Huawei Quarantine Accelerates Tech ‘Balkanization’ Trend

“The three core issues of concern to China are the cancellation of all tariffs, that trade purchases be in line with reality, and that the text of the agreement be revised so as to be more balanced. These issues must be resolved. This trade friction has made us more aware that we have shortcomings in terms of economic structure, quality of development, and core technologies. [We must] enhance the sense of urgency in accelerating indigenous innovation and resolve the bottleneck imposed by insufficient mastery of core technologies. CCP Propaganda Department Commentary on the US confrontation in People’s Daily newspaper last Friday

We have regularly covered the rise of China’s tech sector over the past decade and the complacency in Silicon Valley which has only recently been shattered by Huawei’s threatened dominance of the global 5G rollout. The ‘balkanization’ trend already evident in software ecosystems from messaging to payments will now extend to hardware throughout the supply chain – there will be a China centric physical internet architecture over the next decade centred on Huawei as much as a software one around companies like Alibaba, Tencent and Bytedance with the big ‘neutral’ EM markets like India a key battleground.

In the near term, the notion that China can be quarantined as a technology supplier looks naïve – alternative vendors like Nokia and Ericsson make 5G hardware with Chinese partners in mainland factories for sale globally, leaving their equipment vulnerable to malicious tampering – will they have to relocate production to ‘safe’ locations to sell into the US? If so, the global rollout will be significantly delayed…

Huawei has been rapidly vertically integrating with its own chip making subsidiary, HiSilicon, producing highly advanced 5G designs, albeit fabricated (as for Apple and Google) by TSMC. As a Chinese tech VC contact told me in Shanghai last October, cut China off from TSMC and it would be casus belli like the Japanese oil embargo in 1940. If the US is serious about confronting China’s competitive threat on a sustained basis, it needs to boost government R&D spend on basic science (instead it’s been cut), deepen the capacity of domestic tech supply chains via education investment and targeted tax credits or cutting off broader Chinese access to advanced GPU chips and postgraduate student access to STEM courses at colleges such as MIT and Stanford. Those moves would be expensive and disruptive for the US economy and are still possible future steps if relations become even more antagonistic.

China offers uniquely low (marginal) consumer electronics assembly costs plus high-volume flexibility. You can never replicate the mainland factory dormitory model in the US or even Korea and Taiwan. The increasingly well educated rural migrants filling Foxconn factories are the ultimate ‘on demand’ workforce – manufacturing elsewhere would mean higher assembly costs/decreased flexibility thanks to the constraints of current generation assembly line robotics.

Even with high levels of automation, a fully US assembled iPhone would likely cost about 40% more at the factory gate (with Apple gross margins at ~37%, the current tariffs imply a price rise of about 15% to offset the impact, unless the RMB plunged toward 7.5 versus the USD). For instance, Quanta Computer, the largest laptop maker in the world with clients from Apple to Dell, warned last week that the logistical costs of shifting consumer electronics production out of China could prove as expensive as the tariffs themselves. 

Automation is part of the answer to offshoring from China but changes the business model – assembly by Chinese migrant workers is a marginal cost for a factory owner; robots are a fixed cost, although the assembly of an additional unit has zero marginal costs (excluding overheads like maintenance etc.). New AI software will help but it’s still expensive and time consuming to program factory robots to perform multiple tasks.

The implication of this shift from marginal to fixed costs is that there is a heavy incentive to stick with a specific design: any change requires significant capital investment to update the robotic assembly line – the flexibility of the entire consumer electronics sector will deteriorate, with higher inventories and fixed overheads once it loses China’s unique attributes as a global production base – given wafer thin margins, consumer prices will trend higher even if a face saving deal could avoid further tariffs.

Relocating the supply chain for smartphones or laptops will be hugely disruptive, wherever the destination and it certainly won’t be the US – the much-hyped Foxconn factory to make TV screens in Wisconsin has become a fiasco, despite $4bn in tax breaks and subsidies. The lack of a skilled manufacturing workforce will be a key constraint on US re-shoring, as much as logistics considerations – flying components in from Taiwan/S. Korea to assemble phones in the US makes little sense.

The effort to lobotomise Huawei looks ill thought out and will have generated intense lobbying by the most adversely impacted US suppliers – there will likely be some nuance in the implementation. However, the endgame is now clear and US tech companies will have to mitigate ongoing compliance risks by reducing exposure to Chinese SOEs. We’ve seen a few companies like Go-Pro begin relocation (to Mexico in this case), but this will now accelerate while China will race to become a ‘full stack’ technology power by mastering semiconductor fabrication and an indigenous mobile operating system.

In the case of both Iran and Huawei, the US has unilaterally exercised its global power over international bank payments systems and key technologies like the Android OS to exercise brute force geopolitical leverage – the lesson drawn by many in Europe and Asia is that alternative architectures are now needed. Ultimately, China which remains the only country apart from the US to understand the critical value of ‘platform’ software and is catching up rapidly in AI and quantum computing research, will become an even more formidable competitor to the US tech giants. The Xi 2025 plan, whose ambitions triggered panic in Washington from the Pentagon to Congress, will now be implemented sooner, by any and all means possible.

