4. Empirical Results 40
4.4. The Reaction of European Stocks to Unconventional Monetary Policy 49
no evidence for a causal link between distress risk and size, value and momentum effects. After all, distress risk appears to contribute nothing to explaining stock returns. The excess returns in table 3 are probably explained by correlation of F-Scores with other characteristics, but the idea of a distress risk characteristic bringing order into the mess of characteristics-effects seems wrong.
Will there never be order in the cross-section of stocks? Should we perhaps even abandon the Fama & French (1995, 1996) distress story? A final verdict is deferred to section 5. At this point, it is worth recalling that common characteristics like size, book-to-market equity and momentum have a “catch all” nature. They are most likely collections of several different economic effects, which may very well amplify or cancel each other out. In spite of all efforts to reduce measurement error and arbitrariness, a distress characteristic like the F-Score may ultimately suffer from similar drawbacks. After all, default risk models are also only combinations of accounting and market information. In the end, it comes down to the question of what investors consider to be important. Is a slightly elevated F-Score (or any other default risk score) a considerable signal for distress risk or is the negative momentum (small size / high book-to-market ratio) that enters its computation a more important signal for something else? In most cases, it is unclear to what extent characteristics capture the macroeconomic processes which are decisive for the CCAPM/ICAPM mechanics. Firm characteristics have only in rare cases straightforward interpretations. We should probably not use them so extensively as explanatory variables for returns. Cochrane (2007) suggests to focus on the actual macroeconomic process instead. Following in this vein, instead of defining an elevated book-to-market ratio (or about any other characteristic) as an indicator for distress, we should perhaps ask which firms are especially exposed to tightening lending standards or try to identify industries in decline. Approaches like these are more straightforward because they acknowledge the concept of systematic risk more directly than conventional firm characteristics. Further recommendations for future research based on this thought are provided in section 5.
4.4. The Reaction of European Stocks to Unconventional
most important one among several of such transmission channels (Mishkin 1996, Bernanke & Gertler 1995, Ciccarelli et al. 2015).
Credit channels suggest expansionary monetary policy can reduce the agency prob-lem in financial markets. The theory of cyclical agency costs and its effect on the propensity of investors to finance risky firms has already been discussed above.
Bernanke et al. (1996) document a flight to safety in several credit markets and the first research paper suggests a similar effect takes place in the equity market. Mon-etary policy might counter these effects with expansionary actions. Specifically, central banks could be able to improve the balance sheets of credit-constrained firms as they commit to purchasing assets in several credit (and equity) markets.
Increasing bond (equity) prices will lower risk premia and ease funding conditions for these firms. Asset purchase programs are commonly called unconventional monetary policy. Recently, they have gained popularity among several major cen-tral banks. The fourth research paper asks whether credit channels are operative and central banks can indeed counter the flight to safety, which has been docu-mented in the first research paper. Specifically, the paper investigates the reactions of stocks and CDS in the entire cross-section of French, German, Italian and Span-ish firms in order to provide another perspective on the relation between distress risk and stock returns. It shifts the focus from the long-run back to the short-run.
The previous results suggest that, given the methodological framework at hand, more interesting economic conclusions can be drawn from this perspective. This has been the main motivation for the paper in the overall research context.
Like the first article, this paper makes use of the event study methodology. In contrast to firm specific rating events, the events of interest in this case are market-wide monetary shocks. Since all firms are at the same time affected by them, it is not sensible to apply the Fama et al. (1969) event study methodology outlined in section 3. Instead, the article applies several different methods to extract monetary policy shocks from interest rates (Kuttner 2001, Rogers et al. 2014) and uses these shocks as exogenous variables in time-series and panel regressions. The main research hypotheses test the effectiveness of the credit channel. In detail, they state that unconventional monetary policy shocks give rise to stronger increases (decreases) in stock prices (CDS spreads) when firms are distressed. According to the data, the opposite is true. It appears that firms with low distress risk show the strongest increases (decreases) in stock prices (CDS spreads) suggesting that unconventional monetary policy cannot counter the flight to safety. Investors do not regard these programs as beneficial for distressed firms.
Once more, the evidence underlines that the flight to safety is a powerful concept in financial markets. Not even central banks seem to be able to dissolve it. It is
50
worth recalling that this phenomenon is fully consistent with the idea of distress risk as an ICAPM state variable. Hence, in line with the findings of the first paper, the fourth paper shows the economic distress risk story is visible in the short-run.
Moreover, the paper points to a surprising short-run relation between interest rates and stock returns. Since the beginnings of the EMU, the response of the stock market to conventional interest rate shocks induced by ECB actions has had the same sign as the shock. A main rate decrease of the ECB has, on average, given rise to negative and not positive stock market reactions. These additional results, which stand in harsh contrast to economic intuition, cast doubts on the overall effectiveness of monetary policy in the EMU. Furthermore, this finding shows the potential of the current era of zero-interest rates to twist things up. Who thought a prolonged period of below zero interest rates would be possible ten years ago?
