A Valeant Update: Damaged Goods or Deeply Discounted Drug Company?

Rats get a bad rap for fleeing sinking ships. After all, given that survival is the strongest evolutionary impulse and that rats are not high up in the food chain, why would they not? That idiom, unfortunately, is what came to mind as I took another look at Valeant, the vessel in my investment portfolio that most closely resembles a sinking ship. This is a stock that I had little interest in, during its glory days as the ultimate value investing play, but that I took first a look at, after its precipitous fall from grace in November 2015. While I stayed away from it then, I bought it in May 2016 after it had dropped another 60% and I found it cheap enough to add to my portfolio. I then compounded my losses when I doubled my holding in October 2016, arguing that while it was, at best, an indifferently managed company in a poor business, it was under priced at $14 . With the stock trading at less than $12 (and down to $10.50, as I write this post) and its biggest investor/promoter abandoning it, there is no way that I can avert my eyes any longer from this train wreck. So, here I go!

Valeant: A Short (and Personal) History

I won't bore you by repeating (for a third time) the story of Valeant's fall from investment grace, which happened with stunning speed in 2015, as it went from value investing favorite to untouchable, in the matter of months. My first post, from November 2015, examined the company in the aftermath of the fall, as it was touted as a contrarian bet, trading at close to $90, down more than 50% in a few months. My belief then was that the company's business model, built on acquisitions, debt and drug repricing was broken and that the company, if it became a more conventional drug business company, with low growth driven by R&D, was worth $73 per share. I revisited Valeant in April 2016, after the company had gone through a series of additional setbacks, with many of its wounds self inflicted and reflecting either accounting or management misplays. At the time, with the updated information I had and staying with my story of Valeant transitioning to a boring drug company, with less attractive margins, I estimated a value per share of $44, above the stock price of $33 at the time. I bought my first batch of shares. In the months that followed, Valeant's woes continued, both in terms of operations and stock price. After it announced a revenue drop and a decline in income in an earnings report in November 2016, the stock hit $14 and I had no choice but to revisit it, with a fresh valuation. Adjusting the valuation for the new numbers (and a more pessimistic take on how long it would take for the company to make its way back to being a conventional, R&D-driven pharmaceutical company, I valued the shares at $32.50. That may have been hopeful thinking but I added to my holdings at around $14/share.

Valeant: Updating the Numbers

Since that valuation, not much has gone well for the company and its most recent earnings report suggests that its transition back to health is still hitting roadblocks. While talk of imminent default seems to have subsided, there seems to be overwhelming pessimism on the company's operating  prospects, at least in the near term. In its most recent earnings report, Valeant reported further deterioration in key numbers:

	2016 10K	2015 10K	% Change
Revenues	$9,674.00	$10,442.00	-7.35%
Operating income or EBIT	$3,105.46	$4,550.38	-31.75%
Interest expense	$1,836.00	$1,563.00	17.47%
Book value of equity	$3,258.00	$6,029.00	-45.96%
Book value of debt	$29,852.00	$31,104.00	-4.03%

Much as I would like to believe that this decline is short term and that the stock will come back, there is now a real chance that my story for Valeant, not an optimistic and uplifting story to begin with, is now broken. The company's growth strategy of acquiring other companies, using huge amounts of debt, raising prices on "under priced" drugs and paying as little in taxes as possible were perhaps legally defensible but they were ethically questionable and may have damaged its reputation and credibility so thoroughly that it is now unable to get back to normalcy. This can explain why the company has had so much trouble not only in getting its operations back on track but also why it has been unable to pivot to being a more traditional drug company. If researchers are leery about working in your R&D department, if every price increase you try to make faces scrutiny and push back and your credibility with markets is rock bottom, making the transition will be tough to do. It can also indirectly explain why Valeant may be having trouble selling some of its most lucrative assets, as potential buyers seem wary of the corporate taint and perhaps have lingering doubts about whether they can trust Valeant's numbers.

In fact, the one silver lining that may emerge from this experience is that I now have the perfect example to illustrate why being a business entity that violates the norms of good corporate behavior (even if their actions legal) can destroy value. At least in sectors like health care, where the government is a leading customer and predatory pricing can lead to more than just public shaming, the Valeant story should be a cautionary note for others in the sector who may be embarking on similar paths.

The Ackman Effect

You may find it strange that I would spend this much time talking about Valeant without mentioning what may seem to be the big story about the stock, which is that Bill Ackman, long the company's biggest investor and cheerleader and for much of the last two years, a powerful board member, has admitted defeat, selling the shares that Pershing Square (his investment vehicle) has held in Valeant for about $11 per share, representing a staggering loss of almost 90% on his investment. The reasons for my lack of response are similar to the ones that I voiced in this post, when I remained an Apple stockholders as Carl Icahn sold Apple and Warren Buffett bought the stock in April 2016. As an investor, I have to make my own judgments on whether a stock fits in my portfolio and following others (no matter how much regard I have for them) is me-too-ism, destined for failure.  