 

‘Peak Smartphone’ Slams Tech Hardware

‘…we are reaching ‘peak smartphone’ and the upgrade cycle is lengthening as new features prove less than compelling – the mobile app landscape has certainly become stagnant. Heavy discounting of the Samsung S8 ($150 plus) is apparent already in the US and the recent profit warning by the UK’s largest phone retailer highlighted a consumer behavioural shift. While the hype cycle will intensify ahead of this month’s launch of a premium advanced OLED screen model with facial recognition security, if the queues outside Apple shops for the new iPhones prove surprisingly short (or short lived), watch out below.’ Weekly Insight, September 6th, 2017

‘The ‘Peak Smartphone’ theme justified an underweight stance back in Q4 across the most heavily exposure Asian supply chain stocks, with DDR4 DRAM prices down about 20% from its January peak and NAND flash down a third. Many DRAM bulls put premature faith in AI and AVs as incremental demand drivers, certainly valid medium term, but not on a scale to offset smartphone/PV weakness this year while for chip makers the end of the crypto mining frenzy is starting to impact. TSMC said this week that sales will rise by only a ‘high single-digit’ percentage in USD terms, down from a previous (reduced) projection of 10%.’ Weekly Insight, July 20th 2018

The smartphone saturation risk we covered over a year ago has gone mainstream and rippled through the global hardware supply chain, with NAND flash prices crashing this year, DRAM also now peaking while production volumes for premium new phone models have disappointed across the sector. It’s hard to believe that most tech analysts missed this pretty obvious inflection point, when even the IMF noticed the industry had topped out as an Asian growth driver (smartphone shipments were about a sixth of global trade growth last year), but mindless extrapolation of the prevailing trend remains the default setting of bottom up analysts.

Smartphones have seen little innovation beyond camera quality and biometric security since 2016; the lack of compelling new hardware features (or new apps requiring them), and the growing ‘digital detox’ trend as awareness of the adverse productivity impact of notification addiction rises have both dragged on demand growth. Tighter network upgrade policies as well as limited ‘must have’ innovation have seen US and European consumers replacing phones every 2.5 plus years, a rise of 7-8 months since early 2016.

As we highlighted a year ago, the refurbished market has seen explosive growth and was the fastest growth segment last year, reaching over 140m units and is still growing at a mid-late teens pace. Three-year old ‘as new’ iPhones and Samsungs have been flooding emerging markets at typically a third of the price but nearly all the functionality of new. The weak outlook was confirmed by several Apple suppliers this week including Lumentum, Japan Display and UK chipmaker IQE this week – Apple as a ’luxury’ tech brand has finally succumbed to wider sector dynamics, although higher ASPs and the shift to services mean that the component supply chain takes a bigger hit.

Until 5G rolls out at scale from 2020 (and compelling new use cases beyond watching Netflix on the move have yet to appear), it’s hard to see the wireless sector regaining much impetus. While Samsung and Huawei plan foldable screen launches next year, initial volumes are likely to be modest at a price point above $1,000. Valuations now certainly look far more reasonable and expectations more realistic, but the downgrade cycle looks set to run into Q1 19. Our view remains to focus exposure  on stocks with high exposure to the nascent autonomous vehicle/automation sensor and emerging consumer segments such as smart speakers.

However, there will be an opportunity in the 5G rollout in niche areas such as high-end optical chips/dark fibre as well as smart antennae. Chinese producers will have a head start and gain critical mass, as the country embarks on the telecom equivalent of the hugely impressive high-speed rail network, which I used several times on a research visit last month. There will certainly be opportunities in China for specialist foreign vendors like Nokia, but the ‘full strength’ 5G being implemented via a new national core network is a critical component in the effort to drive domestic suppliers up the hardware value chain, in both phones and wireless infrastructure.

‘Volatility Volcano’ Erupts…

Changes in the real Fed funds rate have historically led realised equity volatility by about two years, due to the lags between official rate moves and risk-taking (the Fed started hiking in December 2015, albeit at a glacial pace). Low realized volatility feeding into quant based theoretical models has always fuelled the intellectual hubris of finance PhDs (think LTCM etc.) and ultimately proved toxic. The pre-crisis period shows that misplaced correlation assumptions can lead to a far more benign assessment of overall asset risk than is prudent.’  Weekly Insight ‘Sitting on the Volatility Volcano…’ Oct 12th 2017

‘That issue of deteriorating market depth and the proliferation of highly correlated factor based strategies which are de facto short volatility/long equity beta (including long duration corporate credit as an equity proxy) will become a big story next year…the value at risk models are in this sustained low realized volatility environment at maximum exposure to (particularly US) equities. A shock to consensus positioning, be it from inflation, policy or politics could see an ‘air pocket’ liquidity event. Overall, it looks wise to look for ways to trade against to trade the prevailing bias that growth, inflation and interest rates are anchored permanently lower.’ Weekly Insight, 18th December 2017

Our view coming into 2017 was that market structure rather than macro was the biggest risk and to prepare for both higher rates and volatility. That meant underweighting rate duration, being long equity reflation winners and finding volatility hedges. The importance of this selloff is to signal a shift to more nuanced risk appetite after the simplistic ‘melt up’ hype. As highlighted in those Q4 notes referencing the ominous LTCM precedent, the quant/factor investing boom was vulnerable to a paradigm shift in its input variables. While the financial engineers tinkering with factor models suffer a reality check, it’s unlikely that the multi-year bull market is over with earnings growth momentum still accelerating in many markets. Most systematic momentum following funds which soared in January are now down YTD, but given limited leverage overall, this doesn’t look a systemic event like LTCM threatened to become.

