Up and Down Wall Street
Markets: What Everyone Knows That Isn’t So
U.S. shares recovered, bond yields stayed low, gold rose, the dollar fell, and EMs surprisingly did better.
By Randall W. Forsyth
In a speech last week, she took note that falling bond yields were helping to offset the tightening in financial conditions wrought by the slide in the equity markets and the widening of credit-risk spreads (a product of the debt-deflation vise squeezing the high-yield bond market), which came after the central bank’s implemented its initial rate hike after keeping its policy target near zero for seven years. Global developments, notably the weakness in China and other emerging economies, also served as counterweights to the steady but modest pace of the U.S. economy.
JPMorgan’s GDP tracking model shows a somewhat better, if still tepid, 1.2% growth pace.
That would be another unanticipated outcome for this surprising year.
Utilities, telecoms, and consumer staples all were winners, even to the extent that these stolid stocks have been bid up to price/earnings ratios that are half again the 17 times expected 2016 earnings that the broad market commands.
The global liquidity trap turns more treacherous
When central banks reduce policy rates, their objective is to stimulate growth. Lower rates are designed to spur savers to spend, redirect capital into higher-return (ie riskier) investments, and drive down borrowing costs for businesses and consumers.
Additionally, lower real interest rates are associated with a weaker currency, which stimulates growth by making exports more competitive. In short, central banks reduce borrowing costs to kindle reflationary behaviour that helps growth. But does this work when monetary policy is driven through the proverbial looking glass of negative rates?
There is a strong argument that when rates go negative it squeezes the speed at which money circulates through the economy, commonly referred to by economists as the velocity of money.
A decline in the velocity of money increases deflationary pressure. Each dollar (or yen or euro) generates less and less economic activity, so policymakers must pump more money into the system to generate growth.
As consumers watch prices decline, they defer purchases, reducing consumption and slowing growth.
Deflation also lifts real interest rates, which drives currency values higher. In today’s mercantilist, beggar-thy-neighbour world of global trade, a strong currency is a headwind to exports.
The ECB continues to grow the definition of assets that qualify for purchase as sovereign debt alone cannot satisfy its appetite for QE. As options for further QE diminish, negative rates have become the shiny new tool kit of monetary policy orthodoxy.
If Doctor Draghi and Doctor Kuroda do not get the outcome they want from their QE prescriptions — which is highly likely — then more negative rates will be on the way.
It would not be a surprise to see the overnight rates in Europe and Japan go to negative 1 per cent or lower, which will in turn pull down other rates along their respective yield curves.
Negative rates at these levels would make US Treasuries much more attractive on a relative basis, driving yields even lower than they are today.
If the European overnight rate were cut to minus 1 per cent from its current level of negative 40 basis points, German 10-year Bunds would be dragged into negative territory and we could see 10-year Treasuries yielding 1 per cent or less.
This experiment with negative interest rates on a global scale is unprecedented. While there may not yet be enough data to draw the final conclusion about the efficacy of negative interest rate regimes, I have little confidence this will work.
Monetary policy primarily addresses cyclical economic problems, not structural ones. Fiscal and regulatory policies are doing little to support growth and in most cases are restraining it. Combined with negative interest rates, the current policy prescriptions are a perilous mix that is deepening the global liquidity trap.
Scott Minerd is global chief investment officer at Guggenheim
As Silicon Valley fights for talent, universities struggle to hold on to their stars
THAT a computer program can repeatedly beat the world champion at Go, a complex board game, is a coup for the fast-moving field of artificial intelligence (AI). Another high-stakes game, however, is taking place behind the scenes, as firms compete to hire the smartest AI experts. Technology giants, including Google, Facebook, Microsoft and Baidu, are racing to expand their AI activities. Last year they spent some $8.5 billion on research, deals and hiring, says Quid, a data firm. That was four times more than in 2010.
In the past universities employed the world’s best AI experts. Now tech firms are plundering departments of robotics and machine learning (where computers learn from data themselves) for the highest-flying faculty and students, luring them with big salaries similar to those fetched by professional athletes.
