In Defense of Narratives

Lately there’s been something of an assault on the narrative as a viable tool in the analyst’s toolbelt.  My friend Barry Ritholtz dissed the narrative in a presentation he gave at his Big Picture Conference in early October (his presentation was titled, “To Win on Wall Street Don’t Tell Stories”), and last week blogger Felix Salmon used the Greg Smith/Goldman Sachs saga to tar the act of narrative construction as little more than an unconscious defense mechanism against the harsh realities of the objective world.

Barry and Mr. Salmon are both on to something — narratives can lead an analyst astray and they can be used as a shield against a difficult-to-accept reality — but neither blogger points out that narratives are indispensable when it comes to making sense of data (in Barry’s case) or reality (in Mr. Salmon’s).  I suspect that both of them would hasten to agree with me on this point, and that both would protest that they were merely arguing against the misuse of narratives.  Nevertheless, I think it’s important to set the record straight, and the record shows that the ability to take facts or data or events and from them construct a narrative is indispensable whether you’re trying to succeed in the market or in life.

Because I’ve got the CFA on the brain, I’ll start there.  On page 572 of Volume 1 of the Level 1 curriculum, authors Fusco, McLeavey, Pinto and Runkle state:

“The absence of an explicit economic rationale for a variable or trading strategy is the “no story” warning sign of a data-mining  problem.  Without a plausible economic rationale or story for why a variable should work, the variable is unlikely to have predictive power.”

The authors go on to cite Leinweber’s 1997 discovery that butter production in Bangladesh, cheese production in the U.S., and the sheep population in both Bangladesh and the U.S. “explain” (statistically) 99% of the movement of the S&P 500 Index.  With a simple narrative such as, “The S&P 500 Index moves in response to myriad monetary, financial, economic, geopolitical, behavioral and idiosyncratic (“company-specific”) factors both domestic and global,” one can easily dispel the notion that butter, cheese and sheep production in Bangladesh is the sole determinant of the S&P 500′s direction.  Without this most basic of narratives, “rational” investors would be flocking to Bangladesh and investing heavily in low latency connections to NYSE’s and Nasdaq’s data servers in New Jersey — and they’d be losing their shirts.  (At least I think they would be.  Truth be told I haven’t bothered to look at the Bangladeshi dairy production figures lately, let alone compare them to the SPX.  Another analyst falls prey to an over-reliance on the narrative!)

I submit that an accurate narrative should in fact be one of the main goals of any analyst — or of any human being who wishes to live in harmony with the rest of the universe — and that attention to facts and data are essential precisely because they allow us to construct a more accurate narrative.  Another of the analyst’s main goals should be to find or construct a viable analytical framework with which he or she may extrapolate future facts or data points.  The narrative is simply the story from the past to the present; the framework sketches out how the story is likely to end based on logic and observation of how similar stories have ended.

More to the point, objective reality is not a dynamic matrix of facts and figures that manifest spontaneously such that the best an analyst can do is assiduously record them and proclaim their existence — as if this constitutes analysis!  Objective reality is an in-progress work of art that simultaneously exists — unequivocally, indisputably, and in fact-and-figure form — and provokes human-artists into acting in ways that alter its existence.  Because human beings naturally construct narratives from their observations of reality, they act according to those narratives.  Thus, objective reality itself takes the form of a narrative, or, more likely, an interplay of myriad narratives.  Facts and figures — “the data” — are there to clue us in to how these narratives are unfolding.

To Barry and Mr. Salmon, I say let’s make a deal:  I’ll concede that too many of us spend too little time observing and gathering data if you’ll concede that proper analysis (and proper living) requires a narrative.

