by Tajinder Dhillon.
When 178-year-old British travel company Thomas Cook failed on Sept. 23, 2019, thousands of travelers were covered by Air Travel Organizers’ Licensing (ATOL), an insurance plan that covered people who purchased package holidays and flights. In addition, the British Civil Aviation Authority executed the largest peacetime repatriation in the nation’s history, bringing back home 150,000 Britons.
Investors, of course, were not so fortunate. The safe arrival of their capital is not protected. However, there were indicators before the company’s collapse that rough weather was ahead.
StarMine by Refinitiv offers a range of alpha-generating stock selection models in addition to a suite of Credit Risk models designed to detect default and bankruptcy risk over a 12-month period. Focusing on the latter would have given investors an early indication that troubles were on the rise for Thomas Cook. Our Combined Credit Risk model is a multi-pronged approach which combines our three stand-alone credit models: SmartRatios Model, Structural Model, and Text Mining model.
Each model is designed to give a unique perspective of credit risk. For example, SmartRatios analyzes financial ratios to determine profitability, leverage, coverage, liquidity, and growth and stability. Our text mining model uses machine learning and natural language processing to measure corporate financial health by quantitatively analyzing text from rich sources including Reuters News, StreetEvents conference call transcripts, corporate filings (10-K, 10-Q, and 8-K) and select research documents.
The Combined Credit Risk model was highly predictive of default/bankruptcy risk for Thomas Cook as shown in Exhibit 1. Having the lowest model ranking possible (a score of 1) in addition to the lowest decile ranking across all three credit risk models is a worrying sign. A low score in SmartRatios indicates low liquidity and high leverage, among other factors, which directly impacted Thomas Cook’s inability to raise funds for creditor demands. With a 26.51% probability of default, our StarMine Implied Rating gives Thomas Cook a “CC” rating, the lowest possible in our mapping table. We can compare the Implied Rating to traditional agencies such as S&P and Moody’s.
Exhibit 1: StarMine Combined Credit Risk model for Thomas Cook
In the graph above, the gold line is the share price of Thomas Cook, the green line is S&P’s rating, and finally, the blue line is the StarMine Implied Rating. In September 2018, the blue line (StarMine Implied Rating) starts to aggressively downgrade Thomas Cook six times from a “B+” to “CC” within 60 days. The green line (S&P agency) remains standstill at a B+ during this same time and initiated the first downgrade in the first quarter of 2019. Leading to the final days of Thomas Cook we can see that the green line matches the blue line. The punch line is that in this example, StarMine provided a signal to investors of possible default/bankruptcy risk one year in advance compared to traditional rating agencies.
If we also observe the Credit Default Swap (CDS) market, premiums for Thomas Cook did not start to materially increase until May 2019, which indicates that the market perhaps was mispricing these instruments.
The Text Mining model, a text-based analysis of company risk, scans thousands of documents across News, StreetEvents, Filings, and Research to detect words and “bag of words” which indicate credit risk. Thomas Cook announced profit warnings in September 2018 in addition to the CFO’s resignation, which was announced by Reuters News. Exhibit 2 showcases how stories such as these contributed to the heightened credit risk.
Exhibit 2: StarMine Text Mining model for Thomas Cook
Moving away from risk and onto alpha, a company that has its shares decline over a sustained period implies that the share price will continue to decline according to the momentum factor. The Price Momentum model looks at three distinct periods (Long-Term, Mid-Term, and Short-Term) to assess momentum. It makes intuitive sense that the model generates a low score of 7 for Thomas Cook in Exhibit 3, given the secular decline in share price over the last year. The model also highlights the performance of Thomas Cook’s industry peers who have seen their shares rise on average by 5.6%, a complimentary signal that share prices of Thomas Cook are likely to decline further (for illustrative purposes, we are assuming the market was not aware of the eventual administration). The Short-Term component is a reversal indicator designed for entry/exit points (i.e., “buy the dip”) which is reason for a component score of 100. In this example, the term ‘don’t try to catch a falling knife’ comes to mind.
Exhibit 3: Price Momentum model for Thomas Cook
When a company sees its share price decline rapidly, it is plausible that it will look “cheap” on a valuation basis. The StarMine Relative Valuation model identifies companies that are cheap or expensive by looking at six fundamental ratios: earnings/price, cash flow/price, EBITDA/EV, sales/EV, book/price and dividends/price (the inverse is used to deal with negative values). Exhibit 4 gives Thomas Cook a Relative Valuation score of 96 in developed Europe and a score of 100 among its U.K. industry peers. This provides a signal that the company is cheap on a valuation basis compared to its peers. For example, Thomas Cook’s forward 12-month P/E ratio of 0.8x meant that you pay £0.80 for every £1 of current earnings, compared to a 14.0x multiple of its industry peers.
Exhibit 4: Relative Valuation model for Thomas Cook
The model also provides a growth table to the reader to ensure they aren’t falling into a “value trap”: a company is cheap, but for good reason. Five-year historical revenue growth is flat at 0.6% compared to a median industry growth rate of 7.6%. Had Thomas Cook reported annual earnings, it is likely they would have experienced negative year-over-year growth of 4.1%.
The purpose of this article is not to name and shame a company. Rather, we highlight the value StarMine brings to the investment-decision making process, providing alpha-generating opportunities for investors while being able quickly to spot red flags, thus enhancing risk management.