20/2/19: Crack and Opioids of Corporate Finance

More addictive than crack or opioids, corporate debt is the sand-castle town's equivalent of water: it holds the 'marvels of castles' together, util it no longer does...

Source: https://twitter.com/lisaabramowicz1/status/1098200828010287104/photo/1

Firstly, as @Lisaabramowicz correctly summarises: "American companies look cash-rich on paper, but average leverage ratios don't tell the story. 5% of S&P 500 companies hold more than half the overall cash; the other 95% of corporations have cash-to-debt levels that are the lowest in data going back to 2004". Which is the happy outrun of the Fed and rest of the CBs' exercises in Quantitive Hosing of the economies with cheap credit over the recent years. So much 'excessive' it hurts: a 1 percentage point climb in corporate debt yields, over the medium term (3-5 years) will shave off almost USD40 billion in annual EBITDA, although tax shields on that debt are likely to siphon off some of this pain to the Federal deficits.

Secondly, this pile up of corporate debt has come with little 'balancesheet rebuilding' or 'resilience to shocks' capacity. Much of the debt uptake in recent years has been squandered by corporates on dividend finance and stock repurchases, superficially boosting the book value and the market value of the companies involved, without improving their future cash flows. And, to add to that pain, without improving future growth prospects.

20/2/19: Broader Measures of Irish Unemployment 4Q 2018

The latest Labour Force Survey for 4Q 2018 for Ireland, published by CSO, shows some decent employment increases over 2018, and a welcomed, but shallow, rise in the labour force participation rates. Alongside with a decrease (over FY 2018) in the headline unemployment rate, these are welcome changes, consistent with overall economic growth picture for the state.

One, much less-reported in the media, set of metrics for labour markets performance is the set of broader unemployment measures provided by the CSO. These are known as Potential Labour Supply stats (PLS1-PLS4). The measures also show improvements over 2018, just in line with overall employment growth. However, these measures clearly indicate that after 11 years running, the 2008-2014 crises remain still evident in the labour force statistics for Ireland.

Here is a chart of all four PLS measures, compared to their pre-2008 averages:

Note: Increase in PLS2-PLS4 series at 3Q 2017 is down to change in assessment methodology under the LFS replacing QNHS, with data pre-3Q 2017 adjusted to reflect that change by the CSO.

As a reminder, the above data series are defined as:

• PLS1 adds discouraged workers. These are individuals who are out of work but who have become disillusioned with job search. 
• PLS2 includes all individuals in Potential Additional Labour Force (PALF). The PALF is made up of two groups: persons seeking work but not immediately available and persons available to work but not seeking, of which discouraged workers make up the largest number. 
• PLS3 includes all those in the previous two categories (PLS1 and PLS2) along with persons outside the labour force but not in education or training. 
• PLS4 is the broadest measure of unemployment or potential labour supply and is calculated by adding part-time underemployed workers to PLS3. Part-time underemployed workers are individuals currently working part time who are willing and available to work additional hours. The broadest measure of unemployment (PLS4) stood at 13.7 per cent in 4Q 2016. At 4Q 2017 it was 18.7 per cent and by 4Q 2018 it was down to 17.5 per cent.

18/2/19: U.S. Treasuries: Not Finding Much Love in Foreign Lands

In recent months, I have been warning about the cliff of new bonds issuance that is coming for the U.S. Treasuries in 2019, pressured by the declining interest in U.S. debt from the rest of the world. December 2018 figures are a further signal reinforcing the importance of this warning (see U.S. yields comparatives here: http://trueeconomics.blogspot.com/2019/02/15219-still-drowning-in-love-for-debt.html).

In December 2018, foreign buyers cut back their purchases of the U.S. Treasuries by the net USD77.35 billion, following a net increase in purchases in November of USD13.2 billion. December net outflow was the largest since January 1978. On a positive note, Chinese holdings of U.S. Treasuries increased in December, after declining for six straight months. China held USD1.123 trillion in U.S. Treasuries in December, up from USD1.121 trillion in November.

Here is the historical chart, including 4Q 2018 estimate:

Not quite an armageddon, but statistically, foreign holdings of the U.S. Treasuries remained basically flat from 1Q 2014. Which would be fine, if (1) U.S. new net issuance was to remain at zero or close to it (which is not the case with accelerating deficits: http://trueeconomics.blogspot.com/2019/02/15219-nothing-to-worry-about-for-those.html), (2) U.S. Fed was not 'normalizing' its asset holdings (which is not the case, as the Fed continues to reduce its balance sheet - see next chart).

Note: January 2019 saw a decline in the benchmark U.S. Treasuries (10 year) yield, compared to 2018 annual yield:

16/2/19: Deep Crises: past, present, future?

Venezuela's economic (and political, social, public, etc) woes have been documented with exhaustion, although no one so far has produced a half-meaningful outline of solutions that are feasible and effective at the same time.

