What Hides Below

November 3, 2019

by Steve Stofka

Think the days of packaging subprime loans together is gone? Nope. They are called asset-backed securities, or ABS. The 60-day delinquency rate on subprime loans is now higher than it was during the financial crisis (Richter, 2019). The dollar amount of 90-day delinquencies has grown more than 60% above the high delinquencies during the financial crisis. Recently Santander U.S.A. was called out for the poor underwriting practices of its subprime loans. In this case, Santander must buy back loans that go into early default because of fraud and poor standards.

Credit card delinquencies issued by small banks have more than doubled since Mr. Trump took office (Boston, Rembert, 2019). Did a more relaxed regulatory environment encourage these banks to take on more risk to boost profits?

In the last century, geologists have developed new measuring and analytical tools to better understand the structure of the Earth. GPS technology can now detect movements of the earth’s crust as little as ¼” (USGS, n.d.). The same can’t be said for human foolishness. During the past half-century, financial analysts and academics have developed an amazing array of statistical and analytical tools to understand and measure risk. Despite that sophistication, the Federal Reserve has mismanaged interest rate policy (Hartcher, 2006). Government regulators have misunderstood risks in the banking and securities markets.

Earthquake threats happen deep underground. I suspect that the same is true about financial risks. To gain a competitive advantage, companies try to hide their strategies and the details of their financial products. On the last pages of quarterly and annual reports, we find a lot of mysterious details in the notes. After the Arthur Anderson accounting scandal in 2002, the Sarbanes-Oxley Act was passed to bring greater transparency and accountability to financial reporting. Six years later, the financial crisis demonstrated that there was a lot of risk still hiding in dark corners.

The financial crisis exposed a lot of malfeasance and foolishness. Some folks think that investors are now more alert. After the crisis, corporate board members and regulators are more active and aware of risk exposures. Are those risks behind us? I doubt it. Believing in the power of their risk models, underwriters, bankers and traders become victims of their own overconfidence (Lewis, 2015).

Each decade California experiences a quake that is more than 6.0 on the Richter scale. Following the quake come the warnings that California will split away from the North American continent. Still waiting. The recession was due to arrive eight years ago. We did experience a mini-recession in 2015-16, but it wasn’t labeled a recession. The slowdown wasn’t slow enough and long enough. Eventually we will have a recession, and all those people who predicted a recession in 2011 and subsequent years will claim they were right. In many areas of life, being right is all about timing. Few of us are that kind of right.

The data demonstrates the difficulty of financial fortune telling. The Callan Periodic Table of Investment Returns shows the returns and rank of ten asset classes over the past two decades (Callan, 2019). An asset class that does well one year doesn’t fare as well the following year. An investor who can read the past doesn’t need to read the future. Does an investor need to diversify among all ten asset classes?  Many investors can achieve some reasonable balance between risk and reward with four to six index funds and leave their ouija boards in the closet.



Boston, C. and Rembert, E. (2019, October 28). Consumer Cracks Emerge as Banks Say Everything Looks Fine. Bloomberg. [Web page]. Retrieved from https://www.bloomberg.com/news/articles/2019-10-28/consumer-cracks-emerge-as-banks-say-everything-looks-fine

Callan. (2019). Periodic Table of Investment Returns. [Web page]. Retrieved from https://www.callan.com/periodic-table/

Hartcher, P. (2006). Bubble man: Alan Greenspan & the missing 7 trillion dollars. New York: W.W. Norton & Co.

Lewis, M. (2015). The Big Short. New York: Penguin Books.

Richter, W. (2019, October 25, 2019). Subprime auto loans blow up. [Web page]. Retrieved from https://wolfstreet.com/2019/10/25/subprime-auto-loans-blow-up-60-day-delinquencies-shoot-past-financial-crisis-peak

Szeglat, M. (n.d.) Photo of lava flow at Kalapana, HI, U.S. [Photo]. Retrieved from https://unsplash.com/photos/NysO5Rdn7Mc

USGS. (n.d.). About GPS. [Web page]. Retrieved from https://earthquake.usgs.gov/monitoring/gps/about.php

It’s Never Happened Before

July 24, 2016

It’s often been said that everyone is entitled to their own opinion but not to their own facts.  Repeated experiments have shown that, through a process of cognitive filtering, we do form our own set of facts. First we filter what we recognize, then we assign different degrees of importance to what we do recognize.  The world is a big lump of Play-Doh that we pull parts from then shape it into a personal ball that we call reality.

