldman Sachs Equity Research (GSER, See Page 99 of prospectus) and for Solar City, the cash flows for that same period were provided by Solar City, conveniently under two scenarios, one with a liquidity crunch and one without. Perhaps, Lazard and Evercore need reminders that if the CF in a DCF is supplied to you by someone else,  you are not valuing the company, and charging millions for plugging in discount rates into preset spreadsheets is outlandish. 
  2. Terminal Value Hijinks: The terminal value is, by far, the biggest single number in a DCF and it is also the number where the most mischief is done in valuation. While some evade these mistakes by using pricing, there is only one consistent way to get terminal value in a DCF and that is to assume perpetual growth. While there are a multitude of estimation issues that plague perpetual growth based terminal value, from not adjusting the cost of capital to reflect mature company status to not modifying the reinvestment to reflect stable growth, there is one mistake that is deadly, and that is assuming a growth rate that is higher than that of the economy forever. With that context, consider these clippings from the prospectus on the assumptions about growth forever made by Evercore in their terminal value calculations:
    Tesla Prospectus
    I follow a rule of keeping the growth rate at or below the risk free rate but I am willing to accept the Lazard growth range of 1.5-3% as within the realm of possibility, but my reaction to the Evercore assumption of 6-8% growth forever in the Tesla valuation or even the 3-5% growth forever with the Solar City valuation cannot be repeated in polite company. 
Not content with creating one set of questionable valuations, both banks doubled down with a number of  of other pricing/valuations, including sum-of-the-parts valuations, pricing and transaction premiums, using a "throw everything at the fan and hope something sticks" strategy.

Now what? 
I don't think that Tesla's Solar City acquisition passes neither the smell test (for conflict of interest) nor the common sense test (of creating value), but I am not a shareholder in either Tesla or Solar City and I don't get a vote. When Tesla shareholders vote, given that owning the stock is by itself an admission that they buy into the Musk vision, I would not be surprised if they go along with his recommendations. Tesla shareholders and Elon Musk are a match made in market heaven and I wish them the best of luck in their life together.

As for the bankers involved in this deal, Lazard's primary sin is laziness, accepting an assignment where they are reduced to plugging in discount rates into someone else's cash flow forecasts and getting paid $2 million plus for that service. In fact, that laziness may also explain the $400 million debt double counting error made by Lazard on this valuation,. Evercore's problems go deeper. The Evercore valuation section of the prospectus is a horror story of bad assumptions piled on impossible ones, painting a picture of ignorance and incompetence. Finally, there is a third investment bank (Goldman Sachs), mentioned only in passing (in the cash flow forecasts provided by their equity research team), whose absence on this deal is a story by itself. Goldman's behavior all through this year, relating to Tesla, has been rife with conflicts of interest, highlighted perhaps by the Goldman equity research report touting Tesla as a buy, just before the Tesla stock offering. It is possible that they decided that their involvement on this deal would be the kiss of death for it, but I am curious about (a) whether Goldman had any input into the choice of Evercore and Lazard as deal bankers, (b) whether Goldman had any role in the estimation of Solar City cash flows, with and without liquidity constraints, and (c) how the Goldman Sachs Equity Research forecast became the basis for the Tesla valuations. Suspicious minds want to know! As investors, the good news is that you have a choice of investment bankers but the bad news is that you are choosing between the lazy, the incompetent and the ethically challenged.

If there were any justice in the world, you would like to see retribution against these banks in the form of legal sanctions and loss of business, but I will not hold my breath waiting for that to happen. The courts have tended to give too much respect for precedence and expert witnesses, even when the precedent or expert testimony fails common sense tests and it is possible that these valuations, while abysmal, will pass the legally defensible test. As for loss of business, my experience in valuation is that rather than being punished for doing bad valuations, bankers are rewarded for their deal-making prowess. So, for the many companies that do bad deals and need an investment banking sign-off on that deal (in the form of a fairness opinion), you will have no trouble finding a banker who will accommodate you.

