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Joshua Mollner

dblp:209/5841 · DBLP profile ↗
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2ranked-venue papers
0as first author
1since 2021 · last 2023
0000-0002-4785-4834ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Theory of computation · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1

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.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Computational finance and economics · 100%

Topics — the 1 heaviest of 1, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational finance and economics
market microstructure
0.712023
Principal Trading Arrangements: Optimality under Temporary and Permanent Price Impact · EC 2023

Methods — techniques the papers use, named apart from their topics

stochastic control · 0.7principal-agent model · 0.7
YearPublicationVenuePosition
2023 Principal Trading Arrangements: Optimality under Temporary and Permanent Price Impact
abstract
We study the optimal execution problem in a principal-agent setting. A client (e.g., a pension fund, endowment, or other institution) contracts to purchase a large position from a dealer at a future point in time. In the interim, the dealer acquires the position from the market, choosing how to divide his trading across time. Price impact may have temporary and permanent components. There is hidden action in that the client cannot directly dictate the dealer's trades. Rather, she chooses a contract with the goal of minimizing her expected payment, given the price process and an understanding of the dealer's incentives. Many contracts used in practice prescribe a payment equal to some weighted average of the market prices within the execution window. We explicitly characterize the optimal such weights: they are symmetric and generally U-shaped over time. This U-shape is strengthened by permanent price impact and weakened by both temporary price impact and dealer risk aversion. In contrast, the first-best solution (which reduces to a classical optimal execution problem) is invariant to these parameters. Back-of-the-envelope calculations suggest that switching to our optimal contract could save clients billions of dollars per year.
Markus Baldauf, Christoph Frei, Joshua Mollner
EC3
2017 Approximate Efficiency in Matching Markets
Nicole Immorlica, Brendan Lucier, E. Glen Weyl, Joshua Mollner
WINE4