Rotten Apple? On innovation and deflation


Apple reported on Tuesday a decrease in quarterly sales for the first time since 2003. The trend in itself was less surprising than its magnitude – revenues dropped by 13% on a YoY basis and, more importantly, fell short of analysts’ estimates. CEO Tim Cook used a bunch of arguments to justify the unexpected underperformance – blaming in turn a strong dollar, difficult economic conditions especially in APAC and difficult “comparisons for iPhone sales” – but could not prevent Apple’s share price from dropping by 8% right after the announcement and is now trading 7% below its pre-announcement level. All equity analysts have revised their target share price downwards and most of them believe that $120 a share is now a realistic long-term value, which only gives a 24% upside to existing shareholders. The Financial Times has even dared to state that “Apple [was now] living in the shadow of its own past success”. After more than a decade of impressive performance, is the love story between the firm and Wall Street coming to an end?

$48bn of shareholder value vanished overnight. Source: Yahoo Finance
$48bn of shareholder value vanished overnight. Source: Yahoo Finance

What is irrefutable is that the market is increasingly realising that Apple will likely remain a one-product shop in the foreseeable future. Growth in ancillary products and services can be perceived as impressive – 30% and 20% YoY respectively – but the iPhone still generates almost two thirds of Apple’s revenues. And when this core engine starts coughing earlier than expected, as it did over the last quarter – 50.4m iPhones shipped over the quarter vs. 51.2m forecast by analysts, down 16% YoY, with an average sales price (ASP) of $641 vs. $658 anticipated – the full firm wobbles.

Split of Apple's Q2 revenues by product. Sources: 8-K report, author analysis
Split of Apple’s Q2 revenues by product. Sources: 8-K report, author analysis

This slowdown could nonetheless have been anticipated. Since 2012, Apple has launched at least a new iPhone model every year in September in an attempt to boost not only its sales volume, but also its ASP as older models became increasingly cheap. This helped the firm create maintain a decent ASP until the next model was launched – a usual pattern in tech: innovation is the best way to fight deflation. Depending on the price point chosen for the new model, the mix between volume and ASP uplift varies – for instance, as the chart below shows, the iPhone 5 was a ‘volume’ hit whereas the iPhone 6 and 6+ primarily lifted the ASP. The issue is that the iPhone 6S and 6S+, launched in September last year, did not manage to achieve any of those two objectives. Analysts blame the extending renewal cycle as a root cause. This is possible. What is certain though is that the ‘boost’ last year was much shorter-lived and the landing is more severe than it was over the previous years. Q3 (ending in June) is expected to bring no improvement, especially on the ASP front, given that Apple just launched the iPhone SE, priced at $400 in order to further penetrate emerging markets.

Quarter-on-quarter evolution of iPhone volume sold and ASP. Sources: Apple 8-K reports, author analysis

Using EV/LTM EBITDA and EV/FWD EBITDA valuation multiple benchmarks to adjust for differences in capital structure, Apple now sits in the same ballpark as many high-tech hardware manufacturers such as IBM, Intel or HP, trailing true ‘software developers’ such as Facebook and Google – a gap that kept widening since Facebook announced brilliant results for the same period. This means two things. First, as previously written, Apple is still largely perceived as a hardware company and it will take time for the markets to believe in the services as a real growth pillar. Second, the market believes that, with an installed base of 500 million iPhones and more than 1 billion Apple device users worldwide, Apple’s golden growth era is now behind and that we should not expect similar the future to be a replica of the past. In the manner of the world’s largest banks which have become ‘too big to fail’, high-tech behemoths are now ‘too big to soar’.