If this post comes across as a diatribe against investment banking, I am sorry and I am not part of the "Blame the Banks for all our problems" school. In fact, I have long argued that bankers are the lubricants of a market economy, working through kinks in the system and filling in capital market needs and defended banking against its most virulent critics. That said, the banking work done on deals like the this one vindicate everyone's worst perceptions of bankers as a hired guns who cannot shoot straight, more Keystone Kops than Wyatt Earps!

YouTube Video

  1. Tesla Prospectus for Solar City Deal

Thursday, September 1, 2016

The School Bell Rings! It's Time for Class!

As most teachers do, I mark time in academic rather than in calendar years and as September dawns, it is New Year's eve for me and a new class is set to begin. In just under a week, on September 7, 2016, I will walk into a classroom and face up to a roomful of students, not quite ready for summer to end, and start teaching, as I have every year since 1984. This semester, I will be back to teaching Valuation to MBAs at Stern, and as I have in semesters past, I invite you to join me on this journey, as we look at the mix of art, science and magic that makes valuation such a fascinating discipline.

Class Philosophy
I have always believe that to teach a class well, you have to start with a story and that the class is an extended serialization of the story. I also believe that to teach well, you have to, at least over time, make that story your own and mold the class to reflect it. In fact, the valuation class that I will be teaching this Fall has its seeds in the very first valuation class that I taught in 1986, but the differences reflect not only how much the world has changed since then, but also how my own thinking on valuation has evolved. The class remains a work in progress, where each time I teach it, I learn something new as well as recognize how much I have left to learn.

I could give you an extended essay on what this class is about, but I would repeating what I said at the start of the Fall 2015 semester in this post. In short, I said this class is not an extended accounting class (where you forecast entire financial statements for extended periods), or a modeling class (where you become an Excel Ninja) or a theory class (since there is so little of it in  valuation to begin with). Instead, here are the broad themes that underlie this class, all captured in the picture below:

If you find this picture a little daunting, I did do a Google talk that encapsulated these themes into about an hour-long session. 

In particular, this class is less about the tools and techniques of valuation and more about developing a foundation that you can use to build your own investment philosophy. I know that faith is a word that is seldom used and often viewed with suspicion by many in the valuation community, but it is at the heart of this class, both in terms of how you build up faith in your own capacity to value assets and businesses and how you hold on to that faith when the market price moves away from your value.  Since I still struggle on both of these fronts, I cannot give you a template for success but I will be open about my own insecurities both about my own valuations and about markets.

Class Structure
Since my objective in the class is that by the end of it, you should be able to attach a number to just about any asset, I will roam the spectrum. I will start with the basics of intrinsic value, partly because it is where I am most comfortable and partly because it provides me with ways of dealing with other approach. The mechanics of estimating discount rates, cash flows, growth and terminal value are not just simple, but easily mechanized. It is the specifics that we will wrestle with in this class:

  • On risk free rates, usually the least troublesome and more easily obtained input in valuation, we will talk about why risk free rates vary across currencies, what to do about currencies that have negative risk free rates and whether normalizing risk free rates (as many practitioners have taken to doing) is a good idea or a bad one.
  • On risk premiums and discount rates, we will wrestle with questions of what risks should and should not be incorporated into discount rates and the different methods of bringing them in. In the process, we will examine how best to estimate equity risk premiums and default spreads, and why even if you don't like betas or portfolio theory, you should should still be able to estimate discount rates and do intrinsic valuation.  
  • On cash flows, we will focus on why accounting inconsistencies (on dealing with R&D, leases and other items) can lead to misstated earnings and how to fix those inconsistencies, examine what should and should not be included in reinvestment (capital expenditures and working capital) and what to do about stock based compensation.
  • On growth, we will start with the easy cases (where historical earnings growth is a good predictor of future growth) but quickly move on to more difficult cases (of companies in transition) and to what some view as impossible cases (like estimating growth in a start-up)>
  • On terminal value, the big number in every DCF,  that can very quickly hijack otherwise well-done valuations, we will develop simple rules for keeping the number in check and put to sleep many myths surrounding it.
We will apply intrinsic valuation to value companies across the life cycle, in different sectors and across different markets. We will value small and large companies, private and public, developed and emerging and discuss how to value movie franchises (like Star Wars), phenomena (Pokemon Go) and sports teams. We will talk about why start ups can and should be valued in the face of daunting uncertainty and how probabilistic tools (simulations and decision trees) can help.