Don't get me wrong! I think Bill Ackman, notwithstanding his Valeant setbacks, is an accomplished investor whose wins outnumber his losses and when he takes a position (long or short) in a stock, I will check it out. That said, I did not buy Valeant because Ackman owned the stock and I am not selling, just because he sold. In fact, and this may seem like a stretch, it is possible that Ackman's presence in the company and the potential veto power that he might have been exercising over big decisions may have become more of an impediment than a help as the company tries to untangle itself from its past. I am not sure how well-sourced these stories are, but there are some that suggest that it was Ackman who was the obstacle to a Salix sale last year.

Valeant: Three Outcomes

As I see it, there are three paths that Valeant can take, going forward.

1. Going Concern: To value Valeant as a going concern, I revisited my valuation from November 2016 and made its pathway to stable drug company more rocky by assuming that revenues would continue to drop 2% a year and margins will stay depressed at 2016 levels for the next 5 years and that revenue growth will stay anemic (3% a year) after that, with a moderate improvement in margins. With those changes put in and leaving the likelihood that the company will not make it at 10% (since the company has made some headway in reducing debt), the value per share that I get is $13.68. 

Download spreadsheet

To illustrate the uncertainty associated with this value estimate, I ran a simulation with my estimated distributions for revenue growth, margins and cost of capital and arrived at the following distribution of values.

The simulation confirms the base case intrinsic valuation, insofar as the median value of $13.31 is close to the price at the time of the valuation ($12) but it provides more information that may or may not tilt the investment decision. There is a clear chance that the equity could go to zero (about 12%), if the value dips below the outstanding debt ($29 billion). At the same time, there is significant upside, if the company can find a way to alter its trajectory and become a boring, low growth drug company.

2. Acquisition Target: It is a sign of desperation when as an investor, your best hope is that someone else will acquire your company and pay a premium for it. I am afraid that the Valeant taint so strong and its structure so opaque and complex that very few acquirers will want to buy the entire company. I see little chance of this bailing me out.

3. Sum of its parts, liquidated: It is true that Valeant has some valuable pieces in it, with Bausch & Lomb and Salix being the biggest prices. While neither business has attracted as much attention as Valeant had hoped, there are two reasons why. The first is that Ackman, with significant losses on the stock and a seat on the board, may have exercised some veto power over any potential sales. The second is that potential buyers may be scared away by Valeant's history. One solution, now that Ackman is no longer at the company, is for Valeant to open its books to potential acquirers and sell its assets individually to the best possible buyers. Note that this liquidation value will have to exceed $29 billion, the outstanding debt, for equity investors to generate any remaining cash.

There is one other macro concern that may make Valeant's future more thorny. As a company that pays a low effective tax rate and borrows lots of money, the proposed changes to the tax law (where the marginal tax rate is likely to be reduced and the tax savings from interest expenses curbed), Valeant will probably have to pay a much higher effective tax rate going forward, one reason why I have shifted to a 30% tax rate for the future.

The Bottom Line

Let's start with the easy judgment. This was not an investment that I should have made and much as I would like to blame macro forces, the company's management and Bill Ackman for my losses, this was my mistake. I was right in my initial post in concluding that the company's old business model (of acquiring growth with borrowed money and repricing drugs) was broken but I clearly underestimated how much damage that model has done to the company's reputation and how much work it will take for it to become a boring, drug company. In fact, it is possible that the damage is so severe, the company will not be able to make the adjustments necessary to survive as a going concern. 

So, now what? I cannot reverse the consequences of my original sin (of buying Valeant at $32) in April 2017 and the secondary sin (of doubling down, when Valeant was trading at $14) by selling now. The question then becomes a simple one. Would I buy Valeant at today's price? If the answer is yes, I should hold and if the answer is no, I should fold. My intrinsic value per share has dropped to just above where the stock is trading at now, and at this stage, my judgment is that, valued as a going concern, it would be trading slightly under value. In a strange way, Bill Ackman's exit is what tipped the scales for me, since it will give Valeant's management, if they are so inclined, the capacity to make the decisions that they may have been constrained from making before. In particular, if they recognize that this may be a clear case where the company is worth more as the sum of its liquidated parts than as a going concern, there is still a chance that I could reduce my losses on this investment. Note, though, that based on my numbers, I don't expect to make my original investment (which averages out to $21/share) back. I am not happy about that but sunk costs are sunk!

As I continue to hold Valeant, I am also aware that I might be committing one of investing's biggest sins, which is an aversion to admitting mistakes by selling losers. My discounted cash flow valuations may be an after-the-fact rationalizing of something that I don't want to do, i.e., sell a big loser. To counter this, I briefly considering selling the shares and rebuying them back immediately; that makes me admit my mistake and take my losses while restarting the investment process with a new buy, but the "wash sales" rule is an impediment to this cleansing exercise. The bottom line is that if I am holding on to Valeant, not for intrinsic value reasons (as I am trying to convince myself) but because I have an investing blind spot, I will be last one to know!

