Aging Gracefully

The OECD had an interesting piece on old age dependency ratios across countries, predicting that on average they would nearly double over the next 35 years for the 20-64 cohort, as per the graph below.

click to enlargeOld Age Dependency Ratio

Japan and Spain come out the highest in the 2050 projection, followed by Greece, Portugal, Italy and Korea. Interestingly, the countries that came out the lowest in the 2050 projection were Australia, the US, Turkey, Mexico and Israel.

Broken Record

Whilst the equity market marches on regardless, hitting highs again today, writing about the never-ending debates over equity valuations makes one feel like a broken record at times. At its current value, I estimate the S&P500 has returned an annualised rate of nearly 11%, excluding dividends, since its low in March 2009. As of the end of September 2017, First Trust estimated the total return from the S&P500 at 18% since March 2009, as per the graph below.

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Goldman Sachs recently published an analysis on a portfolio of 60% in the S&P 500 and 40% in 10-year U.S. Treasuries, as per the graph below, and commented that “we are nearing the longest bull market for balanced equity/bond portfolios in over a century, boosted by a Goldilocks backdrop of strong growth without inflation”. They further stated that “it has seldom been the case that all assets are expensive at the same time—historical examples include the Roaring ‘20s and Golden ‘50s. While in the near term, growth might stay strong and valuations could pick up further, they should become a speed limit for returns”.

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My most recent post on the topic of US equity valuations in May looked at the bull and bear arguments on low interest rates and heighten profit margins by Jeremy Grantham and John Hussman. In that post I further highlighted some of the other factors which are part of the valuation debate such as the elevated corporate leverage levels, reduced capital expenditures, and increased financial risk taking as outlined in the April IMF Global Financial Stability report. I also highlighted, in my view, another influential factor related to aging populations, namely the higher level of risk assets in public pensions as the number of retired members increases.

In other posts, such as this one on the cyclically adjusted PE (CAPE or PE10), I have highlighted the debates around the use of historically applicable earnings data in the use of valuation metrics. Adjustments around changes in accounting methodology (such as FAS 142/144 on intangible write downs), relevant time periods to reflect structural changes in the economy, changes in dividend pay-out ratios, the increased contribution of foreign earnings in US firms, and the reduced contribution of labour costs (due to low real wage inflation) are just some examples of items to consider.

The FT’s John Authers provided an update in June on the debate between Robert Shiller and Jeremy Siegel over CAPE from a CFA conference earlier this year. Jeremy Siegel articulated his critique of the Shiller CAPE in this piece last year. In an article by Robert Shiller in September article, called “The coming bear market?”, he concluded that “the US stock market today looks a lot like it did at the peaks before most of the country’s 13 previous bear markets”.

The contribution of technology firms to the bull market, particularly the so-called FANG or FAANG stocks, has also been a much-debated issue of late. The graph below shows the historical sector breakdown of the S&P500 since 1995.

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A recent article from GMO called “FAANG SCHMAANG: Don’t Blame the Over-valuation of the S&P Solely on Information Technology” tried to quantify the impact that the shift in sector composition upon valuations and concluded that “today’s higher S&P 500 weight in the relatively expensive Information Technology sector is cause for some of its expensiveness, but it does not explain away the bulk of its high absolute and relative valuation level. No matter how you cut it, the S&P 500 (and most other markets for that matter) is expensive”. The graph below shows that they estimate the over-valuation of the S&P500, as at the end of September 2017, using their PE10 measure is only reduced from 46% to 39% if re-balanced to take account of today’s sector weightings.

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In his recent article this month, John Hussman (who meekly referred to “his incorrectly tagged reputation as a permabear”!!) stated that “there’s no need to take a hard-negative outlook here, but don’t allow impatience, fear of missing out, or the illusion of permanently rising stock prices to entice you into entrusting your financial future to the single most overvalued market extreme in history”.

As discussed in my May post, Hussman reiterated his counter-argument to Jeremy Grantham’s argument that structurally low interest rates, in the recent past and in the medium term, can justify a “this time it’s different” case. Hussman again states that “the extreme level of valuations cannot, in fact, be “justified” on the basis of depressed interest rates” and that “lower interest rates only justify higher valuations if the stream of future cash flows is held constant” and that “one of the reasons why reliable valuation measures have retained such a high correlation with subsequent market returns across history, regardless of the level of interest rates, is that the impact of interest rates and growth rates on “terminal” valuations systematically offset each other”.

Hussman also again counters the argument that higher profit margins are the new normal, stating that “it’s important to recognize just how dependent elevated profit margins are on maintaining permanently depressed wages and salaries, as a share of GDP” and that “simply put, elevated corporate profit margins are the precise mirror-image of depressed labour compensation” which he contends is unlikely to last in a low unemployment environment.