Characterizing the portfolio

I’ve reached the part of the CFA curriculum that deals with descriptive statistics, and it occurred to me that I have the perfect vehicle for applying what I’ve learned:  the portfolio.  It took me about 90 minutes to put together a basic appraisal of the portfolio and juxtapose it against an appraisal of a portfolio that tracked my benchmark, the Russell 3000, with no tracking error.  First, let’s look at a histogram that shows the portfolio’s frequency of daily returns in roughly 1% intervals:

Right off the bat, we can see that the distribution is relatively normal looking but with some negative skew (greater frequency of abnormally large negative values).  Most of the 92 daily returns fall in the 0.15% to 1.14% interval.  Crunching the numbers, we find that the portfolio has the following statistical attributes:

Average (mean) daily return:  1.4 basis points

Median daily return:  24 basis points

Standard deviation from the mean:  1.97%

Skew:  -0.65

Excess kurtosis:  0.40

Coefficient of variation (risk per unit of return):  137

Sharpe Ratio:  0.00

The median daily return of 24 basis points confirms that there were more up days than down days for the portfolio, but the mean return of 1.4 basis points is a reminder that there were a handful of really big down days.

The standard deviation from the mean, a measure of dispersion, is 1.97%.  The skew, which we eyeballed earlier when looking at the histogram, is -0.65.  The CFA curriculum notes that “for a sample size of 100 or larger taken from a normal distribution, a skewness coefficient of +/- 0.5 would be considered unusually large” (p. 402).  Our sample size of 92 is pretty close to 100, so we can probably conclude that our skew is “unusually large.”  Given that the CFA curriculum also notes that “some researchers believe that investors should prefer positive skewness,” we’ll frame our skew factor of -0.65 as an undesirable attribute.

Excess kurtosis greater than zero, which the portfolio has, is a sign that more returns reside in the “tails” (i.e. near -5.79% and 4.02%) than normal.  Interestingly, the CFA curriculum notes that “most equity return series have been found to be leptokurtic.”  The authors conclude, “If a return distribution has positive excess kurtosis (leptokurtosis) and we use statistical models that do not account for the fatter tails, we will underestimate the likelihood of very bad or very good outcomes.”

Finally, the coefficient of variation, which measures risk (standard deviation) per unit of return (mean return), is 137.  We’ll use that for comparison with the Russell 3000 portfolio further down in the post.  The Sharpe Ratio, which measures opportunity cost-adjusted return per unit of risk (standard deviation), is essentially zero — not surprising given that the mean return was essentially zero (1.4 bps) as well.

Now let’s have a look at the same information for a portfolio that tracks the Russell 3000 Index.  First, the frequency histogram:

Note that the range for the R3K portfolio – -2.58% to 2.62% — is much tighter than our portfolio’s range of -5.79% to 4.02%.  Must be nice not having SUPERVALU account for 10% of your portfolio.  Most returns are clustered in the -0.50% to 0.02% interval.  It’s difficult to determine skew just by eyeballing the chart given that the tails look similar.  We’ll guess that skew is close to zero even if we can’t quite guess its sign (+ or -).  Here are the raw numbers on the R3K portfolio:

Average (mean) daily return:  2.7 basis points

Median daily return:  -3 basis points

Standard deviation from the mean:  0.95%

Skew:  0.14

Excess kurtosis:  0.72

Coefficient of variation (risk per unit of return):  35

Sharpe Ratio:  0.03

The average daily return of 2.7 bps is nearly twice our portfolio’s 1.4 bps.  The median return is actually slightly negative, a tip off that skew may be positive.  And indeed, skew is positive at 0.14.  We were correct in assuming that the skew was slight (close to zero) after glancing at the histogram.  Excess kurtosis of 0.72 indicates a greater-than-normal frequency of tail-centric values, although it’s less than 1.0, the number above which the authors of the CFA curriculum would consider the excess kurtosis to be ”unusually large.”

The coefficient of variation is 35, which means that an investor in the R3K portfolio is taking about a quarter of the risk per unit of return as an investor in our portfolio.  Yikes.  The Sharpe Ratio of 0.03 reflects the near-zero mean return of 2.7 basis points, but it’s still higher than our portfolio’s Sharpe Ratio of 0.00 (it’s actually 0.0049).