Several decades ago when computer development and design was still fairly primitive, computer scientists envisioned the develpment of algorithms that allowed computers to act with the mental versatility of human beings. Many hoped that this new technology, called artifical intelligence, or simply AI, would be implanted in robots which would handle menial or dangerous tasks, making our lives both safer and less tedious.  Soon robots were deployed on factory floors and were highly effective at repetitive tasks.  The deployment of AI was but a few years distant, it seemed.

The AI project soon ran into difficulties when robots tried to navigate a room with only a few obstacles.  What was a routine task for a two year old toddler was extremely difficult for a robot.  Programmers struggled to write algorithms to distinguish and describe just the shadows of objects, and were especially frustrated that a puppy a few weeks out of the womb could do a better job at navigating a room than the most beautifully complex algorithm they could devise.

A decade or so later, Google and other tech firms are test driving cars with autonomous navigation.  How have AI algorithms progressed from negotiating the obstacles in a room to navigating a highway at 65 MPH?  Working with behavioral scientists and psychologists, programmers began to uncover a rather unflattering but powerful model of human learning, one that philosopher David Hume had posited almost three hundred years ago.

Hume was just a teenager when Isaac Newton, perhaps the greatest scientist that ever lived, died in 1726.  Newton formulated the fundamental laws of motion and gravitation.  Hume, on the other hand, put forth the radical notion that we can not know cause and effect, only the correlation of events. We can imagine that Newton rolled over in his grave a few times at this proposal. Hume contended the forces of motion that Newton had proposed were highly probable correlations only.

Scientists dismissed Hume’s skepticism.  For all practical purposes, the universe was bounded by the laws of classical mechanics that Newton had devised.  Scientists went on to develop a model of a clockwork universe created by God that obeyed a set of rules invented by God and thank you very much.  There was apparently little more to discover until two scientists, Albert Michelson and Edward Morley, went to measure the aether, a fundamental component of the clockwork universe.  They couldn’t measure it.  This “undiscovery” rocked the world of physics because it undermined the theories of planetary motion, of gravitation, and the behavior of light.  Undiscoveries are as important as discoveries.  A hundred years before the Michelson-Morley experiment, chemists were unable to find phlogiston, the supposed fundamental cause of combustion, and caused a radical revision of chemical theory.

Twenty years after the Michelson-Morley experiment, Albert Einstein presented his Special Theory of Relativity but even that theory could not fully explain gravity.  A decade later and a hundred years ago, Einstein theorized that our perception of falling was an illusion based on our perspective, a vantage point as we were falling along the surface, or field, of space time.  The system of relative motion that he introduced has radically altered the science of physics since.  Einstein had introduced the same skepticism to the physical sciences that Hume had introduced to philosophical inquiry.

During the past two hundred years mathematicians have developed a number of statistical tools to measure not only the correlation between events, but the correlation of our past predictions based on correlation. As processors became more powerful and memory storage more compact, programmers turned to those statistical tools to enrich their AI algorithms. A baby can not find its own hands at first.  Through trial and error the baby develops a sensory system called proprioception that is not confused by the conflicting data from the baby’s eyes.  When the baby moves both hands in opposite directions to the center of her vision, the hands have more of a chance of colliding together.  The sense of touch confirms the contact of the two hands.  There may be a slight sound. The brain learns the coincidence, the correlation of these phenomena and forms a learning model of cause and effect.

Shortly after the financial crisis in 2008, the former head of the Federal Reserve, Alan Greenspan, testified before Congress about his personal set of beliefs of cause and effect in finance. Because this set of circumstances had not happened before, Mr. Greenspan thought that it could not happen.  Didn’t he see the dangers of 30-1 leverage ratios by major banks in the U.S.?, Greenspan was asked.  Yes, he saw them but did not fully appeciate the degree of danger.  The rash stupidity of bank officers, the disregard for their own welfare, surprised and disturbed him most.  He could not understand that intelligent people could act with such utter disregard for their own self-interest.  Of course, the bankers didn’t have to look our for themselves.  They paid politicians in Washington to do that for them.

Greenspan is a very smart man, as are most of the economists and financial wizards who did not understand the dangers of the synthethic debt instruments that were being created and traded.  Why?  Because it had not happened before.  We are all subject to this fault in judgment.  We are so guided by past experience that it skews our judgment, our ability to assess both risk and opportunity.