Hussman presents a profit margin adjusted CAPE as of the 3rd of November, reproduced below, which he contends shows that “market valuations are now more extreme than at any point in history, including the 1929 and 2000 market highs”.

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However, I think that his profit margin analysis is harsh. If you adjust historical earnings upwards for newer higher margin levels, of course the historical earning multiples will be lower. I got to thinking about what current valuations would look like against the past if higher historical profit margins, and therefore earnings, had resulted in higher multiples. Using data from Shiller’s website, the graph below does present a striking representation of the relationship between corporate profits (accepting the weaknesses in using profits as a percentage of US GDP) and interest rates.

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Purely as a thought experiment, I played with Shiller’s data, updating the reported earnings for estimates through 2018 (with a small discount to reflect over-zealous estimates as per recent trends of earnings revisions), recent consensus end 2018 S&P500 targets, and consensus inflation and the 10-year US interest rates through 2018. Basically, I tried to represent the base case from current commentators of slowly increasing inflation and interest rates over the short term, with 2018 reported EPS growth of 8% and the S&P500 growing to 2,900 by year end 2018. I then calculated the valuation metrics PE10, the regular PE (using trailing twelve month reported earnings called PE ttm), and the future PE (using forward twelve month reported earnings called PE ftm) to the end of 2018. I further adjusted the earnings multiples, for 2007 and prior, by applying an (principally upward) adjustment equal to a ratio of the pre-2007 actual  corporate profits percentage to GDP divided by a newly assumed normalised percentage of 8.5% (lower than the past 10-year average around 9% to factor in some upward wage pressures over the medium term). The resulting historical multiples and averages are shown below.

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Based upon this analysis, whilst accepting its deeply flawed assumptions, if 2018 follows the base case currently expected (i.e. no external shocks, no big inflation or interest rates moves, steady if not spectacular earnings growth), the S&P500 currently looks over-valued by 50% to 20% using historical norms. If this time it is different and higher profit margins and lower interest rates are the new normal, then the S&P500 looks roughly fairly-valued and current targets for 2018 around 2,900 look achievable. Mind you, it’s a huge leap in mind-set to assume that the long-term average PE is justifiably in the mid-20s.

I continue to be concerned about increasing corporate leverage levels, as highlighted in my May post from the IMF Global Financial Stability report in April, and the unforeseen consequences of rising interest rate after such a long period of abnormally low rates.

In the interim, to paraphrase an ex-President, it’s all about the earnings stupid!

An Apple Appetite

Recently I have been trying to dig deeper into Apple (AAPL) to get a handle on what the near term may mean for this amazing company and thereby get an insight into APPL’s valuation. I have struggled with AAPL’s valuation in previous posts (here and here) but after each of my musings the share price continued on its upward trajectory.

Irrespective of whether iPhone 8 and iPhone X unit sales disappoint (due to unit shortages or otherwise) over the coming months, it seems highly probable to me that Apple will be successful in segmenting their iPhone market further over the medium term and break through the $1000 per iPhone spend in a significant way. Their R&D spend of over $10 billion (including nearly $2 billion of share options) goes a long way to ensuring customers will pay for their innovations.

The reason why AAPL are following the current strategy is a hot topic of debate with analysts. Some see the new iPhone models feed into a super-cycle of updates and continued installed base growth, pointing to the approximate 40% of the current iPhone installed base older than 2 years. Other analysts believe that the smartphone market has plateaued (see graph from Mary Meeker below) and Apple is embarking upon a segmentation strategy to harvest their loyal customer base.

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The estimates for the iPhone installed base vary significantly across analysts from 550 to 750 million units and some, such as Deutsche Bank and BoA ML further, break the base down to core and secondary non-core users. Although most of the estimates are likely out of date as they were published prior to the iPhone 8 and iPhone X announcements, the graphic below illustrates the differing views.

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It is likely no surprise that I am in the plateau camp on future growth of the installed base. I have assumed an installed base of 640 million as at end September 2017 and 40% or approximately 250 million of these are potential iPhones upgraders with phones older than 2 years. I have further assumed that a proportion of the installed base, I selected 10%, are secondary non-core users with a very low propensity to upgrade. That leaves an approximate 190 million potential upgrades for the FY2018. Despite the lack of growth of the market, I assumed another 10 million sales from new purchasers giving a target iPhone unit sales of 200 million for FY2018. 200 million of annual unit iPhone sales is well below most analyst estimates which average around 240 -260 million for FY2018.

