Using structural credit risk models to estimate default dependence requires estimates of correlations of changes in distance-to-default. We present a structural model that yields simple relations between asset value, distance-to-default, and CDS spreads, allowing the correlations to be estimated from CDS spreads. We generalize the model to include a randomly varying default boundary; in this version the distance-to-default dynamics also depend on the movement of the default boundary. The CDS spread correlations we estimate exceed equity correlations, consistent with a randomly varying default boundary. We also present evidence that variations in funding liquidity affect the correlations, consistent with recent models. (JEL G13, G23)

This paper uses a novel dataset of commodity-linked notes (CLNs) to examine the impact of the flows of financial investors on commodity futures prices. Investor flows into and out of CLNs are passed to and withdrawn from the futures markets via issuers' trades to hedge their CLN liabilities. The flows are not based on information about futures price movements but nonetheless cause increases and decreases in commodity futures prices when they are passed through to and withdrawn from the futures markets. These finding are consistent with the hypothesis that non-information-based financial investments have important impacts on commodity prices.

This paper uses a novel dataset of commodity-linked notes (CLNs) to examine the impact of the flows of financial investors on commodity futures prices. Investor flows into and out of CLNs are passed to and withdrawn from the futures markets via issuers' trades to hedge their CLN liabilities. The flows are not based on information about futures price movements but nonetheless cause increases and decreases in commodity futures prices when they are passed through to and withdrawn from the futures markets. These finding are consistent with the hypothesis that non-information-based financial investments have important impacts on commodity prices.