Vyacheslav Fos

Carroll School of Management
Boston College
140 Commonwealth Avenue
Fulton Hall 330
Chestnut Hill, MA 02467

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Institutional Affiliation: Boston College

NBER Working Papers and Publications

December 2016Activism, Strategic Trading, and Liquidity
with Kerry Back, Pierre Collin-Dufresne, Tao Li, Alexander Ljungqvist: w22893
We analyze dynamic trading by an activist investor who can expend costly effort to affect firm value. We obtain the equilibrium in closed form for a general activism technology, including both binary and continuous outcomes. Variation in parameters can produce either positive or negative relations between market liquidity and economic efficiency, depending on the activism technology and model parameters. Two results that contrast with the previous literature are that (a) the relation between market liquidity and economic efficiency is independent of the activist's initial stake for a broad set of activism technologies and (b) an increase in noise trading can reduce market liquidity, because it increases uncertainty about the activist's trades (the activist trades in the opposite direction ...

Published: Kerry Back & Pierre Collin‐Dufresne & Vyacheslav Fos & Tao Li & Alexander Ljungqvist, 2018. "Activism, Strategic Trading, and Liquidity," Econometrica, Econometric Society, vol. 86(4), pages 1431-1463, July. citation courtesy of

November 2013Moral Hazard, Informed Trading, and Stock Prices
with Pierre Collin-Dufresne: w19619
We analyze a model of informed trading where an activist shareholder accumulates shares in an anonymous market and then expends costly effort to increase the firm value. We find that equilibrium prices are affected by the position accumulated by the activist, because the level of effort undertaken is increasing in the size of his acquired position. In equilibrium, price impact has two components: one due to asymmetric information (as in the seminal Kyle (1985) model) and one due to moral hazard (a new source of illiquidity). Price impact is higher the more severe the moral hazard problem, which corresponds to a more productive activist. We thus obtain a trade-off: with more noise trading (less `price efficiency') the activist can build up a larger stake, which leads to more effort expend...
October 2012Do prices reveal the presence of informed trading?
with Pierre Collin-Dufresne: w18452
Using a comprehensive sample of trades by Schedule 13D filers, who possess valuable private information when they accumulate stocks of targeted companies, this paper studies whether several liquidity measures reveal the presence of informed trading. The evidence suggests that when Schedule 13D filers trade aggressively, both high-frequency and low-frequency measures of stock liquidity indicate a higher stock liquidity. Importantly, measures that have been used as direct proxies for adverse selection, such the Kyle (1985) lambda, the Easley et al. (1996) pin measure, and the Amihud (2002) illiquidity measure, suggest that the adverse selection is lower when informed trading takes place. The evidence is consistent with informed traders being more aggressive when measured stock liquidity is h...

Published: Do Prices Reveal the Presence of Informed Trading? PIERRE COLLIN-DUFRESNE andVYACHESLAV FOS† Article first published online: 23 JUL 2015 DOI: 10.1111/jofi.12260 The Journal of Finance Volume 70, Issue 4, pages 1555–1582, August 2015

Insider Trading, Stochastic Liquidity and Equilibrium Prices
with Pierre Collin-Dufresne: w18451
We extend Kyle's (1985) model of insider trading to the case where liquidity provided by noise traders follows a general stochastic process. Even though the level of noise trading volatility is observable, in equilibrium, measured price impact is stochastic. If noise trading volatility is mean-reverting, then the equilibrium price follows a multivariate 'stochastic bridge' process, which displays stochastic volatility. This is because insiders choose to optimally wait to trade more aggressively when noise trading activity is higher. In equilibrium, market makers anticipate this, and adjust prices accordingly. More private information is revealed when volatility is higher. In time series, insiders trade more aggressively, when measured price impact is lower. Therefore, execution costs to ...
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