A Case Study of XTERA Communications Using KRIS Default Probabilities

11/22/2016 08:59 AM

XTERA Communications, Inc. (NASDAQ: XCOM) (“XCOM”, “XTERA”, “the company”) provides optical transport solutions worldwide. Its products include Nu-Wave Optima, a multi-purpose optical networking platform that enables multiple network configurations.

XTERA filed a motion in the US Bankruptcy Court for the sale of substantially all its assets on November 15, 2016. The company had been struggling with liquidity problems for the last nine months, according to the filings that included a declaration in support of the Chapter 11 petition and, after exploring various alternatives, the company decided to pursue Chapter 11 and a post-petition marketing and sale process. The Nasdaq Stock Market announced that it will delist the common stock of XTERA, and the company’s stock was suspended on October 17, 2016 and has not traded on NASDAQ since that time.

This document highlights how KRIS default probabilities and related risk measures would have allowed investors to exit from a position in XTERA well before the default event of November 15.

The default probabilities produced by the KRIS service include both the best practice reduced form default probabilities and the older and less accurate Merton model default probabilities. In this note, we use the KRIS version 6.0 reduced form default probabilities, the newest and most accurate model in the KRIS default models framework.

The Kamakura riskiest companies’ list as on 15 November 2016, the day of the filing, lists XTERA at the 98th percentile of all listed companies in the United States, as evidenced below.

It is however, instructive to note the corresponding percentiles for different dates during 2016, as can be tabulated below:

It can be clearly seen from Figure 2 above that the liquidity crisis has impacted the shortest term in the term-structure of KDPs with the values moving from a very respectable 0.28% on 15 January 2016 to 28.47% on the day of Chapter XI filing, and 3 months before the filing, had risen to an alarming 18.64%. The other points on the term-structure are impacted by other factors including the stock price, which fell from a high of close to USD 6 to USD 0.06 as on filing. The stock price history can be analyzed in Figure 3 below.

Now, let us turn our attention to the details of the probabilities of default, the key creditworthiness assessment metric. Figure 4 below shows the history of the 1-month (in red), 1-year (in blue), 5-year (in orange), and 10-year (in green) default probabilities for XTERA on 15 November 2016:

In Kamakura Corporation’s popular troubled company index, a firm is considered “troubled” if its default probability exceeds one percent. The graph above shows that the 1-month default probability of XTERA gradually increased, and exceeded 40.00% in November 2016, consistent with the liquidity problems identified in the Chapter XI filing. However, it is illuminating to note that a full 10 months before this, the company was showing a deterioration in its creditworthiness, starting December 2015, where all four term structure points on the default curve moved up over 1%. For a fixed income investor, this is tremendous early warning, and highlights exit options well before a default event. This makes for particularly interesting reading in conjunction with the liquidity issues identified, as it is evident that even before the troubling news on the liquidity crunch were aired on November 15, the company was in troubled waters. Whilst the liquidity crisis outlined a specific short-term problem with the company, the Kamakura Default Probabilities showcased the increasing risk both on account of the changing market landscape and of deteriorating fundamentals.

It can be argued compellingly that the KDPs provided a portent of the writing on the wall, where the 1-month KDP tracked the liquidity crisis whilst the 5-year and 10-year KDPs identified a more structural problem.

Another important metric in KRIS is the cumulative default probability for the issuer. On January 15, 2016, the cumulative 10-year default probability for XTERA was an astronomical 19% (Figure 5). This metric was a warning signal provided by KRIS a full ten months before its eventual demise.

In June 2015, the ongoing liquidity issues were clearly identified in the cumulative term structure of KDPs (Figure 6). Since the issue pertained to liquidity, a short-term problem, the impact was emphasized in the one-month KPD rather than through the term structure, but the issues relating to deteriorating financials were impacting the overall structure of the KDPs.

Another indicator that is very valuable as an early warning signal is a comparison to the industry peer group, which in the case of XTERA is the Tech Hardware & Equipment peer group. It can be seen clearly in Figure 7 below that the company’s one-year default probability moved to well above the 90th percentile, and indeed much higher than 2 standard deviations above the median, in late 2015. This is another warning, more than a year before default, to exit from any holdings of XTERA.

Through 2016, this trend was maintained, and it was clear to any observer that the company was gradually moving from its already risky position close to the sector’s 75th percentile of riskiness to well over the 90th percentile.

A critical output from KRIS is the implied ratings framework, where a comparison is made of KDPs to their perceived implied ratings. A glance at this ratings table as of 18 January 2016, outlined as Figure 8, clearly indicates a forecast of deteriorating creditworthiness, and a 99% cumulative probability of the ratings careening to default.

As early warning indicators go, it does not get any clearer than this, where a full 6 months before this predicament came to pass, information in KRIS clearly outlined an exit strategy.

The KRIS default probability models are benchmarked on more than two million observations of firms of all types. The total number of defaults used in the current version 6.0 models is more than 2,600. The unparalleled volume of data and the research insights of Kamakura’s Managing Director Prof. Robert Jarrow make the KRIS default probability service the most accurate early warning credit risk assessment indicator framework available. That is one of the reasons why Credit Magazine named both KRIS and the Kamakura Risk Manager Software package “Innovations of the Year”. For more information about KRIS default probabilities, please contact your Kamakura representative or e-mail Kamakura’s credit experts at

Copyright ©2016 Suresh Sankaran