I estimate a dynamic term structure model on an unbalanced panel of Treasury coupon bonds, without relying on an interpolated zero-coupon yield curve. A linearity-generating model, which separates the parameters that govern the cross-sectional and time-series moments of the model, takes about 8 min to estimate on a sample of over 1 million bond prices. The traditional exponential affine model takes about 2 hr, because of a convexity term in coupon-bond prices that cannot be concentrated out of the cross-sectional likelihood. I quantify the on-the-run premium and a “notes versus bonds” premium from 1990 to 2017 in a single, easy-to-estimate no-arbitrage model. (JEL G12, G14, C33) Received: April 30, 2018; editorial decision November 3, 2020 by Editor Nikolai Roussanov

We price the risky component of specialness spreads—identified by their deviations from the expected auction cycle—within a dynamic term structure model estimated using daily prices of all outstanding Treasury securities and corresponding special collateral (SC) repo rates. This allows us to derive a time-varying SC risk premium that we quantitatively link to various price anomalies, such as the on-the-run premium. The SC risk premium explains about 80% of the on-the-run premium and a substantial share of other Treasury price anomalies, suggesting that unexpected fluctuations in the specialness spreads of recently issued nominal Treasury securities are a common risk factor.

We study capital requirement regulation in a dynamic quantitative model in which nonfinancial firms, as well as households, hold deposits. A novel general equilibrium channel that operates through firms deposits mitigates the cost of increasing capital requirements. In the calibrated model, (a) the optimal capital requirement is 7.3 percentage points higher than in a comparable model in which all the deposits are held by households, and (b) setting the capital requirement higher than the true optimum is not as costly as one would gauge from the comparable model. We also provide some independent evidence that supports our novel channel.

We analyze competition and risk management at central counterparties (CCPs) using a granular transaction-level dataset, and find that CCPs decrease collateral in response to lower collateral at their competitors, an effect that becomes stronger as the correlation between positions increases. To interpret our findings, we derive a model in which collateral is driven by risk and CCP competition. Our results are consistent with the model and suggest that a single monopolistic CCP would require more collateral. We also show that amid the substantial increase in collateral during the Covid-19 pandemic, the probability of a margin breach did not significantly change.