We Need To Talk About Multiple Contraction

In light of recent market moves I wanted to revisit this post about discount rates and how they might impact valuation multiples (spoiler: it’s an inverse relationship). I think the post holds up pretty well. The key feature was this chart:

118_Implied_Cost_Equity_SP
Data & Calculation Sources: Professor Aswath Damodaran & Michael Mauboussin

Recall that there’s an inverse relationship between the discount rate and the multiple you should pay for an earnings stream. The discount rate has two components:

1) a riskfree interest rate representing the time value of money (usually proxied by a long-term government bond yield), and

2) a “risk premium” meant to account for things like economic sensitivity, corporate leverage and the inherent uncertainty surrounding the future.

Back in January I wrote:

By way of anecdotal evidence, sentiment is getting more and more bullish. Every day I am reading articles about the possibility of a market “melt-up.” If the market melts up it may narrow the implied risk premium and further reduce the implied discount rate. If this occurs, it leaves investors even more exposed to a double whammy: simultaneous spikes in both the riskfree interest rate and the risk premium. The years 1961 to 1980 on the chart give you an idea of how destructive a sustained increase in the discount rate can be to equity valuations.

I am reminded of this as I read this post from Josh Brown, featuring the below chart:

daily-shot-sp-attribution
Source: Bloomberg via WSJ Daily Shot & Reformed Broker

Taken together, this is a fairly vivid illustration of why the current level of corporate earnings matters far less than long-run expectations for margins, growth, and (perhaps most importantly) the discount rate.

(You do remember what’s happening with interest rates, don’t you?)

Assuming no growth, a perpetual earnings stream of $1 is worth $20 discounted at 5%.

Raise that discount rate to 10% and the same earnings stream is worth $10.

Raise it to 15% and the value falls below $7.

And so on.

Now, there’s no way to reliably predict what the discount rate will look like over time. The real world is not as simple as my stylized example. On top of that the discount rate is not something we can observe directly. The best we can do is try to back into some estimate based on current market prices and consensus expectations for corporate earnings.

So, what’s the point of the exercise?

First, I don’t think it’s unreasonable to expect some mean reversion when the estimated discount rate seems to lie at an extreme value. And yes, I counted short-term rates at zero percent as “extreme.” As the above attribution chart clearly demonstrates, multiple contraction can be quite painful.

Second, this should explicitly inform your forward-looking return expectations. Generally speaking, the higher the implied discount rate, the higher your implied future returns. There is good economic sense behind this. “Discount rate” in this context is synonymous with “implied IRR.” To look at a 5% implied IRR and expect a 20% compound return as your base case makes no economic sense. Assuming the implied IRR is reasonably accurate, the only way that happens is if you sell the earnings stream to a greater fool at a stupidly inflated price.

Do fools buy things at irrationally high prices?

Yes. Indisputably. All the time.

Does that make price speculation a sound investment strategy?

No, it does not.

“Multiple expansion” is just a fancy way of saying “speculative price increase.”

Likewise, “multiple contraction” is a fancy was of saying “speculative price decline.”

Private Credit Stats

Sometimes I hear people say we “deleveraged” following the 2008 financial crisis. Sure, the consumer may have deleveraged, but I can assure you there’s plenty of debt left sloshing around in the system. A bunch of it has moved from bank balance sheets to what can loosely be thought of as the hedge fund space.

We call this private credit or direct lending. It’s huge right now in the institutional investing world. Sometimes it feels like every scrappy hedge fund guy in the world is launching a private credit vehicle.

Today, I came across a great paper by Shawn Munday, Wendy Hu, Tobias True and Jian Zhang providing an overview of the space. If, like me, you’ve been inundated with pitch decks from private credit funds over the past couple years, you won’t find much in the way of new information. But the stats are worth perusing.

private_credit_aum
Source: Munday, et al
private_credit_Commits
Source: Munday, et al
pooled_MOICs_IRRs
Source: Munday, et al
IRR_by_vintage_year
Source: Munday, et al

If you are an allocator this is nice base rate data for the space. According to the pitch decks everyone is targeting a net IRR in the mid-teens. It doesn’t surprise me that the median IRR for the post-crisis era is closer to 10% than mid-teens.

