In this article, we examine the extent to which firm fundamentals can explain the cross-sectional variation in credit default swap (CDS) spreads. We construct a fundamental CDS valuation by combining the Merton distance-to-default measure with a long list of firm fundamentals via a Bayesian shrinkage method. Regressing CDS quotes against the fundamental valuation cross-sectionally generates an average R 2 of 77%. The explanatory power is stable over time and robust in out-of-sample tests. Deviations between market quotes and the valuation predict future market movements. The results highlight the important role played by firm fundamentals in differentiating the credit spreads of different firms.

We study information substitutability in the financial market through a quasi-natural experiment: the pandemictriggered lockdown that has hampered people's physical interactions hence the ability to collect, process, and transmit interaction-based information. Exploiting the cross-sectional and time-series variations of lockdown and its implications on proximate investment, we investigate how the difficulty of collecting information through physical interactions has prompted a switch to electronic interactions including synchronous interactions such as virtual meetings and asynchronous ones like collecting information from the internet. We show that local-investing funds (LIFs) that mostly relied on physical interactions to access information before the pandemic had even worse performance than other funds, though the difference in performance was insignificant before the lockdown. Moreover, LIFs rebalance portfolios toward faraway stocks due to portfolio diversification and risk reduction. These findings indicate that physical-interaction-based and electronic-based information is not fully substitutable. We also show that the advantages of human-interaction-based information originate mainly from physical contacts, primarily in cafés, restaurants, bars, and fitness centers; and the virtual world based on Zoom/Skype/Team can provide a buffer but cannot substitute personal meetings in generating sufficient information.

The finance industry has grown, financial markets have become more liquid, information technology has been revolutionized. But have financial market prices become more informative? We derive a welfare-based measure of price informativeness: the predicted variation of future cash flows from current market prices. Since 1960, price informativeness has increased at longer horizons (three to five years). The increase is concentrated among firms with greater institutional ownership and share turnover, firms with options trading, and growth firms. Prices have also become a stronger predictor of investment, and investment a stronger predictor of cash flows. These findings suggest increased revelatory price efficiency.

Reduced-form models of default that attribute a large fraction of credit spreads to compensation for credit-event risk typically preclude the most plausible economic justification for such risk to be priced, namely, a contemporaneous drop in the market portfolio. When this "contagion" channel is introduced within a general equilibrium framework for an economy comprising a large number of firms, credit-event risk premia have an upper bound of a few basis points, and are dwarfed by the contagion premium. We provide empirical evidence that indicates credit-event risk premia are less than 1 bp, but contagion risk premia are significant.

We provide time-series and cross-sectional evidence on the significance of a risk-return tradeoff in the bond and equity markets. We find a significantly positive intertemporal relation between expected return and risk in the bond market. We also propose novel measures of systematic and idiosyncratic risk for individual corporate bonds and find a significantly positive cross-sectional relation between systematic risk and expected bond returns, whereas there is no significant link between idiosyncratic risk and future bond returns. We provide an explanation for the significance of systematic (idiosyncratic) risk based on different investor preferences and informational frictions in the bond (equity) market.

We revisit Feldhütter and Schaefer (FS, 2018), who report evidence of a “credit spread puzzle” for high-yield but not investment-grade bonds. We show their results are reversed when their model is calibrated to market values of debt (as required by theory) rather than book values. We then demonstrate that using credit spreads rather than historical default rates to identify the default boundary provides the statistical power necessary to reject their assumption that firm dynamics follow geometric Brownian motion. A large market price of jump risk is required to match historical default rates, which generates a credit spread puzzle for investment-grade but not high-yield bonds.

Benchmark models that exogenously specify equity dynamics cannot explain the large spread in prices between put options written on individual banks and options written on the bank index during the financial crisis. However, theory requires that asset dynamics be specified exogenously and that endogenously determined equity dynamics exhibit a “leverage effect” that increases put prices by fattening the left tail of the distribution. The leverage effect is larger for puts on individual stocks than for puts on the index, thus increasing the basket-index spread. Time-series and cross-sectional variation in the leverage effect explains option prices well.

We identify the unique role of the government bond lending market in collateral transformation during periods of market stress. Using a novel database, we provide evidence that safe assets in the lending market have higher demand, higher borrowing cost, and higher usage of noncash collateral relative to nonsafe assets during stressed market conditions. Moreover, we find that market participants are able to obtain safe assets using relatively low-quality noncash collateral, allowing for collateral transformation. We show that policy interventions by central banks can help reduce safe-asset shortages by returning sought-after safe assets to the market.

This paper constructs a liquidity mismatch index (LMI) to gauge the mismatch between the market liquidity of assets and the funding liquidity of liabilities, for 2,882 bank holding companies over 2002 to 2014. The aggregate LMI decreases from +$4 trillion precrisis to −$6 trillion in 2008. We conduct an LMI stress test revealing the fragility of the banking system in early 2007. Moreover, LMI predicts a bank's stock market crash probability and borrowing decisions from the government during the financial crisis. The LMI is therefore informative about both individual bank liquidity and the liquidity risk of the entire banking system.