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Previous Posts on Valeant

1. Checkmate or Stalemate: Valeant's Fall from Investing Grace (November 2015)
2. Valeant: Information Vacuums, Management Credibility and Investment Value (April 2016)
3. Faith, Feedback and Fear: The Valeant Test (November 2016)

Spreadsheets

1. Valeant Valuation: March 2017

Faith, Feedback and Fear: Ready for the Valeant Test?

It is easier and more fun to write about your winners than your losers, but it is also far more important and valuable to revisit your losers, where the story has not played out the way you hoped it would. It is important because it is easy to lapse into denial and hold on to your losers too long, not only because you let hope override good sense but also because the act of selling is the ultimate admission that you made a mistake. It is valuable because you can learn from these mistakes, if you can set aside pride and preconceptions. So, it is with mixed feelings that I am returning to Valeant, a stock that I bought in May at $27, contending that it was worth $44, but where the market has clearly had other ideas. 

Valeant: Revisiting the Past

I first wrote about Valeant just over a year ago, when it was entering its dark phase, surrounded by scandals, management intrigue and operating problems. At the time, the stock had completed a very quick descent from market star to problem child, with its stock price (market cap) dropping from $180 on October 1, 2015 to $80 on November 6, 2015. While there were many in the value investing community, where it had been a long time favorite, who felt that the market had over reacted, my valuation of $77 left me just short of the market price of $80 at the time. Over the next few months, things went from bad to worse on almost every dimension. The management team disintegrated, with many of the top players leaving in disgrace, and the company held back on reporting its financials because it was having trouble getting its books in order, never a good sign for investors. Testimony by its top managers in front of congressional committee shredded its corporate character and the company faced legal challenges on multiple fronts. The market, not surprisingly, punished the stock as the company lurched from one crisis to another and the stock price dropped almost 75%:

In May 2016, I revisited the company, just after it hired a new CEO (Joseph Papa) and Bill Ackman, a long-time activist investor in the company, decided to take a more active role in the company. In revaluing the company, I noted that the missteps at the company had hamstrung it to the point that it had during the period of a year made the transition from Valeant the Star to Valeant the Dog. The value that I estimated for the company, viewed as such, was $43.56.

Download spreadsheet

In keeping with my theme that the value of a company always comes from an underlying story, it is worth being explicit about the story that I was telling in this valuation. In May 2016, I viewed Valeant as a mature pharmaceutical company that would not only never be able to go back to its “acquisitive” days but was likely to lose ground to other pharmaceutical companies with better R&D models. Consequently, in my valuation, I assumed low revenue growth and lower margins and a return on capital that would converge on the cost of capital over time. My decision in May 2016 was to buy Valeant at $27 because I felt that, notwithstanding the fog of missing information, management changes and legal sanctions, the company was a good buy. 

The Market Speaks

In the months since my buy in May 2015, there has been little to cheer about for Valeant investors. The stock had an extended swoon in late June, recovered somewhat in August, before continuing its descent in the last two months, with three possible explanations for the price performance. One is that the debt overhang, with $30 billion plus in debt due, making it the most highly levered company in the pharmaceutical business, creates market spasms each time worries about default resurface. In fact, every few weeks, another rumor surfaces of Valeant planning to sell a major chunk of itself (Bausch and Lomb, Salix) to remove the debt burden. The second is that the consolidation and cleaning up for past mistakes seems to be taking a lot longer than expected, with revenues stagnating and huge impairment charges pushing equity earnings into negative territory. The third is that the legal jeopardy that was triggered by the events of last year is showing no signs of abating, with the most recent news story about indictment of Valeant executive, Gary Tanner, and Philidor's Andrew Davenport  continuing the drip-drip of bad news on this front.

For most of the last few months, as the price dropped, I have been waiting for something more concrete to emerge, so that I could revalue the company. On November 8, Valeant filed its most recent earnings report for the third quarter, reporting that revenues were down more for the third quarter of 2016 and larger losses than expected. It accompanied the report with forward guidance that suggested continued stagnation in revenues and no quick profit recovery next year, leading to a sell-off in the stock, pushing the price down to just below $14 on November 9. While I the reports is definitely not good news, I must confess that I did not see much in that report that was game or story changing. To see why, take a look at the numbers contained in the most recent earnings report:

