Agent's optimization in unique-contract principal-agent problem with adverse selection is recast as stochastic target problem, enabling principal's objective as stochastic optimal control with partial information and state constraints.
Dynamic trading with predictable returns and transaction costs.Journal of Finance, 68(6):2309–2340
3 Pith papers cite this work. Polarity classification is still indexing.
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Introduces a protocol scoring AI investment advisors on validity under constraints, stability, and agreement with a deterministic baseline, showing agreement often masks invalid actions.
This work derives risk-constrained static and asymmetric dynamic collateral control rules for DeFi spot-perpetual basis trading, validated via Monte Carlo simulations and historical backtests showing dependence on funding environments.
citing papers explorer
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Principal-agent problems with adverse selection: A stochastic target problem formulation
Agent's optimization in unique-contract principal-agent problem with adverse selection is recast as stochastic target problem, enabling principal's objective as stochastic optimal control with partial information and state constraints.
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Auditing AI Investment Recommendations as Executable Actions
Introduces a protocol scoring AI investment advisors on validity under constraints, stability, and agreement with a deterministic baseline, showing agreement often masks invalid actions.
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Dynamic Collateral Control for Permissionless Spot Perpetual Basis Trading
This work derives risk-constrained static and asymmetric dynamic collateral control rules for DeFi spot-perpetual basis trading, validated via Monte Carlo simulations and historical backtests showing dependence on funding environments.