However, the role of ultra-low interest rates as a discounting mechanism and low realised volatility as a driver of equity appetite for factor-based strategies such as risk parity has belatedly come into focus for the consensus. If Q1 16 was about investors stress testing portfolios for deflation risks, this time the adjustment is to a higher risk-free discount rate; the 2-year bond overtaking the S&P dividend yield last month was a cautionary signal. When we initiated a VIX long in our tactical portfolio in October, it was one of the most glaring anomalies across markets and generated a 2.6x return when we took profits in this week’s panic.

The length of this correction will be determined by whether a ‘buy the dip’ mentality prevails among an influx of new Millennial investors evident in recent statements from online brokers like TD Ameritrade, as much as whether 10-yr yields will top out at 3% term. It’s unclear if some have been buying stocks on their credit cards, as they clearly were crypto coins in Q4 according to MasterCard’s latest results call (and watch for a spike in card delinquencies in Q2).

The rise in long-term US rates so far is less about Fed policy or inflation expectations as it is a looser fiscal stance. As highlighted in that December note, the supply of US bonds will rise sharply this year at the same moment that demand potentially ebbs as real economy demand for capital in Europe/EM rises. Meanwhile, the Fed will buy $420bn fewer Treasuries than it did in 2017 and in 2019 will reduce purchases by another $600bn. It certainly helps that the ECB and Bank of Japan will be buying nearly all local sovereign issuance and the jump in yields may encourage some active multi-asset managers to re-weight fixed income over equities, as well as the automatic risk-parity rebalancing.

Exposure to key secular themes such as autonomous vehicles/robots, the shift to ‘biological software’ in the drug industry etc. should be opportunistically accumulated into weakness. Earnings momentum globally remains strong;  the scale of guidance upgrades in Japan which has a dominant position in several emerging technology supply chains such as Lidar, vision sensors, monoclonal antibodies and EV batteries should offer support once markets settle. Meanwhile, active investors can take some comfort from the humiliation of the quants whose share of the market has risen to unhealthy and potentially destabilising levels.

 

Tech ‘Second Movers’Begin to Perform

The right place this year has been in tech, above all for EM investors with the sector now over a quarter of the MSCI index and accounting for almost half of total performance YTD. The rise of ‘embedded intelligence’ as vision and other sensors enabled by AI software become ubiquitous has been a key theme of ours in recent years, and has attracted a belated consensus frenzy this year, with pure play stocks from Nvidia in the US to iFlytek in China soaring. However, the growth into value tilt we’ve suggested since the summer applies within as well as across sectors. There has been a pretty spectacular valuation arbitrage as new hardware technology and business models are adopted from retail to autos, among incumbents who sit on a fraction of the multiples of the perceived pure play tech leaders. We will see a similar trend in banking/insurance over the next couple of years as fintech startups broadly disappoint, but their innovations slash operating and customer acquisition costs for the more far sighted established names.

The global auto sector has rallied hard since the summer, partly because investors are waking up to the fact that several automakers have very undervalued IP in the EV/AV/transportation as a service space that offsets the wider industry stranded asset risk. This reflects the historical pattern as innovation diffuses – the re-rating opportunity from tech will increasingly be among incumbents adopting new technology to boost competitiveness, from Japanese banks like SBI experimenting with blockchain/crypto payments to car makers like GM, Toyota or Ford able to scale EV/AV roll out better than Tesla ever can. Selling digital advertising via click-bait news feeds is infinitely easier than mass manufacturing.

Indeed, the aggregation effects that fuelled social media/search and e-commerce platforms are not generally relevant in hardware, which tends to get commoditized rapidly. From an investment perspective we’ll have a multiplicity of overlapping technologies and ways to play their relative success, most of which will be in long established but reinventing blue chips. Disruption reflected in relative performance may well be driven more from within incumbent sectors (reflected in rising return dispersion) than from outside them.

WalMart has rallied strongly in recent months versus Amazon and GM versus Tesla as both start benefiting from the underestimated ‘second mover’ advantages of allying scale economies with new business models and technologies. GM or GE were not first movers in diesel locomotive engines in the 1930/40s but by rapidly buying up promising start-ups and harnessing them to vast engineering and balance sheet resources ended up dominating the transition from steam over the subsequent two decades, crushing smaller ‘first mover’ competitors along the way.

second movers

The parallels with GM’s pivotal Cruise Automation acquisition and Chevy Bolt platform being rolled out via Lyft are worth watching closely (with Ford attempting a similar reinvention) as are WalMart’s belated e-commerce shift via the Jet.com acquisition. The breathless Silicon Valley hype is ignoring a looming period of accelerated evolution within sectors that will radically change their leadership and where spotting the sector Dodos unable to rapidly evolve within a portfolio is critical.

