A lucid master-class on bubbles

Rob Arnott (and his colleagues) of Research Affiliates had written a rather lucid paper on stock market bubbles in April 2018. You can find it here. If you are either an investor or a student or, perhaps, importantly, a teacher, it is a MUST-READ.

They brilliantly shred the arguments that somehow painfully try to prove that stock markets were efficient. They are nothing but pathetic attempts at post-hoc rationalisations or rationalising a conclusion that the authors had already arrived at. Such papers should ideally be classified under ‘propaganda’ rather than under ‘research’, notwithstanding all the geeky mathematics deployed.

On market efficiency:

The efficient market hypothesis has been stretched to fit observed market behavior, by allowing cross-sectional and intertemporal variations in risk premia. Prices adjust until the marginal investor becomes willing to assume both market risk and assorted factor-related risks. The market’s willingness to bear these risks varies over time. In this view, high valuation levels don’t represent mispricing; the risk premia just happen to be sufficiently low so as to justify the prices.

These models benefit from being constructed on a post hoc basis to be consistent with market events. Fair enough, because a useful model needs to be consistent with observable data. But the models often shift problems in the observable data, such as puzzlingly high volatility in price-to-dividend ratios, into unobservable nooks and crannies. In other words, perhaps bubble-like prices can be perfectly rational as long as we accept curiously high volatility in the curvature of investors’ utility functions. Sadly, these hypotheses and models lack a key attribute of scientific method: they are unfalsifiable. No practical difference exists between an inefficient market and an efficient market in which risk premia vary in this fashion.

All students of finance must memorise these two paragraphs.

On market timing:

At the beginning of 2000, the 10 largest market-cap tech stocks in the United States, collectively representing a 25% share of the S&P 500 Index—Microsoft, Cisco, Intel, IBM, AOL, Oracle, Dell, Sun, Qualcomm, and HP—did not live up to the excessively optimistic expectations. Over the next 18 years, not a single one beat the market: five produced positive returns, averaging 3.2% a year compounded, far lower than the market return, and two failed outright. Of the five that produced negative returns, the average outcome was a loss of 7.2% a year, or 12.6% a year less than the S&P 500.

Lesson: Timing matters. If you buy high, you reap lower returns unless you were lucky to flip the stock quickly and find a greater fool to buy it off you.

On Tesla:

Over the first quarter of 2018, Tesla has been an excellent example of a micro-bubble. Tesla’s current price is arguably fair if most cars are powered by electricity in 10 years, if most of these cars are made by Tesla, if Tesla can make those cars with sufficient margin and quality control and can service the cars properly, and if Tesla can raise additional capital sufficient to cover a $3 billion annual cash drain and another billion to service its debt. To us, that seems an unduly optimistic array of assumptions, especially given the magnitude of Tesla’s debt burden. Such an argument ignores the deep pockets of competitors and the common phenomenon of disruptors being themselves disrupted by newcomers.

On cryptocurrencies:

It boggles the imagination to hear people speaking of “investing” in bitcoin, an electronic entity that offers no hope of future operating profits or dividends, is little used as a surrogate for money in transactions (trading volume is well over 100 times as large as spending volume), offers an uncertain longer-term use case, and has no objective basis to determine fundamental value.

Will bitcoin and a handful of other cryptocurrencies settle in and become a stable store of value, akin to gold or sovereign currencies? Perhaps.

Those of us who are libertarians, wary of government control of the money supply, are rooting for that outcome.

That said, how many investors are holding cryptocurrencies for any purpose other than the expectation that someone else will pay a higher price at some point in the future?….

Even if we assume that bitcoin has merit as a libertarian alternative to government-sourced fiat currency, it’s hard to justify today’s 1,500 different cryptocurrencies. Many of these were launched with the singular goal of making the originator of the cryptocurrency wildly wealthy in an ICO (initial coin offering).

