An Accident Waiting to Happen
I don’t waste tons of time on macro analysis, but I think it’s folly to ignore
macroeconomic data as well. As the most junior component in a corporation’s capital
structure, equity has to be paranoid. Every level of a corporation’s capital structure is a
derivative of the fundamentals of the corporation and a corporation’s fundamentals are
to some degree a derivative of macroeconomic conditions. Therefore, I think it’s just
doctrinaire and received wisdom to ignore macro factors.
There is a massive accumulation of inventory in the economy that has been underway
for a few years. That’s fine coming out of recession, once the liquidation event has
passed, but we’re seven years removed from entering the crisis and inventories are at
their highest level since 2000, according to the inventory / sales ratio on Census
Bureaui data.
I will confine my discussion of the larger inventory / sales ratio to flows and stocks ex.
petroleum. Energy varies wildly in price and we’ve been through some huge cycles in
the last 15 years, so I believe the ratio is best illustrated looking through petroleum.
Below we see the longer-term (back to 1992) inventory / sales ratio, as adjusted:
Exhibit 1: Wholesale Inventory / Sales Ratio, Ex Petroleum
Source: Census Bureau, Bloomberg, VT
1.55
Inventory / Sales (Ex Petroleum)
1.50
1.45
1.40
1.35
1.30
1.25
1.20
We were 1.5 standard deviations from the mean at the end of August, which doesn’t
sound that brutal, but this was the 15th highest reading in the last 284 months. Below
are the 30 highest monthly readings during this period:
Exhibit 2: Wholesale Inventory / Sales Ratio, Ex Petroleum, Rank Ordered
Source: Census Bureau, Bloomberg, NBER, VT
Period
Rank
GDP
Grow th
Period
Rank
GDP
Grow th
1/31/2009
12/31/2008
3/31/2009
11/30/2008
2/28/2009
4/30/2009
5/31/2009
6/30/2001
5/31/2001
4/30/2001
6/30/1992
6/30/2015
6/30/2009
12/31/1992
8/31/2015
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
(5.5%)
(8.5%)
(5.5%)
(8.5%)
(5.5%)
(0.5%)
(0.5%)
2.1%
2.1%
2.1%
4.4%
3.9%
(0.5%)
4.0%
1.5%
3/31/1993
12/31/1993
3/31/2001
10/31/2001
1/31/1992
10/31/2008
5/31/2015
5/31/1992
7/31/2001
3/31/2015
9/30/2001
7/31/2015
2/28/2015
3/31/1992
2/29/1992
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
0.7%
5.3%
(1.1%)
1.1%
3.7%
(8.5%)
3.9%
4.4%
2.1%
0.6%
(1.3%)
1.5%
0.6%
4.7%
4.7%
The shaded rankings indicate the US economy was in a recession at that point, based
on National Bureau of Economic Research dating.ii In five of the non-recession periods,
GDP was growing at a sub-2.0% rate and six of the 14 periods have taken place in
2015. That’s nearly half those periods and GDP accounts are always subject to revision,
as are NBER pronouncements on the timing of recessions.
Let’s take a look at the two components of this ratio over the last three years:
Exhibit 3: Wholesale Inventory, Sales, YoY Growth
Source: Census Bureau, Bloomberg, VT
Inventory
Sales
10.0%
9.0%
8.0%
7.0%
6.0%
5.0%
4.0%
3.0%
2.0%
1.0%
0.0%
The rate of growth of wholesale sales has been declining for many months while
inventory growth has been running well in advance of sales growth for nearly two years,
driving this inventory / sales ratio explosion:
Exhibit 4: Wholesale Inventory / Sales Ratio, Ex Petroleum
Source: Census Bureau, Bloomberg, VT
1.42
Inventory / Sales (Ex Petroleum)
1.40
1.38
1.36
1.34
1.32
1.30
1.28
The Relevance for Profits. The question should always be asked: “If so, so what?” I
was going to write this note before realizing I first had to cover the concept of production
flow as it relates to margins (please click here for that post, Calculating COGS).
Historically, many recessions have been caused by inventory corrections. When there
has been an undesired accumulation of inventory, it can go on until something in the
value chain snaps. Distributors might stop ordering or demand concessions from
producers that are refused, the money market may seize, or there may be an
exogenous shock (energy-related or geopolitical), among other things. The minute
production starts to adjust, unit costs increase and margins start to erode.
That forces a reduction in fixed costs, both in terms of direct labor and overhead and in
terms of SG&A. Fixed assets are liquidated and ready assets are sold.
Exhibit 5: Dialogue from Movie Armageddon, Regarding Landing on a Global
Extinction Event Asteroid and Knocking It Off-Course with a Nuke
Source: IMDB
This is how unemployment increases, asset values are pushed down, unit costs shoot
up and push down margins, and how a breakdown in pricing integrity by panicked
elements in the value chain can further depress margins.
Let’s put it this way – the inventory / sales ratio is a pile of oily rags and dry tinder in the
corner of the basement. There’s a box of matches nearby. And a badly recidivist
pyromaniac has been seen hanging around. Conditions are ripe for a big accident,
according to all precedent.
