Category Archives: General

A Riskier World?

This year’s Davos gathering is likely to be dominated by Donald Trump’s presence. I look forward to seeing him barge past other political and industry leaders to get his prime photo opportunity. As US equity markets continue to make all time highs in an unrelentingly fashion, it is scary to see the melt-up market been cheered on by the vivacious talking heads.

Ahead of Davos, the latest World Economic Forum report on global risks was released today. 59% of the contributors to the annual global risks survey point to an increase in risks in 2018, with environmental and cybersecurity risks continuing their trend of growing prominence, as can be seen below.

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Undoubtedly, environmental risks are the biggest generational challenge we face and it is hard to argue with the statement that “we have been pushing our planet to the brink and the damage is becoming increasingly clear“. That said, what is also striking about these assessments (and its important to remember that they are not predictions) is how the economic risks (light blue squares) have, in the opinion of the contributors, receded as top risks in recent years. The report does state that although the “headline economic indicators suggest the world is finally getting back on track after the global crisis that erupted 10 years ago” there is “continuing underlying concerns”.  Amongst these concerns, the report highlights “potentially unsustainable asset prices, with the world now eight years into a bull run; elevated indebtedness, particularly in China; and continuing strains in the global financial system”.

A short article in the report entitled “Cognitive Bias and Risk Management” by Michele Wucker caught my attention. The article included the following:

Risk management starts with identifying and estimating the probability and impact of a given threat. We can then decide whether a risk falls within our tolerance limits and how to react to reduce the risk or at least our exposure to it. Time and again, however, individuals and organizations stumble during this process—for example, failing to respond to obvious but neglected high-impact “grey rhino” risks while scrambling to identify “black swan” events that, by definition, are not predictable.


One of the most pervasive cognitive blinders is the availability bias, which leads decision-makers to rely on examples and evidence that come immediately to mind. This draws people’s attention to emotionally salient events ahead of objectively more likely and impactful events.

I do wonder about cognitive blinders and grey rhinos for the year ahead.

Keep on moving, 2018

As I re-read my eve of 2017 post, its clear that the trepidation coming into 2017, primarily caused by Brexit and Trump’s election, proved unfounded in the short term. In economic terms, stability proved to be the byword in 2017 in terms of inflation, monetary policy and economic growth, resulting in what the Financial Times are calling a “goldilocks year” for markets in 2017 with the S&P500 gaining an impressive 18%.

Politically, the madness that is British politics resulted in the June election result and the year ended in a classic European fudge of an agreement on the terms of the Brexit divorce, where everybody seemingly got what they wanted. My anxiety over the possibility of a European populist curveball in 2017 proved unfounded with Emmanuel Macron’s election. Indeed, Germany’s election result has proven a brake on any dramatic federalist push by Macron (again the goldilocks metaphor springs to mind).

My prediction that “volatility is likely to be ever present” in US markets as the “realities of governing and the limitations of Trump’s brusque approach becomes apparent” also proved to be misguided – the volatility part not the part about Trump’s brusque approach! According to the fact checkers, Trump made nearly 2,000 false or misleading claims in his first year, that’s an average of over 5 a day! Trump has claimed credit for the amazing performance of the 2017 equity market no less than 85 times (something that may well come back to bite him in the years ahead). The graph below does show the amazing smooth performance of the S&P500 in 2017 compared to historical analysts’ predictions at the beginning of the year (see this recent post on my views relating to the current valuation of the S&P500).

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As for the equity market in 2018, I can’t but help think that volatility will make a come-back in a big way. Looking at the near unanimous positive commentators’ predictions for the US equity market, I am struck by a passage from Andrew Lo’s excellent book “Adaptive Markets” (which I am currently reading) which states that “it seems risk-averse investors process the risk of monetary loss with the same circuit they contemplate viscerally disgusting things, while risk-seeking investors process their potential winnings with the same reward circuits used by drugs like cocaine”. Lo further opines that “if financial gain is associated with risky activities, a potentially devastating loop of positive feedback can emerge in the brain from a period of lucky investments”.

In a recent example of feeding the loop of positive feedback, Credit Suisse stated that “historically, strong returns tend to be followed by strong returns in the subsequent year”. Let’s party on! With a recent survey of retail investors in the US showing that over 50% are bullish and believe now is a good time to get into equities, it looks like now is a time where positive feedback should be restrained rather than being espoused, as Trump’s mistimed plutocratic policies are currently doing. Add in a new FED chair, Jay Powell, and the rotation of many in the FOMC in 2018 which could result in any restriction on the punch bowl getting a pass in the short term. Continuing the goldilocks theme feeding the loop, many commentators are currently predicting that the 10-year treasury yield wouldn’t even breach 3% in 2018! But hey, what do I know? This party will likely just keep on moving through 2018 before it comes to a messy end in 2019 or even 2020.

As my post proved last year, trying to predict the next 12 months is a mugs game. So eh, proving my mug credentials, here goes…

  • I am not even going to try to make any predictions about Trump (I’m not that big of a mug). If the Democrats can get their act together in 2018 and capitalize on Trump’s disapproval ratings with sensible policies and candidates, I think they should win back the House in the November mid-terms. But also gaining control of the Senate may be too big an ask, given the number of Trump strong-holds they’ll have to defend.
  • Will a Brexit deal, both the final divorce terms and an outline on trade terms, get the same fudge treatment by October in 2018? Or could it all fall apart with a Conservative implosion and another possible election in the UK? My guess is on the fudge, kicking the can down the transition road seems the best way out for all. I also don’t see a Prime Minster Corbyn, or a Prime Minister Johnson for that matter. In fact, I suspect this time next year Theresa May will still be the UK leader!
  • China will keep on growing (according to official figures anyway), both in economics terms and in global influence, and despite the IMF’s recent warning about a high probability of financial distress, will continue to massage their economy through choppy waters.
  • Despite a likely messy result in the Italian elections in March with the usual subsequent drawn out coalition drama, a return of Silvio Berlusconi on a bandwagon of populist right-wing policies to power is even too pythonesque for today’s reality (image both Trump and Berlusconi on the world stage!).
  • North Korea is the one that scares me the most, so I hope that the consensus that neither side will go there holds. The increasingly hawkish noises from the US security advisors is a worry.
  • Finally, as always, the winner of the World Cup in June will be ……. the bookies! Boom boom.

A happy and health New Year to all.

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.

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.