Week Ending 3/20/2020: Watching Losses Mount

A day by day account of a tough week.

3/16/2019 Monday

Stock down 12% today!? Funny how I’m so desensitized to 5-8% moves now.

Any random stock gets hit 15% today.

I have several down 20%+ (e.g. SQ, STOR, FNF).

Square's meltdown is entirely expected, I was just too pigheaded to sell before their upcoming investor day.

STOR - the early hits had some elements of reflexivity unwind (this is growth by acquisition after all). But the new hits are due to worries about tenants renegotiating rent deferral or even rent holidays. My view is that's ok, STOR has enough liquidity to survive and thing will be back to normal in an year or so.

FNF was completely shot and I don’t quite get it.

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I suppose this is the beginning of a new, prolonged bear market, under which stocks can be down 90% before it recovers.

The past few years I've WANTED a recession. I figured I hold more liquidity than most and can survive and take advantage of the situation. Now that the crisis is in front of me, the mental stress is almost unbearable.

I'm actually fairly calm during the trading hours. The hard part is after market closes and I go through my portfolio and count the losses. That's when it hits home.

I agonize over my own inaction. Even though I'm technically executing my plan. I upgraded my exposure in January and Feb with the idea that should a 2008 style crisis hits I will keep my stocks and ride out the losses.

Well, that crisis is here. I'm executing my plan. I'm just not sure that is the correct strategy...

Will I end up panic sell at the bottom? To fight that instinct I got a list of stocks and the prices I want to buy them at; and I will force myself into buying when those prices hit. Even if it's tiny positions.

Things are starting to looks worse than 2008 - 1929 / Great Depression is now the comp.


3/17/2019 Tuesday

Stock went up 6% today after Mnuchin and Trump talked about helicopter money.

I added 3% to my equity exposure today. 1% each to STOR/FAF(to replace the FNF I sold earlier)/BRKS. They are cheap enough and solid enough that I'm wiling to sit long term and take short term pain.

I added a little to SQ on whim after the Mnuchin speech, but will have to offload that addition tmw - here's why.

After market closes I had time to reflect. Directionally, the helicopter money approach is correct but I came to the conclusion it just be enough. The local restaurant might pay $15k a month in rent. How is $1000 going to help them stay alive when revenue goes to $0?

Some back of envelop calculation: US has $20trn GDP. Let's say 1/3 of that shuts down. And we shut down for 2 months. You got 20/3/12*2=1.1111. That’s $1 Trillion hit to GDP. But GDP doesn’t count intermediate goods, so the real amount that needs to be bailed out is probably a multiple of that.

Ideally, the government says "let's freeze time, everyone stay home, business keep their employees, we'll pay your expense". But that’s going to be an astronomical number that makes US debt/GDP go to unreasonable amounts and USD will totally lose credibility.

All we can hope for is the shutdowns flatten out the disease curve, buy us time so healthcare system doesn’t get over whelmed. Some business will go bankrupt but hopefully you save enough of them that we don’t get a permanent damage to economy that we cant bounce back from.

There is some offset here. Big companies like Facebook are already reaching out to small businesses and employees, in the form of cash grants and product credits. So maybe everyone shares some pain but no one goes under, then we bounce back?


3/18/2020 Wednesday

Another wild day. S&P down more than 5% today. Frankly, I expected worse. Stock futures were limit down the night before so I knew it was going to be ugly.

It now looks like teh fiscal package wont' be enough, and in any case it hasn't passed yet.

The situation deteriorates every minute.

Stock went down 9-10% ..(this is truly looking like 1929), before clawing back to "only" down 5%ish.

My buy limit order for TTD hit at $153 and so I added a little there. But I'm mentally ready for this thing to be down 80% from peak. That would be below <$60.

I don't know when the market will bottom, but I don't want to reduce on the way down and not have enough exposure when it roars back (and given the speed of the decline, its very possible the market recovery will be just as violent)..

So the plan is add on the way down, however incrementally.

TTD, SQ, UBER. I have small positions in these, all are potential 10 baggers if I can accumulate in the right price. Hopefully by the time market bottoms I have a decent position in each of these (and other oligopolies in structural growth markets with strong moats). Then maybe add on the way up?

It's way early to talk about recovery, but I can dream right?


3/19/2020 Thursday

A relatively calm day in the market. Markets went up but this is a very weak looking bounce.

Some of the big shorts names like Hempton, Cohodes came out yesterday and say they're no longer net short. Ackman talked about buying BX.

Yesterday, I talked about accumulating on the way down. As if to demonstrate the rightness of that logic, Uber was up 37% when I checked. Company says 80% of cost is variable, so they will be able to cut cost, survive and come out stronger.

Natera (NTRA, which I don't have) was also up about 40% today. Any glimmer of hope does wonders for beaten down stocks.

The market heat map (below) shows rotation away from defensive/yield names. the market didn't move up too much, so apparently there's no inflow to funds but managers are positioning for a risk-on rally? If so, they risk getting wipsawed and their selling will exacerbate the downward move. This can end in tears.

It's pretty hard to ignore the market, focus and do fundamental research. But i will try to do that today.

Trades

I cut some DLR as it breached MA50. I also sold EQIX. These are expensive stock that have held up but are liable to get hit. EQIX for example has <2% div yield. That makes the valuation dependent on growth, and that means acquisition - so reflexivity unwinds as stock prices go down.


3/20/2020 Friday

Spent time looking at preferred stocks today. There's a massive dislocation in the credit market. Credit spread have blown out and a bunch of preferreds are now trading at discounts to par.

It's tempting to look at Yield to Call (in some cases showing 30-40% upside) but that is not right for preferred trading at discount:

1) companies have no reason to call securities trading at discount.

2) the logic of yield to call is somewhat circular: to get the YTC you need the prefs to get called. But a company will call only when prefs trade at premium, which happens only when market yield comes down to below the preferred coupon.

So the bottom line is to look at current yield for preferred trading at discount, and compare that to the coupon to see how likely you are to get called at par.

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What an exhausting week. This is supposedly the worst week in the market since 1929.

I guess we are all Bayesians updating probabilities as facts emerge. Each day the economic situation look dramatically worse than before, so in retrospect it's not surprising that market took such a drastic downturn.

Some of us see the facts earlier or update probabilities earlier. I am unfortunately one of the slower ones.

Week of 3/13/2020 - Market Melt Down. A New Era?

3/12/2020

The S&P index dropped 9.5%. The market was almost 30% off its peak.

The decade long bull market is officially over.

Throughout 2019 I consciously high graded my portfolio, away from the speculative micro/nanocaps into large caps. At the same time I capped my equity exposure to 80% through most of 2019.

I came into mid-Feb with equity exposure about 65-70% of my portfolio. Then the market hit. Now I'm roughly 60% equities - I sold very marginally, the reduction is mostly because stocks went down so much that they became a smaller percentage of the mix.

What now? I've sold most of what I wanted to sell. I still have some high growth, high multiple names that are liable to take a 70% drawdown, but I've cut them down to small size and readied myself to ride out the pain. (TTD, SQ, UBER).

I even added - very marginally - to companies that I think will not only survive a recession, but will come out stronger by consolidating weaker competitors.  Examples are GOOGL, ILMN, DIS.

So, What now?

It certainly looks like a recession is unavoidable. Indeed the U.S. faces a tough trade-off  - shutting down everything to protect public health means taking economic hits.

So why have I not cut exposure to 0 or even go short?

Some of this is almost Pavlovian - every time I cut in the past 10 years stock roar back higher. It got even more absurd in the Trump era - as soon as stock goes down 10% there's a Fed cut coming.

Shorts have lost every single time because of policy responses.

So what's the normalized valuation going forward? Any low growth company that's not totally cyclical can probably fetch 20x PE. As policy response grows stronger, I wouldn't be surprised if that number goes to 25x (and with fake earning add backs too as in stock based comp).

So I'm holding, under the assumption that the economy may enter a recession, but comes back in 3-5 years - with even more system leverage.

Why The Economy Might Not Come Back

What could go wrong is if the economy just don't come back. Maybe at some point we just can't borrow our way out of a recession anymore?

The trigger could be this reflexive intersection between markets and politics - as markets go down, the chance of Trump losing re-election increases. Imagine Biden wins in November and Democrats take congress, they will likely roll back the Trump tax cuts. Immediate hit to corporate earnings!

Government is already cracking down on big tech. You layer on more regulation and taxes...

Then we can look forward to a decade of stocks going nowhere.

For now though I'm still holding to my 60% equity exposure. I may regret it one day.


3/13/2020

Stock was going nowhere until the last 30 minutes of trading. Trump spoke in a press conference, and talked about telehealth (TDOC stock went flying as he speaks). Then he brought up Google (GOOGL goes up), then Thermo Fisher, then a steady stream of CEOs.

Then he talked about waiving student loan interest, and buying oil for SPR.

Stock went on a rampage toward the close. It was hilarious! A master class by the best stock pumping president ever!

It's as if Thursday never happend.

This is why I'm afraid of shorting stuff.

Experiment

I'm going to do an experiment. 