EV/EBITDA benchmarks as of 28 April 2016. Sources: CapitalIQ, author analysis

Apple also made a couple of surprising announcement with regards to its financing structure that left analysts even more circumspect. The firm indeed decided to expand its share buyback program from $140bn to $175bn and to increase its quarterly dividend will be increased by 10%. The company is still sitting on more than $230bn of cash and equivalents and this redistribution program should not impede its acquisition firepower if need be. Nonetheless, Apple has been returning increasing amounts of cash to shareholders since 2012 and this cannot be interpreted as a good signal if you remember one of my earlier posts. The firm uses buybacks and dividends to support its share price by implicitly believing that any incremental project it could invest in would not generate any better return than the one shareholders would get elsewhere on the market. With the S&P 500 down 1% over the last 365 days and interest rates at an all-time low, Apple states loud and clear that there are not many growth levers available on the market at a decent price right now.

So, is there any hope? Yes. First, Apple still benefits from a strong brand image and high customer loyalty, which enables it to command a price premium while limiting the risk of massive and sudden ‘customer exodus’. The launch of the iPhone 7 later this year will be a real make-or-break since analysts, as well as the general public, have been waiting for the ‘next big thing’ for too long. apple-icloud-logo1Second, Apple made its entry in the services arena early enough to establish a significant position, primarily through iTunes and, to a lesser extent, iCloud. If it manages to keep a competitive advantage against Amazon, Google and al., Apple will not only be able to maintain a strong financial performance but also get closer in terms of market perception to the real ‘software disrupters’. In the meantime, Wall Street is granting the company the ‘benefit of the doubt’: hard for them to change sides and burn the idol that they used to venerate.

Whatever happens in the future, this is a perfect illustration of the race between innovation and deflation that has been shaking high-tech companies for decades; you need to keep running to stand still. If you stop innovating significantly enough so that your products are not perceived as clearly ahead of the technology curve, you face a huge risk of ‘commoditisation’ and dilution into a very competitive and agile market. Microsoft and Nokia will not disagree.

P.S.: The full Earnings Call presentation and podcast are available on Apple’s website.

Stamping the housing market


Last week the Financial Times used the latest Office for National Statistics (ONS) housing price figures to assess the impact of the stamp duty raise on the housing market. Since the beginning of the month, purchasers of buy to let property and second homes indeed face a 3% stamp duty surcharge. Some experts believed that prospective second home buyers would rush to complete their transaction before the deadline and would thus generate an artificial and temporary price increase.

The FT article took the opposite view and concluded that “UK house price growth weakened slightly in the year to February, to 7.6 per cent […] meaning that a boost reported by mortgage lenders and estate agents ahead of stamp duty changes for buy-to-let investors is yet to show up in official data”. This statement surprised me and I decided to dig further into the data. My take is the following: although the statement may be true at a global level, by performing the analysis for each Government Office Region separately, one could conclude that the impact of the stamp duty reform was actually much more significant.

k12985080To perform this exercise, I used two publicly available sources of data:

  • ‘Number of residents with a second address in a region, who are usually resident outside of that region’ and ‘Number of usual residents in a region with a second address outside of that region’ as per the 2011 census;
  • ‘Mix-adjusted average house prices by region’ published monthly by the ONS.

First, we need to understand that all UK regions are not equal. The more second houses a given area hosts, the more impact the stamp duty reform should have had. The most recent information on the topic comes from the 2011 Census which gives us the number of residents elsewhere with a second address in a given region – e.g. in 2011 184,616 people had a second address in the South East.

Number of usual residents elsewhere with a second address in the area (2011). Source: 2011 Census

Separately, the ONS data gives us the year-on-year house price evolution in each area from July 2015 to February 2016.

Year-on-year housing price evolution by region. Source: ONS
Year-on-year housing price evolution by region. Source: ONS

Nonetheless we are not interested in the price growth rate but by the increase of the growth rate as the stamp duty implementation deadline approaches. I have therefore compared the average housing price increase (in percentage points) in January and February 2016 with the one witnessed in July and August 2015 in each region – I have taken a two-month average to smooth out any shock. The analysis shows wide discrepancies between regions – for instance the growth rate increased by 5.0 percentage points in London over the period but actually decreased by 2.7 pts in Yorks & Humber.