Take for example, the @IIF pitch in: "Venezuela’s economic collapse is almost unprecedented in recent history. Zimbabwe in the last 20 years and the collapse of the Soviet Union are the only comparable episodes." This accompanied the following chart:

What is, however, remarkable in this exposition, is not Venezuela's demise, which is impressive, but the experience of Russia and the contrasting experience of Ukraine in post-Soviet collapse era.

Here is the data from the World Bank on post-USSR collapse recoveries, through 2017. It is the similar to the one used by IIF, but a bit more current and details. And it compares the Western 'darling' of Georgia experience with that of the Ukraine and Russia:

You don't need to have a PhD in economics to comprehend the chart above in political terms: like it or not, the Western 'policies prescriptions' have not been a great source of optimism for Georgia,  Ukraine and Russia in the 1990s.  It hasn't been a great source of optimism for Georgia in the 2000s, and it hasn't been of much use for Ukraine since 2014.

In part, the reason is that the Western prescriptions for policy development and reforms were not exactly followed by these countries in the past, and in part, these prescriptions were not suitable to these economies and their societies. But, also in part, the reason as to why Western reforms did not work their magic in the three former-USSR states is that they were never accompanied by the genuine buy-in from the West. There was no 'great trade' opening, no 'structural FDI rush', no 'Marshall Plan supports'.  What little tangible support was extended to these countries (and other post-Soviet states) from the West was largely siphoned off into the pockets of the Western contractors and domestic oligarchs.

Russian recovery 'miracle' that is traceable above was down to the removal of the Western contractors from the proverbial feeding trough, and consolidation of domestic oligarchs and corrupt elites. One can't call these changes 'liberal' or 'reforms', but they were successful while they lasted (through 2014).

What is also telling is that the rates of recovery - at peak rates - in Georgia (during the hey-days of Western-style reforms) were not quite comparable with the same rate of Russian economic recovery. And that is before one considers the peak recovery in Ukraine since 2014.

Incidentally, returning to the IIF chart above, neither Peru (it took the country 8 years to recover from its 1989 crisis) nor Bolivia (same duration for its crisis of 1982) compare to the cases of the post-USSR collapse crises in magnitude and recovery duration. Zimbabwe does, and it recovered from its 1998-started economic collapse in 18 years, by the end of 2017). Last time I checked, Zimbabwe also did not follow the Western 'prescriptions' in its policies path, and still beats Georgia and Ukraine in terms of its experience (both former USSR states are now in year 28 of post-1989 economic crisis).

16/2/19: Trump-o-rama taking a dip?

Summarizing the U.S. economic 'themes' of the last 21 years:

or put differently: 13 years of 'ugly', 8 years of 'euphoric'.

Source for the great chart (ex-my annotations): https://www.topdowncharts.com/.

15/2/19: Still Drowning in Love [for Debt]...

Debt... Sovereign debt... and Valentines...

A decade post-GFC, we are still shedding love to our overly-indebted sovereigns... so nothing can ever go wrong, again...

15/2/19: Nothing to Worry About for those Fiscally Conservative Republicans

H/T to @soberlook:

U.S. Federal deficit was up $192 billion y/y in December 2018. Nothing to worry about, as fiscal prudence has been the hallmark of the Republican party policies since... well... since some time back...  That, plus think of what fiscal surplus will be once Mexico pays for the Wall, and Europeans pay for the Nato.

Soldier on, Donald.

15/2/19: Euro area is sliding toward recession

Based on the latest data through January 2019, Eurozone’s economic problems are getting worse. In 4Q 2018, Euro area posted real GDP growth of just 0,.2% q/q - matching the print for 3Q 2018. Meanwhile, inflation has fallen from 1.7% in December 2018 to 1.6% in January 2018. And Eurocoin - a leading growth indicator for euro area GDP expansion slipped from 0.42 in December 2018 to 0.31 in January 2019. This marked the third consecutive month of decline in Eurocoin, and the steepest fall in 8 months. Worse, July 23016 was the last time Eurocoin was at this level.

Within the last 12 months, Eurozone growth has officially fallen from 0,.7% q/q in 4Q 2017 to 0.2% in 4Q 2018, HICP effectively stayed the same, with inflation at 1.6% in January 2018 agains 1.5% in January 2018. And forward growth indicator has collapsed from 0.95 in January 2018 to 0.31 in January 2019.

Euro area is heading backward when it comes to economic activity, fast.

Germany just narrowly escaped an official recession, with 4Q growth at zero, and 3Q growth at -0.2%

Italy is in official recession, with 3Q 2018 GDP growth of -0.1% followed by 4Q 2018 growth of -0.2%.

Industrial goods production is now down two consecutive months in the Euro area as a whole, with latest print for December 2018 sitting at - 4.2% decline, following a -3.0% y/y fall in November 2018.

Worse, capital goods industrial production - a signal of forward capacity investment, is now down even more sharply: from -4.4% in November 2018 to -5.5% in December 2018.

