U.S. Cities Look to Shed Ratings While Taking On More Debt



U.S. cities and counties are using fewer ratings to assess the risks of the bonds they sell, providing investors with just one opinion on an increasing amount of new debt, the Wall Street Journal reported. Roughly 25 percent of the dollar value of all municipal debt issued this year carried a single grade from one of the major ratings firms, according to Municipal Market Analytics data as of Oct. 3. If that percentage holds through the end of the year, it would be the highest since the research firm began tracking the data in 2006. For the riskiest debt, the single-grade ratio by dollar volume was 37 percent. Municipal officials and advisers said fewer ratings help cities trim expenses and save time when they borrow money for everything from school construction to sewer repairs. Bond issuers typically pay ratings firms to issue a report. But some analysts said opting for one grade from a single firm puts smaller investors at a disadvantage as less information circulates through the $3.8 trillion municipal market. (Subscription required.)

Report: How Student Loan Debt Hampers Home-Buying



Americans have amassed more than $1.5 trillion in student loan debt, according to the Federal Reserve, which has an outsize impact on potential home buyers, the Washington Post reported. A recent analysis by Zillow found that about one-third of renters who plan to buy a home in the next year carry at least some student loan debt, with an average payment of $388 per month. An analysis that compares national median home values, median household income and student loan debt found that a family earning the median household income can afford to buy 66 percent of homes listed for sale. But those with student loan debt can only afford 52 percent of those homes. Nationally, a renter earning the median household income who doesn’t have student loan debt can afford to buy a home that costs up to $361,800, assuming a 20 percent down payment and a 30-year fixed-rate loan with a mortgage rate of 4.8 percent. A renter in those same circumstances with student loan debt could afford to spend up to $269,400, a difference of $92,400. Affordability is based on the assumption that the buyers are spending no more than 30 percent of their income on the combination of housing costs and student loan repayments.

Analysis: Corporate Debt Crises Could Come Faster and Harder in 2019



At first glance, 2019 might look like a quiet year for distressed-debt investors, judging by the small list of troubled bonds coming due. But the light schedule may be obscuring how quickly some issuers will unravel, according to a Bloomberg News analysis. As Toys “R” Us demonstrated, weak sales and nervous trade creditors can bring down a company long before the maturity dates for loans and bonds. What’s more, secured debt isn’t as secure as it used to be: Top-heavy capital structures and loose covenants could leave little for junior creditors to recover if an issuer goes bust. Even first-lien holders may have to lower their expectations because of loopholes that weaken their claims on collateral, according to Jeanne Manischewitz, co-head of North American credit at York Capital Management. Only $80 billion of loans and $105 billion of speculative-grade bonds will mature through 2020, according to Fitch Ratings. Look for trouble at companies saddled with lots of floating-rate debt and shaky business models, Fitch says.





 

First Futures Contract to Pay Out in Bitcoin Poised for Green Light



The first futures contract that will pay out in cryptocurrency rather than cash is expected to soon get regulatory approval, the Wall Street Journal reported. The contract, launched by New York Stock Exchange owner Intercontinental Exchange Inc., is aimed at institutional players who have stayed out of cryptocurrency markets out of concerns that they are unregulated and susceptible to manipulation. Bitcoin futures allow investors to bet on the price of the cryptocurrency. Other bitcoin-futures contracts exist, but they pay out in dollars. The effort has received backing from major corporations such as Microsoft Corp. and Starbucks Corp., which have the longer-term goal of making cryptocurrency transparent and regulated enough to allow customers to use it for retail purchases, such as a Starbucks latte. Following an extraordinary run-up in Bitcoin prices last year, CME Group Inc., the world’s largest exchange company, and Cboe Global Markets Inc., operator of the biggest U.S. options exchange, both launched futures on the cryptocurrency in December. Since then, the outlook for the cryptocurrency has dimmed considerably. After peaking at around $20,000 last December, Bitcoin’s price has dropped by over 80%. Federal regulators are investigating possible manipulation in Bitcoin markets.







Cryptocurrency and other top insolvency topics will be covered at sessions at ABI’s Annual Spring Meeting April 11-14 in Washington, D.C. The keynote speaker will be legendary investigative journalist Bob Woodward. Register today!

Commentary: A New Way to Spot the Next Financial Crisis



The previous method for modeling the financial world was shown to have huge blind-spots during the 2008 crisis, according to a Wall Street Journal commentary. People didn’t behave in the rational ways economists had assumed, and supposedly freak events appeared with alarming frequency. Investors and regulators have been hunting for alternatives ever since. The latest candidate is “agent-based” modeling. U.K.-based startup Simudyne has joined with U.S. federally funded research company Mitre Corp. to turn an agent-based model of asset fire sales and investor flight from banks and funds into a commercial product. They are using the building blocks of a model of the U.S. financial system that Mitre built for the U.S. Treasury. Traditional financial models assumed that rational, well-informed people acted in efficient markets, allowing economists to analyze markets relatively simply with a few generalized rules. Agent-based modeling instead simulates market activity by creating dynamic computer programs with lots of agents, such as investors and banks, and seeing what happens when they interact.

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