I got a list of companies from $1bn to $10bn market cap, growing revenue >20% a year with decent gross margins (>20%). The objective is to look for stocks that has potential to go up 3x or greater within that universe.

I ran a screen from Fidelity. The result is about 185 names and I will commit to knowing each of them over the next 2 months. So going over 3-5 companies a day would do.

This should be very feasible. I probably know some of these companies already. The challenge is to go through them with a fresh set of eyes and abandon any preconceived notion, ("Wayfair?!  that's a no!"), and really try to think big about what the upsides are for each.

A year from now I'll see how many home runs I missed.

Maybe there will be 0 home runs out of these 185 companies. That's possible too. But I'll try to get as many as I can.

I would love it if someone wants to join me in this effort. If you would like to help, please reach out in the comments or DM me on Twitter.  Thanks!

Changes I Hope to Make to This Blog

Happy New Years! There are some changes to the blog I hope to make this year. They are based on why I write and what I want to get out it.


Why I Write

I had a few objectives in mind when I started writing this blog a few years ago:

• Keep track of my own ideas and evolution as an investor.
• Facilitate discussion to get feedback and sharpen investment ideas.
• Discipline. I’m a full time, individual investor. While that freedom is great, I want to have some sort of weekly deliverable to impose discipline and focus on myself. The blog is that "deliverable".

How did that work out the past few years?

This blog is only ok as a place to track my own ideas. I'd write maybe one post for every 30 ideas I explore. That’s because most ideas were filtered out pretty quickly as not worth my time. And increasingly I'm writing posts that have no definite buy or sell implications.

The "facilitating discussion" objective completely failed. I have not gained any sort of consistent readership, and that means no feedbacks for my posts. Instead I've discovered Twitter, which has served that purpose wonderfully.

The “discipline” objective sort of worked. Although I’m not posting on a weekly basis as originally intended. One reason is as mentioned above- most ideas I explore are not worth a deep dive. In any case, much of investment research revolves creating a hypothesis and disproving them. I’m not sure presenting all these failed hypothesis makes for good blog content. The other reason is I’m not a good writer, and turning my existing notes (primarily in bullet points) into paragraph format takes a lot of time. That’s time detracted from my research and investment activities.


Changes

I think a few changes can address these issues.

First, aim for smaller but more frequent posts. 

I’m thinking like avc.com where a post can just be a couple hundred words and a simple observation. So the blog would be more like a journal where I just record whatever I learned, instead of feeling like I have to write a complete buy/sell thesis on a specific stock.

I'm already posting on Twitter just about every day, so a lot of blog posts this will be elaborations of those same tweets.

Second, I want to try out new formats, particularly videos. I keep a ton of notes during research, but they are in bullet points and it's time consuming to turn them into paragraph/blog format. It may actually be easier to post a video where I show a couple powerpoint slides and just talk through them.

Comments are welcome!

How Small Beats Large

How does a smaller company beat a large company with seemingly unlimited resources?

This is a problem I have been struggling with, and here are some thoughts (basically a synthesis of Porter and Christensen).

The problem has to be looked at from both sides, let's call them SmallCo and BigCo. The SmallCo's strengths alone are not going to be enough, nor the BigCo's weaknesses. It's only when the former's strengths match the latter's weaknesses that you have a David beats Goliath situation.

So let's look at it from both sides, starting with BigCo.

Just because a company has the resources to fight and win on any given single front, does not mean it can do so on all fronts, simultaneously. At some point every empire overextends itself. Where's the weak link?

A large company can have weak points where it lacks a) willingness/motivation, or b) ability to compete.

• Lacking willingness/motivation to compete. Perhaps because
• a) under the radar situation. The market in question is unattractive at the surface, or too small to move the needle for BigCo. 
• b) requires trade-offs. Examples would be if the market takes away resource from BigCo's favored customers, doesn’t match corporate value, or leads to cannibalization of opportunities. In his book "Seeing What's Next", Clay Christensen cited example of a firm that counts on post sale service agreement not being interested in an off-the-shelf /self-service product.
• Lacking ability.
• Perhaps because BigCo's activities and processes are not tailored to the value proposition offered by SmallCo.
• BigCo may have difficulty replicating SmallCo's value chain.

Moving on SmallCo's side. How does SmallCo take advantage of BigCo's weaknesses while avoiding its strengths?  

• Distinct customer segment and value proposition that does not match BigCo's. 
• SmallCo would target over-served customers, under-served customers, non-customers (creating new market)
• Tailored value chain supporting that value proposition. The value chain should show 1) uniqueness, 2) internal fit, 3) independence from BigCo.
• Uniqueness. It has to be different from BigCo's. Otherwise you will just be overwhelmed by brute force.
• Internal Fit (interdependency). The value chain should fit together in a way that’s hard to replicate. Ideally the parts are interdependent on each other. This way your competitive moat compounds and is hard to replicate.
• Independence. Separate value chain. If parts of the value chain overlap, then SmallCo could be forced to play by BigCo's rules.

Basically if your David, make sure you can afford to NOT play by Goliath's rules.

A Short Example with Elastic N.V and Chewy

These are two companies that compete with Amazon in two completely different industries. The differences provide them different strengths and weaknesses relative to Amazon.

Elastic ("ESTC"), which I have written about here, provides search functionalities that Amazon effectively copied. Chewy ("CHWY", as discussed here) is an online pet food/supplies provider. 

Which has a better chance against Amazon?

Amazon's Motivations

I would say Amazon is much more motivated to go after Elastic's search market, which competes with Amazon's AWS segment. This segment of Amazon not only provides more profitability than its e-commerce segment, but it is also growing much faster. A quick look at Amazon's earning releases shows tremendous focus on developing AWS's capabilities. Overall, Elastic's search/indexing market looks strategic to Amazon.

On the other hand, pet e-commerce is seen as a fairly steady, slower growth market. Pets are hardly ever mentioned in Amazon's earning calls. 

Verdict: Amazon is much more motivated to attack Elastic than Chewy.

SmallCo's Value Chain

Chewy has its own distribution facilities, call center, and service reps. These fit together in a way that reinforces Chewy's niche strategy (as discussed here). In terms of pet products, its suppliers does overlap with that of Amazon's, and that could be a problem.

Elastic though, actually deploys its hosted service on AWS! Talk about NOT having an independent value chain! Elastic belated realized Amazon meant harm and started diversifying to Microsoft Azure in addition to Google (GCP), but the damage has been done.

Verdict: Chewy's has a more distinct value chain from Amazon.

We can go further, but this is enough to show that Chewy will have much stronger defense against Amazon's invasion.

What Makes a Winner-Take-All Game

What are the industry contexts that leads to a winner-take-all game? Are there industry properties that naturally encourages consolidation and oligopolies? Network effect is the first that comes to mind. But surely that can’t be the only one? I have been struggling with this question.

Then I realized - invert. The question is really “what makes an industry fragmented?” There’s literally a whole chapter in Michael Porter’s “competitive strategy” that answers this question.

Porter’s Causes of Fragmentation

Here’s Porter’s list of causes for fragmentation:

• Low entry barrier
• Absence of economies of scale or experience curve
• High transportation cost
• High inventory cost or erratic sales fluctuations
• So scale is less of an advantage because your plants can’t operate production continuously. Scale may and down
• No advantages of size in dealing with buyers or suppliers
• Perhaps because buyers or suppliers are even bigger
• Dis-economies of scale in some important aspects
• Rapid product/style changes
• Low overhead important
• Diverse product line that requires customization
• Heavy creative content
• Close local control
• Personal services important
• Local image and local contacts are important
• Diverse market needs
• High product differentiation, particularly if based on image
• Exit barriers. This reinforces low entry barrier, as too many competitors can come into the industry and not exit.
• Local regulation
• Government prohibition or concentration
• Newness. This bears a lengthier discussion. If fragmentation is caused by newness, then it may be a temporary condition. The industry may actually be ripe for consolidation.

Simplified List

We can consolidate this list into a few big buckets: 1) low entry barrier (a pre-requisite to be combined with other attributes according Porter), 2) no advantage to size, 3) diverse buyer segments/needs, and 4) distribution friction (high transport cost, local regulation). Of course, regulation is an ever present force.

Invert back. The reverse of the above properties enables winner-take-all dynamics: 1) high entry barrier/low exit barriers, 2) big advantages to size, 3) homogeneous buyer segments, and 4) low distribution friction.

It’s the “advantage to size” that made me say “duh ! Why didn’t I think of that?” Of course there has to be advantages to size! Otherwise what’s the point of getting bigger? The two most prominent types are:

• Network effect: Better value proposition for the customer as you add nodes to the network
• Economy of scale: Unit cost declines as volume increases.

As a firm gets bigger, the former increases customer benefits (“B”) while the latter decrease cost of production (“C”). Both creates a widening gap between B minus C that leads to increasing returns on capital. 