Increase in housing price growth rate by region, January-February 2016 vs. July-August 2015. Sources: ONS, author analysis

Finally, I look for a correlation between the number of second addresses and the increase in housing price growth rate.

Correlation between housing price growth rate increase and number of second addresses

The correlation between the two variables is clear and we could therefore conclude that the stamp duty change has ‘warmed up’ the housing market in the regions with a high number of second addresses. The stamp duty effect was indeed pushing buyers to complete the transaction as fast as possible, even if it meant paying a higher price (up to 3% more actually). The surge in gross mortgage lending witnessed in March by the Council of Mortgage Lenders supports this conclusion. On a side note, this is another piece of evidence illustrating the fact that the UK housing market remains a ‘seller’s market’ – in a ‘buyer’s market’ you would have conversely seen a drop in prices as sellers try to get rid of their property before having to pay the surcharge.

Stamp_Duty_Paid_mark_for_British_cheques_from_1956It would be interesting to keep an eye on the market prices in the future. Given that purchasers have by definition a limited purchasing power, was the bump just bringing forward future increases (in that case the market should cool off for at least a few months) or will future sellers be able to maintain enough competitive tension to use the ‘overheated’ prices as the new normal?

Watch the step – Paradigm shift ahead

Have you fastened your seat belt?
Have you fastened your seat belt?

Last week the IMF downgraded its global growth forecast for 2016 to 3.4%. Among the developed economies, only the US and the UK show encouraging signs, with forecast growth of around 2.4% for this year. Growth remains limited despite abnormally low interest rates and a debt stock only seen in a WW2 context which low inflation cannot clear. Such a sequence of bad news could trigger only one question: is the ‘crisis’ back?

Advanced economies' debt amount as share of GDP. Source: Le Figaro.
Advanced economies’ debt amount as share of GDP. Source: Le Figaro.

The commodity price drop witnessed at the beginning of the year has taken its toll on the lending and bond side. 46 corporate borrowers have already defaulted on a total of $50bn of debt so far this year. According to the Financial Times, more than 80% of investors expect the default rate on junk-rated companies to reach at least 5% by year-end. This has already caused the liquidity on the bond markets to dry up, practically barring the weakest companies from accessing fresh capital inflows. Private equity sponsors, which are well known for making highly-leveraged acquisitions, have seen the default rate for their leveraged loans go from 0.88% on 31 January to 1.46% as of 31 March. Again, this tightness happens at a time of very affordable debt, which can make us fear the time when Central Banks will sketch a move back towards positive interest rates territory. At a country level, lending from the World Bank has reached its highest level since the aftermath of the 2008 financial crisis. “It is our highest lending in a non-crisis period ever” added the World Bank’s president. If we are not in a crisis then where are we?

What is certain is that the root causes have been identified for months: “sluggish capital investment, falling industrial production and declining business confidence” which partly feed themselves from geopolitical uncertainties (Brexit currently topping the agenda) and a lack of politically supported structural reforms – on the latter, we cannot blame politicians for favouring electorate-friendly measures over high-risk initiatives one year before reelection time.

Three leaders that put their job back in play in 2016 and 2017
Three leaders who will have put their job back in play by 2017

To solve these issues, all only have one word to say: ‘GROWTH’. The IMF estimates that one additional point of growth would enable the advanced economies to bring their indebtedness ratio to pre-crisis levels. But experts strongly diverge on practical ways to get hold of this extra growth.