How do common empirical models fare with negative interest rates? We should routinely control for these unparalleled developments in empirical research.
5. Conclusion
The overriding goal of the thesis has been to assess whether firm distress risk can reconcile the empirical literature with conventional risk-based CCAPM/ICAPM explanations for stocks returns. The theory says risk averse investors should dis-count the value of firms because they dislike asset price risk that is correlated with consumption risk. Distress risk does plausibly create this correlation, for in-stance, when investors depend on labor income. Consequently, the average equity investor should be more reluctant to finance distressed firms than safe firms and she should be especially reluctant to do so when the economy is in a recession. The evidence points to strong cyclical relations between distress risk and stock returns in the short-run. Specifically, investors have a higher propensity to sell off stocks from issuers in the speculative grade rating segment after downgrades when the economy is in a recession. The motives behind this flight to safety appear to be strong. The ECB has recently found it necessary to counter these tendencies with a battery of unconventional monetary policy measures which are supposed to ease funding conditions for distressed firms. However, all this does not seem to affect the behavior of investors. All in all, the CCAPM/ICAPM mechanics are clearly visible in the short-run.
Does the discount on distressed firms give rise to a premium? Can distress risk also explain long-run average returns? Sadly, the results remain inconclusive in this regard. I have spent a lot of time and effort on developing and testing models to measure default risk in order to associate the information provided by these
models with long-run average stock returns. Default risk models are powerful in forecasting corporate defaults. They are an exciting topic on their own and of tremendous importance in practice. However, they seem to bear little consequences for the stock market. Conventional asset pricing tests suggest the relation between default risk scores and excess stock returns is insignificant in the German stock market. Moreover, distress risk cannot provide convincing explanations for other patterns in returns (value and momentum effects).
Why do we see strong reactions of stocks to news about distress in the short-run but no relation between distress risk and long-run average returns? There are two explanations for this. First of all, detecting short run reactions is, by nature, easier than establishing long-run relationships. Numerous factors influence stock returns over the course of a few months, whereas isolating effects in windows spanning a few days is less difficult. Second, conventional theory tells us systematic risk matters in the long-run. Default risk can be measured with very high accuracy, but it is likely that investors can diversify it away. Though corporate defaults follow a procyclical trend, the overall default rate does rarely exceed 4%. Even in such a worst case scenario, an investor who holds the market portfolio will not incur extreme losses from defaults. Losses will only be substantial if the value of all other surviving firms deteriorates, as well.
This brings us to the question whether the definition of distress that has been used in this thesis, the default event, nests this kind of distress risk. Defaults are perhaps too extreme and rare to pose a risk for the average firm. A different way to look at distress risk would be to identify situations when firms are not profitable enough to cover their obligations. Such definitions have already been used to investigate other issues (Andrade & Kaplan 1998, Whitaker 1999). I have experimented with models forecasting early distress instead of defaults, as well. By and large, the results were inconclusive, too. Altering the definition of distress in this fashion reduces the skew in the distribution of risk scores. More firms will be at risk.
However, to what extent is the resulting risk a distress risk and to what extent is it a common profitability risk? The relation between stock returns and the latter is, of course, trivial. The crux is that an informative risk characteristic (one that forecasts default) will always follow a skewed distribution with few firms at risk and many that remain totally unaffected. Defining a distress risk characteristic based on a less extreme definition runs into the danger of being ambiguous, which leads us back to where the empirical literature currently stands.
I conclude that measuring distress risk as a firm characteristic is inappropriate in asset pricing. Interesting alternatives for future research can be found in macroe-conomics. For example, the results presented by Hahn & Lee (2006) and Petkova
52
(2006) suggest that the default spread, the difference between risk-free and corpo-rate bonds, is correlated with the Fama & French risk factors in the US. Similarly, Boons (2016) finds the default spread forecasts credit crunches and exposure to this variable is priced in the cross-section of US stocks. In general, macroeco-nomics opens up natural ways to look at what we call systematic risk in finance.
We should recall the main reason for separating empirical finance from macroe-conomics was that macroeconomic data are typically low-frequency data and less convenient than return data in research. Alas, high availability of (stock) return data has lead to an unprecedented data-mining which is making it harder than ever to understand what explains average stock returns. Firm characteristics do not seem to take us anywhere. Macroeconomic time series are now much longer than they were when research on the cross-section of stocks began and a larger variety of data has become available. Cochrane (2007) says understanding the macroeco-nomic risk that drives asset prices is the trunk of the tree. I agree and suggest that future research should reinforce efforts to explain patterns in the cross-section of stock returns with macroeconomic distress risk.
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