Ideally there’s a positive feedback loop of increasing return to scale: a company grows in size, which gives it some competitive advantages over rivals, this allows the company to gain more market share, and the increased size yields even more competitive advantages. This feedback loop continues as long as the advantage to size overwhelms any advantages to smallness. This is as opposed to the reverse dynamic where a firm’s growth gets constrained by dis-economy of scale (negative feedback loop).

Porter also talked about how to overcome fragmentation and achieve consolidation. His approaches mirror the 4 buckets I gave, with emphasis on increasing scale and using standardization to overcome diverse market needs.

Growth Industries

The last point in Porter's list is "newness". Where the industry is in its life cycle also matters. Winner-take-all games are more likely to happen in fast growing industries facing disruptive innovation. This is because the industry has to create a whole new value chain, and that value chain needs a leader. Ideally the leader pushes forward with standardization schemes, which helps 1) various parts of the chain to interface with each other, 2) customer adoption.


How About Switching Cost and Differentiation?

That’s all great, but how about switching cost and differentiation?

Remember, the above are industry properties that encourage winner-take-all games. They apply to all companies in the industry. But I think switching cost and differentiation are best discussed in terms of how a specific firm can become that “winner”.

Differentiation is obviously a firm specific factor, while switching cost can be both industry-wide and firm specific.

In the industry context, switching cost appears under multiple categories. It is cited as a barrier to entry by Porter and is related to network effect (which I categorize as a form of “advantage to scale”).

Ultimately though, a customer switching from Firm A to Firm B is good for one and bad for another. In this sense the discussion of switching cost requires a company specific perspective. Switching costs can also vary according to company strategy. For example one can increase stickiness by having multiple touch points with its customers.

Naturally, the next question is “how does a company win in a winner-take-all-game”. I’m still thinking through that, so any inputs/comments would be appreciated. Thanks!

Thoughts On Sales and Marketing Effectiveness and Return on Capital

The best companies in the world are those that can invest large amounts at high returns on capital.

ROIC and RONIC (Return on Invested Capital, and Return on New Invested Capital) both use measures of "invested capital", where "capital" refers to capital expenditure and to a lesser extent working capital. (footnote 1)

In new economy industries though, and software in particular, “investments” take not the form of “capex”, but more often sales and marketing expenses to build up a customer base that will then bring recurring revenues. Salesforce.com, for example, persistently “invests” 40%+ of revenue on sales and marketing. Okta, another cloud native, spends (or “invest”?) 50-70% of revenue on sales and marketing. In contrast, traditional "capex" requirements for these companies can be relatively little.

So thinking about returns on capital for these companies is essentially thinking about sales and marketing ROI.

One Way to Measure

This is the unspoken premise behind Theta Equity’s post on Slack. A key component of that paper is measuring returns on sales and marketing with the following procedures (a very high level simplification here):

Sales and marketing ROI = Post Acquisition Value (PAV) divided by Customer Acquisition Cost (CAC)

• PAV is a function of 1) retention, 2) revenue dynamics, and 3) variable margin. First you work out the revenue curve for each acquired customer, then assume some 1) cost of service, R&D, and G&A to get a variable margins curve per customer. Then you discount that at the weighted average cost of capital (WACC) to arrive at PAV.
• For CAC, we can simply take sales/marketing expense and divide that by number of customers.

This is really great work. However, data about customer counts and cohorts are often not available, so here’s my even simpler way to not so much quantify, but think about sales/marketing effectiveness.

Simple Way to Just Think about Sales & Marketing ROI

I  basically compare sales and marketing expense as a percentage of revenue against the revenue growth rate achieved. Then I subjectively judge the recurring nature of that new revenue gained, and conjure up a ball park incremental margin.

I’ll go straight to a hypothetical example. If you spend 50% of this year’s revenue on sales & marketing, and revenue next year only grows 30%, is this a good “investment”?

Of course, the answer depends on lifetime value of that customer. In this example, you start with $100mm of revenue in year 0, and spending $50mm of that on sales and marketing gets you $130mm in revenue next year. This is $30 of incremental revenue for the $50mm sales and marketing “investment”. Now consider the two scenarios:

• A: Assume this new customer give you 3 years of revenue stream, which has 40% incremental EBIT margin (excluding sales and marketing cost).
• Then you would have $30 * 3 * 40%= $36mm of EBIT contribution (again ex sales/marketing cost)
• So you're spending $50mm to get $36mm back. Even without time value discounting, we can say this is no good.

• B: How if that customer life run 10 years, instead of 3 years?
• Then you’re getting $30 * 10 * 40% = $120mm. You spend $50mm to get $120mm (albeit over 10 years). This is much better! 

The income statements give us sales/marketing cost in year 0, as well as the incremental revenue in year 1. So what we have left to figure out is 1) average duration of customer lifetime, 2) margin contribution (ex sales/marketing costs).

There are ways to get ballpark estimates. If the company says customer attrition rate is 10%, you may say customer life time is roughly 1/10% = 10 years. To get margin contribution, you can use data from comparable companies that are more mature.

But still, it would be unwise to simply take empirical data and assume they stay the same. If in the past customer lifetime is 10 years, would you really be comfortable that the new product launched this year will also have 10 years life? The competitive landscape would surely have completely changed during a decade, particularly in the fast changing world of technology.

This is where quantitative data hits their limitations. Your analysis would now shift to focus on qualitative considerations like competitive landscape, market positioning, switching cost, network effects, and so on.

Footnote 1:
Traditional ROIC calculation implies a clean delineation of “capex” and “opex”. These are all just accounting identities though.

In the real world, what matters is cash in and cash out. You incur cash outflows for say 3 years, and expect to get cash inflow for say the next 7 years or even perpetuity. The cash outflow part we call “investment”, the cash inflows parts we call “returns on capital”. In the old ways “investment” is mostly some manufacturing facilities (what counts as capex), but in the broader sense this “investment” could also be a software intellectual properties, brands, customer relationships, or whatever that generates the cash inflows later (“returns" on capital).

What About Those Recessions? (From STOR's 4Q18 Call)

I bought STORE Capital back in mid-2017, right after news came out that Berkshire/Ted Weschler bought it. I remember reading the news at 10pm that night and got so excited that I jumped out of bed, stayed up all night researching, just in time to put in a buy order the next morning.

Since then STOR has provided good returns. More than that, I learned quite a bit about the real estate business by following a good management team.

The 4Q18 earning call was educational. You know one of these moments of mental clarity, when some one says something that (you thought) you knew all along, yet a light bulb just goes off in your head? It's one of those.

I had been thinking about cycles quite a bit, and STOR's CEO Chris Volk says this:

"So the first thing I would talk about is cycle, the notion of cycle, and this gets - a lot of analysts focus on the expansion cycle that this economy has been in for a long period of time and...somehow we must be getting near the end of the cycle..."

"...I think that this economy can grow at 2% to 3% at a margin, but inside of that 2%, 3% there's plenty of recession activity that's happening."

"...So if you were working for Sears Roebuck you might have thought you were in a recession, if you are working for Radio Shack you would have thought there was a recession.

Payless shoes I mean any one of the 9,000 retailers price closed toward and you would have felt pretty bad, right. A fewer in the oil industry, as oil prices plummeted in the Dakotas and elsewhere. And you are located in one of those states, you were thought there was a recession. 

So inside of that 2% to 3% growth there is a lot of kind of creative destruction that's happening that's buried in that."

Duh! Of course!

Instead of waiting/worrying about a big recession all the time, we're better off recognizing that mini "recessions" by sectors have always been with us. Its called creative destruction.

Sometimes real insight is simple and elegant, and right in front of you.

I'm not sure I can add much more without sounding banal. So I'll stop here.

Thoughts on Cycles

Update 2/12/2019
In my original post below, I talked about the concept that fraud is cyclical. It turns out there are words for it - the "bezzle" and "net psychic wealth" - coined by John Kenneth Galbraith. He explains it much more elegantly than I can:

“Weeks, months or years may elapse between the commission of the crime and its discovery. (This is a period, incidentally, when the embezzler has his gain and the man who has been embezzled, oddly enough, feels no loss. There is a net increase in psychic wealth.) At any given time there exists an inventory of undiscovered embezzlement in – or more precisely not in – the country’s business and banks. This inventory – it should perhaps be called the bezzle – amounts at any moment to many millions of dollars. It also varies in size with the business cycle. In good times people are relaxed, trusting, and money is plentiful. But even though money is plentiful, there are always many people who need more. Under these circumstances the rate of embezzlement grows, the rate of discovery falls off, and the bezzle increases rapidly. In depression all this is reversed. Money is watched with a narrow, suspicious eye. The man who handles it is assumed to be dishonest until he proves himself otherwise. Audits are penetrating and meticulous. Commercial morality is enormously improved. The bezzle shrinks.” 

- John Kenneth Galbraith

So the "fraud is cyclical" thing is certainly not any unique insight of mine. In my post, I further distinguish between frauds perpetrated by management, frauds unknown to management, and unintentionally inflated results from murky data.



Original Post (1/19/2019)
I recently read Howard Mark’s “Mastering the Market Cycle”. It was particularly interesting to see how he reconciles common value investing believes like “can’t time the market”, “ignore the macro”, and so on with more acceptable topics like “where are we in the cycle”. I had always thought the differences are little more than semantics, but Howard Mark pointed out some subtle differences that I had not thought of.

