We determine the optimal lifecycle purchasing strategy for deferred income annuities (DIAs)—which are distinct from single-premium income annuities (SPIAs)—for an individual who wishes to maximize the expected utility of his/her annuity income at a fixed time in the future. In contrast to the vast portfolio-choice literature for SPIAs, we focus on the stochasticity of the DIA’s payout yield and address concerns that rates are currently “too low” to justify irreversible annuitization. We assume a mean-reverting model for payout yields and show that a risk-neutral consumer who wishes to maximize his/her expected retirement income should wait until yields reach a threshold—which lies above historical averages—and then purchase the DIA in one lump sum. In contrast, a risk-averse consumer who is concerned the payout yield will remain below average for an extended period and worries about losing mortality credits while waiting, should employ a barrier purchasing strategy, as in the portfolio choice problem under transaction costs. We illustrate how this insight is applied in the context of annuitization. In fact, the optimal behavior of a risk-averse consumer resembles an asymmetric dollar-cost averaging strategy, with a portion of the DIA-budget spent even while payout rates are below historical averages. As part of our analysis we offer an easy-to-use asymptotic approximation for the optimal purchasing strategy (threshold) and provide some numerical examples to illustrate the concept.

We find that higher stock lending fees predict significantly lower future returns after controlling for shorting demand for US stocks during the period 2007–10. These results suggest that active institutional investors on the supply side play an important role in the return predictability of fees and they not only respond to demand but also price in additional information around earnings news announcements. Overall, we find evidence that stock lenders are informed and, together with short sellers, contribute to the price discovery process.

This paper shows that a New Year's gambling preference of individual investors impacts prices and returns of assets with lottery features. January call options, especially the out-of-the-money calls, have higher retail demand and are the most expensive and actively traded. Lottery-type stocks outperform their counterparts in January but tend to underperform in other months. Retail sentiment is more bullish in lottery-type stocks in January than in other months. Furthermore, lottery-type Chinese stocks outperform in the Chinese New Year's Month but not in January. This New Year effect provides new insights into the broad phenomena related to the January effect.

We use our survey of finance professors from universities across the USA to investigate whether men and women react differently to prior gains and losses. We find that after incurring a loss, a large fraction of men continue to invest in stocks, but a majority of women tend to avoid investing in stocks. Even though prior losses increase the expectation of unfavorable market conditions, we find that women are more likely than men to expect unfavorable market conditions irrespective of whether they have made a gain or a loss in their prior stock market investments.

The 2020 CARES Act directed large cash payments to households. We analyze households’ spending responses using data from a Fintech nonprofit, exploring heterogeneity by income, recent income declines, and liquidity as well as linked survey responses about economic expectations. Households respond rapidly to payments, with spending increasing by about $0.14 per dollar during the first week and plateauing around 0.25–0.30 over 3 months. In contrast to previous stimulus programs, we see little response of durables spending. Households with lower incomes, greater income declines, and less liquidity display stronger responses whereas households that expect employment losses and benefit cuts display weaker responses.

This article provides a comprehensive history of default risk for newly originated home mortgages in the USA over the past quarter century. The loan-level source data include the entire guarantee book for Fannie Mae and Freddie Mac. We track many loan characteristics and produce a summary measure of risk. Among our many results, we show that mortgage risk had already risen in the 1990s, planting seeds of the financial crisis well before the actual event. Our results also cast doubt on explanations of the crisis that focus on borrowers with low credit scores. The aggregate series are available for download at https://www.fhfa.gov/papers/wp1902.aspx.