Abstract
Among the many sources of risk explaining corporate bond spreads, the role of liquidity is the least well understood. This article investigates the impact of liquidity risk of unknown functional form on the yield spread over time. Heterogeneity is introduced via a latent group structure explaining differences in nonlinear liquidity effects across groups. A key feature of the model is that it can be estimated from highly unbalanced longitudinal data, allowing us to work with data at minimum levels of temporal aggregation. In an extensive empirical study we apply the suggested method to a large panel of trade data for U.S. corporate bonds. Our procedure identifies nonlinear liquidity effects for a large fraction of the securities. Nonlinearities become more pronounced as bond-idiosyncratic illiquidity increases. The classification clearly distinguishes groups differing, e.g., in bond characteristics such as spread levels and trading activity. While groups share similar dynamics of liquidity effects, their magnitudes as well as the interplay between idiosyncratic and market illiquidity are different across groups.
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