activity
20232026
most citedCovariance matrix filtering and portfolio optimisation: the Average Oracle vs Non-Linear Shrinkage and all the variants of DCC-NLS

2 citations · 3 across the 6 of their papers we have counts for

collaborators

6 papers

q-fin.MF2026

Optimal execution on Uniswap v2/v3 under transient price impact

Bastien Baude, Damien Challet, Ioane Muni Toke

We study the optimal liquidation of a large position on Uniswap v2 and Uniswap v3 in discrete time. The instantaneous price impact is derived from the AMM pricing rule. Transient i…

q-fin.RM2025

Noise-proofing Universal Portfolio Shrinkage

Paul Ruelloux, Christian Bongiorno, Damien Challet

We enhance the Universal Portfolio Shrinkage Approximator (UPSA) of Kelly et al. (2023) by making it more robust with respect to estimation noise and covariate shift. UPSA optimize…

q-fin.MF2025

Optimal risk-aware interest rates for decentralized lending protocols

Bastien Baude, Damien Challet, Ioane Muni Toke

Interest rates in decentralized lending protocols are set algorithmically and adjust to supply and demand for liquidity. In this study, we propose an optimal interest rate model th…

q-fin.TR2024

Consistent time travel for realistic interactions with historical data: reinforcement learning for market making

Vincent Ragel, Damien Challet

Reinforcement learning works best when the impact of the agent's actions on its environment can be perfectly simulated or fully appraised from available data. Some systems are howe…

q-fin.TR2024★ 1 cited

Equity auction dynamics: latent liquidity models with activity acceleration

Mohammed Salek, Damien Challet, Ioane Muni Toke

Equity auctions display several distinctive characteristics in contrast to continuous trading. As the auction time approaches, the rate of events accelerates causing a substantial…

q-fin.ST2023★ 2 cited

Covariance matrix filtering and portfolio optimisation: the Average Oracle vs Non-Linear Shrinkage and all the variants of DCC-NLS

Christian Bongiorno, Damien Challet

The Average Oracle, a simple and very fast covariance filtering method, is shown to yield superior Sharpe ratios than the current state-of-the-art (and complex) methods, Dynamic Co…