To address the limitation of traditional optimal portfolio liquidation models that overlook strategic interactions, this paper develops a bilevel programming model for portfolio liquidation, characterizing the sequential trading game between a leader and a follower. Theoretical analysis explicitly characterizes the follower's optimal strategy, proves that the cash constraint is active at the optimum, and quantifies the leader's additional loss caused by the follower's trading. A hybrid quantum-behaved particle swarm optimization algorithm is designed to solve the nonconvex nested model. Numerical experiments show that a disadvantaged leader tends to preemptively liquidate vulnerable assets to avoid price declines triggered by the follower; ignoring the game mechanism can result in a relative loss of up to 46.6%.
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