To summarize, an investor in the Russell 3000 portfolio would have had a better average return, less risk (as measured by standard deviation), and a more desirable skew than an investor in our portfolio from April 30th to September 7th.  The “less risk” aspect could have been predicted given the fact that there are nearly 3000 stocks in the R3K portfolio versus 10 stocks in our portfolio.  As for the returns and the skew, well, I guess I’m just a crappy stock picker.

Two kernels from the CFA curriculum

“It frequently happens that when a company’s EPS is close to zero — at a low point in the business cycle, for example — its P/E is extremely high.  The high P/E in those circumstances reflects an anticipated future recovery of earnings.  Extreme P/E values need to be investigated and handled with care.” — page 364 of Volume 1 of the 2012 CFA Program Curriculum

“Typically, value stocks are defined as those for which the market price is relatively low in relation to earnings per share, book value per share, or dividends per share.  Growth stocks, on the other hand, have comparatively high prices in relation to those same measures.” — page 380 of Volume 1 of the 2012 CFA Program Curriculum

There’s nothing remotely novel about these two assertions, but as building block-type observations go they’re pretty useful.  Earnings reflect cyclical factors which means high multiples on trailing earnings may not signal an overvalued stock (particularly as earnings per share approaches zero); and, the difference between a value stock and a growth stock is the prevailing multiple.

As far as applicability to my model portfolio goes, the first kernel is more significant for its corollary:  just as an extremely high multiple doesn’t necessarily make for an overvalued stock, an extremely low multiple (read:  SUPERVALU and all the other stocks in the portfolio) doesn’t necessarily make for an undervalued stock.  Stocks are claims on long-term earnings streams, not just next year’s earnings, and if the long-term viability of a company is in doubt it will show up as a deceivingly low multiple on near-term earnings estimates.

The second kernel is really nothing more than a definition, but I’ve highlighted it because it serves as a reminder of the portfolio’s value-centric bent.

Portfolio Update

The model portfolio is down -0.4% since inception (April 30th opening prices adjusted for commission), which compares unfavorably to the Russell 3000′s 2.1% gain over the same period.  Here’s a chart showing the percentage appreciation/depreciation of the portfolio (recall that it was roughly equal-weighted across the ten holdings at inception and that I am not rebalancing it), the stocks in the portfolio, and the Russell 3000:

So obviously SUPERVALU hit a little bit of a snag.  On July 11th after the bell the company reported a big profit miss (19cps versus the median Street estimate of 30cps) and also a revenue miss ($10.59 billion versus the median Street estimate of $10.77 billion).  The stock halved in value the following day and has languished between $2 and $2.50 per share ever since (the stock closed at $5.29 just prior to that earnings release).

SUPERVALU booted its CEO, former Walmart executive Craig Herkert, two weeks later.  Here’s what Herkert had to say about the quarter on the earnings call:

“Our performance reflects the fact that we did not move quickly enough to respond to intensifying competitive conditions in our industry.  Consumers’ price sensitivity has intensified given the continuing weak economic environment, and this has led many retailers to become even more aggressive on promotions and price investment, and to step up their marketing activity in several of our key markets.” (source:  Bloomberg)

The company claims that it is “exploring strategic alternatives to create value for the company’s shareholders,” so it’s possible the company is taken out at some point.  Meanwhile, the stock now trades at 3.5x its 2013 earnings estimate, down from 4.2x heading into its earnings announcement and 6.4x one year ago.  The cheap get cheaper.

A lot can happen in three months

Closer to four months actually.  Work’s been intense and some (positive) personal developments have kept me busy too.  All good stuff.  In the meantime, I’ve begun to study for Level 1 of the CFA exam.

I vacillated for years over whether or not I should attempt to earn the CFA designation, and I always came up with an excuse to put it off.  Either I didn’t think I needed it (2003-2007 when I was trading) or my career as a macro strategist seemed to be going too well to bother with it (2007-2011).  Truth be told, I’ve always looked askance at the CFA program as I reckoned it to be nothing more than a gateway into the business for unimaginative-but-hard-working types.  And I, in my pride, was anything but an unimaginative-but-hard-working type!