Although many lights are red-flashing on the world economy dashboard, I agree with IMF’s Jose Vinals and I do not believe we are heading towards a ‘sudden’ crisis of the type we faced in 2007-2008. I nonetheless think that we are entering a world where low growth and low inflation will become the new norm –

Olivier Blanchard
Olivier Blanchard

former IMF Chief Economist Olivier Blanchard writes about a ‘weak recovery‘ situation. Once decision makers and Central Banks will have realised that achieving 2% of inflation annually is not realistic in a world where innovation builds on limited capital accumulation, where disruption takes place through not only better features but also lower prices and therefore drag inflation down (take the example of Airbnb or Uber) and where 5 out of 10 America’s fastest growing jobs pay less than $25k a year, the money tap will stop running, there will undoubtedly be a few winners but many more clear losers. And the interest rise wall can be closer than we think: in the video below, US Federal Reserve Chair Janet Yellen justified the December 2015 rate increase by the fact that labour statistics were positive – still the case as the US is experiencing its longest-ever streak of private sector job growth ever – and that “the Federal Reserve was feeling reasonably confident in the fact that inflation would move up over the medium-term back to 2%” – i.e. there is no need for inflation to reach 2% for rates to go up again.

The big question is now if the paradigm shift happens, how will it do so, and which target will Central Banks will be asked to go for. A brand new uncharted territory for the economic theory to discover.

Catch me if you can (afford to pay)

Theatrical release poster for the movie “Catch me if you can” (2002).

In an earlier post I discussed the benefits that shoplifting could have on inflation. In a nutshell, my thesis defended the (theoretical) use of ‘moderate’ shoplifting as a way to fight against inflation. Indeed, if the share of stolen goods grows, retailers have to anticipate this behaviour by increasing their prices in order to offset the losses incurred because of theft. I nonetheless ended up moderating my remark by underlining the fact that ‘too much theft could kill theft’. The topic of this post is actually to prove this latter assertion. To do so, I will rely on a powerful and widespread microeconomics tool called ‘game theory’.

According to Wikipedia, game theory is “the study of mathematical models of conflict and cooperation between intelligent rational decision-makers”. Although historians can find traces of rudimentary game theory dating back to the 18th century, this theory started to be properly formalised appeared in the 1920s, championed by brilliant economists such as von Neumann and later John Nash – made famous in the eyes of the general public through the movie A Beautiful Mind. Although the framework sometimes requires ample simplification to be quantitatively workable, it yields satisfactory results in our case.

Note: The following paragraphs may repel non-scientific readers. Those readers may prefer to jump directly to the conclusion, which is signalled by cropped-Untitled.png.

Let us represent today’s problem as a game between two players, namely the shoplifter community and the shop – we use one representative shop and we similarly consider that the shoplifting community can be considered as a relatively homogeneous group. We assume that both players are risk-neutral, i.e. all they care about is their utility at the end of the game, irrespective of the degree of uncertainty surrounding this outcome. The ‘sequential game’ is the following:

  • First, the shop decides whether to set-up a surveillance system (CCTV, security guards etc. at total cost C>0) or not (at no cost).
  • Having observed this choice, the shoplifter decides whether to try to steal or not. The shoplifter’s probability of success depends on the presence of a surveillance system. If there is none, this probability is pmax. If there is one, this probability falls to pmin, where pmin<pmax.
  • Finally, we distribute the rewards. If the shoplifter is successful, he enjoys the product of his theft, assumed to be equivalent to $ in dollars – the same amount is withdrawn from the shop’s utility. If he is caught, he has to face a penalty equivalent to a cost of F – although the penalty may be made of non-monetary items e.g. prison sentences.

We assume F, pmin, pmax and C to be known and constant throughout the problem. The question we try to answer is: to which extent does the outcome of this problem depend on $?

To solve sequential games, game theory uses the principle of ‘backward induction’. We start by deducting the optimal solution for the agent playing last, and we move backward to anticipate each player’s move given the subsequent decisions made by the other players. Here, the shoplifter plays last, so we will pay attention to him first.

The shoplifter will try to steal only if his expected utility is greater than the utility he gets by staying home, which we assume to be equal to 0. Mathematically speaking, this translates into:

  • 4if the shop is equipped or
  • 5if the shop is not.