Personally, I’m inclined think median returns over the next decade will look more like the 2006 and 2007 vintages. Anecdotally, I can tell you there are middle market deals getting done out there with six turns of leverage and 7% yields. Unless you’ve got warrant coverage, you’re not getting anywhere near 15% IRR on a deal like that.

That kind of behavior reeks of yield chasing.

And we all know what happens to yield hogs.

Eventually, they get turned into bacon.

3Q18 US Factor Returns

Below are my factor return charts, updated for 3Q18. As always, this data lags by one month, so it is technically through August 31. Note also that the more recent bout of market volatility lies outside this date range. It will fall inside the next update.

This one features more of the same. Returns to Market and Momentum continue to grind higher, leaving the more value-oriented factors in the dust.

At bottom I’ve added a snap of Research Affiliates’ latest factor valuations. They’re about what you’d expect given the return data, with Illiqudity (think VC and private equity) and Momentum at the high end of their historical ranges. Value remains at the low end.

It’s worth asking: what’s the point of this exercise?

To better understand and contextualize the following (thanks Rusty Guinn):

[T]here is no good or bad environment for active management. There are good or bad environments for the relatively static biases that are almost universal among the pools of capital that benchmark themselves to various indices.

For a diversified portfolio, the variation in returns is explained almost entirely by the aggregate factor exposures. You’d be surprised how many professionals are ignorant of this.

Now, some of that ignorance is deliberate. There’s a reason investment managers don’t often show clients factor-based attribution analyses. The data typically supports the idea that a significant portion of their returns come from the relatively static biases (“tilts”) mentioned above.

As an allocator of capital, it behooves you to be intentional about how your portfolios tilt, and how those tilts manifest themselves in your realized performance. This self awareness lies at the heart of a disciplined and intentional portfolio management process.

3Q18_rolling_avg_factor_returns
Source: Ken French’s Data Library & Demonetized Calculations
3Q18mkt
Source: Ken French’s Data Library & Demonetized Calculations
3q18size
Source: Ken French’s Data Library & Demonetized Calculations
3q18val
Source: Ken French’s Data Library & Demonetized Calculations
3q18mo
Source: Ken French’s Data Library & Demonetized Calculations
3q18_op_profit
Source: Ken French’s Data Library & Demonetized Calculations
3q18inv
Source: Ken French’s Data Library & Demonetized Calculations
201810_RAFI_Factor_Valuations
Source: Research Affiliates

The Incredible Flattening Yield Curve

This is a pretty amazing image, courtesy of J.P. Morgan Asset Management:

2018_0630_US_Yield_Curve
Source: J.P. Morgan Asset Management (obviously)

People are really starting to worry the Fed is going to invert the curve. Historically, an inverted curve (short rates above long rates) has been a pretty good recession indicator. I don’t have a particularly strong opinion about the direction of interest rates, especially now that we are above 2% on the 2-Year. But I do think this chart is telling us something.

If the curve is basically flat from 7 years on out to 30 years, that is not exactly a ringing endorsement of long-term growth and inflation prospects. I’ve heard from some fixed income people that it’s demand for long-dated paper from overseas buyers holding the 30-year yield down. I’ll buy that. But it’s still telling us something about supply and demand for capital along various time horizons.

Namely: we’ve got an awful lot of long duration capital out there looking for a home, and not enough opportunities to absorb it all.

2Q18 US Factor Returns

Below are my latest factor return charts. I update these on quarterly intervals but the underlying data, from Ken French’s Data Library, lags by a month.

Not much to write home about this quarter. The divergence over the past few years between the Momentum and Market factors and the remaining, more value-oriented factors (Value (Price/Book), Operating Profitability, Conservative Investment) remains striking.

The Size factor has also performed well year-to-date. May was a particularly good month for Size (+4.78%) and Momentum (+4.02%). In traditional “style box” terms, this corresponds to small cap growth stocks.

2Q18_Factor_Averages
Source: Ken French’s Data Library
2Q18_Market
Source: Ken French’s Data Library
2Q18_Size
Source: Ken French’s Data Library
2Q18_Value
Source: Ken French’s Data Library
2Q18_Momentum
Source: Ken French’s Data Library
2Q18_Profitability
Source: Ken French’s Data Library
2Q18_Investment
Source: Ken French’s Data Library

Macroeconomics For Lazy Pragmatists

A friend asks:

I’m interested in your thoughts on how you would look at [macroeconomic] fundamentals [for international investing]. Presumably that would involve (among other things) looking at the top industries that drive the national economies?