Having been force-fed a goodly amount of humble pie in the last year, I’ve changed my tune and now find myself enmeshed in the first of six Level 1 study books.  Lo and behold, the material isn’t that painful.  In fact, a lot of it seems quite useful for a top-down guy looking to go bottom up.

In what I’m hoping will be a valuable cross-fertilization exercise, I’ll be blogging about ideas and concepts in the CFA curriculum as they pertain to my pathetic mock portfolio (more on that in a minute) and to my broader goal of becoming a bona fide investor.  I figure the CFA material should improve my investing acumen while blogging about it should enhance my ability to retain the information for the upcoming exam.

A fine theory, isn’t it?

Goodyear…still slogging through the 10-K

I’m still laboring through the Management’s Discussion and Analysis section, and I’ve come across a few notable items in the discussion of the performance of the company’s Strategic Business Units.  First, North America:

  • In the North American business, net sales were roughly $9.9 billion in 2011, up $1.7 billion from 2010′s $8.2 billion.  As sales volume was down a touch on the year (66.0 million tires vs. 2010′s 66.7 million tires), the improvement in net sales resulted from price increases and improved “mix” (i.e. they sold more expensive tires), as well as an increase in non-tire sales (mostly industrial chemicals).  Price and mix accounted for 60% of the increase in sales while increased chemicals sales accounted for most of the rest.
  • Operating income was $276 million (2.8% margin), up $258 million from 2010′s $18 million.  Of the $1 billion in price increases and improved mix at the top line, $883 million flowed through to the bottom line, completely offsetting (and then some) the raw materials cost increases amounting to $706 million.  The rest of the improvement in operating income came from cost cutting and favorable currency movements.

Moving to EMEA (Europe, Middle East & Africa):

  • German net sales accounted for 37% of total EMEA Tire net sales in 2011 — up from 35% of sales in 2010.
  • Europe’s brutal winter helped EMEA sales volume increase to 74.3 million tires from 2010′s 72.0 million tires (“strong winter tire sales” cited in the 10-K).  However, even Original Equipment (“OE”) sales, upon which weather conditions should have a modest, if any, impact, were up 6.7% on the year thanks to increased demand from car and truck makers.
  • Aside from the slight increase in sales volume, EMEA Tire’s results were similar to those of North American Tire.  EMEA Tire also saw a roughly $1 billion top line increase from improved pricing and mix, and it also saw most of that ($930 million) flow down to the bottom line, offsetting sharp increases in raw materials costs ($651 million).  In other words, pricing and mix improvements outweighing an increase in raw materials costs is the main story for EMEA Tire, just as it was for NAT.
  • EMEA Tire didn’t have to cut costs to achieve better results as NAT did, however.  SG&A costs rose by $91 million in the region thanks to higher advertising costs, wage increases and increased warehousing costs.  Despite the increase, 2011 operating income for EMEA Tire jumped to $627 million from 2010′s $319 million.

Switching to Latin America:

  • Right off the bat, Latin American Tire’s (“LAT”) results provoke concern.  Why?  Operating margins dropped to 9.3% in 2011 from 15.3% in 2010 and 16.6% in 2009.
  • The extent of Brazil’s domination of LAT’s operations exceeds Germany’s domination of EMEA Tire:  it accounted for 58% of LAT’s net sales in 2011, down from 61% in 2010.
  • Sales volumes dipped to 19.8 million tires in 2011 from 20.7 million in 2010 (still up from 2009′s 19.1 million).  Competition on the lower end of the quality scale from imported Asian tires apparently explains the dip.  Net sales managed to increase to $2.5 billion from 2010′s $2.2 billion thanks to — you guessed it — improvements in pricing and mix to the tune of $296 million.  The decrease in sales volume took about $100 million off the top line, but that was replaced by a roughly $100 million increase from sales in non-tire-related businesses.
  • As with the other regions, most of the pricing/mix increases flowed down to the bottom line ($266 million), offsetting a $249 million increase in raw materials costs.  Operating income dipped in 2011, however, to $231 million from 2010′s $330 million.  The culprits?  Lower sales volume translated into a $30 million income decline, for one.  Another culprit was wage inflation:  it accounted for $12 million in increased SG&A costs and an unspecified percentage of $61 million in higher conversion costs (conversion costs are those manufacturing and labor costs attributed to converting raw materials into finished products).
  • Apparently, the entire $99 million y/y decline in LAT’s operating income took place in Brazil.