	2016, Q3	2015, Q3	Change	2016, Q1-3	2015, Q1-3	Change
Revenues	$2,480	$2,787	-11.02%	$7,271	$7,689	-5.44%
COGS	$658	$649	1.39%	$1,946	$1,855	4.91%
S,G &A	$661	$698	-5.30%	$2,145	$1,957	9.61%
R&D	$101	$102	-0.98%	$328	$239	37.24%
Amort & Impair, finite-lived intangible assets	$807	$679	18.85%	$2,389	$1,630	46.56%
Goodwill Impairment	$1,049	$-	NA	$1,049	$-	NA
Acquisiton Costs (all)	$67	$213	-63.93%	$131	$648	-65.06%
Operating Income	$(863)	$448	-292.63%	$(716)	$1,366	-152.42%
EBIT pre-acquisition costs	$(796)	$661	-220.42%	$(585)	$2,014	-129.05%
EBITDA	$1,060	$1,340	-20.90%	$2,853	$3,644	-21.71%
EBITDAR	$1,161	$1,442	-19.49%	$3,181	$3,883	-18.08%

It is true that the company is delivering lower revenues than the revenues that I had forecast for the company in May 2016 and it is also true that the company’s profit margins are dropping. However, and this may just be my confirmation bias speaking, as I look at the third quarter numbers, it seems like a significant portion the bad news reported for the quarter reflects repentance for past sins, not fresh transgressions. The company has had to respond to its “price gouger” reputation by showing restraint on further price increases (dampening revenue growth in its drug business) and the losses in the third quarter can be largely attributed to impairments of goodwill and assets acquired during the go-go days. In the table below, I break down the drop in operating income of $2.08 billion from the first 3 quarters of 2015 to the first 3 quarters of 2016 into it's constituent parts: 

	Effect on operating Income	% Effect
Declining Revenues	$(317)	15.27%
Change in Gross Margin	$(192)	9.24%
Change in SG&A	$(188)	9.05%
Change in R&D	$(89)	4.29%
Change in Acquisition Costs	$517	-24.89%
Change in Amortization (Assets + Goodwill)	$(1,808)	87.05%
Change in Operating Income, , First 3Q 2016 vs First 3Q 2015	$(2,077)	100.00%

The numbers suggest that almost 87% of the decline in operating income can be traced to amortization either of finite lived assets or goodwill, though there has been deterioration in the business model as manifested in the decline in sales and gross margins. It is for this reason that the effect this earnings report has had on my “Valeant as Dog” story is muted, largely because the story was not an uplifting one in the first place. My updated version of the story is that Valeant is not that different from my old one (of slow growth and lower margins) with tweaks for an upfront adjustment period where revenues are flat and margins worse than the past, as the company continues to slowly put its past behind it. The value per share that I get with this story is $32.50 and the picture is below:

Download spreadsheet

On November 8, 2016, with the stock price at about $15, it was the biggest loser in my portfolio but if I trust my own updated assessment of value of Valiant, it is now more undervalued (on a percent basis) than it was in May 2016. 

Faith and Feedback

In both my valuation and investments classes, I spend a significant amount of time talking about faith and feedback and how they affect investing.

1. Faith: As an investor, you are acting on faith when you invest, faith in your assessment of value and faith that the market price will move towards that value. If you have no faith in your value, you will find yourself constantly revisiting your valuation, if the market moves in the wrong direction (the one that you did not predict) and tweaking your numbers until your value converges on the price. If you have no faith in markets, you will not have the stomach to stay with your position if the market moves against you. 
2. Feedback: As an investor, you have to be open to feedback, i.e., accept that your story (and valuation) are wrong and that market movements in the wrong direction are a signal that you should be revisiting your valuation. 

I view my investing challenge as maintaining a balance between faith and feedback since too much of one at the expense of the other can be dangerous. Faith without feedback can lead to doubling down or tripling down on your initial investment bet, blind to both new information and your own oversights, and that righteous pathway can lead to investment hell. Feedback without faith will cause an endless loop where market price changes lead you to revisit and change your value and your holding period will be measured in days and weeks instead of months or years.  Stocks like Valeant are an acid test of my balancing act. There is a part of me that is telling me that it is time to listen to the market, take my losses and sell the stock. However, doing that would be a direct contradiction of my investment philosophy and I am not quite ready to abandon it yet. The second is to avoid all mention of the stock and hope that the market corrects on its own, but denial is neither faith nor feedback. The third is to accept the fact that I did underestimate how long it would take Valeant to put its past behind it and to revalue the company with my updated story and that is what I tried to do. That acceptance of feedback, though, has to be accompanied by an affirmation of faith; since it led me to buy the stock at $27, when my estimated value was $43 in May 2016, it should lead me to buy even more at $15, with my estimated value at $32.50. So, I doubled my Valeant holdings, well aware of the many dangers that I face: that the operating decline that you saw in the third quarter of 2016 will continue in the future years, that the debt load will become more painful if interest rates rise and that the recent indictments of executives will expose the firm to more legal jeopardy. If the essence of risk is best captured with the Chinese symbol for crisis, which is a combination of the symbols for danger and opportunity, Valeant would be a perfect illustration of how you cannot have one without the other!

