25/4/18: Draining of the Washington Swamp Reveals Mulvaney

Quote of the month, if not of the year, belongs to yet another Trump Administration 'draing the swamp hero, Mick Mulvaney, currently the White House budget director and, according to some rumours, a prime candidate to be the next Chief of Staff. Speaking at the American Bankers Association, Muvaney, who previously served as a Congressman declared: "We had a hierarchy in my office in Congress. If you're a lobbyist who never gave us money, I didn't talk to you. If you're a lobbyist who gave us money, I might talk to you."

So here we have it, folks: top Trump official claiming on the record to have engaged in a cash-for-influence peddling, the very same offence that Trump campaign routinely accused the Clinton Foundation of.

That is some draining of the Washington swamp that President Trump accomplished. Right there, in swamp's prime dweller's own words.

Link to the quote: http://www.businessinsider.com/mick-mulvaney-tells-bankers-donate-to-congress-for-influence-2018-4.

As an aside, Pew Research data shows that the American people, by a large majority, are aware of the deep corruption in Washington. "Americans think that those who donate a lot of money to elected officials have more political influence than others. An overwhelming majority (77%) supports limits on the amount of money individuals and organizations can spend on political campaigns and issues. And nearly two-thirds of Americans (65%) say new laws could be effective in reducing the role of money in politics." (see http://assets.pewresearch.org/wp-content/uploads/sites/5/2018/04/26140617/4-26-2018-Democracy-release.pdf).

One the results: "Overall, nearly six-in-ten Americans (58%) say democracy in the United States is working very or somewhat well, though just 18% say it is working very well. Four-in-ten say it is working not too well or not at all well."

Any surprise, when the likes of Mulvaney are running public offices?

25/4/18: Dombret on the Future of Europe

An interesting speech by y Dr Andreas Dombret, Member of the Executive Board of the Deutsche Bundesbank, on the future of Europe, with direct referencing to the issues of systemic financial risks (although some of these should qualify as uncertainties) and resilience of the regulatory/governance systems (I wish he focused more on these, however).

https://www.bis.org/review/r180226b.pdf (Links to an external site.)

25/4/18: Tesla: Lessons in Severe and Paired Risks and Uncertainties

Tesla, the darling of environmentally-sensible professors around the academia and financially ignorant herd-following investors around the U.S. urban-suburban enclaves of Tech Roundabouts, Silicon Valleys and Alleys, and Social Media Cul-de-Sacs, has been a master of cash raisings, cash burnings, and target settings. To see this, read this cold-blooded analysis of Tesla's financials: https://www.forbes.com/sites/jimcollins/2018/04/25/a-brief-history-of-tesla-19-billion-raised-and-9-billion-of-negative-cash-flow/2/#3364211daf3d.

Tesla, however, isn't that great at building quality cars in sustainable and risk-resilient ways. To see that, consider this:

