We examine whether the concern about insurers selling similar assets due to an overlap in holdings is justified. We measure this overlap using cosine similarity and find that insurers with more similar portfolios have larger subsequent common sales. When faced with a shock to assets or liabilities, exposed insurers with greater portfolio similarity have larger common sales that impact prices. Our portfolio similarity measure can be used by regulators to predict the common selling of any institution that reports security or asset class holdings, making the measure a useful ex ante predictor of divestment behavior in times of market stress.

We document the phenomenon that average excess returns of out-of-the-money puts and calls on bond futures are negative, both unconditionally and conditionally on economic states. To explain these findings, we develop economically motivated restrictions in the context of a theory in which the pricing kernel is a general diffusion process with spanned and unspanned components. Our reconciliation is a framework that introduces market incompleteness and priced unspanned volatility risks, allowing for time-varying downside and upside futures risk premiums. The estimated model shows consistency with data on bond yields, yield volatilities, bond futures return volatilities, option prices, and option risk premiums.

We exploit the 2020 Treasury market shock to analyze how external and internal constraints impact arbitrageurs. Using regulatory filings, we find that hedge funds reduced arbitrage activities and increased cash holdings, despite stable credit and low contemporaneous redemptions. Creditors’ regulatory and liquidity constraints were not propagated to hedge funds through repo—Treasury arbitrageurs’ predominant financing source. Fund-creditor borrowing data reveal more regulated dealers provided, and more important clients received, disproportionately higher funding. Value-at-risk reported by funds suggests internal risk constraints were binding. Our results support theoretical predictions that arbitrageur risk constraints and precautionary liquidity management can amplify market instability even when contemporaneous financing remains resilient.

We study brokerage platform outages to examine the impact of retail investors on financial markets. We contrast outages at Robinhood, which caters to inexperienced investors, with outages at traditional retail brokers. For stocks with high retail interest, we find that negative shocks to Robinhood investor participation are associated with reduced market order imbalances, increased market liquidity, and lower return volatility, whereas the opposite relations hold following outages at traditional retail brokerages. The findings suggest that herding by inexperienced investors can create inventory risks that harm liquidity in stocks with high retail interest, while other retail trading improves market quality.

We represent risk factors as sums of orthogonal components capturing fluctuations with cycles of different length. The representation leads to novel spectral factor models in which systematic risk is allowed—without being forced—to vary across frequencies. Frequency-specific systematic risk is captured by a notion of spectral beta. We show that traditional factor models restrict the spectral betas to be constant across frequencies. The restriction can hide horizon-specific pricing effects that spectral factor models are designed to reveal. We illustrate how the methods may lead to economically meaningful dimensionality reduction in the factor space.