Reading the book also had me thinking through cycles some more. Here are just some thoughts that I will elaborate in this post.

• Why credit cycles do die of old age, and how lack of new borrowings alone would lead to recession. 
• Instead of looking at asset prices and judge whether they are rich or cheap, look at capital provider’s behaviors. Are deals getting done at ridiculous terms? 
• Thoughts on inflated earnings. While most investors are well aware of natural cyclicality, what’s less well understood are various degrees of fraud and “pushing the envelope” behaviors. 

Why Cycles Do Die of Old Age

Bull markets die with the end of credit cycles, which die of old age.

Over the past 30 years debt to GDP ratio throughout the world has ballooned, meaning new borrowings drive an ever bigger share of spending.

Whenever someone take out a mortgage to build a new home - that stimulates the economy. You take out an auto loan to buy a new car, that stimulate the economy.

But how many mortgages and auto loans can I take on? How many houses and cars can you buy? TVs? If you just bought a new house this year, chances are you’re not about to buy another one next year. Not when you’re up to your neck in debt.

As time goes on we approach some natural limit on indebtedness, and new borrowing activity decreases. Instead of borrowing, we have to pay down debt. That means less spending in the economy, and less spending means less jobs are needed.

This may not be obvious to some – less borrowing and/or paying down debt may be prudent, but it causes the economy to contract.

So thus credit cycles do die of old age, and with that, spending and the associated bull markets die of old age.


Look at What Investors Do, Not What They Say. Oversupply of capital

Here’s maybe the most useful thing I learned from Mark’s book – in judging where we are in the cycle, it’s much better to judge investor behavior rather than asset valuation, or even investor sentiment as expressed through media.

Asset valuation is inevitably subjective (7x PE looks cheap but is that peak earning or not? Depends on if you think if a recession is coming soon right?).

Investor sentiment and news flow can also be misleading. News headlines and Twitter can be flooded with panicky takes, but if VC deals are still getting done at 20x revenue then it’s hard to say the market is in capitulation mode.

Much more reliable are investor actions, as expressed through lending terms, M&A terms, IPO terms.

What does this all mean for us now (December 2018)? The U.S. stock market has taken a beating; news flows are undoubtedly bearish (trade wars! Government shut downs!) And we have cyclicals like Goldman Sachs trading at 7x PE. Are we near bottom of the cycle? I would say hardly.

Masayoshi/Softbank’s Vision Fund is buying anything and everything with Saudi money. Companies are still doing large buybacks. Consumer staples are getting into marijuana space at high valuations. Amazon is still expanding into new industries everyday. These are not signs of capitulation.

Intuitively, ease of financing also implies lowers barriers to entry, excess capacity, and crowded competition in the underlying industries. This “creative destruction” is not good for investors.


Frauds (and false profits) are Also Cyclical

I think frauds are important triggers of financial crisis because the “you think you have money, but suddenly you don’t” effect triggers panics and sudden liquidity demands.

It’s no coincidence that scandals like Enron and Madoff get uncovered at end of the cycle. For one, eroding asset values force investors to take a cold hard look at their portfolio, and there frauds are uncovered. Second, the unveiling of fraud alert the market to huge losses, which leads to a more skeptical market and even more unveiling of frauds.

Frauds are cyclical. They may be discovered only after the fact, but some portion of an economy’s output will always be from questionable behaviors. More at top of cycle, less at bottom of cycle; less frequently discovered at the top, more uncovered near the bottom. 

Frauds may have nothing to do with management’s integrity. Frauds can take place while senior managers are blissfully unaware, or even explicitly forbids it. The Wells Fargo scandal from a few years back - where low level branch employees create fake client accounts to meet aggressive sales goals – is an example.

As the economy expands and firms fight for market share, the pressure to improve performance naturally incentivizes all sorts of fraudulent or “push the envelope” behavior that inflates revenues.

Nor does inflated revenue and data need to come from intentional fraud. Ellen Pao’s “it’s all fake” tweet has an interesting discussion here.

It's all true: Everything is fake. Also mobile user counts are fake. No one has figured out how to count logged-out mobile users, as I learned at reddit. Every time someone switches cell towers, it looks like another user and inflates company user metrics https://t.co/tk1PKuvLL6

— Ellen K. Pao (@ekp) December 27, 2018

Unlogged in devices can create confusion and inflate data. I personally have the experience of inflating advertising metrics recently. I played this videogame where I constantly have to play to level up my avatars. So I quickly learned the common practice of building a macro or bot to “auto-farm”. This game is free to play and depends on advertising revenue. So the company is likely selling overstated user metrics when pitching to advertisers (albeit unknowingly).

Nowadays entire business models are based on advertising revenue, which are based on unreliable user metrics. This inflated revenues and earnings will drop when the cycle ends - and not in a controlled, linear fashion that analysts tend to forecast in their models.

12/30/2018 Views- Not Particularly Cheap

I did almost no trading in December, and very little in November. On 10/28/2018 I wrote: “Now that I'm sitting on more cash and bonds than I have stocks, I'm almost cheering when the market goes down“. I still feel the same today. 

The problem is even after the market down turn, most stock valuations are only fairly valued if you assumes no recession in the next 3 years or so.

For example I am considering buying Goldman Sachs, which trades at about $160. Using consensus 2019 EPS, this trades under 7x earnings. Neither does that EPS look particular peakish. Over the past 10 years pretax profit actually held fairly steady, and the explosive EPS gains mostly came from lower tax rate and much lower share count.

So is GS cheap or what? The problem is about 20% of their revenue comes from the “Investment and Lending” segment, with the majority of that being gains from equity securities. In fact, from 2015-2017, this segment contributed 28% of GS’s pretax earnings! 

In estimating a conservative “normalized” earnings, I assumed 0 on those equity gains, and $160 stock price would represent under 12x P/E. This is a good valuation, but not a huge bargain for a highly leveraged, cyclical company prone to political attacks.

In a down cycle, that Investment & Lending “revenue” might not just be zero, it could be negative. Then this $160 price tag might be outright expensive.

Portfolio Positioning and Asset Allocation
Given my inaction, my stock exposure will likely maintain at the current level of 40-50% of liquid portfolio (basically my entire net worth minus home equities). I'm open to more if I see truly compelling value.

The 40-50% equity level is really more about how much cash I want, and less about how much equity exposure. As a full time individual investor, I don’t have regular income and have always maintained plenty of cash reserves. I also wanted to maintain plenty of “dry powder” to go in big in case there’s a recession.

I'd like to think the 40-50% allocation to equities implies a neutral view regarding the stock market. If stocks goes up I would have more than half of my portfolio invested, “net bullish” if you will. If stock goes down I will have ever decreasing exposure while keeping my dry powder high.

Musings: Cash on the Sidelines and the Illusion of Market Cap Calculations

Cash on the Sidelines

I read Zero Hedge regularly. It is not the most reputable publication, but once in a while it bring up interesting topics. Like this article: Destroying The Myth Of 'Cash On The Sidelines'.

Permabulls love to argue there are all these “cash on the sidelines” ready to buy stocks and jack up prices. The article disagrees with the very idea of it. It quotes Cliff Asness:

“There are no sidelines. Those saying this seem to envision a seller of stocks moving her money to cash and awaiting a chance to return. But they always ignore that this seller sold to somebody, who presumably moved a precisely equal amount of cash off the sidelines.”

Asness is saying there are no sidelines because buy/sell transactions do not increase overall cash in the system, since for every buyer there’s a seller.

I used to think that, and it’s something clever to say. But it’s wrong.

We all know friends, relatives, or neighbors who, at one point or another, try to put their growing cash piles to work. These people clearly have cash and its growing. Where does that come from?

First, it’s called money creation. As people earn wages and deposit that in their bank account, their “cash on the sideline” grows. So you say, “but the employer who paid them now has less cash, so total cash level don’t change right??” Well, at least some of the employers borrowed money, the act of which is how our financial system expands money supply.

Second, there’s asset class rotation. Asness would be right in a world where it’s just cash and equities, (and no liquidity creation). But you know, there’s such a thing as fixed income and bonds and they get used as cash alternatives. You see all these balance sheets where companies list “cash and marketable securities”? That’s your T-bill/CP’s/notes/bonds…etc.

So to the extent bond prices start going down and people rotate into equities, that’s “cash (and marketable securities) on the sidelines” which can boost equity prices.

The Illusion of Market Caps

The big news last week was Amazon buying Wholefood. As CNBC reported here, Amazon is paying $13.7bn for Wholefood, yet AMZN’s market appreciated by $15.6bn when the news hit.

CNBC wrote: “So, you could argue, they are getting Whole Foods for free, and pocketing $1.9 billion as well.”

How could this be? Are investors stupid? One explanation (which is the CNBC editor’s view) is that the market thinks Amazon will get so much synergy that it exceeds the entire cost of acquisition.

