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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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
Order-flow estimates of Kyle lambda predict stock returns and resolve the Constantinides liquidity premium puzzle through an adverse-selection channel without risk compensation.
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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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Liquidity Premium and Investment Horizons
Order-flow estimates of Kyle lambda predict stock returns and resolve the Constantinides liquidity premium puzzle through an adverse-selection channel without risk compensation.