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Attachments

1. Valeant - Valuation in November 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. 

Year	Common Equity	ROE	Expected 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: 

Year	Net Income	Risk-Adjusted Assets	Tier 1 Capital/ Risk Adjusted Assets	Tier 1 Capital	Change in Tier 1 Capital	FCFE = 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. 

Year	FCFE	Terminal Value	Cost of equity	Cumulative Cost of Equity	PV
1	$(11,663)		10.20%	1.1020	$(10,583.40)
2	$(3,658)		10.20%	1.2144	$(3,012.36)
3	$(1,576)		10.20%	1.3383	$(1,177.54)
4	$(133)		10.20%	1.4748	$(90.34)
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


Attachments

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

Mean Reversion: Gravitational Super Force or Dangerous Delusion?

In my last post on the danger of using  single market metrics to time markets, I made the case that though the Shiller CAPE was high, relative to history, it was not a sufficient condition to conclude that US equities were over valued. In the comments that followed, many disagreed. While some took issue with measurement questions, noting that I should have looked at ten-year correlations, not five and one-year numbers, others argued that this metric was never meant for market timing and that the real message was that the expected returns on stocks over the next decade are likely to be low. I was surprised at how few brought up what I think is the central question, which is the assumption that the CAPE or any other market metric will move back to historic norms. This unstated belief that things revert back to the way they used to be is both deeply set, and at the heart of much of value investing, especially of the contrarian stripe. Thus, when you buy low PE stocks and or sell a stock because it has a high PE, you are implicitly assuming that the PE ratios for both will converge on an industry or market average. I am just as prone to this practice as anyone else, when I do intrinsic valuation, when I assume that operating margins and costs of capital for companies tend to converge on industry norms. That said, I continue to worry about how many of my valuation mistakes occur because I don’t question my assumptions about mean reversion enough. So, you should view this post as an attempt to be honest with myself, though I will use CAPE data as an illustrative example of both the allure and the dangers of assuming mean reversion.

Mean Reversion: Basis and Push Back

The notion of mean reversion is widely held and deeply adhered to not just in many disciplines but in every day life. In sports, whether it be baseball, basketball, football or soccer, we use mean reversion to explain why hot (and cold) streaks end. In investments, it is an even stronger force explaining why funds and investors that fly high come back to earth and why strategies that deliver above-average returns are  unable to sustain that momentum.

In statistics, mean reversion is the term used to describe the phenomenon that if you get an extreme value (relative to the average) in a draw of a variable, the second draw from the same distribution is likely to be closer to the average. It was a British statistician, Francis Galton, who first made official note of this process when studying the height of children, noted that extreme characteristics on the part of parent (a really tall or short parent) were not passed on. Instead, he found that the heights reverted back to what he called a mediocre point, a value-laden word that he used to describe the average. In the process, he laid the foundations for linear regressions in statistics.

In markets and in investing, mean reversion has not only taken on a much bigger role but has arguably had a greater impact than in any other discipline. Thus, Jeremy Siegel's argument for why "stocks win in the long term" is based upon his observation that over a very long time period (more than 200 years), stocks have earned higher returns than other asset classes and that there is no 20-year time period in his history where stocks have not outperformed the competition. Before we embark on on examination of the big questions in mean reversion, let's start by laying out two different versions of mean reversion that co-exist in markets.

• In time series mean reversion, you assume that the value of a variable reverts back to a historical average. This, in a sense, is what you are using when looking at the CAPE today at 27.27 (in August 2016) and argue that stocks are over priced because the average CAPE between 1871 and 2016 is closer to 16.
• In cross sectional mean reversion, you assume that the value of a variable reverts back to a cross sectional average. This is the basis for concluding that an oil stock with a  PE ratio of 30 is over priced, because the average PE across oil stocks is closer to 15. 

At the risk of over generalization, much of market timing is built on time series mean reversion, whereas the bulk of stock selection is on the basis of cross sectional mean reversion. While both may draw their inspiration from the same intuition, they do make different underlying assumptions and may pose different dangers for investors.

The nature of markets, though, is that every point of view has a counter, and it should come as no surprise that just as there are a plethora of strategies built around mean reversion, there are almost as many built on the presumption that it will not happen, at least during a specified time horizon. Many momentum-based strategies, such as buying stocks with high relative strength (that have gone up the most over a recent time period) or have had the highest earnings growth in the last few years, are effectively strategies that are betting against mean reversion in the near term. While it is easy to be an absolutist on this issue, the irony is that not only can both sides be right, even though their beliefs seem fundamentally opposed, but worse, both sides can be and often are wrong.

Mean Reversion: The Questions

You can critique mean reversion at two levels. At the level at which it is usually done, it is more about measurement than about process, with arguments centered around both how to compute the mean and the timing and form of the reversion process. There is a fundamental and perhaps more significant critique of the very basis of mean reversion, which is based on structural changes in the process being analyzed.

