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Which corporations had the biggest decreases and biggest increases in credit risk in 2013? The biggest decreases in credit risk in 2013 came from Sharp (OTCPK:SHCAF) (OTCPK:SHCAY), Yellow Media Ltd. (OTC:YLWDF) (OTC:YLWWF), Axtel S.A.B. de C.V. (OTC:AXTLF) of Mexico, A2A S.p.A (OTC:AEMMF) (OTCPK:AEMMY) of Italy, and Supervalu Inc. (NYSE:SVU). The 1 year default probability for Sharp fell 13.49% over the course of 2013. The decreases in 1 year default probabilities were 8.27% for Yellow Media, 7.42% for Axtel, 6.12% for A2A, and 5.60% for Supervalu. We explain the default probabilities and the universe of corporates used for this ranking below.

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The biggest increases in credit risk around the world were recorded by NII Holdings Inc. (NASDAQ:NIHD), OI S.A. (NYSE:OIBR) of Brazil, PDG Realty S.A. (OTC:PDGRF) (OTCPK:PDGRY) of Brazil, Banca Carige S.p.A. (OTC:BCIGF) (OTC:BCIGY) of Italy, and Eurobank Ergasias S.A. (OTCPK:EGFEY) (OTC:EGFEF) of Greece. The 1 year default probability for NII Holdings Inc. increased by 10.32% during 2013. The default probabilities for the other awardees jumped 6.87% for OI S.A., 6.78% for PDG Realty, 6.69% for Banca Carige, and 5.22% for Eurobank Ergasias during the year.

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In the rest of this note, we document the ranking process and explain how each of these ten firms earned these "accolades."

The Ranking Methodology

There are many different methodologies that an analyst could use to measure changes in credit risk during a calendar year. A legacy approach would be to use traditional credit ratings, but such an approach has multiple problems. First, the median time since last ratings change was 815 days according to a recent study by Kamakura Corporation, so ratings are relatively insensitive to changes in the macro economy and the individual corporation's financial condition. Second, in part because of these infrequent changes, ratings are simply less accurate than modern statistical methods, as outlined by Hilscher and Wilson. Thirdly, the U.S. Senate found that the legacy credit ratings institutions have a conflict of interest from their "issuer pays" model. The result is a significant difference in ratings levels for "solicited" versus "unsolicited" ratings, as found in a recent study on the website of the Harvard Law School. The use of ratings for the credit risk ranking would merely perpetuate these problems.

Another potential source of credit risk rankings is the credit default swap market. Unfortunately, there are multiple problems with the CDS market as a ranking source as well. First, on average, in a given week only 875 firms world-wide have any trades at all in the credit default swap market according to a study by Kamakura Corporation using data from the Depository Trust & Clearing Corporation. Second, actual traded credit default swap levels are not reported by DTCC or by the leading CDS data vendors; instead, they report a mix of bids, offered, and trades without transparent disclosure. One vendor reports such data daily on 2,000 reference names even though only 875 firms on average have any trades, meaning that more than half the data is no more credible than Libor. Indeed, lawsuits alleging manipulation of the CDS market have been filed and the European Union has launched an investigation. Again, using such data in this ranking would be problematic.

Instead, we use modern statistical reduced form default probabilities described below and provided by Kamakura Corporation's Kamakura Risk Information Services ("KRIS"). This service provides daily updates of default probabilities with maturities ranging from one month to 10 years on 35,000 public firms. We limit our annual comparison to a subset of this universe. We consider only firms that meet the following criterion:

  1. Since we want the firms to be important in both the equity and debt markets, we require that the firms considered have both publicly traded common stock and legacy credit ratings.
  2. We require that the firm have a history long enough for both its financials and stock price to be available to the KRIS service for the last twelve months.
  3. Since we care about firms which are "still alive," we exclude the firms that have gone bankrupt, defaulted, or are in selective default at either the beginning or end of the year.