 It has been seven years since the market low in March 2009, seven years since the official end of the recession that began in December 2007 and ended in June 2009.  The Shiller price earnings ratio of the SP500 index is very much higher than average.  Even the conventional P/E ratio, the TTM or Trailing Twelve Months ratio, is about 23; the historical average is less than 17. Here is an excellent recent review of P/E ratios.  Low oil prices have helped cripple earnings growth for the SP500 index as a whole but even when excluding energy stocks, both revenue and earnings growth has shrunk.  Yardeni Research has put together several graphs to illustrate the trend.

The Money Flow Index (MFI) is an oscillating measure of buying and selling pressures based on both volume and price.  This index usually ranges from 20 to 80 on a scale of 0 to 100.  This month, the 12 month reading of the SP500 fell below 40.  Such a low reading has been associated with a long period of a rather flat market as happened in 1994-1995.  More often, a low reading is associated with subsequent falls in equity prices, as in early 2000 and late 2007.  Toward the end of 2008, this index fell below 20, indicating extreme selling pressure.  We only have past correlations to guide us.

Bond prices are high.  Vanguard’s ETF of intermediate term bonds, those with maturities of five to ten years, are now yielding less than 2%.  As bond and stock valuations have climbed, have we adjusted our portfolio allocation to stay within our guidelines?  Oops, did we kind of forget to even look anymore?  Did we get lulled into a sense of security?

Saving money is a gamble on the fact that we will get older.  Most of us will experience some reduction in our physical abilities, and a corresponding decrease in the amount of income we earn from our labor.  Saving money therefore seems like a really safe bet.  Once the money is saved, though, another series of gambles begins and these bets are far less certain.  Where to put those savings so that we can get a reasonable balance of return and risk?

 For a short time both the stock and bond markets can experience a surge in selling as they did in 2008. When investors are scared, they run like deer into the safety of cash. After the initial reaction, one or the other of these asset groups will continue to feel selling pressure.  This is why most advisors recommend some balance of stocks and bonds. If the stock market were to drop 50%, or the bond market drop 20%, and stay down for five years, would we be able to meet our income needs?  Such a downturn might be welcome to a 35 year old who can buy equities at a lower price.  For seniors near or in retirement who might have planned to convert some of those higher valuations into income, such a downturn can be devastating.  If such a scenario would be a crisis for you, then it is time to assess your situation and perhaps make changes.

The Long Run

Now the really big picture.  Reflecting the severity of the market downturn that began in late 2007, the 4 year average (50 month) of the S&P500 index is getting close to crossing below the 17 year (200 month) average.  Remember, this is years.  In the normal course of affairs, inflation tends to keep the shorter average above the longer average.  The crossing or “nearing” of these two averages reveals just how sick the past decade has been.  The last time the market showed this indicator of prolonged market weakness was in the first half of 1978, after a 43% market drop in the bear market of 1973-74 and a 19% drop in 1977.

In the last 60 years, was the October 2008 market drop of 17% the deepest monthly plunge in equity prices?  No, that honor goes to the almost 22% dive in October 1987.  For a consecutive 3 month drop, 2008 does barely nudge out 1987, both falling 30%.

Although headlines will speak of the downturn in the Fall of 2008 as the worst since the depression, it is important for Boomers to remember that our parents’ generation suffered through some pretty severe market declines as well.  In 1987, most Boomers were in their thirties and probably had relatively few dollars in the stock market.  We may remember “Black Monday”, October 19, 1987, for the headlines but it was not as personal as the 2008 decline because we were decades before retirement and had less at stake.  What particularly distinguishes the two years is that the unemployment rate continued to fall during the 1987 decline.

Young people don’t remember market crashes the way that older people do.  When we are young, we have – like forever – before we are going to be old.  For the echo boomer generation born in the eighties and nineties, also known as the  “millennials”, or Generation Y, the crash of 2008 will be a faint or non-existent memory when they reach their fifties decades from now.  They will probably get to have their own crash – one that they will remember because they will have more at stake.

When we are in our twenties, someone should prepare us.  We are going to work hard and save money.  We are probably going to put some of that hard earned money in the stock market.  Then, when we are in our fifties, sixties or seventies, we are going to flip out when our stock portfolio drops by 40%.  Would we listen to or remember that sage advice?  Probably not.