Last year Uber, a taxi-hailing firm, recruited 40 of the 140 staff of the National Robotics Engineering Centre at Carnegie Mellon University, and set up a unit to work on self-driving cars. That drew headlines because Uber had earlier promised to fund research at the centre before deciding instead to peel off its staff. Other firms seek talent more quietly but just as doggedly. The migration to the private sector startles many academics. “I cannot even hold onto my grad students,” says Pedro Domingos, a professor at the University of Washington who specialises in machine learning and has himself had job offers from tech firms. “Companies are trying to hire them away before they graduate.”
Experts in machine learning are most in demand. Big tech firms use it in many activities, from basic tasks such as spam-filtering and better targeting of online advertisements, to futuristic endeavours such as self-driving cars or scanning images to identify disease. As tech giants work on features such as virtual personal-assistant technology, to help users organise their lives, or tools to make it easier to search through photographs, they rely on advances in machine learning.
Tech firms’ investment in this area helps to explain how a once-arcane academic gathering, the Conference on Neural Information Processing Systems, held each December in Canada, has become the Davos of AI. Participants go to learn, be seen and get courted by bosses looking for talent. Attendance has tripled since 2010, reaching 3,800 last year.
No reliable statistics exist to show how many academics are joining tech companies. But indications exist. In the field of “deep learning”, where computers draw insights from large data sets using methods similar to a human brain’s neural networks, the share of papers written by authors with some corporate affiliation is up sharply (see chart).
Tech firms have not always lavished such attention and resources on AI experts. The field was largely ignored and underfunded during the “AI winter” of the 1980s and 1990s, when fashionable approaches to AI failed to match their early promise. The present machine-learning boom began in earnest when Google started doing deals focused on AI. In 2014, for example, it bought DeepMind, the startup behind the computer’s victory in Go, from researchers in London. The price was rumoured to be around $600m. Around then Facebook, which also reportedly hoped to buy DeepMind, started a lab focused on artificial intelligence and hired an academic from New York University, Yann LeCun, to run it.
The firms offer academics the chance to see their ideas reach markets quickly, which many like.
Private-sector jobs can also free academics from the uncertainty of securing research grants.
Andrew Ng, who leads AI research for the Chinese internet giant Baidu and used to teach full-time at Stanford, says tech firms offer two especially appealing things: lots of computing power and large data sets. Both are essential for modern machine learning.
All that is to the good, but the hiring spree could also impose costs. One is that universities, unable to offer competitive salaries, will be damaged if too many bright minds are either lured away permanently or distracted from the lecture hall by commitments to tech firms. Whole countries could suffer, too. Most big tech firms have their headquarters in America; places like Canada, whose universities have been at the forefront of AI development, could see little benefit if their brightest staff disappear to firms over the border, says Ajay Agrawal, a professor at the University of Toronto.
Another risk is if expertise in AI is concentrated disproportionately in a few firms. Tech companies make public some of their research through open sourcing. They also promise employees that they can write papers. In practice, however, many profitable findings are not shared. Some worry that Google, the leading firm in the field, could establish something close to an intellectual monopoly.
Anthony Goldbloom of Kaggle, which runs data-science competitions that have resulted in promising academics being hired by firms, compares Google’s pre-eminence in AI to the concentration of talented scientists who laboured on the Manhattan Project, which produced America’s atom bomb.
Whether tech firms, rather than universities, are best placed to deliver general progress in AI is up for debate. Andrew Moore, the dean of Carnegie Mellon University’s computer-science department, worries about the potential for a “seed corn” problem: that universities could one day lack sufficient staff to produce future crops of researchers. As bad, with fewer people doing pure academic research, sharing ideas openly or working on projects with decades-long time horizons, future breakthroughs could also be stunted.
But such risks will not necessarily materialise. The extra money on offer in AI has excited new students to enter the field. And tech firms could help to do even more to develop and replace talent, for example by endowing more professorships and offering more grants to researchers.
Tech firms have the cash to do so, and the motivation. In Silicon Valley it is talent, not money, that is the scarcest resource.
Debunking America’s Populist Narrative
J. Bradford DeLong
BERKELEY – One does not need to be particularly good at hearing to decipher the dog whistles being used during this year’s election campaign in the United States. Listen even briefly, and you will understand that Mexicans and Chinese are working with Wall Street to forge lousy trade deals that rob American workers of their rightful jobs, and that Muslims want to blow everyone up.
