Corporate bonds are a key source of funding for US non-financial corporations and a key investment security for insurance companies, pension funds and mutual funds. Difficulties in the corporate bond market can therefore both hamper access to credit for corporate borrowers and reduce investment opportunities for key financial sub-sectors. In a February 2021 Economy of Liberty Street post, we introduced a unified measure of corporate bond market distress, the Corporate Bond Market Distress Index (CMDI), and then continued in early June 2022 by examining how the bond market works business evolved in 2022 following the Russian invasion of Ukraine and the tightening of US monetary policy. Today we are launching the CMDI as a regularly produced data series, with new readings to be released monthly. In this article, we describe what constitutes corporate bond market distress, motivate the construction of the CMDI, and argue that secondary market metrics alone are not enough to capture market functioning.
Market distress affects both primary and secondary markets
Judge Potter Stewart said “I know it when I see it” in the 1964 Jacobellis vs. Ohio Judgment of the Supreme Court. So what should policymakers pay attention to when determining if a market is in trouble? The Emergency Relief and Reconstruction Act 1932 states that, in order to provide support loans, that:
… the Federal Reserve Bank must obtain proof that this person, partnership or corporation is unable to obtain adequate credit facilities from other banking institutions.
Similarly, the BIS Market Committee points out that:
Market dysfunction can disrupt the flow of credit to the economy, thus impacting real activity and price stability and, therefore, the achievement of central banks’ monetary objectives.
In the context of debt capital markets, access to credit will be compromised in the event of a significant downturn in primary markets where credit flows from investors to businesses.
Primary markets, however, do not exist in isolation and secondary market conditions can affect the functioning of the primary market if, for example, underwriters face uncertain prospects for placing new issues. A well-functioning secondary market is one in which trades can take place quickly and with little impact on prices, the size of trading volume can be absorbed without undue influence on prices, execution is immediate and prices quickly return to “normal” levels after temporary order imbalances. An important feature of episodes of market distress – or “liquidity black holes” – is that large price swings alone are not enough to gauge market functioning, as large price swings may instead indicate a functioning market. smoothly incorporating new information quickly.
How do we recognize distress?
The descriptions above emphasize that market distress is multifaceted, and measures of any aspect of market functioning are likely to present an incomplete picture of distress. To construct the CMDI, we merge information on seven aspects of market functioning: primary market volumes, primary market prices, secondary market volumes, secondary market liquidity, secondary market prices, secondary market default-adjusted prices, and quoted prices on non-traded bonds. — using insights from the machine learning literature on image recognition and language processing to build a unified measure of market functioning. As described in the technical details in According to our report, the CMDI signals market distress as periods when measures of multiple aspects of market functioning signal distress, rather than when measures of individual characteristics of market distress are higher on average.
To understand the difference between these two concepts of merging information from multiple individual measurements, consider the following simple example. Suppose we only use bid-ask spreads and primary market volume. Which of the following two situations is the most painful?
- The bid-ask spread is in its historical upper tenth percentile, so market liquidity is low, while primary market volume is also in its upper tenth percentile, so the issue is still good .
- The bid-ask spread and issue volume are at their corresponding historical medians.
From the perspective of a single measure that averages the measures, the market distress is on the same level in both situations, because the average measure is at the center of the distribution in both cases. A metric that instead identifies distress as distress along a greater number of features will perceive the second situation as potentially more concerning because the bid-ask spread and issue volume provide conflicting signals in the first example. .
The graph below plots the time series of the CMDI with the first principal component (PCA) – a sophisticated way of averaging the measurements— the seven characteristics of market functioning underlying the CMDI. The chart shows that while both approaches correctly identify periods of extreme distress – when the average characteristic indicates distress and the plurality of metrics indicate distress – the CPA over-identifies market distress when market conditions are relatively calm. Our simple example illustrates this intuition: the averaging approach is more likely to be influenced by extreme observations of a given measurement. In the services report, we show that the CMDI is a better predictor of both future realizations of other measures of financial conditions and future realizations of real activity than the CPA, suggesting that the CMDI does indeed provide a “cleaner” signal of market distress.
The PCA approach over-identifies market distress during periods of relative calm
Why not just use secondary market metrics?
If distress in the secondary market coincides with or even precedes distress in the primary market, then credit flow measures may be superfluous in measuring market distress. The following chart plots the time series of monthly changes in the stock of corporate debt, along with two popular measures of secondary market stress: the excess bond premium (EBP) of Gilchrist and Zakrajšek (2012) and the swap on high quality credit default. – bond basis (CDS bond). The chart shows that at least simultaneously, none of these secondary market measures are related to changes in debt stock, so months with slowdowns in (net) bond issuance companies are rarely months with high EBP or months with large dislocations between companies. bond markets and CDS.
Secondary market metrics do not reflect primary market conditions
A “metrics preponderance” approach can be useful in a variety of applications
Overall, the staff report shows that adopting the “parameter dominance” approach to measuring corporate bond market distress produces an index that correctly identifies periods of market distress and predicts future realizations of commonly used measures of market distress. Although we focus on quantifying corporate bond market difficulties, the similarity-based approach to summarizing information about different aspects of business is potentially applicable in a variety of economic contexts, including measuring financial vulnerabilities and identification of recessions or financial crises, as described in a previous Economy of Liberty Street Publish.
Nina Boyarchenko is Head of Macrofinancial Studies in the Research and Statistics Group at the Federal Reserve Bank of New York.
Richard K. Crump is a Financial Research Advisor in Macrofinancial Studies in the Research and Statistics Group at the Federal Reserve Bank of New York.
Anna Kovner is Director of Financial Stability Policy Research in the Bank’s Research and Statistics Group.
Or Shachar is a Financial Research Economist in Capital Markets Studies in the Research and Statistics Group at the Federal Reserve Bank of New York.
How to cite this article:
Nina Boyarchenko, Richard Crump, Anna Kovner, and Or Shachar, “What Is Corporate Bond Market Distress?”, Federal Reserve Bank of New York Economy of Liberty StreetJune 29, 2022, https://libertystreeteconomics.newyorkfed.org/2022/06/what-is-corporate-bond-market-distress/.
Disclaimer
The opinions expressed in this article are those of the authors and do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the authors.