In all, of the 35,000 firms covered by KRIS, 2,486 had legacy ratings. About 2,400 of these firms were not in default and had default probabilities available at both the beginning and the end of the year. We focused on the key 1 year default probability and its change during 2013 in selecting "winners" and "losers." The winners had the biggest drops in 1 year default risk during the year. The losers had the biggest increases in 1 year default risk during the year. We note a few key points about default risk before reviewing the yearly performance for our 5 winners and 5 losers:

  1. Default risk is like the weather: it is constantly changing. Like the weather, it does not change in a constant, steady direction. Credit risk rises and falls, just as weather gets warmer and colder, in fits and starts.
  2. Default risk changes dramatically as risky firms take actions to save themselves from default. Some of these actions will be successful, and default probabilities will fall dramatically after rising to a high level. Some of these rescue actions will not be successful in the long run, even if they reduce risk in the short run.
  3. Unlike ratings, default probabilities have an explicit maturity. Long run default probabilities can remain high even when short term default probabilities are low, and vice versa.
  4. What goes up can come down. More importantly, what comes down can go up. The fact that a company's default risk has declined conveys only its current risk outlook. There is no guarantee that credit risk will not rise substantially in the future. A 1 year default probability that is well below the 5 year default probability, like the case of our "winner" Sharp below, indicates that the long run outlook for the firm is much more risky than the 1 year outlook.

We see all of these patterns in our review.

The Year in Review for the Winners and Losers

Winner Number 5: Supervalu Inc.

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Supervalu Inc. operates as a wholesale distributor to independent retail customers in the United States. Over the course of 2013, the firm's 1 year default probability fell by 5.60% to 0.28% from 5.88% at the beginning of the year. The blue line is the 1 year default probability. The yellow line is the annualized 5 year default probability. The 5 year default probability remains well over 2.00% at year end. The large jumps in default risk during the year coincide with the release of new financial data by the firm.

Winner Number 4: A2A S.p.A.

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A2A S.p.A. is involved in the production, sale and distribution of electricity and gas in Italy. The firm's 1 year default probability has dropped to 0.90%, down 6.12% from 7.02% at the beginning of 2013.

Winner Number 3: Axtel S.A.B. de C.V.

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Axtel runs a telecommunications network in Mexico. The firm's 1 year default probability has fallen to 0.65% by the end of the year. This is down 7.42% from 8.07% at the beginning of the year. The firm's 5 year default probability remains, high, however, at 12.35%.

Winner Number 2: Yellow Media Inc.

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Yellow Media Ltd. serves Canadian companies as a media and marketing company. It offers various versions, both print and electronic, of "yellow pages" advertisements. The firm's 1 year default probability has fallen dramatically over the course of the year and is now less than 1 basis point when rounded to two decimal places. The 5 year default probability is currently 0.32%.

Winner Number 1: Sharp Corporation

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Japan's Sharp Corporation has engineered the largest drop in 1 year default probabilities during the year. The 1 year default probability, still high at 5.22%, is 13.49% below its level at the beginning of the year. The 5 year default probability for the firm has risen in the second half of the year even as the 1 year default probability has stabilized at the current level. The current 5 year default probability is 13.85%, a very high level. Clearly, the company's credit risk remains complex even though 2013 has shown considerable improvement in the 1 year outlook.

Loser Number 5: Eurobank Ergasias S.A.

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Eurobank Ergasias of Greece ranks fifth world-wide in terms of the increase in 1 year default probability over the course of 2013. The year-end to year-end comparison, however, masks a considerable amount of drama during the middle of the year. In June, Eurobank engineered a reverse stock split as part of a revitalization effort. This split initially drove down the bank's default probabilities, but they deteriorated again shortly thereafter. Ultimately, however, the default probabilities declined to their current levels. The 1 year default probability, at 13.46%, is one of the highest among listed corporates world-wide and 5.22% higher than its level at the start of the year.

Loser Number 4: Banca Carige S.p.A.

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Banca Carige S.p.A. of Italy has a current 1 year default probability of 8.50% and a 5 year annualized default probability of 12.08%. Both default probabilities are sharply higher than they were at the start of the year, with the 1 year default probability rising 6.69% in the last 12 months.

