Sergei Glebkin

Assistant Professor of Finance,

Working Papers

Funding Constraints and Information Efficiency (draft coming soon) (with Naveen Gondhi and John Kuong)

We develop a tractable REE model with general portfolio constraints. In application, we study the effect of endogenous margin constraints on information efficiency and identify a novel amplification mechanism. A small negative wealth shock tightens margin constraint which reduces incentives to acquire information. Prices become less informationally efficient and more volatile. Higher price volatility increases margins, further reducing information acquisition incentives and information efficiency. This information spiral exacerbates the effect of wealth shocks on price informativeness, risk premium and volatility. Our model uncovers a new, information-based rationale why the equity capital of investors is important and derive some testable empirical implications.

A Model of Request for Quote Systems in OTC Markets (draft coming soon) (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.

Liquidity vs. Information Efficiency (new version coming soon)

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 (new version coming soon)

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.

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.

Work in progress

Uncertainty and Equilibrium in Supply Function Games (with Marzena J. Rostek and Ji Hee Yoon)