Maybe. But there’s another explanation - that the way we calculate market cap renders it a flawed concept.

The CNBC article wrote: “Amazon's stock was up $32 and change mid-morning. There are 478 million shares outstanding, so Amazon's market cap has appreciated by about $15.6 billion today.”

The flaw is one of extrapolation. The deal was announced on June 16th, 2017. That day 11.47mm shares of AMZN traded.

That tells us the market was willing to pay $32 more for 11.47mm shares. That’s it. It does not mean the market was willing to pay $32 more for all 478mm shares outstanding. In fact, if all 478mm shares were for sale, I’m sure AMZN stock price would crash!

But that’s what our market cap calculation does. We take the increased price for 11.47mm shares, and then extrapolate that to say every single share, to the tune of 478mm shares, gets the increased valuation. We take one single point in the stock’s demand curve, which tells us there’s demand for x # of shares at y price, and extrapolate that to total shares outstanding.

And we do this all the time. We do this whenever we calculate market cap, which goes into enterprise value, EV/EBIT, EV/sales, and so on. 

It get's dangerous when we apply this false logic to value investing. How many times have you heard this type of argument: "This company had one little bad news, and its market capitalization declined by $7bn! How can the worth of the company change that much!?  It's irrational! Misunderstood! Buy buy buy!"

Again, it's extrapolation. We take one single point on the demand curve and assume all shares will clear at that price. Then we make claims about what the whole company is worth.  

This should make you think twice about using these metrics to make buy/sell decisions! Our “fundamental” valuation isn’t just subjective based on our view of the future - it is fundamentally and precisely wrong!

Notes on Wachenheim’s “Common Stocks and Common Sense”

Ed Wachenheim runs Greenhaven Associates, a $6 billion value fund. He piled up an enviable track record over the past 20+ years, regularly making 20%+ a year. And he does this by investing in large caps like IBM and Lowe’s. I’ve been resorting to nanocaps to in my quest for returns, so I wanted to read his book and see how he did it.

The book, "Common Stocks & Common Sense" has an excellent format. It is a series of case studies, each about a particular company Wachenheim invested in.

He would typically start with some historical backgrounds for the industry and the company in question. Then he shows how he develops a thesis, problems the company was having (to the extent there were any), and how the idea played out the next couple years. Throughout these passages Wachenheim would sprinkle in bite sized philosophy about how to use sell-side research, his view toward interviewing management…etc.

We need more books like this. This is a little like “Alchemy of Finance” where Soros documented his real time decision making. If anything, this book provides interesting snapshots of some industries from 1990's to now.

This book was helpful in confirming some of the ideas I have on how to approach research, on top of some great insights. I will first share my observations about Wachenheim’s style, then list out some general takeaways.

Observations of Wachenheim’s style

• Buy large cap liquid securities. 15-25 stocks in the portfolio, try to be fully invested all the time. 
• Targets 20% return. This means individual ideas need much higher upside (say 60%+), because there will be losers also.
• Ignore broad market moves, focus on fundamentals.
• Not a buy and hold forever type of guy. Willing to hold for 2-3 years and sell when the thesis is played out.
• In general stay away from growth stocks with high multiples. But also try to stay away from severely distressed companies. 
• Typical type of plays:
• Turnarounds/ leadership changes: e.g. IBM, Interstate Bakeries
• Cyclicals: e.g. U.S. Home Corp, Centex, Southwest, Lowes, Whirlpool
• Good companies with temporary issues: Union Pacific, Lowes, Boeing, Goldman Sachs 

Miscellaneous Notes and Takeaways

1) Focus on the upside first. Creativity is key in target identification.

Before doing a big deep dive, do a simple model and project 2-5 years out to see if there's enough upside to justify further work. Try to be creative in generating thesis - what can make revenue and margins go up? Can management cut cost here and there? What happens if input cost goes down…etc.

A lot of people say “focus on the downside and the upside will take care of itself”. But at least in the idea generation/filtering stage, you have to demand the upside - else you’re just wasting your time. The focus on downside can come after an idea passes the initial filtering and you’re doing deep dives and running scenarios.


2) Know the long term history of the business and industry. This helps you appreciate the structural difficulties and what it takes to fix them. 

IBM was an example in the book. In the 1990’s the company’s business model of selling, leasing, and servicing mainframes became outdated due to emergence of the PC. That left IBM with a bloated cost structure which old management was not willing to address. The buying opportunity came when Lou Gerstner became the new CEO and showed “the courage to take tough steps”.

Knowing the long term history also helped Wachenheim invest in cyclical companies. He bought Southwest Airlines in 2012, understanding that the decade of 2000's were miserable for airlines and forced them to cut capacity.


3) True insight comes from understand the unit economics of the business well.

Knowing the economics of Union Pacific helped Wachenheim differentiate between a temporary problem and a structural one. In UNP's case, congestions led to train delays, which hurt margins because revenue is a function of volume, while much of the expenses like labor are a function of time. When congestions were fixed, UNP’s margins improved and stock went along with it.

Another example is when he talked about Southwest Airline's capacity utilization. 83.1% utilization might seem like there's some excess capacity. But that is the average. Since unpopular flights (bad hours, remote locations...etc) are going to have many empty seats, the more popular flights are probably operating at full capacity and having wait lists.


4) Historical average P/E of the market is a little less than 16x. When valuing companies Wachenheim would use the 16x as a benchmark and adjust up and down based on business quality.

This is a better approach than using comparable multiples, which may be the most over-rated valuation methodology of all. “Peer comps” is an easy way for unscrupulous bankers and analysts to justify over-valuation in bubbly markets (“hey Alibaba trades at 56x PE so let me value this other shitty e-commerce stock with 45x PE! Look I’m really conservative here!”)


5) Use sell side analysts mostly as a gauge of market consensus, and think “do I see an upside here that consensus is not pricing in?” 

That makes sense because sell side guys get their feedback from buy side community, so these analyst reports in some way reflects prevailing opinions.


6) In my humble opinion, Wachenheim can screen stocks more effectively. He seems to run a lot of screens based on low valuation ratios, which he himself admitted is rarely productive, since these “cheap” stocks are usually cheap for a reason. 

I think you’re better off screening with charts and basic technical analysis. For example if you're looking for out of favor stocks, don't screen for low P/Es, low EV/EBIT...etc. Rather, find some price charts that dropped like a rock more than a year ago, underwent heavy capitulation selling, and have since showed price stabilization along with low volume (a sign of investor disinterest). What I typically do is screen for some minimum quality (low debt, high ROIC...etc) then run them through charts.

Common Quotes and (Maybe Not so Common) Thoughts on Investing

1. Investment vs Speculation - the classical definition

“An investment operation is one which, upon thorough analysis, promises safety of principal and a satisfactory return. Operations not meeting these requirements are speculative.” - Ben Graham, from “Security Analysis”

By this definition “investments” are exceedingly rare in today’s equity market. Good companies don’t trade at <17x earnings. Great companies could be 30x-50x earnings. Justifying those prices often require extrapolating growth out for 5-10 years, then assuming 1) margins and earnings don’t get destroyed by a recession during the forecast period, and 2) multiples don’t decline due to higher risk-free rates (as if there’s such a thing).

Thus, at today’s prices, much of “investing” (certainly much of growth oriented investing) contains implicit macro bets on the direction of economy and interest rates. A high percentage of these same investors would consider questions of interest rates and macroeconomics to be rank speculation. By that logic then, one can only conclude these "investors" are really "speculators".

Given the majority of "investing" today is really speculation, Graham's distinction kind of loses its meaning and usefulness. Perhaps it's time to redefine the two. Personally, I think of investment versus speculation as follows:

• Investment = I'm betting on real world fundamentals playing out as I figured. 
• Speculation = I'm betting on shifting expectations. It doesn’t matter how things actually play out, as long as people think it will go well, they will buy the stock and push prices up.

2. You are NOT the owner

“You are not buying a stock, you are buying part ownership in a business” – Warren Buffett (not sure, really every value investor)

Ok, I get the point, but let’s face it - most of us are not REALLY owners in the business. Understand this is key to avoid getting ripped off by unscrupulous management and insiders. 

To me, ownership means I have access and control. If I own a coffee shop, I would be able to access the shop’s profit and loss data any given day. I would have the power to fire under-performing workers, change the marketing and advertising strategy when it’s not working…etc. 

I own GOOGL stock. But If I call up Google today, I’d be lucky if investor relations call me back in a week, let alone have access to management. I certainly don’t get to tell Sundar Pichai what to do. I’m not really an owner of Google.

When Warren Buffett buys a stock, he’s an owner. He has great access, and has at least some influence on the board. He can influence the companies’ capital allocation decisions and extract cash flows if he needs to.

I think a lot of Buffett’s ability to bet big with conviction comes from having access and control. It also explains why entrepreneurs and business owners are willing to risk their life savings on one idea – essentially take leveraged, super-concentrated bets, while most investment manager consider a 15% position a big position.