We can rewrite the previous two equations as follows: 6and 7. In proper English, these equations illustrate the fact that the shoplifter will only try to steal if the reward is high enough compared with the potential punishment.

If we plot the shoplifter’s decision as a function of $, we come up with the following strategy:


We now turn our attention to the shop, which can perform the same reasoning as the one we just did and is therefore able to predict the shoplifter’s behaviour depending on all the problem’s variables. We can distinguish three cases:

  • If the shoplifter does not try in all cases because the reward is not worth the effort, then it is optimal for the shop not to buy protection.

    "They're fake. Part of the new false sense of security system."
  • If the shoplifter tries only if the shop is not equipped, it is optimal for the shop to protect itself if the expected savings of protecting the shop against theft are greater than the cost of the equipment itself. If the equipment is indeed prohibitively expensive, the shop may be financially better-off letting the theft unmonitored. Mathematically this can be written as: 8or 9. Note that the boundary does not depend on F, i.e. the shop makes his decision irrespective of the legal framework.
  • If the shoplifter tries in all cases, then there is a possibility that the shop pays for the equipment and gets stolen from. The related equation is therefore 10or 11.

Although we could continue to solve the game using abstract variables, the conclusion is more powerful if we now switch to a numerical illustration.

Let us set the fine F to £500, the cost of equipment C to £200, the probability of successful theft without any equipment to pmax=80% and the probability of successful theft with equipment to pmin=5%. We can now replace the formulaic boundaries driving the shoplifter’s behaviour in the axis above by their numerical values, respectively £125 and £9,500. The latter value can appear as very high, but is only due to the fact that the shoplifter has a very high chance of being detected and will therefore only try his luck if the reward significantly outgrows the (almost certain) penalty.


For the shop, the reasoning is as follows:

  • “If the expected reward is less than £125, the theft will not even try so I do not spend any money on surveillance”.
  • “If the reward is between £125 and £9,500, then the theft will only try if I am unprotected. On my side, I am better-off on average by setting up a surveillance system only if the expected take is greater than .”
  • “If the reward is greater than £9,500, then the theft will always try. On my side, I am better-off on average by setting up a surveillance system only if the expected take is greater than . This condition is always verified given that we are only considering takes greater than £9,500 in this third case.

idea-light-bulb-clip-art-black-and-white-MTLEnkBTaNote: The non-scientific reader may resume from here. That makes the article quite shorter I must admit.

As a summary, if we put the decision of the theft and the decision of the shop together as functions of $, our conclusion is the following:


How can we interpret those results?

  • If the expected take is too small (smaller than £125 in our example), the fine is relatively too high for the shoplifter to take the risk. In this first case, the shop is actually protected by the legislation around shoplifting.
  • If the expected take is high enough, i.e. in our example between £125 and £250, then the law does not provide a strong enough deterrent while the equipment is relatively too costly for the shop given the expected loss it faces. Within this ‘window of opportunity’ the optimal choice for the shoplifter is actually to try his luck.
  • If the expected take is between £250 and £9,500 the shoplifter will not try: his probability of success is too low given the implementation of the surveillance system.
  • Finally, if the expected take is greater than £9,500, the shoplifter is willing to take all possible risks – but, realistically, how likely is the shoplifter to manage to steal £9,500 worth of goods with only a 5% chance of being detected?

Game theory here shows us that, provided that the shop can perfectly anticipate the value of $ and both players are rational and risk-neutral, there is indeed a gap where attempted shoplifting makes rational sense for everyone. Nonetheless, as already pointed out in my earlier post, economists have managed to translate rationality in their models, but morality has been so far largely left behind.

Million Dollar Baby

Note: This post had been in my ‘draft’ basket for a while, but Michael Skapinker’s remarkable column in yesterday’s Financial Times put it back at the top of my pile.