The Measurement Critique

Let’s say that both you and I both believe in mean reversion. Will we respond to data in the same way and behave the same way? I don't think so and that is because there are layers of judgments that lie under the words “mean” and “reversion”, where we can disagree. 

• On the mean, the numbers that you arrive at can be different, depending upon the time period you look at (if it time series mean reversion) or the cross sectional sample (if it is a cross sectional mean reversion), and you can get very different values with the arithmetic average as opposed to the median. With cross sectional data, for instance, the oil company analysis may be altered depending on whether your sample is of all oil companies, just larger integrated oil companies or smaller, emerging market oil companies. For time series variations, consider the historical time series of CAPE and how different the "mean" looks depending on the time period used and how it was computed.
  
• On the reversion part, there can be differences in judgment as well. First, even if we both agree that there is mean reversion, we can disagree on how quickly it will happen. That has profound consequences for investing, because there may be a time horizon threshold at which we may not be to devise an investment strategy to take advantage of the reversion. Second, we can disagree over how the metric in question will adjust. To illustrate, assume that the mean reversion metric is CAPE and that we both agree that  the CAPE of 27 should drop to the historic norm of 16 over the next decade. This can be accomplished by a drop in stock prices (a market crash) or by a surge in earnings (if you can make an argument that earnings are depressed and are due for recovery). The implications for investing can be very different.

In summary, there is a lot more nuance to mean reversion than its strongest proponents let on. One reason that they try to make their case look stronger than it is may be because they are selling others on their investment thesis and hoping that if they can convince enough people to make it self fulfilling. The other, and perhaps more dangerous reason, is to convince themselves that they are right, as a precursor to action. 

The Fundamental Critique

The process of mean reversion is built on the presumption that the underlying distribution (whether it be a time series or cross sectional) is stationary and that while there may be big swings from year to year (or from company to company), the numbers revert back to a norm. That is the elephant in the room, the really big assumption, that drives all mean reversion and it is its weakest link. If there are structural changes that alter the underlying distribution, there is no quicker way to ruin that trusting in mean reversion. The types of structural changes that can cause distribution to go awry range the spectrum, and the following is a list, albeit not comprehensive, of why these changes in the context of mean reversion over time.

• The first is aging, with the argument easiest to make with individual companies and more difficult with entire markets. As companies move through the life cycle, you will generally see the numbers for the company reflect that aging, rather moving to historic norms. That is especially true for growth rates, with growth rates decreasing as a company scales up and becomes more mature, but it is also true of both other operating numbers (margins, costs of capital) as well as pricing metrics (price earnings ratios and EV multiples). While markets, composed of portfolios of companies, are less susceptible to aging, you could argue that aging equity markets (the US, Japan and Europe) will exhibit different characteristics than they did when were younger and more vibrant. 
• The second is technology and industry structure, shaking up both the product market structure and creating challenges for accountants. This is true clearly at the company level, as is the case with retailing, where Amazon's entry and subsequent growth has laid waste to historic norms for this sector, bringing down operating margins and changing reinvestment patterns. It is also true at the market level, where an increasing proportion of the equity market (say, the S&P 500) are service and technology stocks and the accounting for expenses in these sectors (with many capital expenses being treated as operating expenses) creating questions about whether the E in the PE for the S&P 500 is even comparable over time.
• The third is changes in consumer and investor preferences, with the first affecting the numbers in product markets and the latter in financial markets. For instance, there is an argument to be made that the surge in index funds has altered how stocks are priced today, as opposed to two or three decades ago.

In the context of CAPE, again, and using Shiller's entire database, which goes back to 1871, let's take a quick look at how much both the US economy has grown and changed since 1871 and how those changes have affected the composition of US stocks.

In 1871, coming out of the civil war, the US was more emerging than developed market, with the growth and risk that goes with that characterization. In 1900, the US equity market had become the largest in the world, but 63% of its value came from railroad stocks, reflecting both their importance to the US economy then and their need for equity capital. For most of the next few decades, the US continued on its path as a growth market and economy, though the growth trend was brought to a stop by the great depression.  The Second World War firmly established the US as the center of the global economy and the period between 1945 and 2000 represents the golden age of mean reversion, a period where at least in the US, mean reversion worked like a charm not just across stocks but across time. It is worth noting that many of the now-accepted standard practices in both corporate finance and valuation, from using historical risk premiums for stocks to attaching premiums for expected returns to small-cap stocks to believing that value stocks beat growth stocks (with low PBV or low PE as a proxy for value) came from researchers poring over this abnormally mean-reverting financial history. I trace my awakening to the dangers of mean reversion to the 2008 crisis but I believe that the signs of structural change were around me for at least a decade prior. After all, the shift from a US-centric global economy to one that was more broadly based started occurring in the 1970s and continued, with fits and bounds, in the decades after. Similarly, the US dollar's reign as the global currency was challenged by the introduction of the Euro in 1999 and put under further strain by the growth in emerging market currencies.