Finally, we turn to the Asia Pacific region:

  • Asia Pacific Tire’s (“APT”) results look very similar, at first blush, to LAT’s:  dip in sales volume (to 20.5 million tires from 21.4 million), increase in net sales ($2.4 billion from $2.1 billion), dip in operating income ($234 million from $250 million) and declining operating margins (9.8% from 2010′s 12.1% and 2009′s 12.3%).  Basically, the same broad strokes as LAT.
  • The company blames the Japanese earthquake (Q2) and the Thai floods (Q4) for much of the decline in OE sales.  On the replacement sales front, declines in New Zealand and Australia (“weak retail environment”) outweighed increases in China and India.
  • The increase in net sales resulted from better pricing and mix, and also favorable currency movements in Australia and China.  The $16 million decline in operating income was almost entirely caused by the Thai floods, which took $12 million off the bottom line due to lower sales volumes and higher conversion costs. Making the income decline worse were the $40 million in start-up costs for a new facility in Pulandian, China, higher SG&A costs and modestly higher transportation costs.  The $277 million boost from pricing and mix offset the $216 million increase in raw materials costs.
  • Australia is the behemoth in the region, accounting for 44% of APT’s net sales in 2011 (up from 43% in 2010).

That’s it for today.  A clearer picture of Goodyear is starting to emerge…exciting stuff!

JPMorgan: The Philanthropists

“‘Two years ago they kind of kicked off [renewed market activity in risky  assets],’ said one banker who sells financial debt. ‘It was like they provided some kind of ‘philanthropic’ service to the market to encourage it to get going.’”

from JPMorgan unit has $100bn of risky bonds, by Sam Jones, Tracy Alloway and Tom Braithwaite in the FT

I forwarded this comment around to some friends recently, and I didn’t get much feedback.  I suppose we shouldn’t be shocked that a bank as large and influential as JPM played a role in the economic and market recovery of 2009-10.  That was a period, if you recall, in which so many laws, rules, conventions and taboos were broken by high ranking government and banking officials in an effort to put a floor under the stock market (and other markets for “risky assets”) that it was impossible to be overly galled by any one action.

Still, this revelation — if true — that JPMorgan was the agent by which policy decisions manifested themselves in market prices (prices which might not otherwise have reacted to said decisions) is truly valuable.  It confirms a long-held suspicion of mine, that price movements aren’t always the result of spontaneous, simultaneous impulses from a decentralized network of market participants in reaction to new information — not, in other words, like a school of fish darting to and fro with perfect synchronicity.  Instead, this tidbit of information on JPM’s presence in the markets suggests that a single player — a connected player, a player embedded in the fabric of government policy — stuck its rather thick neck out and signaled to its competitor-peers that it was safe to speculate.

Again, we don’t know that this is true, and even if it is true it’s not totally shocking.  Nonetheless, in a mosaic theory kind of way it complements a narrative about how our markets work that has always appealed to me:  reflexivity between price and reality isn’t un-governed.  Sometimes, governments and other vested interests intervene in markets in a very tangible way.

Couple things on Goodyear

A couple of items from the Goodyear 10-K stood out.  First, they’ve got a lot of debt and significant pension obligations:

$ millions

Second, U.S. operations lose money every year (although 2011 was a close call):

Looking at the above chart, it occurs to me that the improvement in U.S. pretax income in 2011 is likely a result of the closure of the Union City, Tennessee facility that management keeps talking about.  That thing must have been bleeding cash.