On the ‘costs’ and distortions of the crypto bubble:

The bitcoin bubble also serves as a wonderful example of how bubbles create harmful distortions in the real economy. The website Digiconomist estimates the run-rate annual electricity utilization of the bitcoin network at 56 billion kilowatt-hours. That’s more than enough to power all the households in Los Angeles for a year, and nearly enough to meet all of Israel’s power demands. Bitcoin already consumes about 0.25% of total global electricity consumption! All just to “produce” new coins on a nonphysical ledger and move these coins around on electronic exchanges….

From the footnotes: One aspect of bitcoin-related energy consumption that won’t disappear so easily is the residual carbon footprint left by bitcoin mining, which is currently dispensing as much CO2 a year as 1,000,000 transatlantic flights.

On the bubble in current technology stocks:

At the end of January 2018, the seven largest-cap stocks in the world were all tech fliers: Alphabet, Apple, Microsoft, Facebook, Amazon, Tencent, and Alibaba. Never before has any sector so dominated the global roster of largest market-cap companies. At the peak of the tech boom, four of the top seven companies by market cap were in the tech sector, and at the peak of the oil bubble, five of the top seven were in the energy sector. Only the Japanese stock market’s bubble at yearend 1989 has matched today’s tech sector dominance of the global market-capitalization league tables. Not only do we have the FANGs, we have FANG+ futures, affording investors a chance to buy the world’s trendiest tech stocks with almost no collateral, and the list is amended quarterly to make sure only the trendiest are on the list.

Yet, how shorting can be perilous:

During the three months August–October 2008, the Zimbabwean dollar plunged from 10 to 1000 per the US dollar, a 100-fold currency collapse. At first, the Zimbabwean stock market was unfazed, rising 500-fold in just eight weeks, while the currency fell 10-fold. Thus, in US dollar terms, the stock market rose an astounding 50-fold over those eight weeks. In the next two weeks, however, the stock market toppled 85% and the currency tumbled another 3-fold. Adjusted for the plummeting Zimbabwean currency, the nation’s stock market plunged 95% in two weeks.

There is really no cataylst that trigger a bubble collapse. I keep saying that to my students and clients:

The all-too-common question—“What’s the catalyst that will cause the market to turn, the bubble to burst?”—is simply a distraction because a catalyst is, by definition, a surprise to most of the market.

What, for example, was the proximate catalyst that ended the tech bubble in March 2000? We have yet to hear a persuasive answer. Yet, the quest for a catalyst is fun and potentially profitable; after all, a few people will identify the catalyst, if there is one, in advance.

You can see why I was very excited about reading this paper and very excited to share it here too. It is a treasure trove of common-sense, practical and valuable wisdom.

Many, many thanks to Rob Arnott and his co-authors.

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Questions for the weekend

(1) In Universities, how can Economics Departments premising their theories on human rationality co-exist with Consumer Marketing theories, textbooks and courses?

(2) How do the ‘Universalists’ and ‘Citizens of the world’ explain their own and others’ tribal loyalties to football clubs (around the world) and cricket clubs (think IPL in India)?

I have my own answers but I would lik to hear yours.

What is the right lens for viewing India’s inflation?

My friend Srini Thiruvadanthai had flagged this speech by Prof. Pulapre Balakrishnan in 2014.  The lecture delivered on the occasion of his receiving the Malcom Adiseshiah award in 2014.

He makes useful points and it is a useful read but his points are not terribly novel. That India’s inflation is primarily caused by agricultural supply shocks and food prices and that they influence both growth (negatively) and inflation (positively, ie., higher) is not particularly new. It may be called ‘structuralist’ as opposed to ‘monetarist’, etc. That is ‘Economistspeak’. In plain English, agricultural supply factors explain India’s relative stagflationary experience compared to the West.

Frankly, a truly structuralist explanation was given by Nageswaran and Natarajan (2016): ‘Can India grow?’ [Link]. Of course, I am tooting my own horn here.

Second, his puzzle as to how potential growth could decline at the same time as actual growth was declining can be addressed by the fact that he is documenting: public sector capital formation.

Third, he is relatively less critical of UPA II (and UPA I which sowed the seeds) policies for the decline in public sector capital formation than he should be.

Fourth, if the NDA government had tried to increase public sector capital formation – as it has – while keeping up government welfare expenditure – as it has – then it explains its faith and reliance on tax terrorism and, even to some extent, demonetisation.

