In practice, heterogeneously informed speculators combine private information about multiple stocks with information in prices, taking into account how their trades influence the inferences of other speculators via prices. We show how this speculation causes prices to be more correlated than asset fundamentals, raising price volatility. The covariance structure of asset fundamentals drives that of prices, while the covariance structure of liquidity trade drives that of order flows. We characterize how speculator profits vary with the distributions of information and liquidity trade across assets and speculators, and relate the cross‐asset factor structure of order flows to that of returns.

We examine a decentralized monetary economy in which households can use a means of exchange (barter or gold) other than fiat money. The alternative means of exchange may drive out money even if monetary exchange Pareto dominates. Legal restrictions prohibiting other means of exchange may therefore be necessary. With stochastic preferences, households may use barter to supplement monetary purchases when they have an unexpectedly high demand. However, this may drive down the value of money (in all states) so low that households are again better off with fiat money alone. The paper provides both stochastic and nonstochastic examples in which eliminating markets for goods or assets that compete with fiat money improves welfare.

This paper develops a test for herding in forecasts by professional financial analysts that is robust to (a) correlated information amongst analysts; (b) common unforecasted industry-wide earnings shocks; (c) information arrival over the forecasting cycle; (d) the possibility that the earnings that analysts forecast differ from what the econometrician observes; and (e) systematic optimism or pessimism among analysts. We find that forecasts are biased, but that analysts do not herd. Instead, analysts “anti-herd”: Analysts systematically issue biased contrarian forecasts that overshoot the publicly-available consensus forecast in the direction of their private information.

We investigate the susceptibility of democracies to demagogues, studying tensions between representatives who guard voters’ long-run interests and demagogues who cater to voters’ short-run desires. Parties propose consumption and investment. Voters base choices on current-period consumption and valence shocks. Younger/poorer economies and economically disadvantaged voters are attracted to the demagogue’s disinvestment policies, forcing farsighted representatives to mimic them. This electoral competition can destroy democracy: if capital falls below a critical level, a death spiral ensues with capital stocks falling thereafter. We identify when economic development mitigates this risk and characterize how the death-spiral risk declines as capital grows large.

We estimate the dynamics of recommendations by financial analysts, uncovering the determinants of inertia in their recommendations. We provide overwhelming evidence that analysts revise recommendations reluctantly, introducing frictions to avoid frequent revisions. More generally, we characterize the sources underlying the infrequent revisions that analysts make. Publicly available data matter far less for explaining recommendation dynamics than do the recommendation frictions and the long‐lived information that analysts acquire but the econometrician does not observe. Estimates suggest that analysts structure recommendations strategically to generate a profitable order flow from retail traders. We provide extensive evidence that our model describes how investors believe analysts make recommendations, and that investors value private information revealed by analysts' recommendations.

Amihud’s stock (il)liquidity measure averages daily ratios of the absolute close-to-close return to dollar volume, including overnight returns. Our modified measure uses open-to-close returns matching return and trading volume measurement windows. It is more strongly correlated with trading-cost measures (by 8%–37%) and better explains cross-sections of returns, doubling estimated liquidity premiums. Using nonsynchronous trading near close, we show overnight returns are primarily information driven: including them in Amihud’s proxy for price impacts of trading magnifies measurement error, understating liquidity premiums. Our modification helps wherever Amihud’s measure is required. Our measures are publicly available for 1964–2019 and can be updated. (JEL G12, G14) Received June 2, 2020; editorial decision September 11, 2020 by Editor Jeffrey Pontiff.

Dramatic microstructure changes in equity markets have made standard liquidity measures less accurate proxies for trading costs. We develop trade-time liquidity measures that reflect per-dollar price impacts of fixed-dollar volumes. Our measures better capture institutional trading costs and better explain the cross-section of returns than do standard measures, especially in recent years. Despite improvements in measures of market quality, expected trading costs have explanatory power for the cross-section of expected returns: we obtain monthly liquidity premium estimates of 5.3 bp for expected returns and 2.4 bp for risk-adjusted returns. Estimated premiums rise after the financial crisis and remain high thereafter.

We endogenize entry to a security-bid auction, where participation is costly and bidders must decide given their private valuations whether to participate. We first consider any minimum reserve security-bid of a fixed expected value that weakly exceeds the asset's value when retained by the seller. DeMarzo, Kremer, and Skrzypacz (2005) establish that with a fixed number of bidders, auctions with steeper securities yield the seller more revenues. Counterintuitively, we find that auctions with steeper securities also attract more entry, further enhancing the revenues from such auctions. We then establish that with optimal reserve securities, auctions with steeper securities always yield higher expected revenues.

Order flow segmentation prevents direct interactions between U.S. retail and institutional investors. Using the imbalance in observable internalized retail trades, we show wholesalers use retail flow to provide liquidity to institutional investors, especially when liquidity is scarce. Our institutional liquidity cost ( $ ILC $ ) measures average absolute retail trade imbalances, positing that institutions holding stocks with greater such averages more often resort to the expensive wholesaler-provided liquidity. $ ILC $ is correlated with expected institutional price impacts. Unlike existing illiquidity measures, $ ILC $ has economically meaningful relations with institutional holding horizons and yields annualized liquidity premia of 2.7%–3.2% post-2010, even after excluding microcap stocks.