As an example, being a value investor in tech is generally a losing proposition but Intel which in terms of chip sector evolution has become a ‘second mover’ by missing the GPU versus CPU shift has been racing to integrate a series of strategic acquisitions (notably Mobileye in autos and Nervana in AI chip design) to play catch up in this market – if it succeeds against low expectations, the huge valuation discount to the perceived AI market leaders will close and versus AMD relative performance has now turned decisively. Tech disruption won’t be the much feared extinction event for adaptable incumbents – the quality of management will be key alongside aggressive M&A to preempt new entrant threats, but there are growing signs that hugely rated tech insurgents are not  going to have it all their own way for much longer. Therein lies the investment opportunity…

 

Blockchain Deconstructs the Corporation…

JPM CEO Jamie Dimon recently declared that he would sack any of his traders playing bitcoin which he compared to Tulip mania, but given the broad volatility famine that has crushed Wall Street’s Q3 results, any half decent trader would surely be keeping their skills sharp in the wild world of cryptocurrencies. It’s important to differentiate between permissioned networks (e.g. across banks to settle securities) with a central authority and fully autonomous ‘permissionless’ ones such as that underpinning bitcoin, which threaten the role of banks as the apex of a longstanding financial hierarchy. Near term, blockchain offers banks, insurers and asset managers a margin windfall by slashing processing costs – long term, it threatens to undermine their gatekeeping role.

While I’ve been a sceptic of the recent ICO boom and the resulting profusion of new cryptocurrencies (supply certainly isn’t limited in the aggregate), but blockchain is probably comparable in long-term impact to the TCP/IP internet protocol in the 1990s. In other words, it could prove as significant an enabling technology in transactional terms as the original internet protocol was in transforming communications. By now, all investors are aware of the disruption risk to many incumbent business models from new technologies that shatter barriers to entry and compress margins and pricing power, but there is an even more fundamental question looming.

Could the firm, in the sense of the formal corporate entities that have evolved since Dutch spice expeditions to Asia gathered risk sharing investors in the 17th century, now become unbundled?  The information search comparative advantage of the firm versus consumer  or individual entrepreneur in classic microeconomic theory has narrowed dramatically while the cost of enforcing and supervising contract execution has tumbled via sharing economy models and soon the widespread use of digital ledgers.

As a reminder, blockchain is a distributed ledger technology, and uses a self-sustaining, peer-to-peer database to record and manage transactions in a decentralized manner. Verification of data is undertaken via complex algorithms and consensus among multiple systems, making it almost completely tamper-proof.  Data is transferred or stored using a series of blocks, each of which have a cryptographic hash protecting its contents. Any update or transaction on the data creates a new record in the form of another block, which is added to the existing blockchain.

The defining, radical characteristic of the digital economy in terms of traditional economics is its zero-marginal cost and we’ve now reached a point where something can be simultaneously digital and unique, without any tangible representation (bitcoin being a case in point). The bedrock of economic exchange is trust, and we now have technology that allows a reliable degree of trust to be established between total strangers in order to share resources, which has had profound implications for investors. That principle can be applied via the blockchain to anything from stock certificates to trust contracts, property title deeds etc. In that scenario, the elaborate hierarchy of trust we have built over several centuries via the legal system and complex compliance and oversight procedures becomes increasingly redundant.

This new distributed trust architecture could replicate much of the organization of a firm built on contracts, from incorporation to supply chain relationships to employee relations. If contracts can be automated, then what will happen to traditional firm hierarchical management structures, processes, and intermediaries like lawyers? Much of the corporate world is built on exploiting transactional ‘friction’ and information asymmetries between consumers and suppliers – the Internet over the past two decades has been a force for reducing these profit opportunities, from hotel room pricing to asset management. While crowdsourced trust between strangers via sharing economy platforms has been powerful in this respect, the advent of the blockchain over the next few years looks far more revolutionary.

As I’ve highlighted in many notes, online services and the advent of AI software are reducing slack and redundancy in the economic system – the internet from its inception has been about reducing search costs and price asymmetries between producers and consumers i.e. acting as a fundamentally deflationary force (a shift which central bankers still struggle to adapt their outdated equilibrium models to). Sharing economy platforms are zero marginal cost business models in terms of adding inventory (e.g.  advertising for Google/Facebook).

Google, Facebook, Twitter or Airbnb rely on the contributions of users as a means to generate value within their own platforms. Of course, in the existing sharing economy model, the value produced by participants is harvested by the platform owner with most of those contributing to the value production getting nothing beyond free access to services like social media, search or marketing their products.

