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 About Martin Zorn

Martin Zorn currently serves as Kamakura's president and chief operating officer.  In this role he oversees all day-to-day operations serving Kamakura risk management clients in 37 countries.  He joined Kamakura in January 2011 as chief financial officer and chief administrative officer. Read More

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Kamakura Blog

Feb 22

Written by: Martin Zorn
2/22/2016 10:30 PM 

While often attempted history proves that one cannot repeal the business and credit cycle.  The cycle always seems to be the same although the triggers and environment may be different.  Losses peak, loan demand and supply dry up, the appetite for risk evaporates while households and businesses begin the process of repairing their respective balance sheets.  Slowly investors start stretching for yield and lenders (banks, shadow banks and capital markets) begin to ease credit terms, soon followed by increased usage of leverage.  A review of the Federal Reserve Senior Credit Officer Survey bears out this cycle. 

This cyclical nature of credit and default risk can clearly be seen from the history of the Kamakura Troubled Company Index going back to its introduction in 1990.

The Kamakura troubled company registered its historic low of 3.95 on August 4, 2014 that also represents the low for the current cycle.  The index reflects the percentage of the Kamakura 34,000 public firm universe that has a default probability over 1.00%.  An increase in the index reflects declining credit quality while a decrease reflects improving credit quality.  In a similar vein the lower the index the less risk that is reflected in the market.  As one can see from the chart below the troubled company index has been rising since August reflecting increased risk over the past six months.

Even before the uptick in the index, we were able to see signs of increasing risk from other measures.  One of the advantages of the Kamakura default probabilities is the ability to view the full term structure of default.  The Troubled Company Index measures the one-year default probability while the user has the ability to examine both short-term and longer-term probabilities, as far out as ten years.  During the summer, while the Index was hitting bottom, we were able to see a distinct upturn in the default probabilities at the 3 and 5-year points on the term structure.  For bondholders or for term lenders this should have been significant.  One should think of this in the same way that one can interpolate a forward curve for interest rates.

If history is a guide it will be the marginal debt that was assumed last summer that will prove to the riskiest in the next cycle. History also tells us that short-term default probabilities tend to rise quickly and often the acceleration is related to a systemic shock.  Today we have no shortage of triggering suspects: geopolitical conditions including ISIS or the Ukraine, the contagion of negative interest rates, deflationary pressure, foreign exchange wars, the collapse of oil prices or other commodities or the divergent strategies by central banks.

Let’s look at a combination of term structure and companies exposed to the risks outlined above.  I have chosen the Swiss firm, Transocean, as it is the highest rated company within the energy segment that also has one of the highest default probabilities within the segment.

We can see the rapid rise in the one-year default probability that corresponds to the fall in oil prices as well as the impact of the actions by the Swiss National Bank.  In the graph below we examine the term structure which shows the default probability begin to fall after one year.

By comparison we will take a look at the term default curve for JC Penney(JCP).  The retail segment represents another high-risk segment with 2015 bankruptcies filed by Radio Shack, Wet Seal, Deb Shops, Body Central, Target-Canada among others already this year.  The problems for retailers are both longer term and more structural than the energy segment and that can be seen from the difference in the term structure below.

Kamakura provides many tools for the astute analyst to uncover risk.  Using the term structure one is able to more accurately measure risk whether you are an investor in commercial paper, overnight lending or a 30-year bond.  Two other key metrics include the relative absolute default probability and the change in default probability.

The first chart shows the 99th percentile (the 1 percent with the highest risk) of rated companies with the highest 3-month default probability.  BPZ Resources (BPZ) leads that list.

The second chart shows the 99th percentile of the same list sorted by the names that had the greatest increase in their default risk over the past thirty days. In this case Piraeus Bank SA of Greece (TPEIR) tops the risk list.

Doing the same analysis, but now looking at the 99th percentile based on the 5-year default probability, PDG Realty SA of Brazil (PDGR3) tops the list.  I should point out that all of these searches can be screened by country, sector or rating (rated, non-rated, high-yield, all) in addition to term.

The following charts are examples of a sector analysis for the 3-month and 1-year probability risk.  It was easy to follow up by segment and in turn identify Sprint (S) and BPZ Resources Inc. (BPZ) as the riskiest companies in each segment.

In less than thirty minutes one is able to use KRIS to identify industries, segments, markets and companies that represent heightened risk profiles regardless of the exposure term, the point in the business or the credit cycle.  Additional tools are available to stress test the exposure so that the astute analyst can be ahead of the market in reducing risk or conversely comfortable with taking risk when others are offloading it.