This question inspired me. Now, I am not a “macro guy” and I am definitely not an academic. I am mostly concerned with understanding the handful of key drivers that might impact a given investment. So if you are a pedant you can quit reading now. You’re not going to find anything to like about this.

Have all the pedants left now?

Great. Before we get in to economic fundamentals it’s worth specifying the high level variables that shape every investment environment:

  • Economic growth prospects & fundamentals
  • Rule of law / protection of property rights
  • Asset valuations

The ideal investing environment is one with strong economic fundamentals; where the rule of law is upheld; and where cheap valuations are cheap. The stars will almost never align in this way, if for no other reason that if the first two variables are looking good, you are going to have to pay up for assets. But that’s the dream, anyway.

This post will focus on the first bullet: economic growth prospects and fundamentals.

The Most Important Things

Before we go any further, I need to emphasize that investing is not as simple as saying: “oh GDP growth looks good so it’s a good time to invest.” In fact, there is essentially zero correlation between GDP growth and stock market performance. What macro analysis helps you do is assess the drivers and risks associated with an economy. When you consider those drivers and risks in relation to valuations, you can use them to help formulate and/or evaluate various investment cases.

Seth Klarman said it best: every asset is a buy at one price, a hold at another price, and a sell at another.

Note that all of this is addressed toward folks who are thinking of investing with a fundamental view over a multi-year time horizon. If you are trying to swing trade currencies you will need to look at the world very differently. (And good luck with that, by the way)

Some of you might say, “well I will be a contrarian and just push money into bombed out economies where stocks trade on single-digit PEs and mean reversion will do the heavy lifting.” That’s all well and good. But if you really think this way I would expect to see a not-insignificant exposure to places like Russia, Brazil and Turkey in your portfolio today.

Otherwise quit kidding yourself. You are a phony.

Why Macro Matters

I talk to a lot of investors who say “we’re bottom-up stock pickers” as if the macroeconomic environment somehow has no impact on their portfolios. I am not sure if these people are genuinely delusional or if this is just something they are used to putting in their pitch decks and have come to recite by rote without thinking.

If you genuinely believe this I think you are reckless at best and a complete idiot at worst. Of course the macroeconomic environment matters. At the very least it shapes the opportunity set.

We also do people a huge disservice by teaching them economics as if it’s physics. Not only is it obnoxiously intimidating but it lends economics a false sense of precision. I believe we should really teach economics using an ecological framework. Macro fundamentals define our economic habitat. There is often a feedback loop between macro fundamentals and investor behavior. If you can develop actionable insights into that feedback loop, you can make a lot of money.

So what we’re really doing with macro analysis is trying to understand our habitat. Thinking about it this way de-emphasizes making point estimates of future economic growth, which are notoriously inaccurate.

What Does a Healthy Habitat Look Like?

In the natural world, we can evaluate the health of an ecosystem based on its values. Here are some ecosystem values courtesy of the EPA:

Ecosystem_Values
Source: EPA.gov

Economies can be evaluated along similar lines:

  • “Biotic Resources” (Demographics)
    • Is the labor force growing?
    • Is the labor force becoming more or less productive?
    • How educated and innovative is the labor force?
  • “Biodiversity” (How Diversified Is The Economy?)
    • Is economic activity highly concentrated in particular industries? If so, what are their characteristics?
    • Is there a diverse array of financial market participants providing ample liquidity? Or are markets fragmented and illiquid?
  • “Energy & Nutrients” (How Is The Economy Financed?)
    • What does national income look like?
    • Is there a current account deficit? If so, is the country heavily dependent on external debt?
    • Where is the economy in the credit cycle?

More Energy & Nutrients

I want to spend a little more time on “Energy & Nutrients” as this is where many of the traditional textbook macro concepts come into play. More importantly, when this area of the ecosystem gets squirrelly, really nasty outcomes tend to result. Financial crises and deep depressions and hyperinflations and such.

