Sergei Glebkin

Assistant Professor of Finance,

Working Papers

Funding Constraints and Informational Efficiency (with Naveen Gondhi & John Kuong), R&R RFS

We develop a tractable rational expectations model that allows for general price-dependent portfolio constraints and study a setting where constraints arise because of margin requirements. 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. This information spiral implies that risk premium, return volatility, and Sharpe ratio may rise significantly as investors' wealth declines.

Liquidity vs. Information Efficiency

I analyze a market with large and small traders with different values. I show that illiquidity and information efficiency are complements. Policy measures promoting liquidity might be harmful for information efficiency and vice versa. An increase in risk-bearing capacity may harm liquidity. An increase in the precision of information may harm information efficiency. Increasing market power or breaking up a centralized market into two separate exchanges might improve welfare. Multiple equilibria, in which higher liquidity is associated with lower information efficiency, are possible. Applied to crude oil market the model highlights (1) informational frictions and (2) market power of producers amplified by (1) as possible drivers of recent sharp price changes.

Strategic Trading without Normality

I present a model of strategic trading a la Kyle (1989) that does not require the assumption of normally distributed asset payoffs. I propose a constructive solution method: finding the equilibrium reduces to solving a linear ordinary differential equation. With non-normal payoffs, the price response becomes an asymmetric, non-linear function of order size: greater for buys than sells and concave (convex) for small sell (buy) orders when asset payoffs are positively skewed; concave for large sell (buy) orders when payoffs are bounded below (above). The model can speak to key empirical findings and provides new predictions concerning the shape of price impact.

A Model of Request for Quote Systems in OTC Markets (with Ji Shen and Bart Zhou Yueshen)

The “Request-for-Quote” (RFQ) system has become a major trading protocol in over-the-counter markets. It allows traders to contact multiple counterparties for prices at the same time. Through a dynamic model, this paper examines the features and implications of RFQ. In equilibrium, the contacted traders strategically quote prices via a mixed-strategy, due to the endogenous uncertainty of competitor types. The model yields testable predictions about price distribution, quote response rate, and their dynamics both in steady state and in transition. Compared to a bilateral-bargain setting, RFQ leads to more efficient allocation but, with low search friction, traders may refrain from using it.

Old Working Papers

Capital Market Equilibrium with Competition Among Institutional Investors (with Dmitry Makarov)

We develop a dynamic general equilibrium model to study how competition among institutional investors affects the stock market characteristics - level, expected return, and volatility. We consider an economy in which multiple fund managers strategically interact with each other, as each manager tries to increase her performance relative to the others. We fully characterize an equilibrium in this economy, and find that a more intense competition is associated with a higher level of the market, lower expected market return, while market volatility is not affected by competition. These findings are broadly consistent with the data.