1. Tesla can't procure new parts that would be consistent with quality controls norms used in traditional automotive industry: https://www.thecarconnection.com/news/1116291_tesla-turns-to-local-machine-shops-to-fix-parts-before-theyre-installed-on-new-cars.
2. Tesla's SCM systems are so bad, it is storing faulty components at its factory. As if lean SCM strategies have some how bypassed the 21st century Silicon Valley: http://www.thedrive.com/news/20114/defective-tesla-parts-are-stacked-outside-of-california-machine-shop-report-shows.
3. It's luxury vehicles line is littered with recalls relating to major faults: https://www.wired.com/story/tesla-model-s-steering-bolt-recall/. Which makes one pause and think: if Tesla can't secure quality design and execution at premium price points, what will you get for $45,000 Model 3?
4. Tesla burns through billions of cash year on year, and yet it cannot deliver on volume & quality mix for its 'make-or-break' Model 3: http://www.thetruthaboutcars.com/2018/04/hitting-ramp-tesla-built-nearly-21-percent-first-quarter-model-3s-last-week/.
5. Tesla's push toward automation is an experiment within an experiment, and, as such, it is a nesting of one tail risk uncertainty within another tail risk uncertainty. We don't have many examples of such, but here is one: https://arstechnica.com/cars/2018/04/experts-say-tesla-has-repeated-car-industry-mistakes-from-the-1980s/ and it did not end too well. The reason why? Because uncertainty is hard to deal with on its own. When two sources of uncertainty correlate positively in terms of their adverse impact, likelihood, velocity of evolution and proximity, you have a powerful conventional explosive wrapped around a tightly packed enriched uranium core. The end result can be fugly.
6. Build quality is poor: https://cleantechnica.com/2018/02/03/munro-compares-tesla-model-3-build-quality-kia-90s/.  So poor, Tesla is running "reworking" and "remanufacturing" poor quality cars facilities, including a set-aside factory next to its main production facilities, which takes in faulty vehicles rolled off the main production lines: https://www.bloomberg.com/view/articles/2018-03-22/elon-musk-is-a-modern-henry-ford-that-s-bad.
7. Meanwhile, and this is really a black eye for Tesla-promoting arm-chair tenured environmentalists, there is a pesky issue with Tesla's predatory workforce practices, ranging from allegations of discrimination https://www.sfgate.com/business/article/Tesla-Racial-Bias-Suit-Tests-the-Rights-of-12827883.php, to problems with unfair pay practices https://www.technologyreview.com/the-download/610186/tesla-says-it-has-a-plan-to-improve-working-conditions/, and unions busting: http://inthesetimes.com/working/entry/21065/tesla-workers-elon-musk-factory-fremont-united-auto-workers.  To be ahead of the curve here, consider Tesla an Uber-light governance minefield. The State of California, for one, is looking into some of that already: https://gizmodo.com/california-is-investigating-tesla-following-a-damning-r-1825368102.
8. Adding insult to the injury outlined in (7) above, Tesla seems to be institutionally unable to cope with change. In 2017, Musk attempted to address working conditions issues by providing new targets for fixing these: https://techcrunch.com/2017/02/24/elon-musk-addresses-working-condition-claims-in-tesla-staff-wide-email/. The attempt was largely an exercise in ignoring the problems, stating they don't exist, and then promising to fix them. A year later, problems are still there and no fixes have been delivered: https://www.buzzfeed.com/carolineodonovan/tesla-fremont-factory-injuries?utm_term=.qa8EzdgEw#.dto7Dnp7A. Then again, if Tesla can't deliver on core production targets, why would anyone expect it to act differently on non-core governance issues?

Here's the problem, summed up in a tight quote:

Now, personally, I admire Musk's entrepreneurial spirit and ability. But I do not own Tesla stock and do not intend to buy its cars. Because when on strips out all the hype surrounding this company, it's 'disruption' model borrows heavily from governance paradigms set up by another Silicon Valley 'disruption darling' - Uber, its financial model borrows heavily from the dot.com era pioneers, and its management model is more proximate to the 20th century Detroit than to the 21st century Germany.

If you hold Tesla stock, you need to decide whether all of the 8 points above can be addressed successfully, alongside the problems of production targets ramp up, new models launches and other core manufacturing bottlenecks, within an uncertain time frame that avoids triggering severe financial distress? If your answer is 'yes' I would love to hear from you how that can be possible for a company that never in its history delivered on a major target set on time. If your answer is 'no', you should consider timing your exit.

19/4/18: Geopolitical Risk: Who Cares?..

Geo-political risks, geo-shmalitical risks... who cares... not the markets...

None of the geopolitical risks registered on S&P 500 companies reporting radar according to Factset in 1Q 2018 https://insight.factset.com/more-than-half-of-sp-500-companies-citing-positive-impact-from-fx-on-q1-earnings-calls.  This is not very surprising as majority of earnings for 1Q accumulated before any spikes in these, and as "Tariffs" category probably absorbed the 'China' effect. Notably, however, earnings were impacted adversely by trade conflict and cyber risks (total of 3/25 companies impacted).