Of the 200 million iPhone unit sales for FY2018, I have further assumed 45 million are iPhone X and just over half are iPhone 8, with the remainder being iPhone 7 and older models. For Q42017, I am assuming only 9 million iPhone 8 sales with 35 million of iPhone 7 and older models (influenced by the amount of inventory clearance sales I have seen in retail stores). The graph below shows my installed base assumptions, with my estimates for sales of the iPhone 8, iPhone X and it successor models over FY 2018 and FY2019 (I am assuming 200 million units is the new normal for annual iPhone sales through to FY2020).

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The resulting average selling price (ASP) for FY2018 is $785 with annual FY2018 revenues from iPhone of $157 billion. For FY2019, I have assumed a ASP of $860 with annual FY2019 iPhone revenues of $172 billion. The graph below shows my revenue assumptions over FY 2018 and FY2019 across all products.

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The EPS estimates coming out of my model, using the assumptions above (amongst others), for FY2018, FY2019 and FY2020 are $10.17, $11.45 and $11.81 respectively (I agree with the estimates of $9.00 for FY2017). That represents 13% EPS growth for 2018 and 2019, slowing to 3% in 2020. At the current share price of $160, the forward PE (excluding cash) would look as per the graph below.

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My analysis suggests that AAPL either deserves a higher multiple than the recent past to justify its current value or it will have to convince enough new iPhone users to buy its new products to take market share from its competitors and sell more than 200 million iPhone annually for the foreseeable future.

Given the potential headwinds for iPhone 8 and iPhone X over the short term, the current price may be difficult to defend near term as the market gets used to lower iPhone sales at higher prices (and hopefully margins too). Then again, going negative on AAPL hasn’t proven fruitful in the past and the analysts are currently hyping up AAPL’s prospects with price targets heading solidly towards $200.

Given my previous history of questioning AAPL’s valuation, maybe indecision is the best answer for the time being……

CAT Calls

Following on from a recent post on windstorms in the US, I have taken several loss preliminary estimates recently published by firms (and these are very early estimates and therefore subject to change) and overlaid them against the South-East US probable maximum loss (PML) curves and Atlantic hurricane scenarios previously presented, as below. The range of insured losses for Harvey, Irma and Maria (now referred to as HIM) are from $70 billion to $115 billion, averaging around $90 billion.

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The loss estimates by firm depend heavily upon the risk profile of each. As a generalisation, it could be said that the aggregate US wind losses are averaging around the 1 in 100 loss level.

Given there was over $20 billion of insured losses from H1 and factoring in developing losses such as the Mexico earthquake, the California wildfires and the current windstorm Ophelia hitting Ireland, annual insured losses for 2017 could easily reach $120 billion. The graph below shows the 2016 estimates from Swiss Re and my $120 billion 2017 guesstimate (it goes without saying that much could still happen for the remainder of the year).

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At a $120 billion level of insured loss for 2017, the 10 year average increase from around $55 billion to $65 billion. In a post in early 2016, I estimated that catastrophe pricing was about 25% too low based upon annual average losses of $40 billion per year. We will see whether the 2017 losses are enough to deplete the overcapitalisation in the market and return pricing towards their technical rate. I wouldn’t hold my breath on that as although there may be material aggregate losses in the private collateralised market and other pockets of the retrocession market, the appetite of yield seeking investors will likely remain unabated in the current interest rate environment.

Although the comparison between calendar year ratios and credit defaults is fraught with credibility issues (developed accident year ratios to developed default rates are arguably more comparable), I updated my previous underwriting cycle analysis (here in 2014 and here in 2013). Taking the calendar year net loss ratios of Munich Re and Lloyds of London excluding catastrophe and large losses (H1 results for 2017), I then applied a crude discount measure using historical risk-free rates plus 100 basis points to reflect the time value of money, and called the resulting metric the adjusted loss ratio (adjusted LR). I compared these adjusted LRs for Munich and Lloyds to S&P global bond credit default rates (by year of origin), as per the graph below.

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This shows that the years of relatively benign attritional claims together with the compounding impact of soft pricing over the past years may finally be coming to an end. Time will tell. All in all, it makes for a very interesting period for the market over the next 6 to 12 months.

In the interim, let’s hope for minimal human damage from the current California wildfires and windstorm Ophelia.

Remember deleveraging?

There is a lot of interesting stuff in the latest IMF Financial Stability Report. After much research on global debts levels (as per this post in 2014 and this one in 2015) over the past few years, the graph below on G20 gross debt levels from the IMF shows how little progress has been made.

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When looked at by advanced economy, the trend in gross debt from 2006 to 2016 looks startling, particularly for government debt.

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As the IMF state, “one lesson from the global financial crisis is that excessive debt that creates debt servicing problems can lead to financial strains” and “another lesson is that gross liabilities matter”.

The question does arise as to the economic impact of these debt levels if interest rates start to rise across advanced economies?