3. Bet you didn’t know Ben Graham said this!

"It would be extremely unwise - and hypocritical - for anybody to buy a list of common stocks and say that he was interested only in his dividend return and cared nothing at all about price changes…the problem is not whether price changes should be disregarded - because clearly they should not be - but rather in what way can the investor and the security analyst deal intelligently with price changes which take place." - Ben Graham, from Current Problems in Security Analysis

In recent years the so called "dividend growth investing" crowd blindly chased yield without regard to valuation. They would pull up some old Benjamin Graham quote about ignoring "Mr. Market", and babble on about "long term investing" to justify their pavlovian "buy the dip" strategy.

Yet Benjamin Graham himself would say stock prices clearly matter. After all, if you make 3% dividend and risk 10% on principal, what's so good with that?

This is all the more so if you’re not really an owner like Buffett, but rather an OPMI: outside passive minority investor.

Now, what are prices dependent on? Why, supply and demand, of course. That’s a function of 1) people’s ability to buy (liquidity on their hands), and 2) willingness to buy (based on their assessment of company’s future outlook and “intrinsic value”, versus their alternatives).

This leads me to the next point.

4. What is it worth? And to whom?

“Value investing is figuring out what something is worth and paying a lot less for it.” – Joel Greenblatt

This quote is helpful to the extent it points out “value investing” is not just low P/E, low EV/FCF, or some other valuation metric. Warren Buffet would agree: there's no "value" versus "growth" investing. You're always looking for value.

What’s not helpful though, are the discussions that typical follow. Typically, these discussions of “what something is worth” automatically jump to some sort of discounted cash flow analysis, complete with disclaimers on how estimating “intrinsic value” is more of an art than science.

I think there’s a lot of talk about “intrinsic value” and not enough about “intrinsic value to whom?” The latter question matters. A control investor looking to extract synergy sees a different set of cash flows versus a mutual fund investor. The Bank of Japan, which has been gobbling up local equities, sees a different set of “values” from what Warren Buffett sees.

An example of the “intrinsic value to whom?” question is Canadian real estates. Consider a very logical housing investor. He might value a house by projecting out rental income minus various expenses, capitalize that cash flow stream with some desired yield. He then arrives at an "intrinsic value" that's way lower than the market price, and declares the housing market a bubble.

A rich guy from China, however, may be willing to pay a multiple of the market price. Why? because he's not just buying a house. He’s buying fresh air, safe food, quality education for his kids…etc. Heck, even just freedom of using gmail without getting censored by the government. A few millions for a crappy Canadian house is a bargain for that guy. 

The "value to whom" question matters. Knowing who's the buyer and the seller matters.

5. Compounders? or just justification to buy high?

“Given the three ingredients of a) optimistic assumptions as to the rate of earnings growth, b) a sufficiently long projection of this growth into the future, and c) the miraculous workings of compound interest - and the security analyst is supplied with a new kind of philosopher's stone which can produce or justify any desired valuation for a really good stock” - Ben Graham, from The New Speculation in Common Stocks

Nowadays, a typical “compounder” thesis goes something like this. This company is run by management with great integrity. The company has such and such competitive advantage: low cost structure, differentiated business model, this and that. The company is awesome. This company trades at some expensive looking valuation. But hey, if you project revenue out 5 years at 30% growth rate, put some 30x terminal EV/EBIT on it (all justified by qualitative discussion of competitive advantage), then we can get to 15% IRR.

Is this really margin of safety? Or are we just stretching ourselves to justify buying a good company? 

I have no problem against paying up for compounders. In fact I have lots of these: GOOGL, BABA, JD, EW...etc. But I'm under no illusion of what will happen to these stock when investors decide they will only look 3 years ahead instead of 7 years ahead.

Week ending 3/10/2017: Losing Streak

From red hot to ice cold. My major stock holdings have drifted lower. My small, speculative positions have blown up and given back their gains. In the past months I twice sold stocks (Fortress and Nimble Storage) days before they get acquired at huge premiums. Even currency trades, a barometer with which I judge my understanding of the world, went from positive to negative.

It’s a combination of bad shots and bad luck. What do you do when you keep shooting bricks and air balls? Do you keep shooting? Or do you bench yourself?

For now it’s the latter. I have cut back on losers and winners alike. Despite having a plethora of stock ideas, I’m putting them on hold until I can figure out what’s going on.

Major Stock Positions

Fidelity National Financial (FNF). Spinoffs coming 2H16 to unlock value. The core title insurance business is cheap at about 10-12x PE. This is a great business and we may be on the cusp of a wave of millennials buying their first homes.

Beijing Enterprises Holdings (0392.HK). Just too cheap.

Sallie Mae (SLM). A play on deregulation, tax cut, and higher interest rates.

Aetna (AET) and United Health (UNH). Insurers have the best bargaining power in healthcare.

Medtronics (MDT). SURTAVI trial results coming March 17th. A good read could boost the market size of TAVR heart valves and MDT’s market share.

Vipshop (VIPS). Incredibly cheap for a company with 20%+ revenue growth. The market should come around to it one day.

Most of these have done well the past 2 months but are now showing weakness. I’m actually praying for FNF, SLM, and VIPS to go lower so I can buy more. Beijing Enterprises had a nice run the past month but looks about to be beaten down again. The negative sentiment in Chinese stocks persists (this applies to Beijing Enterprises as well as VIPS) and I think part of it is the market assigning a steady decline in Chinese Yuan.

Inotek and Negative Enterprise Value Situations

2017 will be an interesting year in biotech. When “clinical stage” biotechs fail their trials and still have cash left, what do they do? These stocks can trade at below value of cash on balance sheet, so the market is basically saying management will entrench themselves and burn away cash. There’s a bunch of these companies in the market right now. Ovascience, Inotek, Ophthotech…etc. Merrimack is another one that could have negative EV soon.

I replaced my OvaScience position with another negative EV play, Inotek. This company develops eye drugs. It has one more phase 3 trial result coming up, and no more pipelines after that.

In this way Inotek is superior to OvaScience, which has multiple years of pipeline (thus excuses to burn cash and destroy shareholder value). If the trial fails, Inotek would still be sitting on cash of $2-2.5/share and no debt. The company trades at 1.6 when I bought (up to 1.8 today).

It’s hard to say what management will do. Ideally they just return cash to shareholders. But they could try to acquire some product pipeline. Or they could refuse to admit defeat and do another phase 3 trial on the same failed molecule. In short, anything to keep paying themselves.

So this is potentially an activist situation. But I’m not sure how much good that can do. The board has no investor representation and only one director is up for election in 2017.

Ophthotech is another eye drug company with negative enterprise value. They have already said they will not return cash, but will look to acquire. So Inotek could be a target.

On “M&A Valuation”

What are these “plethora of ideas” that I’m holding back from? I have one general observation about the whole IT/medtech space.

I’m seeing lots of companies like this: revenue growing fast – say 20%+ or even 100%+ a year. Stock trades at 2-4 times EV/revenue. Big net cash positions. GAAP losses but approaching cash flows break even (because of stock based comp and D&A). High gross margins. The biggest expenses tend to be sales/marketing /G&A.

From the perspective of a strategic acquirer, you can synergize and cut down SG&A by half or even more. If you do that, most of these companies are essentially valued at <10x EV/forward EBIT, maybe lower.

So if you start modeling “acquirer perspective”, they all look like slam dunks. On a standalone basis though, most of them will never be profitable (unless you literally project growth like 10 years out).

Off the top of my head, Novocure (NVCR), Atricure (ATRC), Nutanix (NTNX) are just a few that fits in this category. The list is long.

The megacaps are sitting on huge cash piles. Tax reform could add to that by allowing big tech companies to repatriate cash. This all bodes well for M&A. Of course, not every company will be bought out, but increasingly market valuations are based on perceived M&A potential.

Keeping Track of Ideas from This Year

After analyzing my results year to date, I see the need to be more concentrated and find more “investments” as opposed to “trades”.

Here is a table of my write-ups on this blog year to date, and how they’re doing

There’s also stuff that I did not write about that detracted from my returns. Macro trades/hedges killed me this year. Those deserve a separate post-mortem but I think the writing process forced me to think through everything more completely, yielding better results.



What’s interesting in the table above is how active management detracted from my returns. One clear pattern above is “actual return since write up” is much lower than “hypothetical return from buy & hold”. This is because I sold early: either I cut positions early, or traded in and out of the stock.

Why is that? Sometimes a sell is justified – as in when stocks simply reached my estimate of fair value, or when my thesis proved false.

But other sells are more questionable. Sometimes I would sell a position just because new facts came out and I have not had time to assess the situation. So I would sell first, sit on the sidelines until I get around to updating my assessments. This has saved me from losses in the past but can also be costly as stocks fly upward. I think it’s a sign that I have too many positions and not enough focus (I have 30-40 positions going most of the time).

Some Ideas Look Better in Models Than in Real Life

Sometimes it’s the nature of the idea itself that limited the upside. I can explain this better by grouping ideas into categories:

Pure mis-valuations

Examples: FNFV

Problem is that the initial asymmetric risk/reward goes away as soon as price moves up, so you get limited upside. Let’s say I think company A should be worth between $90 to 130. Stock is at $100 so you say “downside is 10% and upside is 30%, and the probabilities are about 50/50, this is nice risk-reward”. So you buy.

