When Banks Pay Borrowers’s Mortgage Interest, Europe Edition

Falling interest rates in Europe have put some banks in an interesting position: owing money on loans to borrowers.The Wall Street Journal reports on the curiosity:

At least one Spanish bank, Bankinter SA, the country’s seventh-largest lender by market value, has been paying some customers interest on mortgages by deducting that amount from the principal the borrower owes.

The problem is just one of many challenges caused by interest rates falling below zero, known as a negative interest rate. All over Europe, banks are being compelled to rebuild computer programs, update legal documents and redo spreadsheets to account for negative rates.

Interest rates have been falling sharply, in some cases into negative territory, since the European Central Bank last year introduced measures meant to spur the economy in the eurozone, including cutting its own deposit rate. The ECB in March also launched a bond-buying program, driving down yields on eurozone debt in hopes of fostering lending.

So in Spain, Portugal, and Italy, the base interest rate used for many loans, especially mortgages, is the euro interbank offered rate, or Euribor. The rate is based on how much it costs European banks to borrow from each other. Banks set interest rates on many loans as a small percentage above or below a benchmark such as Euribor. If the spread plus the Euribor is below 0, the Bank pays the borrower.

JPMorgan Chase Has More than 1,000 Models in Production

This afternoon, I spent some time reviewing the annual shareholder letter from JPMorgan Chase. The most interesting bit to me was this section on Model Risk Management (“Model review”) at the Bank:

More than 300 employees are working in Model Risk and Development. In 2014, this highly specialized team completed over 500 model reviews, implemented a system to assess the ongoing performance of the 1,000+ most complex models in the firm, and continued to enhance capital and loss models for our company.

So there at least 1,000 models currently in production at JPMorgan Chase, which doesn’t include the non-complex models…

I also thought Jamie Dimon’s comments on the Comprehensive Capital Analysis and Review (CCAR) were illuminating:

We believe that we would perform far better under the Fed’s stress scenario than the Fed’s stress test implies. Let me be perfectly clear – I support the Fed’s stress test, and we at JPMorgan Chase think that it is important that the Fed stress test each bank the way it does. But it also is important for our shareholders to understand the difference between the Fed’s stress test and what we think actually would happen. Here are a few examples of where we are fairly sure we would do better than the stress test would imply:

  • We would be far more aggressive on cutting expenses, particularly compensation, than the stress test allows.
  • We would quickly cut our dividend and stock buyback programs to conserve capital. In fact, we reduced our dividend dramatically in the first quarter of 2009 and stopped all stock buybacks in the first quarter of 2008.
  • We would not let our balance sheet grow quickly. And if we made an acquisition, we would make sure we were properly capitalized for it. When we bought Washington Mutual (WaMu) in September of 2008, we immediately raised $11.5 billion in common equity to protect our capital position. There is no way we would make an acquisition that would leave us in a precarious capital position.
  • And last, our trading losses would unlikely be $20 billion as the stress test shows. The stress test assumes that dramatic market moves all take place on one day and that there is very little recovery of values. In the real world, prices drop over time, and the volatility of prices causes bid/ask spreads to widen – which helps marketmakers. In a real-world example, in the six months after the Lehman Brothers crisis, J.P. Morgan’s actual trading results were $4 billion of losses – a significant portion of which related to the Bear Stearns acquisition – which would not be repeated. We also believe that our trading exposures are much more conservative today than they were during the crisis.

The last point is important because the way the scenarios have worked in the recent years for CCAR, the assumption was that there was a one-time (one day to less than a month-long), massive shock to the equity markets (50 to 60% drop in the severely adverse case).

Early Retirement and the Paradox of Success

This is a good piece in The New York Times on the paradox of success:

Similarly, to succeed in the N.F.L., it is not enough to be strong and fast. Witness all the college players who exhibit all the physical skills they need in the league’s draft who never succeed as professionals. Rather, the best players display a certain manic competitiveness such that they keep playing. The Denver Broncos’ quarterback, Peyton Manning, has won a Super Bowl and made $230 million from football alone, and he looked to be in profound physical pain at the end of last season. Yet with his intensively competitive streak, he intends to come back next season at age 39.

The paradox of success is this: The mental wiring that enables a person to claw to the tippy-top of Corporate America or sports or entertainment or any other field that offers vast wealth is the same mental wiring that most of the time leads people not to retire before they have to — no matter what the diminishing marginal utility of money would suggest.

More here.

