Tag Archives: aging populations

Still Dancing

The latest market wobble this week comes under the guise of the endless Trump soap opera and the first widespread use of the impeachment word. I doubt it will be the last time we hear that word! The bookies are now offering even odds of impeachment. My guess is that Trump’s biggest stumble will come over some business conflict of interest and/or a re-emergence of proof of his caveman behaviour towards woman. The prospect of a President Pence is unlikely to deeply upset (the non-crazy) republicans or the market. The issue is likely “when not if” and the impact will depend upon whether the republicans still control Congress.

Despite the week’s wobble, the S&P500 is still up over 6% this year. May is always a good month to assess market valuation and revisit the on-going debate on whether historical metrics or forward looking metrics are valid in this low interest rate/elevated profit margin world. Examples of recent posts on this topic include this post one highlighted McKinsey’s work on the changing nature of earnings and this post looked at the impact of technology on profit profiles.

The hedge fund guru Paul Tudor Jones recently stated that a chart of the market’s value relative to US GDP, sometimes called the Buffet indicator as below, should be “terrifying” to central bankers and an indicator that investors are unrealistically valuing future growth in the economy.

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Other historical indicators such as the S&P500 trailing 12 month PE or the PE10 (aka Shiller CAPE) suggest the market is 60% to 75% overvalued (this old post outlines some of the on-going arguments around CAPE).

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So, it was fascinating to see a value investor as respected as Jeremy Grantham of GMO recently issue a piece called “This time seems very very different” stating that “the single largest input to higher margins, though, is likely to be the existence of much lower real interest rates since 1997 combined with higher leverage” and that “pre-1997 real rates averaged 200 bps higher than now and leverage was 25% lower”. Graham argues that low interest rates, relative to historical levels, are here for some time to come due to structural reasons including income inequality and aging populations resulting in more aged savers and less younger spenders. Increased monopoly, political, and brand power in modern business models have, according to Graham, reduced the normal competitive pressures and created a new stickiness in profits that has sustained higher margins.

The ever-cautious John Hussman is disgusted that such a person as Jeremy Grantham would dare join the “this time it’s different” crowd. In a rebuttal piece, Hussman discounts interest rates as the reason for elevated profits (he points out that debt of U.S. corporations as a ratio to revenues is more than double its historical median) and firmly puts the reason down to declining labour compensation as a share of output prices, as illustrated by the Hussman graph below.

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Hussman argues that labour costs and profit margins are in the process of being normalised as the labour market tightens. Bloomberg had an interesting article recently on wage growth and whether the Phillips Curve is still valid. Hussman states that “valuations are now so obscenely elevated that even an outcome that fluctuates modestly about some new, higher average [profit margin] would easily take the S&P 500 35-40% lower over the completion of the current market cycle”. Hussman favoured valuation metric of the ratio of nonfinancial market capitalization to corporate gross value-added (including estimated foreign revenues), shown below, predicts a rocky road ahead.

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The bulls point to a growing economy and ongoing earnings growth, as illustrated by the S&P figures below on operating EPS projections, particularly in the technology, industrials, energy, healthcare and consumer sectors.

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Taking operating earnings as a valid valuation metric, the S&P figures show that EPS estimates for 2017 and 2018 (with a small haircut increasing in time to discount the consistent over optimism of analyst forward estimates) support the bull argument that current valuations will be justified by earnings growth over the coming quarters, as shown below.

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The IMF Global Financial Stability report from April contains some interesting stuff on risks facing the corporate sector. They highlight that financial risk taking (defined as purchases of financial assets, M&A and shareholder pay-outs) has averaged $940 billion a year over the past three years for S&P 500 firms representing more than half of free corporate cash flow, with the health care and information technology sectors being the biggest culprits. The IMF point to elevated leverage levels, as seen in the graph below, reflective of a mature credit cycle which could end badly if interest rates rise above the historical low levels of recent times.

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The report highlights that debt levels are uneven with particularly exposed sectors being energy, real estate and utilities, as can be seen below.

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The IMF looked beyond the S&P500 to a broader set of nearly 4,000 US firms to show a similar rise in leverage and capability to service debt, as illustrated below.