What are the answers to agricultural negative supply side shocks – if they are as correlated with India’s growth slowdown and inflation acceleration – the lecture is silent on those. I think Nageswaran and Natarajan (2016) is a better attempt at identifying (if not answer) the structural impediments to economic growth in India – both in agriculture and in industry.

Given his ‘structural’ view of India’s inflation, he wonders if conventional monetary policy framework, ‘inflation targeting’ was appropriate for India. ‘Inflation targeting’ works for normal economies where inflation is caused by excess cyclical growth in aggregate demand. Of course, we have different problems with an ‘inflation targeting’ regime but he raises the question – that others have raised before and after him too – of the suitability of the ‘inflation targeting’ regime in the Indian context where inflation is thought to be caused by agricultural supply shocks and where it does not arrive via the standard excess cyclical aggregate demand growth.

An important question is if the structural view of Indian inflation – the agricultural supply shcok induced view of inflation – is correct. Is it really an agricultural supply issue or is it an intermediation/rent-seeking behaviour? That is the question.

So much has been written about the difference between the farm-gate price and the retail price in India, with a good portion of it being deadweight loss (lost in transit – rotting, stolen, etc.) But, more important than that, is it really the intermediaries who are contributing to the structural view of inflation? If so, is it right to call it an ‘agricultural supply shock’?

If it is wrong to call it as such, then why is it wrong to apply standard monetary tools to combat it? After all, if financing costs are made higher, will the intermediaries not find it difficult to buy and hoard and hence, be forced to release supply to the market?

In sum, I am challenging the ‘structural’/agricultural supply shock view of India’s inflation. Pl. feel free to tell me the chinks in the argument and point to any research that delves into this issue.

Land acquisition in India

It is five years since the UPA government passed its Land Acqusition Bill. I don’t think there is any systematic study of its impact on costs and delays, etc.

A ‘Financial Express’ story says that it is hurting infrastructure. A story in ‘Indian Express’ published two months earlier, tries to paint a different picture.

A Reuters story from last year cites a joint secretary in the department of land resources  (which Ministry?) saying that acquisition takes almost five years (59 months).

Does anyone know of any formal study on this issue?

Explaining charlatans with charlatanism

A good friend recommended that I read this piece by John Ganz on the ‘age of charlatans’ that are allegedly living in. I did so.

When people feel overwhelmed and disenfrachised, they fall for ‘snake oil’ solutions and false promises. They fall for charlatans. That is his simple message.

But, he sets it up somewhat too cleverly and in the process, practising a bit of charlatanism himself. He cites passages from his favourite author who wrote about this some sixty years ago and then writes about some contemporary politicians and scholars in the next pararaph, practising a bit of ‘post-hoc ergo procter hoc’ logic. No explanation as to why these characters exemplify the previous paragraph. Are we expected to accept that because he says so?

I suppose it is not entirely a coincidence that the characters he chooses to be critical of belong to the ‘Right’ in the United States. I had not read Jordan Peterson’s book but the way he handled a journalist in a TV interview without once losing patience with her aggressive questions was an abject lesson to many of us.

Critics usually don’t make a distinction between Trump’s personality and his policies. The latter to be called ‘charlatanism’ needs to be established. It will take time and outcomes could surprise or vindicate critics. Too early to say. Many in the West think globalisation and free trade were the false utopia promised by globalisers-charlatans and that is why they chose these ‘charlatans’ over them.

His last three sentences try to redeem the article but, by then, he had lost me.

Market Concentration, markups and profits

Srinivas Thiruvadanthai had queried in his Twitter handle if one could have good data on the distribution of US corporate profits between companies. I would be interested in that question too. So, I went looking. This is what I found:

slightly more than 100 firms earned about half of the total profit made by US public firms in 1975. By 2015, just 30 did. Zoom out a little and the trend is even more astonishing. The top 200 companies by earnings raked in more than all listed firms, combined. Indeed, the aggregate earnings of the 3,500 or so other listed companies is negative. [Link]

The article above has some nice charts and links to this paper too about the decline of the number of listed firms in the US.

