We analyze a tractable rational expectations equilibrium model with margin constraints. We argue that constraints affect and are affected by informational efficiency, leading to a novel amplification mechanism. A decline in wealth tightens constraints and reduces investors’ incentive to acquire information, lowering price informativeness. Lower informativeness, in turn, increases the risk borne by financiers who fund trades, leading them to further tighten constraints faced by investors. This information spiral leads to (i) significant increases in risk premium and return volatility in crises, when investors’ wealth declines, (ii) complementarities in information acquisition in crises, and (iii) complementarities in margin requirements.

This paper studies simultaneous multilateral search (SMS) in over-the-counter (OTC) markets: when searching, an investor contacts several potential counterparties and then trades with the one offering the best quote. Search intensity (how frequently one can search) and search capacity (how many potential counterparties one can contact) affect market qualities differently. Contrasting SMS to bilateral bargaining (BB), the model shows that investors might favor BB over SMS if search intensity is high or in distress. Such preference for BB hurts allocative efficiency and suggests an intrinsic hindrance in the adoption of all-to-all and request-for-quote type of electronic trading in OTC markets.

We characterize the unique equilibrium in an economy populated by strategic CARA investors who trade multiple risky assets with arbitrarily distributed payoffs. We use our explicit solution to study the joint behaviour of illiquidity of option contracts and show that, contrary to the conventional wisdom, option bid-ask spreads may decrease in risk aversion, physical variance, and open interest but increase after earnings announcements. All these predictions are confirmed empirically using a large panel dataset of US stock options.

We consider a market where large investors do not only trade on information about asset fundamentals. When they trade more aggressively, the price becomes less informative. Other investors who learn from prices, in turn, are less concerned about adverse selection and provide more liquidity, causing large investors to trade even more aggressively. This trading complementarity can engender three unconventional results: i) increased competition among large investors makes all investors worse off, ii) more precise private information reduces price informativeness, creating complementarities in information acquisition, and iii) multiple equilibria emerge. Our results have implications for competition and transparency policies in financial markets.

We study how wealth inequality affects market quality—specifically, liquidity and information efficiency. To this end, we introduce CHILE, an asset-pricing framework with asymmetric information, general utility functions, and arbitrary payoffs. It features a large economy (LE) with continuous-and-heterogeneous information (CHI). Making the rich richer and the poor poorer reduces information efficiency but improves liquidity. Making the rich more informed and the poor less informed has the same effect. With endogenous information, richer agents acquire more information, reinforcing the above outcomes. Overall, widening wealth inequality is a double-edged sword for market quality, increasing liquidity but harming information efficiency.

We develop a tractable model to study how asset concentration among a few large investors impacts asset prices and liquidity. Consistent with existing empirical evidence: (i) greater concentration is associated with higher volatility and returns, and (ii) large investors' turnover share is smaller than their proportion of total wealth. Surprisingly, higher concentration enhances liquidity, aligning with our new empirical findings. We show that increased concentration can benefit all investors in sufficiently non-competitive markets. We link the wedge between competitive and non-competitive outcomes to the Herfindahl-Hirschman Index measuring wealth concentration. The wedge can remain positive even in large markets.

We analyze asset prices and liquidity in an economy with large investors and many risky assets. The model allows for general investors' preferences and distributions of asset payoffs. We propose a constructive solution approach: solving for equilibrium reduces to solving nonlinear first-order ODE. We show that the equilibrium is unique under mild restrictions on payoffs and preferences. Liquidity risk is priced in equilibrium, leading to deviations from the consumption-CAPM. In stark contrast to a constant absolute risk aversion (CARA) benchmark, in a model with wealth effects, we obtain (1) illiquidity of risk-free assets (such as, e.g., Treasuries); (2) illiquidity contagion (a sell-off in one asset may have a price impact on assets with unrelated fundamentals) and asymmetry in cross-asset price impacts; (3) market liquidity may decrease in the number of traders and their wealth; and (4) in the presence of liquidity shortage, price impact may become negative giving rise to an illiquidity premium in asset prices; (5) safe assets are more illiquid because they have a larger price impact. In the presence of wealth heterogeneity, large traders trade more but also reduce their demands more. As a group, they account for a smaller fraction of orders compared to small investors. Fatter-tailed wealth distribution makes markets less liquid.

We study joint price formation in the dealer-to-dealer (D2D) and dealer-to-customer (D2C) segments of the foreign exchange (FX) market, both theoretically and empirically. Our theory accounts for dealer heterogeneity, market power, and non-exclusive customer-dealer relationship and shows that several statistics of the cross-section of D2C quotes help predict D2D prices and liquidity. In particular, D2D prices are negatively related to cross-sectional covariance between D2C mid-quotes and spreads, contrary to predictions of other theories of two-tiered markets. Our predictions are confirmed empirically using unique proprietary D2C data. Model calibration reveals and quantifies the FX market’s inelasticity and non-competitiveness.