Housing has become a real issue for British inhabitants in general, and Londoners in particular. LSE Professor Paul Cheshire has made a new contribution in this debate through a widely echoed report which concludes that one of four London homes will cost more than £1m by 2020, with the Financial Times concluding in the same article that “‘not just having a mum and dad who bought a house, but a grandparent too’ would be needed to get on the [property] ladder in the future”. So far, the latest data seem to prove him right.

The fact that owner occupiers and renters are not in the same boat is not news. The latest English Housing Survey supports that assertion in many respects. The share of overcrowded dwellings is almost four times higher in rented places (5-6% compared with 1-2%) and the gap is increasing. Conversely, the share of owned dwellings which are under-occupied has been soaring over the last two decades and now concerns more than 50% of the properties – partly due to the fact that almost all houses larger than 110 sq. m. are owned – compared with 9% and 13% for socially and privately rented dwellings, respectively. The share of non-decent homes has been decreasing across all types of occupations, but more than one out of four privately rented dwellings is still affected by ‘decency’ issues, primarily damp. For all those reasons, owner occupiers understandably report a higher satisfaction level than all types of renters (both social & private).

Share of non-decent homes, by tenure. Source: English Housing Survey 2014-15.
Share of non-decent homes, by tenure.
Source: English Housing Survey 2014-15.

Although the benefit of home ownership in terms of life satisfaction is indisputable, and despite the low interest rates and the numerous government schemes aimed at favouring ‘prime ownership’, UK inhabitants remain negative about their chances to ever get on the property ladder. Only 60% of private renters expect to buy one day, although the age for first time buyers has been continuously rising. For the youngest (25 to 34 years old), the mirage of ownership is vanishing at fast pace.

Split of households with a HRP aged 25-34, by tenure. Source: English Housing Survey 2014-15.
Split of households with a HRP aged 25-34, by tenure.
Source: English Housing Survey 2014-15.

In his report, Prof. Cheshire adds to the pessimism. Analysing the historical evolution of house prices in the UK, Prof. Cheshire concludes that “the key variables we have found have influenced house prices are real incomes, changes in population and house construction and interest rates”, with the former being “by far the most influential”. That being said, the relationship is clearly not 1:1, since real incomes have gone up by a factor of more than 3 since the early 1950s and the price of houses in London has been multiplied by 10 in half the time according to the Halifax House Price Index.

Quarterly evolution of house prices in London. Indexed at 100 for the average of 1983 prices. Source: Halifax House Price Index.

Government schemes or massive foreign capital inflows are not part of the list. In one hand, this is reassuring, as this means that house prices are directly linked to the income UK workers receive. On the other hand, this also means that an increase in inequalities between the richest and the poorest will leave more and more people on the side of the property ladder.


Prof. Cheshire’s quantitative forecast adds further colour. His econometric model, calibrated using historical data, forecasts an average house price increase of 23% by 2020 and 97% by 2030, with significant disparities between areas. London will be most heavily hit, with 25% of houses being priced at £1m or more by 2030 and the price of a house in the lowest quartile of all prices representing 17 times the income of a person earning the lowest quartile wage at that time, compared with 11.5 times today.

House Prices Observed and Predicted 1961 to 2030 – in logs. Source: Future Britain: Housing Millionaires and housing paupers.
House Prices Observed and Predicted 1961 to 2030 – in logs.
Source: Future Britain: Housing Millionaires and housing paupers.

Experts agree to say that the price surge we have been witnessing is also due to an imbalance between supply and demand. On that front, the Financial Times recently highlighted that new house building was still apathetic, leading the government’s ‘1m homes built by 2020’ target to be considered as increasingly unrealistic. The root causes of this supply shortage are subject to debate, but the UK regulatory and planning systems surrounding the building industry are often pointed out as major roadblocks – at least this is an area where the British and the French converge. There is however an urgent need for action: as rightly pointed out by Skapinker, at that pace, London will become unaffordable for the next wave of young talents it used to attract.