Goodyear…properties and legal proceedings

I believe I left off with Goodyear’s Risk Factors in my last post.  Now we’ll turn briefly to their 53 manufacturing facilities scattered across the globe.  Eighteen of them can be found in North America:  nine tire plants, 4 chemical plants, 2 aviation retread plants, a tire mold plant (for making the molds used to make the tires), a tire retread plant and a mix plant.

MENA Tire, meanwhile, has 19 facilities:  sixteen tire plants, a tire mold plant, an aviation retread plant and a mix plant.  Asia Pacific Tire and Latin American Tire own and operate 9 and 6 facilities, respectively.  The company also owns and operates 2 R&D centers and technical centers, as well as three tire proving grounds.  The company operates, but does not own, fourteen hundred retail outlets, 50 tire retreading facilities and 170 warehouse distribution facilities (these properties are leased).

Plant utilization rose to 91% in 2011 from 88% in 2010 and 73% in 2009.  Credited with the increase in utilization in 2011 was the July 2011 closure of a high-cost facility in Union City, Tennessee.

Let’s turn now to legal proceedings.  The company spent $23 million in 2011 defending itself against asbestos-related claims.  It received subpoenas from the DoJ and European antitrust officials related to an alleged price fixing scheme in the marine hose industry (marine hoses connect the valves from docked oil tankers to the valves on the dock for transportation purposes).  It is defending itself against allegations of anticompetitive behavior in South Africa, bribes in Kenya and Angola, and taking improper tax credits in Brazil.

Finally, we’ve pushed through to the Management’s Discussion and Analysis section!  It was tedious, but we made it!  The MD&A section will be covered in my next post.

A macro thought

The portfolio slipped up today relative to the Russell 3000:  the portfolio fell -0.8% versus the R3K’s -0.4% drop.  Free Solar fell out of bed, losing -6.4% on the day, and that accounted for all of my underperformance and then some.  SUPERVALU was the other loser, dropping -1.6%, bringing its seven-day performance to an astonishingly bad -12.0%.  Assurance Guaranty is down -9.0% in that time frame.  My three airline stocks, Western Digital and Navarre are propping the portfolio up at the moment.

On a macro note (because I can’t resist), it was interesting to see the NFIB Small Business Optimism survey surprise to the upside this morning.  Some of the survey components like profit growth and capex intentions pushed to new highs for the cycle.  I continue to wince as both bulls and bears (who are rightly fixated on Europe) whine about how the other side doesn’t get it.  News flash to both sides:  you’re both going to be disappointed.

The U.S. economy is being propped up by stock market manipulation (a financial palliative) and by massive fiscal deficits (an economic palliative).  The corporate sector in the States is intent upon “maximizing shareholder value” and so it’s skimming off most of the fiscal largesse for itself.  That’s keeping corporate profit margins elevated, thus inflating the earnings component of the market’s P/E and masking the stock market bubble.  Unfortunately, elevated profit margins are also depriving the household sector of the income growth needed to restore its collective balance sheet to health, and that’s keeping a lid on the cyclical economic upswing.

Can this “unbalanced balance” in the U.S. continue?  Yes, it can — so long as relative prices remain steady.  Whether or not shale gas turns out to be a panacea, we are massive consumers of energy both at the household and corporate level.  Energy prices and the prices of other commodities therefore need to stay in check (particularly non-ag commodities, since we are net exporters in the ag department).

Steady relative prices eh?  Seems easy enough, but keep in mind that the key to perpetuating this unbalanced balance is unrelenting monetary emission by the Treasury Department (for the economy) and the Fed (for the banking system).  Unrelenting monetary emission tends to put upward pressure on commodity prices.

In summary, the U.S. is a ramshackle economy which, despite some vestigial competitive advantages over other countries, has been corroded and weakened by decades of central planning and central banking.  The current “recovery” will plod along as long as the Fed makes dollars available to Europeans (it will) and as long as relative pricing is steady.  In this regard, evaporating demand for commodities in recession-stricken Europe and maladjusted China may create the pricing backdrop the U.S. economy needs to stay afloat in the next year or so.

Bullish (on the U.S. economy)?  Nah.  Just not as bearish as some of my friends.