Let’s start with the classic GDP identity:

GDP = Government Spending + Consumer Spending + Investments + (Exports – Imports)

More commonly written as:

GDP (or Y) = G + C + I + (X-M) 

Most of this is pretty self-explanatory, but the X – M term bears further scrutiny. This term is also called the “current account.” If it is positive you are net exporter (trade surplus) and if it is negative you are a net importer (trade deficit). Negative current account balances must be financed somehow. Countries do this either by selling claims on their assets to foreigners or by drawing down foreign currency reserves.

You can decompose and rearrange this identity in various ways. I’m not going to spend a bunch of time doing that here. You can find plenty of resources online. For now just trust me when I say the current account is equal to the difference between investment and domestic savings.

This is a critical concept because there are three and exactly three ways to finance private investment (a.k.a economic growth): 1) out of consumer savings, 2) with a current account (trade) surplus, 3) debt and equity issuance.

There is a school of thought among certain individuals that trade deficits are always and everywhere evil. That issue lies well beyond the scope of this post. What’s more relevant is the potential for dangerous imbalances to build up inside economies dependent on external financing. Dangerous imbalances are the stuff of financial crises, political revolutions and sovereign defaults.

The Example of Egypt

The Egyptian economy is a disaster.

For much of the recent past Egypt was dependent on direct foreign investment and tourism for foreign currency to fund its current account deficit (Egypt imports significant quantities of food and fuel). These sources of financing dried up following the country’s 2010 revolution and ensuing political turmoil, draining foreign currency reserves, driving up government debt levels and ultimately forcing a devaluation of the Egyptian pound (which is pegged to the dollar in a futile valiant effort to maintain price stability).

Egypt_Current_Account
Source: Trading Economics
Egypt_FX_Reserves_USD
Source: Trading Economics
Egypt_Govt_Debt_GDP
Source: Trading Economics

Essentially, the Egyptian government printed money to finance economic activity. Naturally, this resulted in a dramatic spike in inflation.

Egypt_Inflation
Source: Trading Economics

Needless to say this is a fragile ecosystem (spoiler: most developing economies are). That doesn’t mean all Egyptian securities are automatically bad investments. However, it has direct implications for the kind of margin of safety you should demand when considering an investment.

You will notice I haven’t said anything about the domestic credit cycle. That’s because I’m not going to bang on about the credit cycle here when I can just have you watch Ray Dalio explain it in a slick YouTube video.

To Conclude: A Brief Note On Currencies

I picked the Egypt example above because of the currency component. Currency is an important wrinkle in international investing. There are lots of different approaches to currency valuation but longer term investors should mostly be focus on the idea of purchasing power parity. All else equal, a basket of goods in Country A should cost the same as an identical basket of goods in Country B.

In the real world all else is not equal. Namely: inflation. So if inflation is 2% in Country A and 10% in Country B, we would expect Country B’s currency to depreciate by 8% relative to Country A.

Purchasing power parity tends to hold up pretty well over long time horizons. In the short term, however, divergences can be significant. For our purposes the important thing to recognize is that a country’s national income and balance of payments have a direct impact on the inflation rate. Inflation differentials are important variables to consider when making international investments, because they influence the currency component of the investment return, which can be significant.

Nerd Stuff: Factor Valuation Edition

I have to give Research Affiliates some serious props for their online interactive (and, yes, free tools). I mentioned the asset allocation tool in a post from earlier this week. If you didn’t check out the tool then, you really should.

I did not realize until this morning that Research Affiliates also has a similar tool for factors, called Smart Beta Interactive. This allows you to slice and dice factor strategies and also the underlying factors themselves. I highly recommend checking this one out out, too.

Anyway, this post isn’t meant to be a Research Affiliates commercial. Instead, this is going to be a post on reflexivity. Behold, factor valuations for the US market:

RAFI_1Q18_Factor_Valuations
Source: Research Affiliates

Regarding their methodology, Research Affiliates states:

Just like stocks, bonds, sectors, countries, or any other financial instrument, equity factors and the strategies based on them can become cheap or expensive. We measure relative valuations of the long vs. short sides to estimate how cheap or expensive a factor is. We find that when relative valuation is low compared to its own history, that factor is positioned to outperform. When valuation is high it is likely to disappoint.

This is reflexivity in action. Briefly, reflexivity is a concept popularized by George Soros. The idea is that by taking advantage of perceived opportunities in the markets, we change the nature of the opportunities. Howard Marks likens this to a golf course where the terrain changes in response to each shot.

