Demo Data from EDBT 2026 / reviewers in the wild / expert
Mikhail Panov
dblp:147/5860
· DBLP profile ↗
2ranked-venue papers
1as first author
1since 2021 · last 2023
0000-0001-5832-8277ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 1 first-author · 1 since 2021Theory of computation · 2 · 1 first-author · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Theoretical computer science
2 papers |
Algorithmic game theory and mechanism design · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Algorithmic game theory and mechanism design › solution concepts in games › equilibrium concepts
subgame perfect equilibrium |
0.7 | 1 | 2023 | Agreements of Continuous-Time Games · EC 2023 |
Algorithmic game theory and mechanism design
stochastic games |
0.2 | 1 | 2023 | Agreements of Continuous-Time Games · EC 2023 |
Algorithmic game theory and mechanism design › market dynamics
market microstructure |
0.2 | 1 | 2014 | Strategic trading in informationally complex environments · EC 2014 |
Methods — techniques the papers use, named apart from their topics
game theory · 0.7equilibrium formalization · 0.7kyle model · 0.2equilibrium analysis · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Agreements of Continuous-Time GamesabstractI propose a formalization of pure-strategy subgame perfect equilibria in general continuous-time games. The main idea is to formulate self-enforcing agreements corresponding to a strategic interaction directly, without setting up a whole extensive-form game. My method allows for non-Markov players' behavior, and it does not impose restrictions on players' strategies. The method applies to a broad class of games, including stochastic games, in which arbitrarily many players can have both observable and hidden actions. In many cases, my approach produces tractable and explicit solutions. Mikhail Panov |
EC | 1 |
| 2014 | Strategic trading in informationally complex environmentsabstractWe study trading behavior and the properties of prices in informationally complex markets. Our model is based on the single-period version of the linear-normal framework of [Kyle 1985]. We allow for essentially arbitrary correlations among the random variables involved in the model: the true value of the traded asset, the signals of strategic traders, the signals of competitive market makers, and the demand coming from liquidity traders. We first show that there always exists a unique linear equilibrium, characterize it analytically, and illustrate its properties in a series of examples. We then use this equilibrium characterization to study the informational efficiency of prices as the number of strategic traders becomes large. If the demand from liquidity traders is uncorrelated with the true value of the asset or is positively correlated with it (conditional on other signals), then prices in large markets aggregate all available information. If, however, the demand from liquidity traders is negatively correlated with the true value of the asset, then prices in large markets aggregate all available information except that contained in liquidity demand. Nicolas S. Lambert, Michael Ostrovsky, Mikhail Panov |
EC | 3 |