15/4/18: US Trade Wars and the Global Economy

My interview for Icelandic TV on the threat of trade wars led by the U.S. :http://www.visir.is/section/MEDIA99&fileid=VTV094E2C7D-0F20-48CA-ADB4-8F8515C4B1E7

15/4/18: EuromoneyCountryRisk 1Q 2018 report

Euromoney Country Risk 1Q 2018 report (gated link) is out, quoting, amongst others, myself on geopolitical and macroeconomic headwinds to global economic growth:

Two interesting tables/charts:

My quote:

11/4/18: Social Mobility in the U.S.: Another Chunk of the Facade Goes Down

Via @QZ - share of young Americans living with parents and grandparents is now back to the WW2 levels:

Source: https://qz.com/1248081/the-share-of-americans-age-25-29-living-with-parents-is-the-highest-in-75-years/

No kidding. 33 trillion dollars of economic rescues/stimuli/QE etc and the Great Recovery, the Bull Economy, the Zero Unemployment Goldilocks Era, the MAGA thingy all are a straight line up to rising rates of inter-family subsidies.

11/4/18: Sand Castles of Local Government Regulations in U.S. Property Markets

A new paper, "Sand Castles Before the Tide? Affordable Housing in Expensive Cities" by Gabriel Metcalf in the Journal of Economic Perspectives (Volume 32, Number 1—Winter 2018—Pages 59–80, https://pubs.aeaweb.org/doi/pdfplus/10.1257/jep.32.1.59) looks at evolution of house prices in the major urban areas of the U.S. where "the demand for housing is growing at a much faster rate than the supply. These so-called “superstars” include New York City, Boston, Washington, DC, San Francisco, Los Angeles, Seattle, and Denver (Gyourko, Mayer, and Sinai 2013)."

These cities have "a seemingly permanent crisis of affordable housing," despite the fact that "...policymakers expend great amounts of energy trying to bring down housing costs with subsidies for affordable housing and sometimes with rent control. But these efforts are undermined by planning decisions that make housing for most people vastly more expensive than it has to be by restricting the supply of new units even in the face of growing demand."

The author provides an interesting data summary for these cities. Table 2 in the paper reports the proportion of housing units that are price-controlled or subsidised:

Of all cities areas covered, only one - Dallas - has unregulated rental market share of >50% of the total supply. Put differently, in all but one cities, subsidised and/or rent-controlled housing accounts for more than 50% of the total rental market. Only four out of 11 cities have owner-occupied housing share of the overall property market in excess of 50%.

The rest of the paper proceeds to tell us all the possible reasons as to why this capture of the property markets by price fixing and state ownership is just not enough.  Some of these reasons and arguments are not bad. Some are simply the dogmatic rehashing of the traditional Government-will-solve-everything mantra. That said, the section on the effects of poor regulation (not in quantity, but quality) of the housing markets is spot on and worth reading.

The author first tackles the issue of zoning regulations, arguing (correctly, imo) that zoning regulations both restrict supply and distort types of supply away from what is needed in addressing affordable housing shortages. The section is very brief.

The same applies to the housing approval process, that, according to the author, can result in "more uncertainty and greater risk" which result "a higher cost of capital. Longer approval processes translate into higher carrying costs for the land... Perhaps the greatest negative impact of an uncertain and hyperpoliticized entitlement process is that it functions as a barrier to entry for developers and investors into a market. The net effect is to reduce competition among developers."

"The fourth type of local regulation on housing development is financial: fees and exactions... if the rules are inherently unpredictable and changeable, it is nearly impossible to bid rationally on land, which inevitably drives up the cost of capital, and results in inefficient outcomes. ...the market price for housing has to remain high enough to cover the cost of the fees and exactions, so these function as a price floor that keeps housing more expensive than it otherwise would be."

In summary, and I find myself in agreement with author on this, "For the country as a whole, the restrictive housing policies of the cities in expensive metro areas leads to the segregation of the wealthy into zoned enclave communities; a reduced ability of lower-income people to move to areas of higher opportunity; a diversion of enormous wealth into rent-seeking behavior by landowners; and a decrease in economic productivity for the country as a whole, because labor is not able to be allocated to the most productive economic clusters".