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Another graph I found interesting from the IMF report was the one below on the level of historical capital expenditure relative to total assets, as below. A possible explanation is the growth in technology driven business models which don’t require large plant & property investments. The IMF report does point out that tax cuts or offshore tax holidays will, based upon past examples, likely result in more financial risk taking actions rather than increased investment.

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I also found a paper referenced in the report on pensions (“Pension Fund Asset Allocation and Liability Discount Rates” by Aleksandar Andonov, Rob Bauer and Martijn Cremers) interesting as I had suspected that low interest rates have encouraged baby boomers to be over-invested in equities relative to historical fixed income allocations. The paper defines risky assets as investments in public equity, alternative assets, and high-yield bonds. The authors state that “a 10% increase in the percentage of retired members of U.S. public pension funds is associated with a 5.93% increase in their allocation to risky assets” and for all other funds “a 10% increase in the percentage of retired members is associated with a 1.67% lower allocation to risky assets”.  The graph below shows public pension higher allocation to risky assets up to 2012. It would be fascinating to see if this trend has continued to today.

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They further conclude that “this increased risk-taking enables more mature U.S. public funds to use higher discount rates, as a 10% increase in their percentage of retired members is associated with a 75 basis point increase in their discount rate” and that “our regulatory incentives hypothesis argues that the GASB guidelines give U.S. public funds an incentive to increase their allocation to risky assets with higher expected returns in order to justify a higher discount rate and report a lower value of liabilities”. The graph below illustrates the stark difference between the US and Europe.

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So, in conclusion, unless Mr Trump does something really stupid (currently around 50:50 in my opinion) like start a war, current valuations can be justified within a +/- 10% range by bulls assuming the possibility of fiscal stimulus and/or tax cuts is still on the table. However, there are cracks in the system and as interest rates start to increase over the medium term, I suspect vulnerabilities will be exposed in the current bull argument. I am happy to take some profits here and have reduced by equity exposure to around 35% of my portfolio to see how things go over the summer (sell in May and go away if you like). The ability of Trump to deliver tax cuts and/or fiscal stimulus has to be question given his erratic behaviour.

Anecdotally my impression is that aging investors are more exposed to equities than historically or than prudent risk management would dictate, even in this interest rate environment, and this is a contributing factor behind current sunny valuations. Any serious or sudden wobble in equity markets may be magnified by a stampede of such investors trying to protect their savings and the mammoth gains of the 8 year old bull market. For the moment through, to misquote Chuck Price, as long as the music is playing investors are still dancing.

Pimping the Peers (Part 2)

In the last post on this topic, I highlighted how new technologies, broadly under the fintech tag, had the potential to disrupt the banking sector, primarily by means of automating processes rather than any major reinventing of business models (although I did end that post with a bit of a rant about innovation and human behaviour). Blockchain is the hot topic that seems to be cropping up everywhere (I’ll leave that for another time). This post is about insurance and new technology, or in the jargon, insurtech.

The traditional business model in the insurance industry is not reacting well to a world of low or negative interest rates. For the life insurance sector, the duration mismatch between their liabilities and their assets is having a perverse impact as interest rates have fallen. Savings returns for aging populations have been sacrificed in Central Bank’s attempt to stimulate economic growth.

In addition, the traditional distribution channel for selling life insurer’s products, and the old adage is that these products are sold rather than bought, has relied too heavily on aging tied agents whose focus is on the wealthy client that can generate more fees than the middle class. The industry is generally at a loss on how to sell products in a low interest world to the mass market and to the new tech savvy generation. As a result, the industry and others are throwing money at a rash of new start-ups in insurance, as the exhibit on some of the current hyped firms focusing on life insurance below illustrates.

