Issuer Quality and Corporate Bond Returns

By Robin Greenwood, S. G. Hanson. 2013

298 citations recorded by the source corpus.

Changes in the pricing of credit risk disproportionately affect the debt financing costs faced by low credit quality firms. As a result, time-series variation in the average quality of debt issuers may be useful for forecasting excess corporate bond returns. We show that when issuance comes disproportionately from lower quality borrowers, future excess returns on high yield and investment grade bonds are low and often significantly negative. The degree of predictability is large in both economic and statistical terms, with univariate R2 statistics as high as 30% at a 3-year horizon. The results are difficult to reconcile with integrated-markets models in which the rationally determined price of risk fluctuates in a countercyclical fashion. The results can be partially explained by models in which shocks to intermediary capital or agency problems drive variation in required returns. Finally, we consider models in which investor over-extrapolation plays a role and find some evidence in favor of these models.

Subfields: Finance

View Paper: https://www.semanticscholar.org/paper/d5e000ea634db4056c42e80e6cca52a9d8bc0e84

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Citations in the corpus

Do Managers Overreact to Salient Risks? Evidence from Hurricane Strikes (2017, background): “Initially propelled by Minksy (1977) and Kindleberger (1978), this literature conjectures that in good times, agents tend to extrapolate the current state of the world as if it would last forever (e.g., Cheng et al., 2014; Greenwood and Hanson, 2013, 2015; Greenwood and Shleifer, 2014).”
The Term Structure of Growth-at-Risk (2018, unknown): “In addition, lower risk premia may be associated with exuberant sentiment, and Greenwood and Hanson (2013) show that periods of compressed risk premia can be expected to be followed by a reversal of valuations.”
Why Does Fast Loan Growth Predict Poor Performance for Banks (2018, unknown): “Greenwood and Hanson (2015) explain waves in ship prices by combining competition neglect and extrapolative expectations.”
Psychology-based Models of Asset Prices and Trading Volume (2018, background): “Finally, Greenwood and Hanson (2015) argue that a type of bounded rationality called competition neglect contributes to over-extrapolation of fundamentals.”
Psychology and the Financial Crisis of 2007-2008 (2011, background): “Another belief-based theory of overvaluation argues that bubbles arise because investors extrapolate past outcomes – returns, earnings growth, or default rates -- too far into the future (Lakonishok, Shleifer, Vishny, 1994; Barberis, Shleifer, Vishny, 1998; Greenwood and Hanson, 2010). This assumpti”
Climate Change News Risk and Corporate Bond Returns (2020, unknown): “Following Greenwood and Hanson (2013), we control for the leverage ratio (LEVERAGE), which is the sum of long-term debt, short-term debt, minority interest, and preferred stock, scaled by total assets.”
Predictable Financial Crises (2020, background): “…credit as a share of total credit, and narrow credit spreads all predict financial fragility and deteriorating macroeconomic outcomes (see also Greenwood and Hanson (2013), Baron and Xiong (2017), Lopez-Salido, Stein, and Zakrajšek (2017), Mian, Sufi, and Verner (2017), Krishnamurthy and Muir…”
Monetary Policy, Financial Conditions, and Financial Stability (2014, unknown): “In addition, others have shown that easing of monetary policy tends to reduce credit risk premiums on corporate bonds (Gertler and Karadi 2013; Greenwood and Hanson 2013; Gilchrist, López-Salido, and Zakraǰsek 2015).”
Overreaction in Macroeconomic Expectations (2018, unknown): “…the cross section of stock returns (La Porta 1996, Bordalo, Gennaioli, La Porta, and Shleifer 2019, henceforth BGLS), credit spreads (Greenwood and Hanson 2013, Bordalo, Gennaioli, and Shleifer 2018), short-term interest rates (Cieslak 2018), and corporate earnings (DeBondt and Thaler 1990,…”
How Does Credit Supply Expansion Affect the Real Economy? The Productive Capacity and Household Demand Channels (2020, unknown): “8 percentage points between (1)See for example, Reinhart and Rogoff (2009), Jordà et al. (2013), Krishnamurthy and Muir (2017), Mian et al. (2017), Baron and Xiong (2017), and López-Salido et al.”
Credit-Market Sentiment and the Business Cycle (2017, unknown): “All of this is closely consistent with the results reported in Greenwood and Hanson (2013). Turning to the upper panel of Table 2, column (1) shows that this approach yields an estimate of the impact of ∆ŝt on ∆yt that is strongly statistically significant and, if anything, larger (in absolute terms”
Banks as patient fixed-income investors (2014, background): “Interestingly, there was a thriving original issue high-yield bond market in the first several decades of the 20th century, many decades before Michael Milken (Greenwood and Hanson, 2013).”