Here’s how this happens in practice:

Step 1: Someone figures out something that generates excess returns. That person makes money hand over fist.

Step 2: Other people either figure the “something” out on their own or they copy the person who is making money hand over fist.

Step 3: As people pile into the trade, the “something” becomes more and more expensive.

Step 4: The “something” becomes fairly valued.

Step 5: The “something” becomes overvalued.

Step 6: People realize the “something” has gotten so expensive it cannot possibly generate a reasonable return in the future. If prices have gotten really out of hand (and particularly if leverage is involved) there will be a crash. Otherwise future returns may simply settle down to “meh” levels.

Step 7: As the “something” shows weaker and weaker performance, it gets cheaper and cheaper, until some contrarian sees a high enough expected return and starts buying. The cycle then repeats. Obviously these cycles vary dramatically in their magnitude and length.

I do not consider myself a quant by any means, but I think the two most important things for quants to understand are: 1) why a factor or strategy should work in the first place, and be able to explain it in terms of basic economic or behavioral principles; 2) reflexivity.

Many people believe AI is going to push humans out of the financial markets. There is some truth in this. Big mutual fund companies that have built businesses on the old “style box” approach to portfolio construction are in trouble. The quants can build similar funds with more targeted exposures, in a more tax efficient ETF wrapper, and with lower expenses.

What I think people underweight is the impact of reflexivity. If the AIs aren’t trained to understand reflexivity, they will cause some nasty losses at some point. Personally, I think there will be an AI-driven financial crisis some day, and that it will have its roots in AI herding behavior. We are probably a ways away from that. But technology moves pretty fast. So maybe it will come sooner than I think.

Anyway, back to factor valuations.

What stands out to me is Momentum and Illiquidity at the upper ends of their historical valuation ranges. On the Momentum side this is stuff like FANG or FAANMG or whatever the acronym happens to be this week. On the Illiquidity side it’s private equity and venture capital. If you have read past posts of mine you know I believe most private equity investors these days are lambs headed to slaughter.

There tends to be a lot of antipathy between quant and fundamental people. Even (perhaps especially) if they are co-workers. The fundamental people are afraid of the quants. Partly because they are afraid of the math (a less valid fear), and partly because they see the quants as a threat (a more valid fear). Quants, meanwhile, tend to believe the fundamental people are just winging it.

In reality I think this is more an issue of language barrier and professional rivalry than true disagreement over how markets work or what is happening in the markets at a given point in time. In my experience, the best fundamental investors employ quant-like pattern recognition in filtering and processing ideas. Many quants, meanwhile, are using the same variables the fundamental people look at to build their models.

Personally, I think anyone who wants to survive in the investment profession over the next twenty years is going to have to be something of a cyborg.

Though, come to think of it, that probably applies to every industry.

Lies, Damn Lies and Active Share

These days it is fashionable to evaluate investment managers on a statistic called active share. Active share measures the similarity between a fund and a benchmark. Specifically, it compares the weighted portfolio holdings of a given portfolio to those of a benchmark index.

If I own everything in the S&P 500 portfolio in the same proportions my active share is 0%. In theory an index fund would have 0% active share but transactional frictions will create small differences.

Anyway, if I want high active share I can get it in several ways:

  • Own things that aren’t in the benchmark
  • Refuse to own things that are in the benchmark
  • Underweight things versus the benchmark
  • Overweight things versus the benchmark

All active share can tell you is that a thing is different from a given index. Full stop.

Shrewd marketing people have done their best to distort this to mean “funds with high active share are better.” This is nonsense. If I pick 10 stocks outside the S&P 500 at random I will show an active share of 100%. You would have to be an idiot to buy my fund on the basis of its active share.

Shrewd marketing people get traction with the notion that “funds with high active share are better” because it IS true that dramatic outperformance results from being 1) very different, and 2) very right. Very different on its own doesn’t get the job done. Being very different and very wrong for example is ticket to the poorhouse.

Active share is a popular statistic because it is easy to calculate and easy to understand. People are always on the lookout for that “one weird trick” they can use to hack the system for more money, better looks and lots of sex.

Unfortunately that’s not how quantitative analysis works.