7/2/19: S&P on Irish Banks Outlook

S&P on Irish banks outlook for 2019, with my comments included: https://www.spglobal.com/marketintelligence/en/news-insights/trending/wU14cpHw2NfouDi3MnHVQw2.

7/2/19: Global Trade Indicators: Tanking

There is no reason to panic about global growth. None. None at all...

Source: topdowncharts.com with my annotations

Nothing to see here. Because, obviously, structurally and statistically lower growth in trade turning negative on foot of Baltic Dry Index literally collapsing over the last two weeks, while China data and stock markets signals remain negative, is just a glitch...

5/2/19: The Myth of the Euro: Economic Convergence

The last eight years of Euro's 20 years in existence have been a disaster for the thesis of economic convergence - the idea that the common currency is a necessary condition for delivering economic growth to the 'peripheral' euro area economies in the need of 'convergence' with the more advanced economies levels of economic development.

The chart below plots annual rates of GDP growth for the original Eurozone 12 economies, broken into two groups: the more advanced EA8 economies and the so-called Club Med or the 'peripheral' economies.

It is clear from the chart that in  growth terms, using annual rates or the averages over each decade, the Euro creation did not sustain significant enough convergence of the 'peripheral' economies of Greece, Italy, Portugal and Spain with the EA8 more advanced economies of the original euro 12 states. Worse, since the Global Financial Crisis onset, we are witnessing a massive divergence in economic activity.

To highlight the compounding effects of these annual growth rates dynamics, consider an index of real GDP levels set at 100 for 1990 levels for both the EA8 and the 'peripheral' states:

Not only the divergence is dramatic, but the euro area 'peripheral' economies have not fully recovered from the 2008-2013 crisis, with their total real GDP sitting still 3.2 percentage points below the pre-crisis peak (attained in 2007), marking 2018 as the eleventh year of the crisis for these economies.  With Italy now in a technical recession - posting two consecutive quarters of negative growth in 3Q and 4Q 2018 based on preliminary data, and that recession accelerating (from -0.1% contraction in 3Q to -0.2% drop in 4Q) we are unlikely to see any fabled 'Euro-induced convergence' between the lower income states of the so-called Euro 'periphery' and the Euro area 8 states.

17/1/19: Why limits to AI are VUCA-rich and human-centric

Why ethics, and proper understanding of VUCA environments (environments characterized by volatility/risk, uncertainty, complexity and ambiguity) will matter more in the future than they matter even today? Because AI will require human control, and that control won't happen along programming skills axis, but will trace ethical and VUCA environments considerations.

Here's a neat intro: https://qz.com/1211313/artificial-intelligences-paper-clip-maximizer-metaphor-can-explain-humanitys-imminent-doom/. The examples are neat, but now consider one of them, touched in passim in the article: translation and interpretation. Near-perfect (native-level) language capabilities for AI are not only 'visible on the horizon', but are approaching us with a break-neck speed. Hardware - bio-tech link that can be embedded into our hearing and speech systems - is 'visible on the horizon'. With that, routine translation-requiring exchanges, such as basic meetings and discussions that do not involve complex, ambiguous and highly costly terms, are likely to be automated or outsourced to the AI. But there will remain the 'black swan' interactions - exchanges that involve huge costs of getting the meaning of the exchange exactly right, and also trace VUCA-type environment of the exchange (ambiguity and complexity are natural domains of semiotics). Here, human oversight over AI and even human displacement of AI will be required. And this oversight will not be based on technical / terminological skills of translators or interpreters, but on their ability to manage ambiguity and complexity. That, and ethics...

Another example is even closer to our times: AI-managed trading in financial assets.  In normal markets, when there is a clear, stable and historically anchored trend for asset prices, AI can't be beat in terms of efficiency of trades placements and execution. By removing / controlling for our human behavioral biases, AI can effectively avoid big risk spillovers across traders and investors sharing the same information in the markets (although, AI can also amplify some costly biases, such as herding). However, this advantage becomes turns a loss, when markets are trading in a VUCA environment. When ambiguity about investors sentiment and/or direction, or complexity of counterparties underlying a transaction, or uncertainty about price trends enters the decision-making equation, algorithmic trading platforms have three sets of problems they must confront simultaneously:

1. How do we detect the need for, structure, price and execute a potential shift in investment strategy (for example, from optimizing yield to maximizing portfolio resilience)? 
2. How do we use AI to identify the points for switching from consensus strategy to contrarian strategy, especially if algos are subject to herding risks?
3. How do we migrate across unstable information sets (as information fades in and out of relevance or stability of core statistics is undermined)?

For a professional trader/investor, these are 'natural' spaces for decision making. They are also VUCA-rich environments. And they are environments in which errors carry significant costs. They can also be coincident with ethical considerations, especially for mandated investment undertakings, such as ESG funds. Like in the case of translation/interpretation, nuance can be more important than the core algorithm, and this is especially true when ambiguity and complexity rule.