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Optimal Strategies For Information Updating, Learning and Investment Under Knightian Uncertainty

In this paper, we investigate the value of learning options under the Knightian uncertainty. A theoretical framework is presented for determining optimal strategies for information updating, real investment strategies based on the updated information, and evaluating the information to resolve Knightian uncertainty. To this end, we formulate the problem of determining optimal real investment strategies under Knightian uncertainty using the real options framework. The formulation is notable for its inclusion of proactive information gathering. An analytical examination is conducted using a simplified model. Numerical demonstrations are used to complement this examination and determine optimal strategies, as well as to quantify the value of learning options across a range of scenarios.