Next month the stock moves 10% to $110. But the fundamentals have not changed so your valuation range stays at $90-$130. With stock now at $110 the upside/downside is now at 18% each, and the probabilities are still 50/50. This bet is no longer tilted in your favor, so you exit the trade.

Despite the perceived 30% upside at trade inception, you exit the trade at a mere 10% gain.

Lousy businesses at attractive prices

Example: Omega Protein

These are naturally not going to be long term holds. You’re just looking for fundamentals to shift in a better direction and thus stock price along with it. But ultimately the fundamentals is capped (still a lousy business), so the upside is limited like the above “pure mis-valuation” category.


Cyclicals

Examples: Select Harvest, Sterling Construction

The problem with these is you’re looking to catch a cyclical bottom in the industry. In practice there’s also an element of price speculation. That tends to keeps my confidence low and my positions small.

In the case of Select Harvest that I missed the move completely (waiting for a pull back that never happened). In the case of Sterling Construction, I cut stakes early because I didn’t have enough conviction, only to buy back later at higher prices. Perhaps I will learn to get more conviction and bet bigger one day.




Going forward, I want to have a lower number of positions be more focused on each. And also less of these “this is a crappy to ok business but it’s cheap” ideas, and find more companies with structural growth prospects. 

"Investing" is preferable to "Trading". “Value investing” does not have to be “cigarette butt investing”. These are, of course, easier said then done and will depend on what the market gives you. For now I have been forced to look into smaller companies and foreign stocks.

When Does it Make Sense to Adjust for Amortization of Intangible Assets?

Buffet’s 2015 annual report contained his usual warning about amortization charges.

“… serious investors should understand the disparate nature of intangible assets. Some truly deplete in value over time, while others in no way lose value. For software, as a big example, amortization charges are very real expenses. Conversely, the concept of recording charges against other intangibles, such as customer relationships, arises from purchase-accounting rules and clearly does not reflect economic reality

Buffet goes on to say about 20% of Berkshire’s amortization charges are “real”, therefore adding back about 80% of amortization charges in his non-GAAP presentations.

For a lot of companies, non-GAAP earnings routinely doubles that of the GAAP version after adjusting for amortization of intangibles and stock-based compensation. Clearly these are no trivial matter. Since Buffett already criticized the latter, here I want to focus on the former.

Most Intangible Amortizations are Real Expenses

If the key question is, as Buffett suggested, whether the intangible asset depletes over time, then I would say most of them do. They are called “finite-lived intangibles” for a reason. Software and patents are fairly obvious - they deplete due to technological obsolescence and legal expirations, respectively. But even customer relationships and brands depletes overtime. 

Buffett cited customer relationship as an intangible asset that does not deplete. But I would argue even that decays overtime as your customers change (they move out of your geography, retire, move to another company…etc.) and competitors try to steal your customers. Brand value decays as well. If you literally buy out the Coca-Cola brand for a gazillion dollars and then subsequently spend zero on marketing, advertising, or promotional budgets while Pepsi continues their efforts, I believe even Coke would gradually lose “mind share” and its revenue will slowly decay overtime.

Criteria for Adding Back Amortization Charges

So when is it ok to add back amortization of intangibles? I think the real question is not whether something depletes – they pretty much all do. What really matters are 1) whether the company is spending to replace or maintain that earning power and 2) whether that cost is already accounted for.

Due to the quirks of accounting, intangible assets are capitalized when they are acquired. But the costs to internally replace that earning power (think R&D, advertising expense, marketing expense, and so on) are usually expensed. This means they already flow through the income statement, as opposed to getting capitalized on the balance sheet then amortized later.

Go back to the Coke example. Let’s say you buy out the Coke brand, and now you got a massive intangible asset and lots of amortization expenses. But instead of letting it rust, you actively incur expenses on sales/marketing/advertising to maintain or increase that brand value. Since these costs are already reflected in the income statement, not adding back amortization expense would be double counting.

Compare this to depreciation of hard assets. Since ongoing cost of maintenance would be capitalized and not expensed in the income statement, an accurate earning measure would either treat depreciation as a real expense, or add it back but subtract an estimate of maintenance capex.

The Verdict

To conclude, adding back amortization of intangibles makes sense. Not because they are not “real expenses”, but because the cost of replacing that intangible asset is likely already reflected in the income statement and you don’t want to double count. It is “likely”, but not always, because the appropriate treatment would differ company by company, and asset by asset. There’s no one size fits all answer.

Berkshire Hathaway is unlikely to skimp on spending to maintain its earning power, so Buffett’s adding back 80% of their intangible amortization seems sensible.

On the other hand, if a company’s core business model is acquisition of intangibles (say patents for drugs), yet does nothing to maintain or replace its decay (no R&D capability in house), then adding back amortization would be voodoo math.



Notes:

1) Whether a number is “correct” will depend on how it’s used. So if you add back amortization to earning or free cash flows per share, then apply a low multiple to account for the gradual depletion of earning power, then I have no problem with that. But more often than not people add back amortization of intangibles to come up with EPS or FCF/share, then apply 15-20x or even higher valuation multiple – therefore implying the earning stream is perpetual.

2) Intangibles have to be judged on a case by case basis because the same thing could be expensed or capitalized depend on situation (as this article explains, it depends on whether the intangible is acquired versus internally generated, and “identifiable” vs “unidentifiable”)

Which Securities are Most Likely to Trend?

The title really should be “finding the least efficient markets – Part I”. But that’s such a broad subject I will just focus on one little part of that here.

Greenblatt’s book “You Can Be A Stock Market Genius” outlined some intuitive ways to find inefficient markets – spinoffs, M&A, bankruptcies…etc. But one of the most common forms of inefficiency is right there on the stock chart – the trend.

If you visualize the price chart of a perfectly efficient security, what would that look like? I imagine it would have sudden gaps up or down as new information comes out, followed by flat lines in times of no news. This is because in a perfectly efficient market, rational investors absorb and digest the same information instantaneously, and that should immediately be reflected in prices.

But often we observe security prices that trend. Prices go up for 3 days in a row, a week in a row…and so on. To me that is proof that the market is not perfectly efficient - there are delays in information dissemination, interpretation, and actions on the parts of investors. Whatever the causes, the trend presents good trading opportunities.

The trend is your friend. But how do you identify securities that are most likely to trend? We need ways to quantify “trendiness”. Here is one simple way to do it: count the number of times where prices move in the same direction (“sequence”), divide by the number of times when prices reverse (“reversals”). This is called the “Cowles-Jones ratio” (CJ ratio).

For example if you have price time series data that goes like this: 1, 2, 1, 2, 1, 2. That’s 5 reversals and not a single “sequence”. The CJ ratio would be 0. On the other hand, if your data is this: “21, 22, 23, 24, 19, 18” That’s 4 times where price moved in the same direction and 1 reversal. (22, 23, 24 all moved in the same direction, then a reversal on 19, and finally 18 moved in the same direction as the last number). In the latter case the CJ ratio would be 4 / 1 = 4. So if you go long the security whenever price first ticks upward, your chance of winning is 4 times that of losing.

Calculating this number for SP 500 components from 1/1/2013 to 9/30/2015, I find the average CJ ratio to be 97%. I expected a number close to 1 so this is reasonable. Below are the stocks that with CJ ratios that are 2 standard deviation above the mean – i.e the trendiest stocks since 1/1/2013.

So the “trendiest” stocks have CJ ratio around 1.1 – 1.2 range. A simple strategy would go something like this: go long whenever you see prices shift directions and go up; and short if prices reverse and go down. Your win percentage would be better than 50/50.


Now check out the common currency pairs. Total trading days are more than those for stocks because the stock market get various holidays off.



Note that even the least trendy FX pair is more likely to trend than the trendiest of stocks! That makes sense to me. The forex markets are full of non-economic players like central banks and commercials for whom profit maximization is not the top priority. Then you also have mom and pop participants. When my dad wants to buy some NZD he literally goes to the local banking branch and buy them! That surely creates lags and opportunities not seen in the stock market.

These numbers change depending on what time period you use. But in general I do find currencies to be trendier than stocks.

There are other ways to measure trendiness – perhaps one can quantify autocorrelations, or run backtests using simple moving average crossover rules and then rank the results. As I learn more ways to detect trends (and get more mathematically skilled) I will post my discoveries.

Shorting AUD/USD: on FDI and Reflexive Potential

Summary Reasons for Shorting AUD/USD

• Technical downtrend is intact
• Demand of AUD will be weaker in the future due to lower FDI and portfolio flows. Trade balance is negative but that’s a less important factor in my mind.
• Factors that make AUD’s “reflexive” – price movement here can be self-reinforcing, rather than self-correcting 

Shorting AUD/USD is a fairly popular trade. Here are what I gather as the most cited rationales for shorting AUD/USD. Australia's main exports are iron ore and coal but prices for which have fallen and will likely stay low due to weak demand from China. Trade balance will deteriorate. The Reserve Bank of Australia thinks further depreciation is necessary and will keep rates low or even cut rates to stimulate the economy.