So, how did 2008 change my thinking about markets, investing and valuation? First, globalization is here to stay and while it has brought pluses, it has already brought some minuses. As I noted in my post on country risk, no investor or company can afford to stay localized any more, since not only do market crisis in one country quickly become global epidemics, but a company that depends on just its domestic market for operations (revenues and production) is now more the exception than the rule. Second, the fact that financial service firms were at the center of the crisis, has had long term consequences. Not only has it led to a loss of faith in banks as well-regulated entities, run by sensible (and risk averse) people, but it has increased the role of central bankers in economies, with perverse consequences. In their zeal to be saviors of the economy, central bankers (in my view) have contributed to an environment of low economic growth and higher risk premiums. Third, the low economic growth and low inflation has resulted in interest rates lower than they have been historically in most currencies and negative interest rates in some. I know that there are many who believe that I am over reacting and that it only a question of time before we revert back to more normal interest rates, higher economic growth and typical inflation but I am not convinced. 

From Statistical Significance to Investment Return Payoff

The standard approach to showing mean reversion is start with historical data and establish mean reversion with statistics. I will start with that basis, again using CAPE as my illustrative example, but will then build on it to show why, even if you believe in mean reversion and you base it on sound statistics, it is so difficult to convert statistical significance into market-beating returns.

The statistics

If you were looking at a data series, how would you go about showing mean reversion? There are three simple statistical devices that you can draw. The first is graphical, a scatter plot of the data that shows the mean reversion over time. In the context of CAPE, for instance, this is the graph that you saw in my last post:

Historical data on Shiller CAPE

The problem with this plot is that it is weak evidence for investing, since you don't make money from buying or selling PE but from buying and selling stocks. In fact, even in this plot, you can see that the CAPE case that stocks are over priced is weakened because I have used a 25-year median for comparison. A stronger graphical backing for mean reversion would then graph stock returns in subsequent time periods as  a function of the CAPE today, with a higher CAPE (relative to history) translating into lower returns in a future period. 

Looking at this data, at least, the evidence seems strong that a high CAPE today goes with lower stock returns in future periods, with the mean reversion becoming stronger for longer time periods.

The relationship between the market timing metric and returns can be quantified in one of two ways. You could compute the correlation between the metric and returns, with a more negative correlation indicating stronger mean reversion. Updating my CAPE/ returns correlation metric, with 10-year returns added to the mix, you can see again the basis for the market timing argument:

You an build on these correlations and run regressions (linear or otherwise) where you regress returns in future periods against the value of the metric today. The results of those regressions, with CAPE as the market metric, are summarized below:

What does this mean? If you buy into mean reversion and can live with the noise or error in your estimate (captured in the R-squared), these regressions back up the correlation findings, insofar as your CAPE-based predictions get more precise for longer time period returns. In fact, if you are one of those who lives and dies by statistics, using today's CAPE of 27.27 in this regression will yield a predicted annualized return of 4.30% on stocks for the next 10 years:

Expected annualized return in next 10 years = 16.24% - 0.0044 (27.27) = 4.30%

Scary, right? But before you over react, first recognize that this prediction comes with a standard error and range and second, please read on.

The Investment Action

If you have sat through a statistics class, you have probably heard the oft-repeated caution that "correlation is not causation", a good warning if you are a researcher trying to explain a phenomenon but not particularly relevant, if you are an investor. After all, if you can consistently make a lot of money from a strategy, do you really need to know why? The biggest challenge in investing is whether you can convert statistical significance ( a high correlation or a regression with impressive predictive power) into investment strategy. It is at this level that market timing metrics run into trouble, and using CAPE again, here are the two ways in which you can use the results from the data to change the way you invest.

If you are willing to buy into the notion that the structural changes in the economy and markets have not changed the historical mean reversion tendencies in the CAPE, the most benign and defensible use of the data is to reset expectations. In other words, if you are an investor in stocks today, you should expect to make lower returns for the next 10 years than you have historically. This has consequences for how much investors should save for future retirement or how much states should set aside to cover future contractual obligations, with both set asides increasing because your expected returns are lower. 