On Bad Investments and Marathons

This week, The New York Times launched Upshot , described as “a plainspoken guide to the news” and in essence, similar to two other explanatory new sites that have recently launched (Vox.com and FiveThirtyEight.com). My favorite piece so far on Upshot is Justin Wolfers’s “What Good Marathons and Bad Investments Have in Common” (because it combines two of my interests: finance and running):

In the usual analysis, economists suggest it’s worth putting in effort as long as the marginal benefit from doing so exceeds the corresponding marginal cost of that effort. The fact that so many people think it worth the effort to run a 2:59 or 3:59 marathon rather than a 3:01 or 4:01 suggests that achieving goals brings a psychological benefit, and that missing them yields the costly sting of failure.

But in other domains, this discontinuity between meeting a goal and being forced to confront a loss can lead to bad economic decisions. Because losses are psychologically painful, we sometimes strain too hard to avoid them.

For instance, when you sell your house, your goal may be to get at least what you paid for it. But this simple goal has led to disastrous decisions for those who bought homes in Florida or Nevada during the housing bubble. Too many homeowners set their selling prices with an eye on recouping past investments rather than on current market conditions, and as a result, their homes didn’t sell, deepening their financial distress.

Well worth the read in entirety.

The 2014 Annual Shareholder Letter from Warren Buffett

Fortune Magazine has a sneak peek into the annual shareholder letter than Warren Buffett will soon share with the Berkshire Hathaway shareholders. He shares two personal stories from his life and how the investment decisions have paid off over time. He echoes his wisdom in the following points:

  • You don’t need to be an expert in order to achieve satisfactory investment returns. But if you aren’t, you must recognize your limitations and follow a course certain to work reasonably well. Keep things simple and don’t swing for the fences. When promised quick profits, respond with a quick “no.”

  • Focus on the future productivity of the asset you are considering. If you don’t feel comfortable making a rough estimate of the asset’s future earnings, just forget it and move on. No one has the ability to evaluate every investment possibility. But omniscience isn’t necessary; you only need to understand the actions you undertake.

  • If you instead focus on the prospective price change of a contemplated purchase, you are speculating. There is nothing improper about that. I know, however, that I am unable to speculate successfully, and I am skeptical of those who claim sustained success at doing so. Half of all coin-flippers will win their first toss; none of those winners has an expectation of profit if he continues to play the game. And the fact that a given asset has appreciated in the recent past is never a reason to buy it.

  • With my two small investments, I thought only of what the properties would produce and cared not at all about their daily valuations. Games are won by players who focus on the playing field — not by those whose eyes are glued to the scoreboard. If you can enjoy Saturdays and Sundays without looking at stock prices, give it a try on weekdays.

  • Forming macro opinions or listening to the macro or market predictions of others is a waste of time. Indeed, it is dangerous because it may blur your vision of the facts that are truly important. (When I hear TV commentators glibly opine on what the market will do next, I am reminded of Mickey Mantle’s scathing comment: “You don’t know how easy this game is until you get into that broadcasting booth.”)

Read the rest here.

Marc Andreessen on the Future of Bitcoin

Marc Andreessen, writing in The New York Times, has a very good piece titled “Why Bitcoin Matters” explaining Bitcoin and its potential. You have to remember that Mr. Andreessen has skin in the game (to quote Nassim Taleb), because he will do very well if Bitcoin succeeds. However, it is still worth the read.

What’s the future of Bitcoin?

Bitcoin is a classic network effect, a positive feedback loop. The more people who use Bitcoin, the more valuable Bitcoin is for everyone who uses it, and the higher the incentive for the next user to start using the technology. Bitcoin shares this network effect property with the telephone system, the web, and popular Internet services like eBay and Facebook.

In fact, Bitcoin is a four-sided network effect. There are four constituencies that participate in expanding the value of Bitcoin as a consequence of their own self-interested participation. Those constituencies are (1) consumers who pay with Bitcoin, (2) merchants who accept Bitcoin, (3) “miners” who run the computers that process and validate all the transactions and enable the distributed trust network to exist, and (4) developers and entrepreneurs who are building new products and services with and on top of Bitcoin.

All four sides of the network effect are playing a valuable part in expanding the value of the overall system, but the fourth is particularly important.

All over Silicon Valley and around the world, many thousands of programmers are using Bitcoin as a building block for a kaleidoscope of new product and service ideas that were not possible before. And at our venture capital firm, Andreessen Horowitz, we are seeing a rapidly increasing number of outstanding entrepreneurs – not a few with highly respected track records in the financial industry – building companies on top of Bitcoin.

For this reason alone, new challengers to Bitcoin face a hard uphill battle. If something is to displace Bitcoin now, it will have to have sizable improvements and it will have to happen quickly. Otherwise, this network effect will carry Bitcoin to dominance.