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As the exhibit illustrates, the focus of these new start-ups is weighted towards technologies around product development, distribution, and underwriting. Some will likely succeed in trying to differentiate further the existing clientele of life insurers (e.g. real time health data). Many will be gobbled up or disappear. Differing attitudes between those aged under 34 and the older generation towards online distribution channels can be clearly seen in the survey results in the exhibit below.

click to enlargeattitudes-to-life-insurance-distribution-channels

With longevity and low interest rates the dominant challenges for life insurers today, automation of processes will assist in cutting expenses in the provision of products (mainly to the existing customer base) but will not likely meaningfully address the twin elephants in the room.  Citigroup reckons that in 20 of the largest OECD countries the unfunded government liability for pensions is around $78 trillion which compares to approximately $50 trillion in GDP for all OECD countries in 2015. I look forward to conversing with a robo-advisor in the near future on what products it recommends for that problem!

Insurance itself is hundreds of years old and although the wonderfully namely bottomry (the earliest form of marine hull insurance) or ancient burial societies are early examples, non-life insurance really took off with mass markets after the great fire of London in 1666.

The most hyped example of insurtech in the non-life sector is the impact of technologies on the motor business like drive-less cars and car telematics. This paper from Swiss Re shows that the impact over the next 20 years of such advances on motor premia could be dramatic.

Much of the focus from insurtech innovation is on reducing expenses, an item that the industry is not light on. The graph below shows examples of the level of acquisition and overhead expenses in the non-life sector across different jurisdictions.

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A recent report from Aon Benfield went further and looked at expenses across the value chain in the US P&C insurance sector, as below. Aon Benfield estimated overall expenses make up approximately half of gross risk premium, much of which represents juicy disruption targets for new technology in the insurtech world.

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Insurance itself is based upon the law of large numbers and serves a socially useful function in reducing economic volatility by transferring risks from businesses and consumers. In 1906, Alfred Manes defined insurance as “an economic institution resting on the principle of mutuality, established for the purpose of supplying a fund, the need for which arises from a chance occurrence whose probability can be estimated”.

One of the issues identified with the current non-life insurance sector is the so-called protection gap. This is in effect where insurers’ risk management practises have got incredibly adapt at identifying and excluding those risks most likely to result in a claim. Although good for profits, it does bring the social usefulness of the transference of only the pristine risks into question (for everybody else). The graph below from Swiss Re illustrates the point by showing economic and insured losses from natural catastrophe events as a % of GDP.

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It’s in the context of low investment returns and competitive underwriting markets (in themselves being driven by low risk premia across asset classes) that a new technology driven approach to the mutual insurance model is being used to attack expense and protection gap issues.

Mutuals represent the original business model for many insurers (back to burial schemes and the great fire of 1666) and still represent approximately a third of the sector in the US and Europe today. Peer to peer insurers are what some are calling the new technology driven mutuals. In fact, most of the successful P2P models to date, firms like Guevara, Friendsurance, and Inspeer are really intermediaries who pool consumers together for group discounts or self-financing of high deductibles.

Lemonade, which launched in New York this week, is a peer to peer platform which issues its own insurance policies and seeks to address the protection gap issue by offering broader coverage. The firm has been heavily reinsured by some big names in insurance like Berkshire Hathaway and Lloyd’s. It offers a fee based model, whereby the policyholders pay claims through mutualisation (assumingly by pools determined by pre-defined criteria). Daniel Schreiber, CEO and co-founder of Lemonade says that the firm will be ”the only insurer that doesn’t make money by denying claims”. Dan Ariely, a big deal in the world of Behavioral Economics, has been named as Chief Behavioral Officer, presumably in an effort to assist in constructing pools of well behaved policyholders.

The graphic below tries to illustrate how the business model is evolving (or should that be repeating?). Technology offers policyholders the opportunity to join with others to pool risk, hitherto a process that was confined to associations amongst professional groups or groups bound by location. Whether technology offers the same opportunity to underwrite risks profitably (or at least not at a loss) but with a larger reach remains to be seen.

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It does occur to me that it may be successful in addressing areas of dislocation in the industry, such as shortfalls in coverage for flood insurance, where a common risk and mitigant can be identified and addressed in the terms of the respective pool taking the risks on.

For specialty re/insurers, we have already seen a bifurcation between the capital providers/risk takers and the risk portfolio managers in the ILS arena. Newer technology driven mutual based insurers also offer the industry a separation of the management of risk pools and the risk capital provided to underwrite them. I wish them well in their attempts at updating this most ancient of businesses and I repeat what I said in part 1 of this post – don’t let the sweet scent of shiny new technology distract you from the smell of the risk…..