Can the Fed Ride to the Rescue? May I be succinct? I have no idea. I do believe,
though, an under-appreciated effect of Fed policy in the post-crisis era has been to
promote the accumulation of inventory. People generally understand it has caused
asset inflation in homes and real assets, as well as financial assets, but I don’t think the
inventory piece of that is well recognized. The downside to that is what happens when
inventory goes into liquidation? I don’t think the Fed is going to be able to help that.
Traders in financial assets might like that, but is an ink company or a beer wholesaler
going to respond and say, “Yeah, risk on, baby!” I doubt it. Actually, I’ll just say no
unless the Fed wants to start with helicopter money. And I’m not speaking
metaphorically there; it actually mails people currency or credits their bank accounts
with money.
I don’t know when or if this will become a problem. That’s the fun of exogenous shocks.
I just know the pressure is building. Why don’t firms respond now? It’s all based in
incentives. For one, the cost of carrying inventory is low. It’s certainly low in terms of
explicit capital costs. The cost of equity hasn’t moved as much as interest rates, in my
opinion, and many corporate executives and boards ignore the implicit cost of equity.
There’s also the margin damage a downshift in production would entail. I have a short
on where I can see their inventories exploding. If they slow down production, their
margins are going to get whacked. Check out their days in inventory:
Exhibit 6: “X” Company DSI
Source: Company filings, VT
200
180
160
140
120
100
80
This stock has already gotten hammered on earnings revisions and I think it’s easy to
see it getting halved again if they slow down and have to take another 25% to 50%
reduction in annualized earnings power (as seen by the market). I plan on covering and
going long when this gets crushed, management gets pushed out, and the Board comes
to its senses on a runaway M&A spree that has been very iffy and has gotten worse. I
wouldn’t have a hard time believing this is happening across industries.
In Which Industries Are We Seeing Pressure? Below is a table of the various sectors
captured in the Census Bureau data, ranked by the standard deviation of current DSI
from the 1992-present mean (in 1-2 cases, the 1997-present mean). I also looked at the
sensitivity of DSI to a 1 and 2 standard deviation decline in YoY sales, which you see on
the right side of the table. This is the standard deviation of the resulting DSI that would
come about if YoY sales declined by one and two standard deviations from the longerterm mean in YoY changes in sales for each category. Apologies here if the prose is
clumsy.
Exhibit 7: Days Sales in Inventory, Current; Sensitivities
Source: Census Bureau, Bloomberg, VT
Machinery
Metals
Alcohol
Hardw are, plumbing, heating
Apparel
Autos
Durables
Lumber
Chemical
Petroleum
Nondurable
Farm products
Furniture
Computers
Grocery
Professional, Comm'l equipment
Paper
Drug
Electrical
Total
Total ex petroleum
DSI
Aug-15
87
69
41
64
61
53
50
47
37
13
29
36
49
26
20
33
28
31
30
39
42
St Dev
Current
2.4
2.4
1.9
1.6
1.6
1.5
1.4
1.3
1.1
0.8
0.7
0.7
0.6
0.3
0.3
(0.3)
(0.4)
(0.8)
(1.4)
1.1
1.5
St Dev of DSI w ith sales drop of
1 st dev
2 st dev
3.3
4.8
4.6
8.1
2.4
2.9
3.0
4.7
2.3
3.4
1.9
2.2
3.1
5.1
2.5
3.9
3.9
6.2
4.2
9.8
2.2
3.7
2.6
5.3
1.7
3.0
1.6
2.6
0.9
1.4
0.2
0.8
0.6
1.9
(0.7)
(0.4)
(0.8)
(0.2)
2.5
3.1
4.8
4.0
Graphing the 1992-present history of the standard deviation of DSI from the mean
provides the same pattern as exhibit 1, but frames a bit differently:
Exhibit 8: Inventory / Sales Ratio, Standard Deviation from Long-Run Average
Source: Census Bureau, VT
5.0
4.0
3.0
2.0
1.0
0.0
(1.0)
(2.0)
(3.0)
To argue the other side of the case, industrial distributors may be carrying LIFO layers
that embed much higher variable costs, which would inflate in the inventory / sales ratio
in the numerator while the current sales results would contain prices closer to spot
market conditions, deflating the denominator. Units in inventory, or real inventories, are
likely dropping faster than stated inventory value if LIFO layers embed higher costs and
haven’t yet cleared from balance sheets. To me, these are the most valid antithetical
points on the other side of my dire hypothesis. There aren’t enough data in the Census
Bureau reports to sift through the issue more clearly, but reasoning from micro to
macro, I can see this side of the issue.
i
The Monthly & Annual Wholesale Trade report (http://www.census.gov/wholesale/index.html) from the
Census Bureau is a sample collected from a number of wholesale firms representing an annualized
population size of $5.3 trillion in wholesale sales and $580 billion in inventories.
ii
http://www.nber.org/cycles.html