Chicago Booth School’s promarket.org blog has a post on the 70-year history of corporate profits. It is a summary of a long paper:

Two notable policy changes point to the early 1980s as a possible break in the trends in competition. First, there was an increase in antitrust enforcement from the mid-1940s to the early 1980s, followed by a decline from the early 1980s to the present.3) Second, the Department of Justice adopted a more lenient merger guideline in 1982. As Peltzman (2014) shows, industry concentration began rising after this change to the merger guideline. [Link]

The promarket.org blog post links to some very interesting NBER papers:

(i) Labor Market Concentration [Link]

(ii) Declining Competition and Investment in the U.S. [Link]

(iii) Strong Employers and Weak Employees: How Does Employer Concentration Affect Wages? [Link]

(iv) Accounting for Rising Corporate Profits: Intangibles or Regulatory Rents? [Link]

(v) Are U.S. Industries Becoming More Concentrated? [Link] – this one is from 2015 and above others are more recent

Consistent with rising product and labour market concentration, the IMF Blog has an interesting chart on rising markups in advanced economies (not just in the USA) and its conclusion too is very instructive:

The paper also finds a negative association in firms between labor shares and markups, implying that the labor share of income declines in industries where market power rises. In other words, with higher market power, the share of firms’ revenue going to workers decreases, while the share of revenue going to profits increases. [Link]

The blog post is based on a working paper that is yet to be released.

The blog post has a link to the session on ‘Digitisation and the new gilded age’ held as part of the Spring IMF-World Bank meetings in April. Should be interesting.

What these posts and news make clear is that it is not just competition from Chinese imports, globalisation of work (outsourcing and offshoring of services)  and higher immigration that had reduced labour share of income in advanced economies but also higher market concentration that has increased profit share of income. Clearly, these are inter-dependent and inter-connected phenomenon. For example, to ward off external competition, firms merge and smaller firms disappear, leading to increased concentration. That leads to other consequences.

But, policymakers, commentators and journalists have been asleep at the wheel even though some of these papers had begun to appear from 2010 onwards. Now, they look askance at public rage and spout venom at populists who have tapped into this rage.

Making sense of Trump and trade

The title of this post is misleading. It gives the impression that I have figured it out. No, I have not. I am still making sense of both. But, I can begin to see why President Trump is viewed either as too crazy or too much of a genius. These extreme characterisations seem more appropriate than middle ones.

The image of a relatively young and boyish looking Canadian Prime Minister being attacked by a much older person and the Head of State of a much bigger country appeared like an unfair game until you read this one. All the sky-high tariff rates that President Trump mentioned are true!

The article too provides a partial explanation for why the Canadian Prime Minister’s Liberal Party lost the Ontario provincial elections so badly. I did not know about it at all. This Wikipedia entry is good enough for us and the statistics are so clear that you do not have to worry about the commentary. You can figure out what happened yourself.

On ZTE, the President’s U-Turns have baffled and frustrated many, including me. But, it may be a much longer game of chickens and charade. You can figure it out yourself if you have subscription to ‘Wall Street Journal’ and can read this article. I won’t elaborate.

Jamil Anderlini wrote in FT this morning that President Trump seems to have conceded more than President Kim did in their summit meeting in Singapore yesterday. To a degree, Wall Street Journal agreed. The comments on Jamil’s article were strongly critical of him and his judgement. To be fair to him, he had sided with Trump on his trade battle with China but then we all thought that Trump had backtracked on ZTE (or, may be not). Second, we live in a world where analysts and commentators are required to make instant judgements on matters that are slow-moving. So, the comments might be a trifle too harsh.

May be, the header of his article on the Trump-Kim summit was too sweeping and too hasty. See below:

anderlini.png

This WSJ Opinion (‘Best of the web’) contrasts the reporting in New York Times now with its reporting in 1993 when a similar opening to North Korea was made under Bill Clinton.

FT readers too have commented that, had the meeting taken place between Obama and Kim, the FT would have reported it very differently. That should make some of these newspapers reflect as to what really are they achieving with their biases and how far their reputation for objectivity had sunk.