Investment Timing Under Incomplete Information
研究了项目价值可观测但驱动参数未知时的最优投资时机问题，发现最优投资区域由价值-信念状态空间中的连续非递减边界刻画，且决策者总能从不确定的漂移中获益。
We study the decision of when to invest in a project whose value is perfectly observable but driven by a parameter that is unknown to the decision maker ex ante. This problem is equivalent to an optimal stopping problem for a bivariate Markov process. Using filtering and martingale techniques, we show that the optimal investment region is characterized by a continuous and nondecreasing boundary in the value-belief state space. This generates path-dependency in the optimal investment strategy. We further show that the decision maker always benefits from an uncertain drift relative to an average drift situation and that the value of the option to invest is not globally increasing with respect to the volatility of the value process.