About half way through the class, we will turn our attention to pricing assets/businesses, where rather than build up to a value from a company's fundamentals, we price it, based on how the market is pricing similar companies. Put simply, we will shine a light on the practice of using pricing multiples (PE, EV/EBITDA, EV/Sales) and comparable companies not with the intent of improving how it is done. We will also talk about why, even when you are careful and take care of the details, your pricing of a company can be very different form its value.

In the last segment of the class, we will stretch our valuation muscles by talking about how option pricing models can sometime be used to estimate the additional value in a business, such as undeveloped reserves for a natural resource company or expansion potential for a young growth firm, and sometimes to value equity in deeply distressed companies. We will close by looking at acquisition valuation, where good sense seems to be in short supply, and how understanding value can be critical to corporate managers.

Want to sit in?
If you are intrigued or interested, you are welcome to sit in on the class (online and unofficially). While my immediate attention will be reserved for the Stern MBAs who will be registered in this class, you will have access to all of the resources that they do, starting with the lectures but also extending to lecture notes, quizzes/exams and even emails. The bad news is that I will be unable to grade your work or give you a certificate of completion. The good news is that the price is right. There are three ways in which you can join the class:

  1. My website: The most comprehensive and most updated center of all things related to this class at this link. You will find the webcasts, lecture notes, past exams, reading and even the emails I send on this class here.
  2. iTunes U: Just as I am not an Excel Ninja, my capacity to deal with html is primitive and my website's design reflects that lack of sophistication. If you prefer more polish, you can try the iTunes U app in the Apple app store. It is a free app that you can download and install on your Apple device. Once you have it installed, click on the add course and enter the enroll code FER-SFJ-AKA. Like magic, the class should pop up on your shelf. If you don't have an Apple device, you can get to the course on your computer using this link. If you have an Android device, you can use a workaround by downloading this app first. Like all things Apple, the set up is amazing and easy to work with.
  3. YouTube: The problem with the first two choices is that they presuppose that you don't have a broadband constraint, perhaps a phone internet connection or worse. My suggestion is that you use the YouTube playlist that I have created for this class at this link. The nice thing about YouTube is that it adjusts the image quality to your connection speed. So, it should work in almost any setting.
Since I have made this offer for almost 20 years now, predating the MOOC boom and bust, I can offer some suggestions. First, it is a lot of work to watch two 80-minute lectures a week, try your hand out at working through actual valuations and finish the class in fifteen weeks, if you have other things going on in your life (and who does not?). My suggestion is that you cut yourself some slack and take more time, since the materials will stay up for at least a year after the class ends. Second, watching a lecture online for almost an hour and a half can be painful and for those of you who find the pain unbearable, I do have an alternative. A couple of years ago, I created an online version of this class, shrinking each 80-minute session into 10-15 minute sessions and this class is also available on my website at this link, on iTunes U at this link and on YouTube. Third, whichever version of the class you take will stick more if you pick a company and value it and even more, if you keep doing it. 

The End Game
I would love to tell you that I live a life of serenity and that I am sharing for noble reasons, but that would not be true. I am sharing my class for the most selfish of all reasons. I am a performer (and every teacher is) and what performer does not wish for a bigger audience? If I am going to prepare and deliver a class, would I not rather have thirty thousand people watch the class than three hundred. If you get something of value from this class, and you feel the urge to repay me, I will make the same suggestion that I did last year. Learning is one of those rare resources that is never diminished by sharing. So, please pass it on to someone else! See you in class!

  1. Entry Page for the Valuation Spring 2016 (on my website)
  2. Webpage for the Valuation Spring 2016 class webcasts (on my website)
  3. iTunes U for the Valuation Spring 2016 class (Enroll code on device: FER-SFJ-AKA)
  4. YouTube Playlist for the Valuation Spring 2016 class
  5. Webpage for Valuation Online class (short sessions)
  6. iTunes U for the Valuation Online class (short sessions)
  7. YouTube for the Valuation Online class (short sessions)