How Fickle Markets Are Challenging ECB’s Mario Draghi
The bank faces challenges from market moves
By Richard Barley
How Covenants Make Us
The War Whose Name No One Dares to Utter
Editor, This Week in Geopolitics
Wisdom wanes for ‘don’t fight the Fed’
For generations, “Don’t fight the Fed” was a mantra beaten into market neophytes by Wall Street’s grizzled veterans. Now the tables seem to have turned.
The US bond market, through low yields, has long reflected the wider market view that the Fed’s outlook for the economy, inflation and interest rate policy was optimistic.
Now it appears the Fed is coming around to the market’s view, as the central bank worries more about the negatives than the positives in the economy.
“We feel too close to the market fearing central bank ineffectiveness for comfort. The market rejoices in Yellen’s dovishness, but with a fear about how long the impact will last.”
Ostensibly, the data still matters. Speaking to the Economic Club of New York, Ms Yellen reiterated the Fed mantra that “our actions are data-dependent”.
Many analysts and investors, however, have seized on the dichotomy between the reasonable economic fundamentals and Fed dovishness as proof the US central bank is more influenced by markets than it dares admit.
Fed officials bridle at suggestions they can be pushed around by markets. Ms Yellen is the official who matters, so when she speaks of the need to “take into account the potential fallout from recent global economic and financial developments, which have been marked by bouts of turbulence since the turn of the year”, it is fair to assume the Fed no longer treats market mood with blithe disregard.
Some feared the market turmoil was severe enough to raise the risk of a US recession. But the US economy has proved resilient and markets have snapped back. That is largely thanks to the market anticipating Fed caution and its retreat from the prospect of four interest rate rises in 2016, as Ms Yellen herself noted.
According to Steven Englander at Citigroup, this suggests she regards this hair trigger reaction as “not only correct but desirable and likely to be confirmed by subsequent Fed action”.
This offsetting theme is one Ms Yellen likes. The market is helping to act as an “automatic stabiliser” for the economy because incoming data surprises “typically induce changes in market expectations about the likely future path of policy, resulting in movements in bond yields that act to buffer the economy from shocks”, she said.
But is Ms Yellen in danger of letting markets dictate Fed policy? After all, she recognised that the headwinds of weak global growth, low oil and China uncertainty were likely to ease, and yet despite efforts by hawkish Fed members to talk up rate-rise prospects, the dovish tone of Ms Yellen prevails.
Acute sensitivity to market ructions follows the financial crisis, when the Fed was slow to track parts of the bond market. Nonetheless, some investors are wary that the central bank’s ability and inclination to support the market — in the face of the economic data — could in the long run prove unhealthy as it introduces a more fickle dynamic into policymaking.
For example, if markets continue to heal from the early-year fright, it could force the Fed to restore its initial rate outlook for 2016. If that sends markets back into a tailspin it may spur the Fed to once again reverse course.
“It’s a delicate balancing act they [the Fed officials] have to figure out,” says Gregory Peters, a bond fund manager at Prudential.
Les doy cordialmente la bienvenida a este Blog informativo con artículos, análisis y comentarios de publicaciones especializadas y especialmente seleccionadas, principalmente sobre temas económicos, financieros y políticos de actualidad, que esperamos y deseamos, sean de su máximo interés, utilidad y conveniencia.
Pensamos que solo comprendiendo cabalmente el presente, es que podemos proyectarnos acertadamente hacia el futuro.
Gonzalo Raffo de Lavalle
Las convicciones son mas peligrosos enemigos de la verdad que las mentiras.
Quien conoce su ignorancia revela la mas profunda sabiduría. Quien ignora su ignorancia vive en la mas profunda ilusión.
“There are decades when nothing happens and there are weeks when decades happen.”
Vladimir Ilyich Lenin
You only find out who is swimming naked when the tide goes out.
No soy alguien que sabe, sino alguien que busca.
Only Gold is money. Everything else is debt.
Las grandes almas tienen voluntades; las débiles tan solo deseos.
Quien no lo ha dado todo no ha dado nada.
History repeats itself, first as tragedy, second as farce.
We are travelers on a cosmic journey, stardust, swirling and dancing in the eddies and whirlpools of infinity. Life is eternal. We have stopped for a moment to encounter each other, to meet, to love, to share.This is a precious moment. It is a little parenthesis in eternity.
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