Determinants of Short-Term Corporate Yield Spreads: Evidence from the Commercial Paper Market
Jing-Zhi Huang, Bibo Liu, Zhan Shi
Review of Finance, Volume 27, Issue 2, March 2023, Pages 539–579, https://doi.org/10.1093/rof/rfac030
What drives short-term credit spreads is a very important question in credit markets, especially given the role played by short-term corporate debt in the global financial crisis. However, in spite of a large literature on the determinants of credit spreads in general, the empirical literature on short-term spreads is very limited, perhaps because of data limitations.
In this paper, we shed light on the determinants of short-term corporate credit spreads from at least three new perspectives. First, we employ a novel data set of secondary market transactions in Chinese commercial paper over the period May 2014 to December 2020. This market has four unique features that make it particularly suitable for addressing the main question of this study: (1) Secondary market transactions account for 78% of total daily transaction volumes in this market, compared with less than 10% in the US market. This feature makes it possible to implement transaction-based liquidity measures for the commercial paper market. (2) The Chinese commercial paper issuers are heterogeneous in terms of creditworthiness, whereas almost all commercial paper issuers in the US are large, well-capitalized firms. (3) commercial paper in China tends to have a much longer maturity than commercial paper in the US. For instance, the average maturity is about 248 days for Chinese commercial paper and about 45 days for the US in our sample. (4) Longer-term corporate debts and commercial paper are traded in the same market; as such, commercial paper in China can be viewed as exactly equivalent to short-term corporate bonds.
Second, we quantify liquidity and default risk components in short-term spreads using the structural approach to credit risk modeling. In particular, we propose and implement a jump-diffusion structural model that incorporates corporate debt market illiquidity and therefore is particularly suitable for modeling commercial paper spreads. The model is essentially a simplified He and Xiong (2012) model augmented with a double-exponential jump component in the underlying asset return process, albeit without rollover risk. Importantly, the model-implied corporate yield spreads can be decomposed into a diffusion credit component, a jump credit component, and a liquidity component.
Third, we show that liquidity is much more important than credit risk in determining commercial paper spreads in China (see Figure). For instance, our model-based decomposition results show that, on average, credit risk and market liquidity account for about 25% and 52% of commercial paper yield spreads, respectively. Moreover, based on a more recent sample of commercial paper issues and more recently developed liquidity measures, we find similar results in the US commercial paper market over the period May 2014 to April 2020.
Overall, this paper provides a comprehensive study on the determinants of short-term credit spreads using security level data in both the Chinese and the US commercial paper markets. We find that there is a credit spread puzzle (à la Huang and Huang 2012) in both markets. Market liquidity, however, shows much greater importance than credit risk in explaining these commercial paper spreads and therefore helps mitigate the puzzle.
Figure 1: Mean and Median of Predicted Commercial Paper Yield Spreads in China
This figure plots the mean and median of commercial paper yield spreads by rating category. The five bars in each rating category, in turn, represent yield spreads in the data (blue) and those generated by our proposed structural model ? the He-Xiong model with double-exponential jumps (HX-J in green) ? and its three special cases. The latter include the Black and Cox (1976) model (orange), the double-exponential jump-diffusion (DEJD) model (yellow), and a simplified He and Xiong (2012) model (HX in purple). Note that the Black-Cox median spread is virtually zero for all rating groups. The sample period spans from May 2014 to December 2020.