It is when you decide to use the CAPE findings to do market timing that the tests become more arduous and difficult to meet. To understand what this means, let's go back to the basic asset allocation decision that all investment begins with. Given your risk aversion (a function of both your psychological make-up and the environment you are in) and liquidity needs (a function of your age, wealth and dependents), there is a certain mix of stocks, bonds and cash that is right for you. With market timing, you will alter this mix to reflect your views on desirable (or under priced) markets and undesirable ones. Thus, your natural mix is 60% stocks, 30% bonds and 10% cash, and you believe (using whatever market timing metric you choose) that stocks are over priced, you would lower your allocation to stocks and increase your allocation to either bonds or cash. You could further refine this market timing algorithm for domestic stocks versus foreign stocks or bring in other asset classes such as collectibles and real estate. The test of a market timing strategy therefore requires more structure than the statistical analysis of checking for correlation or regression:

1. Timing threshold: If you decide that you will time markets using a metric, you have to follow through with specifics. For instance, with CAPE as your market metric, and a high (low) CAPE being used as an indicator of an over valued (under valued) market, you have to indicate the trigger  that will initiate action. In other words, does the CAPE have to be 10% higher, 25% higher or 50% higher than the historic average for you to start moving money out of stocks?
2. Asset class alternatives: If you decide to move money out of stocks, you have to also specify where the money will go and you have four choices. 
3. Holding period: You will have to specify how long you plan to stay with the "market timed" allocation mix, with the answers ranging from a pre-specified time horizon (1 year, 2 years or 5 years) to until the market timing metric returns to safe territory. 
4. Allocation Constraints (if any): The allocation that you have for an asset class can be floored at zero, if you are a long only investor, but can be negative, if you are willing to go short. The cap on what you can allocate to an asset class is 100%, if you cannot or choose not to borrow money, but can be greater than 100%, if you can. 

Put simply, the lower your threshold, the more alternatives you have to investing in stocks, the shorter your holding period and the fewer your constraints, the more active you are as a market timer. It is in this context that I tried out different market timing strategies built around CAPE. The table below lists out the returns from a buy and hold strategy with a fixed mix of stocks, bonds and bills (60%, 30% and 10%) and contrasts it with returns over the same period from using a CAPE timing strategy of reducing the equity allocation to 40% if the CAPE is 25% higher than a 50-year median value and increasing the equity allocation to 80% if the CAPE is 25% lower than a 50-year median value. I report the numbers for the entire time period 1917-2016 and break it down into two fifty-year time periods (1917-1966, 1967-2016):

Download market timing spreadsheet

With this mix of timing choices (50-year median, 25% threshold and the given changes to equity allocation), the Shiller CAPE outperforms the buy and hold strategy for the 1917-2016 time period  but  under performs in the last fifty year time period. I know that your timing choices can be very different from mine and I have created options in this spreadsheet to let you change the choices to reflect your preferences to see if you can deliver better market timing results using CAPE. I did try a few variants and here is what I found.

1. Time Period: With every variation of timing that I tried, the CAPE delivers a positive market timing payoff in the first half of the entire time period (from 1917 to 1966) and a negative one in the second half (1967-2016). In fact, I could not find a combination of timing devices that delivered positive payoff in the second time period.
2. Choice of median: Using the lifetime median delivers better results during the "good" period (1917-1966) but worse results during the "bad" period (1967-2016). Using a shorter time periods for the median reduces the outperformance in the first half of the analysis period but improves it in the second half.
3. Buy and Sell: The CAPE's timing payoff is greater when it is used as a buying metric than as a selling metric. In fact, you make a positive payoff from using a low CAPE as a buying indicator over the entire period but using it is a signal of over priced markets costs you money in both time period. 
4. Market Timing magnitude: Increasing the degree to which you tilt towards or away from stocks, in reaction to the CAPE, just magnifies the return difference, positive or negative. Thus, in the first half of the century (1917-1966), changing your equity exposure more increases the payoff to market timing. In the second half, it makes the negative payoff worse.

In many ways, this testing is tilted in favor of finding that the Shiller CAPE works. First, while I have been careful not to use ex-post data, I have acted as if I know what the earnings for the year will be, at the end of each year, when my market timing decision is made. In reality, on December 31, 2012, I would know only the earnings for the first three quarters of 2012 and not quite the full year. Second, I am ignoring the transactions costs and taxes due from shifting large amounts in and out of stocks in my timing years. Those will represent a significant drain on my returns as an investor. Finally, I am assuming that there have been no structural shifts large enough to cause the mean reversion to break down. In spite of all of this, I am hard pressed to explain why we are so swayed by arguments based on this metric.

Conclusion

These are dangerous times for those who believe in mean reversion, for two reasons. The first is that our access to historical data is getting broader and deeper, with mixed consequences. Having more data allows us to find out more about the underlying fundamentals but since that data goes back so far, much of what we find no longer has relevance. The second is that doing statistical analysis no longer requires either homework or effort, with tools at our fingertips and statistical results are only a click away. Both in academia and in practice, I see more and more use of statistical significance as proof that you can beat markets and my reason devising and testing out market timing strategies with CAPE were not meant to be an assault on CAPE but more a cautionary note that statistical correlation is not cash in the bank. This may also explain why there are so many ways to beat the market, on paper, and so few seem to be able to deliver those magical excess returns, in practice. 

YouTube Video

Datasets

1. CAPE: 1881-2016 (Shiller Data)
2. Stock, Bond and Bill Returns (1881-2016)
3. Market Timing Spreadsheet