Blockchain changes that because it facilitates the exchange of value in a secure and decentralized manner, without the need for an intermediary – to that extent, it’s a medium term threat to incumbent web giant business models, which are centralized rather than distributed and extract economic rent from often unwitting users. Digital ledgers and smart contracts reduce the capacity of the firm to enforce and exploit ‘trust arbitrage’. A far more fluid economic structure will develop over the next decade and beyond, with project focused associations of specialists coalescing and disbanding, their contractual obligations and financial entitlements will be delivered via blockchain.

Next year, we will begin to see significant blockchain and ‘smart contract’ deployment across the finance sector from maritime insurance contracts that rewrite themselves in real time to asset leasing and securities settlement. The logistics/freight forwarding business is another ripe for disruption and millions of mid-level admin jobs will be automated out of existence globally over the next few years as a result. While positive for early mover finance sector margins over the next few years, the implications for prime real estate look ominous, as office towers, which are simply warehouses of human inventory, begin to empty out.

Blockchain protocols make it technologically possible for a ‘Decentralized Autonomous Organization’ (DAO) of individuals with relevant skills to associate and organize for a specific task with the power to execute smart contracts between them and a client that can replicate many of the functions of a traditional corporate entity.  This shift marks the advent of a new generation of “dematerialized” organizations that do not require physical offices, assets, or even formal employees. Of course, this utopian vision won’t apply where regulatory compliance demands a centralized authority or significant capital/fixed investment is required but can certainly work across many ‘asset light’ service sectors from design to advertising and professional services, where freelancing is already common.

There is also a trade-off between blockchain network size versus transaction frequency. The blockchain is so far struggling to solve this trade-off between network size versus transactional frequency, and until that technical dilemma is resolved it’s hard to see this technology competing with existing payment networks like credit card networks or SWIFT on a global scale anytime soon (i.e. achieving several thousand transactions per second).

However, despite these and other limitations, the huge scale of capital now being invested in this area (some of it via the notorious ICOs) and surging interest from blue chip companies (particularly in Japan, as covered recently) suggest that every investor needs to reflect on the nature and implications of this potentially revolutionary technology. The current generation of cryptocurrencies may ultimately fall by the wayside, but the innovations that enabled them almost certainly won’t…

Tech Barbarians at the Gate?

As the global economy rapidly digitizes, the threat from radical new business models is critical for investors to understand. Plans to attack sectors from energy to banking are advancing rapidly and on my trips to Silicon Valley I’ve noted that the smartest software coders and entrepreneurs are often driven by an almost messianic libertarian zeal to overthrow the existing order. The top down, centralized paradigm from utilities to telecoms and banking will be gradually eroded by these new models which only have to take a tiny market share to create disproportionate damage on incumbent margins and valuations. Indeed, the smarter companies in vulnerable sectors like banking are already trying to co-opt Silicon Valley to improve their relative competitive position.

However, most corporate boards are thinking like French generals as they huddled behind the Maginot line in 1939, oblivious to the risk that German generals would simply outflank them. The role of rapid shifts in technology as a driver of macro trends in recent years remains largely overlooked, but as noted previously it has been a key factor driving weak corporate capex (as fast deflating IT gains a larger share – more data servers, fewer fixed structures to generate incremental revenue) to disinflation and weak wage growth/rising inequality.

In this new era, an unprecedented amount of economic power is concentrating in no more than 20-30 global tech companies through whose servers the key raw material of the information age passes i.e. consumer profiling data which can be process via proprietary algorithms to do anything from inferred credit scoring to targeted location based advertising. They’re driving tanks at breakneck speed while much of the non-tech corporate world is still digging trenches…
With the explosive growth in cheap smartphones and ubiquitous Wi-Fi bringing hundreds of millions of emerging economy consumers online every year for the first time, we’re entering an era when messaging platforms may dominate, as ubiquitous smartphones/free Wi-Fi mean that operating systems and carrier networks matter far less. The gatekeepers are companies like Tencent and Facebook collecting behavioural data on approaching 2bn potential customers between them. It’s not a question of if but how these huge audiences will be monetized.

The biggest issue for investors outside the tech sector to ponder on a 3-5 year view remains the trend toward tech enabled ‘unbundling’ in many sectors i.e. the value proposition underpinning many blue chip non-tech companies is disassembled and rebuilt as supposedly impregnable barriers to entry tumble (from wireless bandwidth to utility grids). The hugely complex logistics of ‘sharing economy’ models like Uber or Air BnB are only possible because of ever more advanced smartphones and fast advancing artificial intelligence and ever cheaper cloud based data analytics – those models can be extended to many more sectors as what works for taxis will also work for say parcel/food delivery.