The article provides a good summary and some good insights into potential solutions to the problems summarised above and to the phenomenon of the failure in collective action that occurs between city-level Government policies and those of the wider (commutable) metropolitan areas.

One thing that is, however, clear that housing affordability in major cities has not been meaningfully supported by the already extensive regulatory, price control and subsidy-providing systems. The idea that rent controls can offset bad regulatory and permissioning, as well as financial charging policies is simply not supported by the evidence provided for the largest and growing cities in the U.S.

9/4/18: Some evidence on Chinese tech & IP practices

Not being a fan of the current U.S. Presidential Administration (easy enough to confess to that, being a libertarian), and not being a fan of trade wars (even easier to confess to that, being a libertarian), I must note that the U.S. does indeed have a serious and legitimate problem with Chinese long-term industrial and economic development strategies.

And the U.S. is not alone in that, for Europe - a major engine of innovation, and to a lesser extent, Japan and South Korea, as well as pretty much every other nation injecting new technologies into the modern global economy - also have the same China problem. That problem is: Chinese State policy-linked practices of predatory technology transfers from the Western companies to Chinese markets and industries.

How do we know? Well, besides the Chinese own strategic approach to demanding technology transfers by global multinationals and other innovating firms alike as a ticket to accessing the Chinese markets, we also have empirical studies that attempt to capture data on the West-to-China technology leakages.

Here is one. "International Joint Ventures and Internal vs. External Technology Transfer: Evidence from China" authored by Kun Jiang, Wolfgang Keller, Larry D. Qiu, and William Ridley and released as the  NBER Working Paper No. 24455 (March 2018: http://www.nber.org/papers/w24455) used "administrative data on all international joint ventures in China from 1998 to 2007—roughly a quarter of all international joint ventures in the world".

The authors found that:

1) "... Chinese firms chosen to be partners of foreign investors tend to be larger, more productive, and more likely subsidized than other Chinese firms". In other words, your technology partner in China is more likely to be a State-connected firm.

2) "... there is substantial technology transfer both to the joint venture and to the Chinese joint venture partner". In other words, technology transfers leak within joint ventures - your partner in China is your first channel for losing intellectual property control.

3) "... with technology spillovers typically outweighing negative competition effects, joint ventures generate on net positive externalities to other Chinese firms in the same industry. Joint venture externalities are large, perhaps twice the size of wholly-owned FDI spillovers, and it is R&D-intensive firms, including the joint ventures themselves, that benefit most from these externalities". In other words, your technology feeds Chinese partners, although it benefits your joint venture too.

4) "... external effects from joint ventures are highest in R&D-intensive industries, and the largest externalities tend to arise in industries with a large concentration of joint ventures with a U.S. partner". In other words, if you are bringing into an joint venture an R&D intensive technology, your impact on diffusing your own intellectual property to broader Chinese markets will be greater.

To sum all of this up: over the period 1998-2007, China-based international joint ventures involving R&D intensive, technology-rich foreign partners acted as effective channels for diffusion of new, predominantly Western, but also Japanese and Korean, technologies into the Chinese markets. Which would be fine, if it were not driven by the direct dictate from Beijing.

8/4/18: U.S. economy: entrepreneurship is not 'the new thing' outside Academia

These days, every business school on every university campus is sporting a burgeoning post-graduate program in Entrepreneurship. And this trend is driven by the perceived - and often hyped up by the media and by business futurists - rise in entrepreneurship in the modern society. Apparently, allegedly, an increasing proportion of today's business students want to start their own businesses (despite the fact the vast majority have never worked in a start-up and have no expertise to run one). The new dynamism of the economy, the college-to-start up model of business education, the 'can do' attitude (or aspirations) are all part and parcel of the mythological creature that is the New Economy.

In reality, of course, brutally put, there is no evidence of rising demand for entrepreneurship. And, worse, in fact, there has been a dramatic decline in entrepreneurial rates in the U.S. economy:

Source: http://rooseveltinstitute.org/wp-content/uploads/2018/03/Powerless.pdf.