I agree with that line of reasoning, but trade balance and lower interest rates are not the only reasons that AUD will continue to depreciate. Going forward, in my opinion, foreign direct investment and potential for “reflexivity” will be bigger drivers of AUD decline.

Importance of Foreign Direct Investment

In the chart below, I used balance of payments (BOP) from 2006 to 2014 as proxy for historical inflows and outflows. Australia has persistently ran trade deficits and even bigger primary income deficits. What propped up demand for AUD in the past few years were foreign direct investments (FDI) and sometimes portfolio flows.

Note how trade balance is a relatively minor contributor versus other flows. Primary income is mostly stable while portfolio investment is fickle (and likely negative going forward). FDI though, has been consistently strong, but will likely deteriorate drastically going forward.

FDI is concentrated in the mining sector (~roughly 40% of foreign investment in Australia), and that is likely to drop off given prevailing weakness in commodity prices. Demand from China will stay weak given its continued shift away from an investment driven economy.

Reflexivity - Quick Background

But how much of that is already priced in? That’s always tough to know. A different question though, is will lower exchange rates hurt economic fundamentals and lead to even lower prices? i.e. is there a reflexive relationship here? I think so, but first a quick summary of George Soros’ reflexivity framework (as it relates to currencies) is as follows:  

• Prices are driven by different factors of supply and demand. Some of these factors are self correcting, and some are self-reinforcing. 
• Self-correcting means weaker prices -> improving demand vs supply -> stabilization in prices. 
• Self-reinforcing means weaker prices -> deteriorating demand vs supply -> further weakening in prices. 
• To see if a trend will continue, an analyst can break down price into different sources of supply/demand, and determine if self-reinforcing flows outweigh the self-correcting ones. 

In the context of foreign exchange:

• Price = nominal exchange rates. Supply and demand are inflows and outflows in the balance of payments items. 
• Trade balance is typically a self-correcting: lower nominal currency -> lower real currency -> better trade competitiveness and trade balance -> stabilization of currency 
• Portfolio investments tend to be self -reinforcing: lower nominal currency -> expectation of even lower FX -> expected currency losses tend to outweigh interest rate differentials for bonds and detract from equities returns). 
• FDI could be either self-correcting or self-reinforcing 

Analysis

With that background, here’s why I think AUD/USD will be a reflexive situation that keeps driving downward.

1. The main self-correcting flow, trade balance, is a relatively minor factor here (as shown in the BOP chart above). Further, Australia’s trade balance will likely see less improvement from currency devaluation due to its unique situation. Lower prices of main exports (iron ore and coal) is not going to help much if the problem is structurally lower demand from your customer in the first place. Australia’s main competitor in iron ore is Brazil and that currency is even weaker. So Australia is not going to get much of a boost in trade balance from weaker AUD.

2. FDI is likely a self-reinforcing flow in this case – weaker AUD will lead to weaker FDI. Remember again, FDI for Australia is big in the mining sector. With commodities, prices are in USD but local production costs are in the local currencies. When Australia and Brazil’s currency weaken versus the USD, local costs are effectively lowered and that will pass through to lower commodity prices. Would you invest in a mining project when 1) commodity prices will likely stay low or get even worse, and 2) the sector already has excess capacity? I don’t think so.

3. Portfolio inflows are self-reinforcing. For Australia, portfolio flows are mostly debt securities as opposed to equity. 10 year government bonds for Australia yield ~2.85% versus ~2.25% in the United States. What little extra yield you get from investing in an Australian bond could easily be overwhelmed by movements in currencies, which is decidedly negative in this case.

My conclusion is that the downward move in AUD/USD will continue, because the self-reinforcing elements (FDI and portfolio outflows) outweighs the self-correcting mechanism of trade balance.

This may take a while to play out though, and you incur negative carry on the trade. So timing and technicals do matter. AUD/USD hovers around 0.74 at the time of this writing. I am short and have a stop loss around 0.77 and my eventual target is as low as 0.65. The risk is if Australia comes out with massive investment project (develop North Australia for example) and attracts money from abroad. But that is unlikely in the current government and in any case unlikely to offset weakness in mining projects.

Spotting Turns in Market Cycles

This is the hypothesis I’m working under. To the well-read there’s nothing new here, and lots of market players probably already look at the world this way. But it took me a while to piece it together, as schools don’t teach this and you don’t get this type of stuff from reading Warren Buffett. 

First though, I want to address a common misunderstanding of credit and growth.

An Essential Point about Debt and Growth

I was reading an old economic report from Goldman Sachs by Andrew Tilton. In that report there is a sentence that stood out with its clarity of thought.

“…the growth rate of spending is related to the second derivative of credit – accelerating credit can fuel an increase in growth, but credit cannot accelerate forever, and when it begins to decelerate there will be a negative impact on spending growth.”

Everyone knows that spending growth can be driven by changes in credit – duh!? But that’s actually not exactly right. It’s really the second derivative of credit. There’s a subtle but incredibly important difference here - one that most people have a hazy understanding of (including myself until recently). That lack of clarity shows up when people talk about the world’s high level of debt, and they say something like this: “You can’t cure debt with more debt. Forget about actually pay down debt, how about just stop borrowing for a start? Is that too much to ask?”

Let’s walk through this with a simple example. Let’s simplify and say the whole nation is just one person. Let’s say I want to buy some fancy car for $100k. I don’t have the money, so I borrow $100k and buy. GDP for that year is $100k. Next year though, if I don’t do anything – not paying down debt or increasing debt), GDP naturally goes down to $0! In order to keep GDP flat, I’d have to borrow another $100k to buy another car– doubling my debt just to have 0% GDP growth.

This is what Goldman means by spending growth being related to the acceleration (2nd derivative) of credit, and not just changes (1st derivative) in credit. That is the tyranny of debt addiction. GDP growth could go negative just from people borrowing less than before (in the above example, say I only borrow and spend $50k in year 2, then GDP is down 50%).

Per Federal Reserve data, U.S. total credit market borrowing (SAAR) was $2,472bn in 4Q14. GDP was $17,701bn for the same period. So new borrowing contributed to ~14% of the GDP. If everyone stops borrowing, GDP would take a 14% hit. We would have massive unemployment and social unrest.

That’s just not an option. So the sensible way to “deleverage” is not to decrease the level of outstanding debt in absolute terms. But rather to INCREASE debt at a slower rate, and try to increase income at a faster pace, so that both debt and GDP increase in absolute amounts, but the ratio of Debt/GDP declines. In this sense, we have no choice but to “cure debt with more debt”

Implications 

So what does that have to do with investments? In my last post I mentioned Kostolany’s explanation of how liquidity drives broader markets. But he gave little guidance on when that would happen. Ray Dalio though, has a framework on the typical deleveraging processes and when central banks need to provide liquidity to the market. Combining the two frameworks should us a better sense of credit cycles and turns in the equity market.

I read Dalio’s writings on credit cycles a long time ago but did not understand it completely. Turns out understanding the above dynamics of debt and GDP growth was the missing piece – particularly the “why” behind various government’s alternatives. I went back and re-read his stuff and everything became clearer this time around.

In his paper “An In-Depth Look at Deleveragings”, Dalio mapped out the typical steps to deleveraging. In the first phase of deleveraging, debt growth either decelerates or turn outright negative, and countries attempt to cope via some form of austerity. Debt to GDP ratio will go up mostly because of declines in GDP. In the second phase, austerity and resource transfer reached its limits, and central banks are forced to pull the monetary policy lever and pump some liquidity into the system.

That’s when the stock market will take off despite the weak economy. The increased liquidity mostly goes to juice up the financial markets first, since people still lack confidence in the real economy.

So here are the big picture steps: Watch out for countries that are in the start or middle of deleveraging. Ideally you find a country that had explosive growth in Debt/GDP ratios and then a subsequent deceleration of debt which triggers a deleveraging cycle. Follow that deleveraging cycle and wait for central bank to print money – that would be time to play the stock market.

Appendix: Where is the U.S. in the Cycle?

Where is the U.S. in the long term cycle? The blue line in the chart below shows nominal Debt/GDP levels. The takeaways are 1) the U.S. went on a debt binge starting late 1970’s, so it’s possible that much of our GDP growth the past 40 years are just a debt fueled mirage. 2) The Great Financial Crisis was the first time we deleveraged to any material extent since the 1940s’. 3) Despite the deleveraging since 2008, debt/GDP is still at an extremely high level. 4) the pace of deleveraging has slowed and we actually have signs of re-leveraging.

My data does not go back to show the Great Depression. But per Dalio’s data, Debt to GDP went all the way from 155% in 1930 to 252% in 1932, then down to 168% in 1937. That’s a much greater swing of leverage levels – one that probably contributed to the rise of Hitler and World War II.

Given the still high level of debt and the deflationary forces of any potential deleveraging, as well as the already high P/E levels, I have to agree with the common notion that equity markets are in for long years of low returns ahead.