Dynamic Dispersed Information and the Credit Spread Puzzle

We develop a dynamic nonlinear, noisy REE model of credit risk pricing un- der dispersed information that can theoretically and quantitatively account for the credit spread puzzle. The first contribution is a sharp analytical characteri- zation of the dynamic REE equilibrium and its comparative statics. Second, we show that the nonlinearity of the bond payoff in the environment with dispersed information and limits to arbitrage leads to underpricing of corporate debt and to spreads that over-state the probability of default. This underpricing is most pronounced for high investment grade, short maturity bonds. Third, we calibrate to the empirical data on the belief dispersion and show that the model generates spreads that explain between 16 to 42% of the empirical values for 4-year high investment grade, and 35 to 46% for 10-year, high investment grade bonds. These magnitudes are in line with empirical estimates linking bond spreads to empirical measures of investor disagreement, and substantially higher than most structural models of credit risk. The primary contribution of our paper in moving NREE models towards a more realistic asset pricing environment – dynamic, nonlinear, and quantitative – that holds significant promise for explaining empirical asset pricing puzzles.