The Next Wave

As part of my summer reading, I finished Paul Mason’s book “PostCapitalism: A Guide To Our Future” and although it’s an engaging read with many thoughtful insights, the concluding chapters on the future and policy implications were disappointing.

Mason points to many of the same issues as Martin Wolf did in his book (see post) as reasons for our current situation, namely the inherent instability in allowing private profit seeking banks to create fiat money, ineffective regulation (and the impossibility of effective regulation), increased financialization, global flow imbalances, aging populations, climate change and the disruptive impact of new information technologies. This 2005 paper from Gretta Krippner on the financialization of the US economy and reports from S&P (here and here) on the policy implementations of aging demographics are interesting sources cited in the book.

It is on the impact of the information technology and networks that Mason has the most interesting things to say. Mason uses Nikolai Kondratieff’s long wave theory on structural cycles of 50-60 years to frame the information technological age as the 5th wave. The graphic below tries to summarise one view of Kondratieff waves (and there are so many variations!) as per the book.

click to enlargeHistory Rhyming in Kondratieff Waves

The existence of such historical cycles are dismissed by many economists and historians, although this 2010 paper concludes there is a statistical justification in GDP data for the existence of such waves.

Mason shows his left wing disposition in arguing that a little known theory from Karl Marx’s 1858 notebook called the Fragment on Machines gives an insight into the future. The driving force of production is knowledge, Marx theorises, which is social and therefore the future system will have to develop the intellectual power of the worker, enhancing what Marx referred to as the general intellect. Mason contends that the intelligent network we are seeing unfold today fits into Marx’s theory as a proxy for the general intellect.

Mason also promotes the labour theory of value, as espoused by Marx and others, where automation is predicted to reduce the necessary labour in production and make work optional for many in a post-capitalist world. To highlight the relevance of this possibility, a 2013 study asserted that 47% of existing jobs in the US would be replaced by automation. References to Alexander Bogdanov’s sci-fi novel Red Star in 1909 may push the socialist utopia concept driven by the information age too far although Mason does give realistically harsh assessments of Soviet communism and other such misguided socialist experiments.

The network effect was first discussed by Theodore Vail of Bell Telephone 100 years ago with Robert Metcalfe, the inventor of the Ethernet switch, claiming in 1980 that a network’s value is the number of users squared. Mason argues that the intelligent network, whereby every person and thing (through the internet of things) is wired to the network, could even reduce the marginal cost of energy and physical goods in the same way the internet has for digital products. Many of these ideas are also present in Jeremy Rifken’s 2014 book “Zero Marginal Cost Society”. Mason further argues that the network makes it possible to organise production in a decentralized and collaborative way, utilizing neither the market nor management hierarchy, and that info-capitalism has created a new agent of change in history: the educated and connected person.

The weakest part of the book are the final chapters on possible policy responses which Mason calls Project Zero with the following aims: a zero carbon energy system, the production of products and services with near zero marginal costs, and the goal of pushing the necessary labour time close to zero for workers. Mason proposes a trial and error process using agent based modelling to be adopted by policy makers to test post-capitalism concepts. He refers to a Wiki-State, a state that acts like the business model of Wikipedia nurturing new economic forms without burdensome bureaucracies. Such a state should promote collaborative business models, suppress or socialize info-monopolies, end fractional banking (as per the Chicago Plan), and follow policies such as a minimum basic wage for all to accommodate the move to new ways of working. All very laudable but a bit too Red Star-ish for me!

Nonetheless, Mason’s book has some interesting arguments that make his book worth the read.

 

An aside – As highlighted above, there are many variations on the Kondratieff long wave out there. An interesting one is that included in a 2010 Allianz report which, using the 10 year average yield on the S&P500 as the determinant, asserts that we are actually entering the 6th Kondratieff wave (I have updated it to Q3 2015)!

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Looking through some of the mountain of theories on long waves reminds me of a 2004 quote from Benoit Mandelbrot that “Human nature yearns to see order and hierarchy in the world. It will invent it if it cannot find it.