Negative Interest Rates and Assorted Fixed Income Weirdness

One Claudio Borio, head of the monetary and economic department at the BIS, recently remarked of $14.8 trillion in negative-yielding debt worldwide: “A growing number of investors are paying for the privilege of parting with their money. Even at the height of the Great Financial Crisis, this would have been unthinkable. There is something vaguely troubling when the unthinkable becomes routine.”

Even with near zero or negative interest rates, bond managers are arguing for “still give us money” because they can make up “negative yield” with capital appreciation.

From fixed income manager Nuveen: “Consider that the Bloomberg Barclays Germany Treasury Bond Index began the year with a -0.1% yield, but has returned over 6% in euros year to date. Negative yielding bonds may not be attractive for most individual investors if held to maturity, but their prices may still rise over shorter periods, giving them value if used judiciously in diversified portfolios.”

So bonds are now like a stock with locked in negative cashflow but don’t worry you will get appreciation? Isn’t it weird that investors are seeking safety by putting their money in bonds with a guaranteed loss of principal?

It Could be Worse: We could be Passive Fixed Income Investors

From Peter Chiappinelli, Strategist at GMO, spoke interesting and eloquently at a recent Grant’s conference, but really just repeated what he said from March 10, 2017.

“In Taoist philosophy, there is an important concept called wu wei, which translates loosely to “doing-by-not-doing.” While Lao Tzu, the 6th century BC author of the Tao Te Ching and founder of Taoism, most assuredly was not writing about fixed income portfolios, the idea of “doing-by-not doing” aptly applies to what we see happening in passive bond index space today. Many have extolled the virtues of a wu wei approach to investing, and 2016 was a banner year for flows into all sorts of passive strategies through index funds and ETFs. But we think this is no time for wu wei in bonds; in fact, passively getting exposure to the Bloomberg Barclays US Aggregate Bond Index (aka “the Agg”) is downright dangerous today.”

The first is self evident: the Agg ends up owning the debt of the companies with the most of it, which in theory means the index is overexposed to riskier businesses. In other words, as a company’s debt burden becomes larger, the Agg buys more of it.

The second is that the Agg naturally becomes overexposed to whichever capital intensive sector is most exuberant over a particular cycle. So, during the TMT supercycles of the late 90s, tech and telecoms made up 16 per cent of the corporate portion of the index by the turn of the millennium. During the banking bubble of the noughties it got even more extreme, rising to a third of the index’s entire corporate exposure by the time the mortgage-backed security market cracked: investment grade leverage levels have never been higher. The Agg’s duration risk is near all-time highs.

The Stock Market Knows All

Maybe the stock market is the great predictor and gives no credence to Sanders/Warren. As a good fun, Warren defines “full-financing” as funding only the added federal cost of Medicare-For-All – not the underlying $72 trillion shortfall Medicare faces NOW over the next 30 years. Perhaps candidates should figure out how to pay for the current Medicare system before expanding it?

But Does Anyone Really Understand What Goes on in Chinese Debt Markets: From the FT.

China’s Tewoo Group has forced investors to take losses on a US dollar bond, marking the largest failure to repay dollar debt by a state-owned company in two decades and provoking fears of a wave of defaults.

The commodities trader, which is wholly owned by the city government of Tianjin, completed an exchange offer this week that made investors take significant discounts on their holdings in the company’s debt. The offer was “tantamount to a default”, S&P Global Ratings said on Thursday, and is expected to reframe how global investors view the market for government-backed corporate debt.

“The market has been building to something like this,” said Fraser Howie, an independent analyst and co-author of the book Red Capitalism: The Fragile Financial Foundation of China’s Extraordinary Rise. State-owned enterprises “cannot be assumed to be backed by the state when it comes to bond repayment”, he added. Until this year, no Chinese company backed by the state had been allowed to default on its dollar debt since the collapse of Guangdong International Trust and Investment Company, or Gitic, in 1998.

A missed payment on a US dollar bond in February by Qinghai Provincial Investment Group signalled that state support was waning, although the company made the payment within a five-day grace period. Tewoo’s restructuring represents a radical shift in how the Chinese government deals with failures at debt-strapped state enterprises by forcing investors to take losses.

The restructuring offer, which has been accepted by investors, gave Tewoo bondholders two options. The first was to take deep discounts on four outstanding bonds — one of which, a $300m bond, matures on Monday. The other option was to exchange the Tewoo bonds for that of another Tianjin-based state enterprise and accept far lower coupons. Given the economic downturn in China, the Chinese government may lack the resources to bail out all defaulting companies and will probably be forced to accept more market-based restructurings, global investors have warned.

“We expect the government to be more selective in where it uses its resources,” said Alaa Bushehri, head of emerging markets corporate debt at BNP Paribas Asset Management in London. “It doesn’t do anyone any good to be in that comfort zone.” Gitic’s default in 1998 sent a shockwave through Asia’s US dollar debt market as investors were forced to recalibrate anticipated state support for government-owned companies. But the collapse of the company came at a time when the borrowings of Chinese state-owned enterprises were still small. Today, state groups are some of the largest debt issuers in Asia, and Beijing is wary that an end to the state’s implicit guarantee will force a repricing of risk associated with such companies and drive up borrowing costs. Some analysts expect that Tewoo’s problems, and the lack of support from the city government in Tianjin, are just the beginning of a series of defaults at government-backed groups.

“We believe Tianjin is not an exception and other local governments with deteriorating fiscal profiles might also see eroding support for their uncompetitive and distressed SOEs,” S&P said on Thursday.

Passive Investing noted recently in the Economist:

Quant funds can be divided into two groups: those like Stockfish, which use machines to mimic human strategies; and those like AlphaZero, which create strategies themselves. For 30 years quantitative investing started with a hypothesis, says a quant investor. Investors would test it against historical data and make a judgment as to whether it would continue to be useful. Now the order has been reversed. “We start with the data and look for a hypothesis,” he says.

Humans are not out of the picture entirely. Their role is to pick and choose which data to feed into the machine. “You have to tell the algorithm what data to look at,” says the same investor. “If you apply a machine-learning algorithm to too large a dataset often it tends to revert to a very simple strategy.

Others are outright sceptics—among them Mr Dalio. In chess, he points out, the rules stay the same. Markets, by contrast, evolve, not least because people learn, and what they learn becomes incorporated in prices. “If somebody discovers what you’ve discovered, not only is it worthless, but it becomes over-discounted, and it will produce losses. There is no guarantee that strategies that worked before will work again,” he says. A machine-learning strategy that does not employ human logic is “bound to blow up eventually if it’s not accompanied by deep thinking. The reason is that by the standards of ai applications the relevant datasets are tiny.

“What determines the amount of data that you really have to work from is the size of the thing that you’re trying to forecast,” says Mr Kelly. For investors in the stock market that might be monthly returns, for which there are several decades’ worth of data—just a few hundred data-points. That is nothing compared with the gigabytes of data used to train algorithms to recognise faces or drive cars.