Quantitative analysis isn’t “pure” mathematical reasoning. It’s inductive reasoning. When we prove things in mathematics, we know they are true. We don’t actually prove anything using statistics. Rather, we “fail to reject the null hypothesis at such-and-such a confidence interval.” This is the problem of induction.

Doing a statistical analysis of an investment strategy is like trying to assemble a puzzle where the pieces are constantly changing shape (albeit pretty slowly and by pretty small amounts). Active share is just one of those pieces. Even then you have to recognize that the results of the analysis are backward looking. There’s no guarantee those statistical relationships will persist in the future.

So, you know, caveat emptor.

Cause and Effect

This is a quick follow-on from an older post. That post discussed the issue of low interest rates and their impact on justified valuation multiples. I wrote:

A popular contrarian narrative in the markets is that central bankers have artificially suppressed interest rates, and that absent their interventions the “natural” rate of interest would be higher (implying a higher discount rate and thus lower sustainable valuation multiples). The key risk to this thesis is that low rates are not some exogenous happening imposed on the market by a bunch of cognac swilling technocrats, but rather a consequence of secular shifts in the global supply and demand for funds. Specifically, that these days there is a whole boatload of money out there that needs to be invested to fund future liabilities and too few attractive investment opportunities to absorb it all.

If low rates are actually a function of the supply and demand for funds, it doesn’t ultimately matter what central bankers intend do with monetary policy. Market forces will keep rates low and elevated valuations will remain justified.

A friend questioned what I was driving at here, and whether it would be possible to falsify this thesis. For the record, I have no idea whether I’m right or wrong. I’m just trying to envision different possibilities.

That said, I am pretty sure the answer lies in the shape of the yield curve.

As many, many, many commentators have already observed, the Treasury yield curve hasn’t made a parallel shift upward as the Fed raised short-term rates. The short end of the curve has come up pretty significantly but the long end has basically held steady. This is important because central banks tend to have less influence over long-term rates than short-term rates.

chart
Source: Bondsupermart.com

As the Fed continues to shrink its balance sheet, what we would hope to see is the yield curve making a nice, steady, parallel shift upward. What we do not want to see is the 30-year Treasury yield stuck at 3%. The 30-year Treasury yield stuck at 3%, in the absence of Fed intervention, would support the theory that there are structural factors holding down future expected returns. Namely: an excess supply of financial capital relative to opportunities.

My previous posts on this subject have dealt with the risks of naively extrapolating very low interest rates forever. You can attack the issue from different angles but each case more or less boils down to overpaying for risky cash flows.

What I have not done is explored strategies for taking advantage of such an environment. As with the risks, you can attack the issue from a number of different angles. But again, they share a common thread. Here each strategy more or less boils down to taking on duration.

I want to examine this further in a future post, but here is a little teaser…

Duration is most commonly used to analyze interest rate risk in the fixed income world. But the concept can also be applied to other asset classes. Long duration equities are things like venture capital and development stage biotech companies, where cash flows are but a twinkle in your eye when you invest. Long duration equities usually can’t sustain themselves without repeated infusions of investor cash. They thrive when capital is cheap. They die when capital gets expensive.

If you knew capital was going to be remain cheap forever, you would probably want to make long duration equities a significant portion of your portfolio. You could get comfortable investing in really big ideas that would take a long time to be profitable. I am talking about massive, capital intensive projects with the potential to change the world (think SpaceX).

And here’s where I might start getting a little loopy…

…because what if an excess of financial capital is a precondition for tackling the really big projects that will advance us as a species?

Netflix Levers Up (again)

From Dow Jones Newswires (emphasis mine):

Netflix Inc. (NFLX) said Monday it is planning to tap the high-yield bond market with a $1.5 billion deal. The company said it will use the proceeds for general corporate purposes, including content acquisition, production and development, capex, investments, working capital and potential acquisitions and strategic deals. The company’s most active bonds, the 4.875% notes that mature in April of 2028, last traded at 96.50 cents on the dollar to yield 5.332%, or at a yield spread of 239 basis points over Treasurys, according to trading platform MarketAxess.

I’m not going to belabor the point here. You can decide for yourself whether 5.332% is appropriate compensation for lending on a 10-year term to a company management says will burn $3bn to $4bn of free cash in 2018.

Disclosure: No position.