In many ways, the popular  ‘secular stagnation’ thesis is largely missing the point as much innovation is now focused on radical new business models to optimize the utilisation of existing resources and the software platforms that support them, which thanks to the smartphone boom can explode to global scale at astonishing speed and low cost.  Like the horsemanship and mobility of the Barbarian tribes ravaging the outposts of the late Roman empire, that will eventually change everything…  

Tech Driven ‘Creative Destruction’ Remains Key Global Trend…

‘Admittedly, during the First and Second Industrial Revolutions the magnitude of the destructive component of innovation was probably small compared to the net value added to employment, NNP or to welfare. However, we conjecture that recently the new technologies are often creating products which are close substitutes for the ones they replace whose value depreciates substantially in the process of destruction.’ New NBER paper on the latest wave of technology driven ‘creative destruction’

Academic economists are beginning to wake up to the macro implications of the accelerating digitization and dematerialization of the global economy, which has been a key structural theme both in terms of its impact on interest rates, inflation etc. but also portfolio weightings – earnings power across many established sectors will be destroyed by new entrants, who will see earnings explode even as they offer services at a fraction of the cost of incumbents e.g. instant messaging versus SMS revenues. The point the study is making is that unlike previous disruptive cycles (the industrial revolution from the mid-19th century, the first IT revolution from the 1970s) much of this mobile/cloud based service innovation destroys value within the overall economy to the extent that there is a net loss of profits, jobs etc., a topic I’ve covered recently in notes looking at deep automation/robotics and the sharing economy trend. However, one thing I’d note is that nearly every tech innovation of recent years from instant messaging to social media has been initially dismissed as trivial, but that ignores the huge impact of rapidly scaling network effects in creating utility for consumers and market value for investors. The value of LinkedIn or WeChat to users lies in the critical mass of peers they offer access to and the value to investors is the near zero marginal cost of adding new users. There are certainly too many mobile messaging services and the sector in aggregate is overvalued, as highlighted in previous notes, but the opportunity for the winners to take revenue from the established offline media and financial services sectors remains compelling. Against this secular backdrop, the NASDAQ Internet Index hasn’t quite regained its March peak but is 20% above the low set in early May after a brutal selloff as momentum positions unwound; the US Biotech Index, which led the momentum stock selloff in Q2, has broken out to a marginal new high and is up almost 30% from its mid-April low. Analysts have been upgrading their earnings estimates for the Biotech sector, with earnings now expected to rise almost 40% this year.

Meantime, Facebook, Google, and Twitter all reported above consensus results for Q2 and forward earnings for the internet sector have risen to a new record with about 20% compound earnings growth expected across the sector over the next few years. Chinese web stocks have generally continued to beat expectations from Tencent to Alibaba, the former driven by mobile gaming leveraging the 350m WeChat user base and the latter by mobile e-commerce, with active users up to 188m in Q2 and mobile up to almost 33% of gross sales volume. I noted in the 10th September note last year on the sector that: ‘China’s combined dominance as a smartphone market and manufacturing base has very bullish implications for domestic web software and service companies. For software companies from Google to Microsoft, smartphones are simply the platform for profitable content delivery. The value of content consumed on Android devices will explode in the coming years, starting with ‘in -app’ click through purchases in games and ads viewed while browsing, but smartphones will become the terminal of choice for e-commerce and the decision point for offline retail purchases too.’ Alibaba’s float is likely to drive volatility in smaller Asian tech sector names as portfolios reposition to fund their allocation, particularly as the internet sector has regained its Q2 losses, but it’s hard to see Alibaba generating the 13x 10-year returns of Google which was a very misunderstood business model at its $95 IPO price. For non-benchmark huggers, there will be a tactical trading opportunity in the wider Chinese tech ecosystem over the next couple of months – the secular outlook for the digitization of the Chinese and other EM economies remains very bullish. On that note the more modest but still multibillion float of e-commerce start-up incubator Rocket Internet bears watching. It’s an odd company which has been accused of ‘cloning’ established online business models, with its hugely well-funded operations led by former management consultants rather than entrepreneurs and little of the typical Silicon Valley start-up culture. Nonetheless, it has established leading positions in e-commerce markets across ASEAN, which ex Singapore are several years behind China in terms of development but will catch up rapidly as smartphone penetration rates rise and mobile payment systems mature.

Silicon Valley Driving Economic ‘Optimization’…

‘Like the internet, Bitcoin is a platform. It’s less what can it do today, more what can it do in the future. Digital cash, digital keys, digital voting, digital stocks, digital bonds…Bitcoin could basically reconstruct the financial industry in an untrusted peer-to-peer environment. This is why all the technologists look at it and get excited.’

