Knowledge that Transforms

The Society for Financial Studies (SFS) is a global, nonprofit academic society in finance. It owns and runs three academic journals: (1) the Review of Asset Pricing Studies, (2) the Review of Corporate Finance Studies, and (3) the Review of Financial Studies. It also organizes two annual academic conferences: (1) the SFS Cavalcade Asia-Pacific and (2) the SFS Cavalcade North America. It also runs several smaller, specialized conferences and financially supports and co-sponsors other independent conferences. Its governing board is the SFS Council. SFS holds an annual membership meeting in May every year. At that meeting the SFS President, Executive Editors, Cavalcade Chair, and Secretary-Treasurer report on SFS activities. This year, for the first time, we have written up those reports and integrated them into this annual report of the Society for Financial Studies, which will be published in all three SFS journals. The reasons for doing this are to share this information more broadly with SFS members and friends and to create a permanent record for the long run (that is, institutional memory).

Risk-neutral distributions of the S&P 500 are informative about the COVID-19 pandemic beyond what one can learn from index values and the market fear gauge of the VIX alone. We learn that, on February 20, 2020, the index did not yet reflect the impending crisis. Only on March 16, 2020, was the full impact visible, with a pronounced bimodality for longer-maturity options revealing a sizeable crash scenario. The corresponding physical distribution is more symmetric and features a high-volatility crash scenario. Firms bought crash protection ahead of the index crash, whereas retail customers bought it as the index was already recovering.

Standard finite horizon tests uncover only weak evidence of the predictive power of the real exchange rate for excess currency returns. On the other hand, in long-horizon tests, the real exchange rate strongly and negatively predicts future excess currency returns. Conversely, we can attribute most of the variability in real exchange rates to changes in currency risk premiums. The “habit” and “long-run risks” models replicate the predictive power of the real exchange rate for excess currency returns, but substantially overstate the fraction of the volatility of the real exchange rate due to risk premiums. Received December 14, 2017; Editorial decision October 14, 2018 by Editor: Raman Uppal.

We use party-identifying language—like “liberal media” and “MAGA”—to identify Republican users on the investor social platform StockTwits. Using a difference-in-difference design, we find that partisan Republicans remain relatively unfazed in their beliefs about equities during the COVID-19 pandemic, while other users become considerably more pessimistic. In cross-sectional tests, we find Republicans become relatively more optimistic about stocks that suffered the most during the COVID-19 crisis, but more pessimistic about Chinese stocks. Finally, stocks with the greatest partisan disagreement on StockTwits have significantly more trading in the broader market, explaining 28% of the increase in stock turnover during the pandemic.

We find that a business-cycle component of the aggregate dividend yield strongly predicts short-term aggregate dividend growth and consumption growth, whereas its low-frequency counterpart significantly forecasts long-horizon market returns. The dividend yield—the sum of these two components—has difficulty revealing variations in expected cash flow growth, because its low-frequency component tends to disguise such variations. Yet the low-frequency component has significant forecasting power for multiperiod returns at horizons of several years to as long as around 20 years, which is longer than the horizons typically exploited in prior studies that provide weak statistical evidence to challenge multiperiod return predictability.

We analyze the dynamics of earnings forecasts and discount rates implicit in valuations during the COVID-19 crisis. Forecasts over 2020 earnings have been progressively reduced by 16%. Longer-run forecasts have reacted much less. We estimate an implicit discount rate going from 8.5% in mid-February to 11% at the end of March and reverting to its initial level in mid-May. Over the period, the unlevered asset risk premium increases by 50bp, the leverage effect also increases by 50bp, while the risk free rate decreases by 100bp. Hence, analysts’ forecast revisions explain all of the decrease in equity values between January 2020 and mid-May 2020.

Exploiting a unique identification strategy based on inaccurate news analytics, we document an effect of news analytics on the market independent of the informational content of the news. We show that news analytics speed up the stock price and trading volume response to articles, but reduce liquidity. Inaccurate news analytics lead to small price distortions that are corrected quickly. The market impact of news analytics is greatest for press releases, as news analytics exhibit a particular skill in “seeing through” the positive spin of press releases. Furthermore, we provide evidence that high-frequency traders rely on the information from news analytics for directional trading on company-specific news. Received: May 17, 2018; Editorial decision: June 14, 2019 by Editor: Thierry Foucault.

Using the first reported case of COVID-19 in a given U.S. county as the event day, we find that firms headquartered in an affected county experience, on average, a 27-bps lower return in the 10-day post-event window. This negative effect nearly doubles in magnitude for firms in counties with a higher infection rate (−50 bps). We test a number of transmission channels. Firms belonging to labor-intensive industries and those located in counties with a large mobility decline have worse stock performance. Firms sensitive to COVID-19-induced uncertainty also exhibit more negative returns. Finally, more negative stock returns are associated with downward revisions in earnings forecasts.

This is the first paper to examine how the COVID-19 shock transmitted from the asset markets to capital markets. Using a novel measure of the exposure of commercial real estate (CRE) portfolios to the increase in the number of COVID-19 cases (GeoCOVID), we find a one-standard-deviation increase in GeoCOVID on day t-1 is associated with a 0.24 to 0.93 percentage points decrease in abnormal returns over 1- to 3-day windows. There is substantial variation across property types. Local and state policy interventions helped to moderate the negative return impact of GeoCOVID. However, there is little evidence that reopenings affected the performance of CRE markets.

We use data from aggregate stock and dividend futures markets to quantify how investors’ expectations about economic growth evolved across horizons following the outbreak of the novel coronavirus (COVID-19) and subsequent policy responses until July 2020. Dividend futures, which are claims to dividends on the aggregate stock market in a particular year, can be used to directly compute a lower bound on growth expectations across maturities or to estimate expected growth using a forecasting model. We show how the actual forecast and the bound evolve over time. As of July 20th, our forecast of annual growth in dividends points to a decline of 8% in both the United States and Japan and a 14% decline in the European Union compared to January 1. Our forecast of GDP growth points to a decline of 2% in the United States and Japan and 3% in the European Union. The lower bound on the change in expected dividends is -17% in the United States and Japan and -28% in the European Union at the 2-year horizon. News about U.S. monetary policy and the fiscal stimulus bill around March 24 boosted the stock market and long-term growth but did little to increase short-term growth expectations. Expected dividend growth has improved since April 1 in all geographies.