July 2022

Accuracy Talks Straight #5 – The Academic Insight

Philippe Raimbourg
Director of the Ecole de Management de la Sorbonne (Université Panthéon-Sorbonne)
Affiliate professor at ESCP Business School

The dynamics of corporate credit spreads

The analysis of credit spread dynamics largely relates to the analysis of financial ratings and their impact on the quoted prices of debt securities.

This issue has been documented regularly for over 50 years and has led to numerous statistical studies. For the most part, these studies are consistent and highlight the different reactions of investors to cases of downgrading and upgrading. Observing the quoted prices of debt securities highlights the financial market’s expectation for downgrading, with quoted prices trending significantly downwards several trading days before the downgrade itself. On the agency’s announcement date, the market’s reactions are small in scale. By contrast, upgrades are hardly ever anticipated, with debt security holders particularly vigilant so as not to incur capital losses as a result of a downgrade. It is worth noting that because of the limited maturity of the debt securities, buying orders are structurally higher than selling orders; as a result, the latter are more easily seen as signals of mistrust by the market.

More recent studies have focused on the impact of rating changes on the volatility and liquidity of securities. Downgrades are preceded by an increase in volatility and a wider bid-ask spread, demonstrating a fall in liquidity; uncertainty as to the credit risk of the security in question leads to different reactions from investors and disparate valuations. Publishing the rating effectively homogenises investor perceptions, reduces volatility and increases liquidity. The effects are not so clear-cut when upgrading because, with the change to the rating being unanticipated, the effect of perception homogenisation is weaker and counterbalanced by the desire of some investors to profit from the improved credit quality to make speculative gains.

These studies shed new light on the question of the utility of rating agencies. The agencies effectively send information to investors, but perhaps not to all of them. Indeed, informed investors may outpace the agencies in the monitoring of the issuers’ credit quality. However, less informed investors need the opinion of the agency to be certain that the observed decrease in prices effectively corresponds to a downgrade in credit quality. The agency’s announcement removes all disparity of perception between investors and highlights the utility of the agency, which stabilises prices and increases liquidity. The dynamics of credit spreads cannot be studied separately from those of other marketable securities. After all, the debt world is not cut off from the equity world, something that we can easily understand through intuition alone. A fall in share prices is generally the result of operational difficulties leading to a reduction in operating cash flows and lower coverage of remuneration expenses and debt repayments. In parallel, this lower share value means an increase in financial leverage and, at a given volatility of the rate of return on assets, an increase in the volatility of the rate of return on equity. A reduction in the share price, an increase in financial leverage and a rise in the share price volatility and credit risk therefore all combine. From a theoretical point of view, Robert Merton was the first to express the credit spread as a function of the share price. We will not cover his work here. We will instead look into the credit-equity relationship as it is frequently used in the finance industry. Indeed, typically a power function denominated on growth rates is used for this purpose.

CDSt / CDSREF = [ SREF / St ] α

The credit spread growth rate, measured by the CDS, is therefore a function of the rate of decline of the share price modulo a power α that we assume to be positive, where REF serves as a basis for calculating the rate of change of the CDS and the share.

Knowledge of the parameter α makes it possible to specify this relationship fully. We first note that, as defined by the preceding equation, α is the opposite of the elasticity of the CDS value compared with the share value. By taking the logarithm of this equation, we get:

Ln [CDSt / CDSREF] = – α Ln [ St / SREF ]

α = – Ln [CDSt / CDSREF] / Ln [ St / SREF ]

A ratio of two relative growth rates, the α parameter is indeed, to the nearest sign, the elasticity of the CDS value compared with the share value that we can also write as:

α = – [S/CDS] [δCDS / δS]

By expressing the derivative of the CDS value in relation to the share value [δCDS / δS], we are led to the following value of the α parameter:

α = 1 + l avec l = D/(S+D)

The debt and equity worlds are therefore closely related: an inverse relationship links credit spreads and share prices; this relationship is heavily dependent on the financial structure of the company and its leverage calculated in relation to the balance sheet total (S+D). The higher this leverage, the more any potential underperformance in share price will lead to significant increases in the credit spread.

From an empirical perspective, though this correlation appears relatively low when the markets are calm, it is very high when the markets are volatile. When the leverage is low, the graph representing the development of credit spreads (in ordinates) in relation to share prices highlights a relatively linear relationship close to horizontal; however, when leverage is much higher, a highly convex line appears.

With this relationship established, we can now question the sense behind it, or, if we prefer, ask what the lead market is. To do so, it is necessary to undertake credit market and equity market co-integration tests, and that the arbitrageurs will be responsible for making the long-term equilibrium in these two markets consistent.

To this end, two series of econometric tests are conducted symmetrically. The first series aims to explain the changes in share prices by those in CDS, whether delayed or not by several periods, and vice versa as regards changes in the value of CDS, in the latter case incorporating changes in financial leverage. These relationships, tested over the period 2008–2020 for 220 listed securities on the S&P 500 index, bring to light the following results:

– There are information channels between the listed equity segment and the CDS market. These information channels concern all businesses, no matter their sector or their level of debt: ‘informed’ traders, because of the existence of financial leverage, make decisions just as much on the equity market as on the credit market.

– In the majority of cases (two thirds of companies reviewed), the lead market is the equity market whose developments determine around 70% of the developments in the CDS market.

– However, in the case of companies with significant leverage, the price discovery process starts with the CDS market, which explains more than 50% of price variations. This empirical work is evidence, if any were needed, of the importance of the structural credit risk model proposed by the Nobel laureate Robert Merton in 1974.


Lovo, S., Raimbourg Ph., Salvadè F. (2022), ‘Credit Rating Agencies, Information Asymmetry, and US Bond Liquidity’, Journal of Business, Finance and Accounting, https://doi. org/10.1111/jbfa.12610

Zimmermann, P. (2015), ‘Revisiting the Credit-Equity Power Relationship’, The Journal of Fixed Income, 24, 3, 77-87.

Zimmermann, P. (2021), ‘The Role of the Leverage Effect in the Price Discovery Process of Credit Markets’, Journal of Economic Dynamics and Control, 122, 104033.

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