Loser Number 3: PDG Realty S.A.

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PDG Realty S.A. is a Brazilian real estate company. Its default probabilities for both 1 year and 5 year maturities have climbed steadily during the year, with the 1 year default probability now at 8.68%, up 6.78%.

Loser Number 2: OI S.A.

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OI S.A. provides telecommunications services in Brazil. Like its competitor Telecom Italia, which has large operations in Brazil, the firm has been a victim of the disruption of the telecommunications industry by new technology. OI S.A.'s 1 year default probability has risen to 7.70%, up 6.87% at the start of the year.

Loser Number 1: NII Holdings Inc.

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NII Holdings offers telecommunications services in Mexico, Brazil, Argentina, Peru, and Chile. Other than the firms that defaulted in 2013, NII Holdings Inc. has experienced the largest increase in its 1 year default probability in 2013. The current 1 year default probability, 11.62%, is 10.32% higher than at the start of the year. The annualized 5 year default probability for the firm is 24.52%, a very high level that indicates a turbulent future.

Turbulence in the Midst of Exuberance

By definition, the largest decreases and increases in 1 year default probabilities come from 10 companies who had very high default risk at either the start of the year, the end of the year, or both. Telecommunications and Latin America were common themes among the 10 exciting firms on the 2013 list. Their experience is a warning that, even when world-wide corporate credit conditions are at the 90th percentile, investors should be extremely careful in their investment strategy. "High yield" means high yield, not high return, and the yields are normally high for a reason: high risk.

Author's Note

Regular readers of these notes are aware that we generally do not list the major news headlines relevant to the firm in question. We believe that other authors on Seeking Alpha, Yahoo, at The New York Times, The Financial Times, and the Wall Street Journal do a fine job of this. Our omission of those headlines is intentional. Similarly, to argue that a specific news event is more important than all other news events in the outlook for the firm is something we again believe is inappropriate for this author. Our focus is on current bond prices, credit spreads, and default probabilities, key statistics that we feel are critical for both fixed income and equity investors.

Background on Default Probabilities Used

The Kamakura Risk Information Services version 5.0 Jarrow-Chava reduced form default probability model makes default predictions using a sophisticated combination of financial ratios, stock price history, and macro-economic factors. The version 5.0 model was estimated over the period from 1990 to 2008, and includes the insights of the worst part of the recent credit crisis. Kamakura default probabilities are based on 1.76 million observations and more than 2000 defaults. The term structure of default is constructed by using a related series of econometric relationships estimated on this data base. An overview of the full suite of related default probability models is available here.

General Background on Reduced Form Models

For a general introduction to reduced form credit models, Hilscher, Jarrow and van Deventer (2008) is a good place to begin. Hilscher and Wilson (2013) have shown that reduced form default probabilities are more accurate than legacy credit ratings by a substantial amount. Van Deventer (2012) explains the benefits and the process for replacing legacy credit ratings with reduced form default probabilities in the credit risk management process. The theoretical basis for reduced form credit models was established by Jarrow and Turnbull (1995) and extended by Jarrow (2001). Shumway (2001) was one of the first researchers to employ logistic regression to estimate reduced form default probabilities. Chava and Jarrow (2004) applied logistic regression to a monthly database of public firms. Campbell, Hilscher and Szilagyi (2008) demonstrated that the reduced form approach to default modeling was substantially more accurate than the Merton model of risky debt. Bharath and Shumway (2008), working completely independently, reached the same conclusions. A follow-on paper by Campbell, Hilscher and Szilagyi (2011) confirmed their earlier conclusions in a paper that was awarded the Markowitz Prize for best paper in the Journal of Investment Management by a judging panel that included Prof. Robert Merton.

Disclosure: I have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it. I have no business relationship with any company whose stock is mentioned in this article.

Additional disclosure: Kamakura Corporation has business relationships with a number of organizations mentioned in this article.

Source: 2013 World-Wide Credit Risk Winners And Losers