Internet pioneer and venture capitalist Marc Andreessen speaking recently

  • Last week on my visit to Silicon Valley, digital currencies were the recurrent subject of conversations with VC investors, academics and tech start-ups – achieving a breakthrough appeals to the overwhelmingly libertarian instincts of the (surprisingly small and incestuous) West Coast tech elite.  I’m now even more convinced that the financial sector faces significant disruption over the next 5-10 years as peer-to-peer online financial exchanges gradually move into the mainstream. Regardless of whether Bitcoin or its successors ever gain mass acceptance for transactional purposes, this uniquely secure architecture based on massive computational power means that a highly distributed alternative to the centralized and costly infrastructure of Wall Street banks is within reach. As I pointed out in the recent sharing economy note, the bedrock of economic exchange is trust, and technology now allows a reliable degree of trust to be established between total strangers in order to share resources and securely arrange complex financial transactions, all of which has profound implications for investors.
  • Google was holding its annual developers conference in SF while I was there, focused on spreading Android far beyond smart phones into home appliances and wearable devices; the city was full of out of town software geeks navigating the endless street sleepers (many of the latter with serious mental health issues but then many of the most creative tech innovators have been on the spectrum – visionary oddballs thrive in a way culturally impossible in Asia). The event was packed, unsurprising when Google has shelled out $5bn over the past year on its independent developers compared to $2bn the year before, and scale is becoming critically important in mobile – for smaller companies, carving out a niche within the distinct ‘ecosystem’ of a giant like Google or Tencent is the only rational business model.
  • I was struck repeatedly on my trip by the innovative ways US service sector companies are using technology to boost efficiency to an extent rarely seen in Europe or Japan (although those markets are where the margin windfall upside from adopting US best practice will ultimately be greatest). The ability to quantify productivity at the micro level within companies is clearly surging even as the macro stats struggle to capture the impact. Indeed, after the Q1 GDP revision to -2.9% against the backdrop of a solid labour market, US productivity in the conventionally calculated GDP/hours worked calculation has collapsed in recent months, falling 5-6% y/y in Q1. However, that approach as noted previously works in a ‘heavy’ economy with predominantly tangible output like China, but is struggling to cope with a digitized and dematerialized one, where the biggest investment is in intellectual property products. When your marginal cost and labour input both approach zero for an increment of output (helping explain the astronomic valuations for companies like Uber and AirBnB) your productivity gain approaches infinity. Of course, in the more mundane world of physical infrastructure, the US is chronically under investing and remains backward in using public-private partnerships to fund toll roads, airports etc. as is common from France to China.
  • Productivity on a top down basis is basically a residual within the economic system and the more appropriate metric is now corporate margins/profitability (and indeed very modest wage pressures). As for the Q1 GDP revision, one key factor was a dramatic reduction in estimated consumer spending on healthcare as Obamacare went live; I highlighted a disinflationary trend in the bloated US healthcare sector in a recent note (inflation at the lowest since 1981 etc.) and near term this has an adverse impact on GDP but has to be a good thing – soaring benefit costs since the mid-1990s suppressed wage growth and diverted potential discretionary spending. The bottom line for investors is that profound structural shifts in the global economy driven by both technology and demographic trends will make the macro data unusually confusing (e.g.  20somethings who own little more than a laptop and phone being the biggest age cohort in the US right now, China’s deposit growth ebbing with the working age population). Optimization is the buzzword I kept hearing from both the money men and engineers and it captures the macro impact of tech innovation – ironically, the Soviets with their ‘cybernetics’ initiative in the 1960s to boost productivity (and a wonderful book on the subject is ‘Red Plenty’) were the first to attempt the use of algorithms to optimize resource use but of course the huge perverse economic incentives within the communist system, political sclerosis as well as contemporary technology limitations made it a hopeless dream. However, it’s perhaps no coincidence that a disproportionate number of the leading software engineers in Silicon Valley are mathematically gifted Russian dreamers.

The ‘Sharing Economy’ Shock…

The bedrock of economic exchange is trust, and technology now allows a reliable degree of ‘crowd sourced’ trust to be established between total strangers in order to share resources, which has profound implications for investors. As I’ve highlighted many times, a range of new online services are reducing slack and redundancy in the economic system – the internet from its inception has been about reducing search costs and price asymmetries between producers and consumers i.e a fundamentally deflationary force. These ‘sharing economy’ business models are typically zero marginal cost in terms of adding inventory, simply acting as a marketplace brokering transactions between individuals and thus have a potentially exponential growth path, explaining heady venture capital valuations.

Opportunities for these business models to tap into idle or underutilized inventory abound – the average car in a large Western city sits unused 90% of the time, and the opportunity to tap into that unused transportation capacity is the target of numerous start-ups. One of the most interesting I’ve seen recently is a grocery shopping service, that for a small fee sends a freelance ‘personal shopper’ and their car to the supermarket of your choice, to be delivered to your home. No new depots or delivery vans as captured by conventional capital spending measures and yet incremental productive capacity unleashed – this trend will make the US and other advanced economies inherently ‘lighter’ over the next decade.

We are seeing hundreds of similar ‘sharing economy’ apps from parking space rental in unused urban front drives to appliance sharing (does every garden shed really need a lawnmower?). Aside from the incremental impact of underutilized capacity being monetized over the next few years (implying fewer new hotel rooms/cars etc.), we are seeing an interesting cultural shift among the under 30s in the desirability or need for ownership, whether of a property or consumer durable.

Meantime, drivers of London’s iconic black taxi cabs (the ones that spew out noxious diesel fumes and often equally noxious political opinions if you’re unwise enough to engage in conversation with the driver) are planning to paralyse the city next month in protest against Uber’s expansion to London with its smartphone app based private car hire service. With average earnings of £40-60k depending on hours and whether they own or rent their cabs, taxi drivers pull in up to twice national average earnings for a skill which was rendered obsolete by technology a decade ago i.e. memorizing a map of London. They are likely to go apoplectic when US service Lyft (which is more of a pure sharing economy model allowing private individuals to become ad hoc taxi drivers) inevitably arrives in the UK. It’s a bit like dockside stevedores fighting the advent of containerization back in the 1960s, the hopeless battle of a closed shop against technological innovation and another bastion of premium semi-skilled incomes being demolished by Silicon Valley invaders – the overachieving geeks love nothing more than blowing up barriers to entry with some clever code.

