Adrien d´Avernas

This paper provides a general model of stablecoins, cryptocurrencies pegged to a traditional currency. We characterize the optimal design of a stablecoin protocol that generates seigniorage fees from issuance. We use this framework to assess the ability of various protocol designs to maintain the peg. Our model rationalizes algorithmic backing of stablecoins but highlights its greater fragility relative to collateralization. Immutable smart contracts improve stability because the issuer suffers from a commitment problem. Even under full collateralization, promises to repurchase stablecoins when demand drops are not credible. Alternatively, the protocol can restore commitment by decentralizing issuance, and this highlights a new benefit of DeFi protocols.

This paper proposes a new model of monetary policy implementation to account for two key developments: (i) the introduction of intraday liquidity requirements and (ii) the decreasing relevance of the federal funds market in favor of repurchase agreement (repo) markets with nonbank participants. Our paper studies how liquidity requirements prevent banks from arbitraging between the fed funds and repo markets and generate large repo spikes. We propose a simple measure of excess intraday reserves. Consistent with our theory, this metric is close to zero in 2019Q2, when U.S. repo markets experienced a spike of 400 basis points.

We use machine learning to examine the predictability of hold-to-maturity returns on single stock options. In sharp contrast to the implications of standard asset pricing theory, we find that the expected return of the underlying stock fails to forecast option returns, but does explain cross-sectional variation in option prices. Option trading strategies based on the underlying's expected stock return deliver anomalously low returns. These findings challenge canonical option pricing models and suggest that options are not a suitable instrument to harvest stock risk premia.

We provide a simple model of investment by a firm funded with debt and equity and empirical evidence to demonstrate that, once we control for the debt overhang problem with credit spreads, asset volatility is an unambiguously positive signal for investment, while equity volatility sends a mixed signal: Elevated volatility raises the option value of equity and increases investment for financially sound firms, but exacerbates debt overhang and decreases investment for firms close to default. Our study provides a simple unified understanding of the structural and empirical relationships between investment, credit spreads, equity versus asset volatility, leverage, and Tobin's .

We propose a model of post-Great Financial Crisis (GFC) money markets and monetary policy implementation. In our framework, capital regulation may deter banks from intermediating liquidity derived from holding reserves to shadow banks. Consequently, money markets can be segmented, and the scarcity of Treasury bills available to shadow banks is the main driver of short-term spreads. In this regime, open market operations have an inverse effect on net liquidity provision when swapping ample reserves for scarce T-bills or repos. Our model quantitatively accounts for post-2010 time series for repo rates, T-bill yields, and the Fed's reverse repo facility usage.

This work proposes a framework to study the risk-benefit trade-off of quantitative easing (QE) for the consolidated government, integrating the central bank and treasury department. In a simple model with distortionary taxes, nominal frictions, and a zero lower bound, we characterize the optimal size of a QE program as equalizing the marginal benefit from stimulating output to the marginal cost of induced rollover risk for taxpayers. A conservative quantification of this trade-off suggests that QE programs in the US made a positive net present contribution to welfare.

This paper presents a dynamic asset pricing model of Treasury bonds with banks subject to both capital and liquidity requirements. Capital requirements and households’ preference for money-like assets push non-banks to be the primary holders of Treasuries, thereby exposing Treasury yields to funding shocks originating in repo markets. When holding sufficient reserves, banks mitigate those shocks by lending in repo when the funding supply tightens. When reserves are scarce, banks stop lending. Repo rates and Treasury yields spike up to reflect those funding imbalances. Our model highlights the key role of both sides of the central bank's balance sheet as well as agents' anticipation about the duration of shocks and policy intervention in explaining observed Treasury market disruptions.

We provide a parsimonious model and extensive empirical evidence supporting the idea that much of the variation in deposit-pricing behavior across large vs. small banks reflects differences in ``preferences and technologies''. Large banks offer superior liquidity services, but lower deposit rates, and locate where customers value their services. In addition to receiving a lower level of deposit rates on average, customers of large banks exhibit lower demand elasticities with respect to deposit rate spreads. As a result, despite the fact that the locations of large-bank branches have demographics typically associated with greater financial sophistication, large-bank customers earn lower average deposit rates. Our explanation for deposit pricing behavior challenges the idea that deposit pricing is mainly driven by pricing power derived from the large observed degree of concentration in the banking industry.

The deposit business differs at large versus small banks. We provide a parsimonious model and extensive empirical evidence supporting the idea that much of the variation in deposit-pricing behavior between large and small banks reflects differences in "preferences and technologies." Large banks offer superior liquidity services but lower deposit rates, and locate where customers value their services. In addition to receiving a lower level of deposit rates on average, customers of large banks exhibit lower demand elasticities with respect to deposit rate spreads. As a result, despite the fact that the locations of large-bank branches have demographics typically associated with greater financial sophistication, large-bank customers earn lower average deposit rates. Our explanation for deposit pricing behavior challenges the idea that deposit pricing is mainly driven by pricing power derived from the large observed degree of concentration in the banking industry.

This paper provides a general framework for analyzing the stability of stablecoins, cryptocurrencies pegged to a traditional currency. We study the problem of a monopolist platform that can earn seigniorage revenues from issuing stablecoins. We characterize stablecoin issuance-redemption and pegging dynamics under various degrees of commitment to policies. Even under full commitment, the stablecoin peg is vulnerable to large demand shocks. Backing stablecoins with collateral helps to stabilize the platform but is costly for the platform’s equity (token) holders. Combined with collateral, decentralization can act as a substitute for commitment.