One immediately obvious and enormous area for Bitcoin-based innovation is international remittance. Every day, hundreds of millions of low-income people go to work in hard jobs in foreign countries to make money to send back to their families in their home countries – over $400 billion in total annually, according to the World Bank. Every day, banks and payment companies extract mind-boggling fees, up to 10 percent and sometimes even higher, to send this money.

Switching to Bitcoin, which charges no or very low fees, for these remittance payments will therefore raise the quality of life of migrant workers and their families significantly. In fact, it is hard to think of any one thing that would have a faster and more positive effect on so many people in the world’s poorest countries.

Moreover, Bitcoin generally can be a powerful force to bring a much larger number of people around the world into the modern economic system. Only about 20 countries around the world have what we would consider to be fully modern banking and payment systems; the other roughly 175 have a long way to go. As a result, many people in many countries are excluded from products and services that we in the West take for granted. Even Netflix, a completely virtual service, is only available in about 40 countries. Bitcoin, as a global payment system anyone can use from anywhere at any time, can be a powerful catalyst to extend the benefits of the modern economic system to virtually everyone on the planet.

And even here in the United States, a long-recognized problem is the extremely high fees that the “unbanked” — people without conventional bank accounts – pay for even basic financial services. Bitcoin can be used to go straight at that problem, by making it easy to offer extremely low-fee services to people outside of the traditional financial system.

A third fascinating use case for Bitcoin is micropayments, or ultrasmall payments. Micropayments have never been feasible, despite 20 years of attempts, because it is not cost effective to run small payments (think $1 and below, down to pennies or fractions of a penny) through the existing credit/debit and banking systems. The fee structure of those systems makes that nonviable.

All of a sudden, with Bitcoin, that’s trivially easy. Bitcoins have the nifty property of infinite divisibility: currently down to eight decimal places after the dot, but more in the future. So you can specify an arbitrarily small amount of money, like a thousandth of a penny, and send it to anyone in the world for free or near-free.

I think this is the most interesting/compelling use of Bitcoin to me:

Think about content monetization, for example. One reason media businesses such as newspapers struggle to charge for content is because they need to charge either all (pay the entire subscription fee for all the content) or nothing (which then results in all those terrible banner ads everywhere on the web). All of a sudden, with Bitcoin, there is an economically viable way to charge arbitrarily small amounts of money per article, or per section, or per hour, or per video play, or per archive access, or per news alert.

For example, I don’t want to pay the monthly subscription to The New York Times, because while I read a lot on the site, I don’t see the benefit of paying for a subscription when I can get to the articles for free via social media channels. But if the cost was something small, say $0.05 per article, then I would be more inclined to browse from the homepage directly.

The Human Element in Quantification

I enjoyed Felix Salmon’s piece in Wired titled “Why Quants Don’t Know Everything.” The premise of the piece is that while what quants do is important, the human element cannot be ignored.

The reason the quants win is that they’re almost always right—at least at first. They find numerical patterns or invent ingenious algorithms that increase profits or solve problems in ways that no amount of subjective experience can match. But what happens after the quants win is not always the data-driven paradise that they and their boosters expected. The more a field is run by a system, the more that system creates incentives for everyone (employees, customers, competitors) to change their behavior in perverse ways—providing more of whatever the system is designed to measure and produce, whether that actually creates any value or not. It’s a problem that can’t be solved until the quants learn a little bit from the old-fashioned ways of thinking they’ve displaced.

Felix discusses the four stages in the rise of the quants: 1) pre-disruption, 2) disruption, 3) overshoot, and 4) synthesis, described below:

It’s increasingly clear that for smart organizations, living by numbers alone simply won’t work. That’s why they arrive at stage four: synthesis—the practice of marrying quantitative insights with old-fashioned subjective experience. Nate Silver himself has written thoughtfully about examples of this in his book, The Signal and the Noise. He cites baseball, which in the post-Moneyball era adopted a “fusion approach” that leans on both statistics and scouting. Silver credits it with delivering the Boston Red Sox’s first World Series title in 86 years. Or consider weather forecasting: The National Weather Service employs meteorologists who, understanding the dynamics of weather systems, can improve forecasts by as much as 25 percent compared with computers alone. A similar synthesis holds in eco­nomic forecasting: Adding human judgment to statistical methods makes results roughly 15 percent more accurate. And it’s even true in chess: While the best computers can now easily beat the best humans, they can in turn be beaten by humans aided by computers.

Very interesting throughout, and highly recommended.