The original sharing economy shock hit the music and media industries a decade ago, as consumers dis-intermediated the industry giants to become producers of their own content, creating huge value for platforms that rode the trend like YouTube. As covered in previous posts, the financial world is now in the cross hairs of the tech giants monetizing messaging apps as well as innumerable well-funded start-ups; we’re seeing a surge in innovation from peer-to-peer lenders such as Lending Tree to angel VC funding. Fund managers won’t be immune – for instance, online brokerage start-up Motif Investing offers professionally weighted stock baskets based on crowd sourced top-down thematic asset allocation ideas.

I’m in Silicon Valley next month visiting VC and hedge funds and looking at the next wave of these disruptive business models, which bear close watching for their impact on established industries and the confusion they are already creating in interpreting increasingly outmoded economic statistics (e.g. the freelancing/self-employment trend distorting employment data). We’re entering a world where anyone in a major city can use these platforms to freelance as an amateur landlord, taxi driver, tutor etc. and derive multiple income streams but also in the early stages of a technology driven economic shift which will have major implications for trend inflation, capex and profit margins over the next decade and should be a key investor (and indeed policymaker) focus.

Investors Focus on Tech Disruption Risks…

On my latest roadshow around Asia, the macro implications of new technologies were a key presentation theme and topic for debate as much as China’s leverage unwind, and indeed tech has been a sustained overweight and the subject of several notes over the past year, including the ‘Rise of the Machines’ looking at the next wave of automation published last April. On that topic, I suggest that every investor reads “The Second Machine Age” by Erik Brynjolfsson and Andrew McAfee of MIT, which I finished on my travels (and “The Zero Marginal Cost Society” by Jeremy Rifkin covers the same ground, albeit with a more utopian bias). They posit that advances in computer technology, robotics and artificial intelligence mean that an algorithm driven automation wave will erase many job functions over the next decade. It will also slash the profitability of many consumer facing sectors, as we’ve seen already from music to mobile operators, by crashing entry costs and margins. In Shibuya in Tokyo, I visited a café with 3D printing machines for hire for instant prototyping (mostly for Kawaii trinkets, from what I saw, but this technology is now going mainstream for niches like biomedical implants), an early sign of a very different future for mass manufacturing and the associated global supply chain. I met a hedge fund manager who is so paranoid about being eavesdropped that he uses the highly secure Telegram app for his instant messaging, and a proxy web server that hops around a dozen countries for everything else – I didn’t ask if he’s taking his fees in Bitcoins. Meantime, Alibaba bought a controlling stake in ChinaVision to launch a Netflix style content streaming business and a stake in a US messaging app to combat Tencent’s mobile threat ahead of its landmark US listing (which will likely ring the bell on the increasingly frothy wider social media/mobile web subsector near-term – note the selloff in equally heated US biotech).

The integration of neuroscience and software to give say a factory robot the intelligence to ‘learn by doing’ i.e. rewriting its own software code by simply repeating a task, would have profound implications. Indeed the topic of machine learning and its macro consequences are critical for investors to understand – one point I’ve made repeatedly is that the ‘cognitive threshold’ for a job in terms of its automation vulnerability is rising very rapidly now, and given the immutable IQ bell curve a substantial proportion of the population will simply become surplus to requirements. There are of course plenty of signs of this already, including high levels of graduate unemployment globally – about 3m Korean graduates are ‘economically inactive’ in an academically obsessed country, while US graduate underemployment is becoming entrenched. This looks quite different from the industrial revolution that began 150 years ago and which saw a huge migration in Europe and then the US from farms and country to factories and cities, driving a virtuous urbanisation/productivity cycle as repeated in recent decades in China. A trend I’ve highlighted is the growing concentration of household and corporate wealth and cash flows, the latter focused on the tech sector which is leading the overall economy toward a growing ‘dematerialization’ i.e. we need less capital and labour input for every increment of GDP and corporate revenue (and China will belatedly make that same shift, as its own tech giants begin devouring SOE margins). Think for instance of the implications of all those taxi booking apps proliferating from the US to China – by matching supply and demand more precisely and adding private limo supply (and in Uber’s case removing fixed pricing), they reduce redundancy and the overall fleet of vehicles required to serve any given population – Airbnb is doing the same to hotels by adding private spare bedrooms as a competitor.

Sophisticated data analysis reduces capacity slack in the system (as airlines have known for many years) but huge chunks of the global economy are now becoming subject to similar optimising ‘yield management’ software. If Amazon can generate a million USD of incremental turnover with a tenth of the labour and even less real estate overhead of a WalMart, the only rational response of the latter (and Tesco etc.) is to restructure their business model as margins get compressed. Having a large legacy workforce and real estate assets to restructure and downsize as new online entrants cherry pick your client base is a looming threat – there will however be a first-mover advantage for those adapting business models early.