Now, consider the two data series above, together: firm entry (new firms creation) and firm exist rates. As the blue line trended down, rapidly, without a pause, the green line remained relatively flat. Which means that the ratio of entries to exits has fallen over the time, pretty dramatically. In the 1970s and 1980s, firms entries had, on average been more frequent and less likely to be associated with higher firm exits. In the 1990s,  both relationship deteriorated. In the 2000s, both literally went down the drain.

So as the rate of new businesses additions went down, the rate of old businesses exiting did not change that much. So much for dynamism and for 'entrepreneurial spirits' of the young. The start ups mythology is strong. But the reality of the U.S. economy is that of concentration, market power, monopolization and decline of entrepreneurship. Funny thing, how Silicon Valley propaganda works, right?

How do we know the bit about monopolization? Why, look at profit share of output:

Still want to build up that 'entrepreneurship program' in the University? Because students want to learn about starting their own businesses? Should you really think twice?

8/4/18: Tail Risk and Liquidity Risk: What about that Alpha?

An interesting data set that illustrates two key concepts relating to financial returns, covered extensively in my courses:

1. Liquidity risk factor - inducing added risk premium on lower liquidity assets; and
2. The importance of large scale corrections in long term data series (geometric vs arithmetic averaging for returns)

Indirectly, the above also indicates the ambiguous nature of returns alpha (also a subject of my class presentations, especially in the Applied Investment & Trading course in MSc Finance, TCD): micro- small- and to a lesser extent mid-cap stocks selections are often used to justify alpha-linked fees by investment advisers. Of course, in all, ranking in liquidity risks helps explain much of geometric returns rankings, while across all, geometric averaging discount over arithmetic averaging returns helps highlight the differentials in tail risks.

Sounds pretty much on the money.

8/4/18: Talent vs Luck: Differentiating Success from Failure

In their paper, "Talent vs Luck: the role of randomness in success and failure", A. Pluchino. A. E. Biondo, A. Rapisarda (25 Feb 2018: https://arxiv.org/pdf/1802.07068.pdf) tackle the mythology of the "dominant meritocratic paradigm of highly competitive Western cultures... rooted on the belief that success is due mainly, if not exclusively, to personal qualities such as talent, intelligence, skills, efforts or risk taking".

The authors note that, although "sometimes, we are willing to admit that a certain degree of luck could also play a role in achieving significant material success, ...it is rather common to underestimate the importance of external forces in individual successful stories".

Some priors first: "intelligence or talent exhibit a Gaussian distribution among the population, whereas the distribution of wealth - considered a proxy of success - follows typically a power law (Pareto law). Such a discrepancy between a Normal distribution of inputs, suggests that some hidden ingredient is at work behind the scenes."

The authors show evidence that suggests that "such an [missing] ingredient is just randomness". Or, put differently, a chance.

The authors "show that, if it is true that some degree of talent is necessary to be successful in life, almost never the most talented people reach the highest peaks of success, being overtaken by mediocre but sensibly luckier individuals."

Two pictures are worth a 1000 words, each:

Figure 5 taken from the paper shows:

• In panel (a): Total number of lucky events and
• In panel (b): Total number of unlucky events 

Both are shown as "function of the capital/success of the agents"

Overall, "the plot shows the existence of a strong correlation between success and luck: the most successful individuals are also the luckiest ones, while the less successful are also the unluckiest ones."

Figure 7 shows:
In panel (a): Distribution of the final capital/success for a population with different random initial conditions, that follows a power law.
In panel (b): The final capital of the most successful individuals is "reported as function of their talent".

Overall, "people with a medium-high talent result to be, on average, more successful than people with low or medium-low talent, but very often the most successful individual is a moderately gifted agent and only rarely the most talented one.


Main conclusions on the paper are:

• "The model shows the importance, very frequently underestimated, of lucky events in determining the final level of individual success." 
• "Since rewards and resources are usually given to those that have already reached a high level of success, mistakenly considered as a measure of competence/talent, this result is even a more harmful disincentive, causing a lack of opportunities for the most talented ones."

The results are "a warning against the risks of what we call the ”naive meritocracy” which, underestimating the role of randomness among the determinants of success, often fail to give honors and rewards to the most competent people."