An irreversible investment problem with a learning-by-doing feature
Erik Ekstr\"om, Yerkin Kitapbayev, Alessandro Milazzo, Topias, Tolonen-Weckstr\"om

TL;DR
This paper models an irreversible investment problem where learning-by-doing causes the learning rate to increase with investment, leading to a strategy of gradual investment characterized by a boundary solved via differential equations.
Contribution
It introduces a novel learning-by-doing feature with increasing learning rate in an irreversible investment model and characterizes the optimal strategy through a differential boundary problem.
Findings
Optimal investment strategy is gradual and boundary-based.
The boundary is characterized by a differential equation.
Discrete and continuous models are both analyzed.
Abstract
We study a model of irreversible investment for a decision-maker who has the possibility to gradually invest in a project with unknown value. In this setting, we introduce and explore a feature of "learning-by-doing", where the learning rate of the unknown project value is increasing in the decision-maker's level of investment in the project. We show that, under some conditions on the functional dependence of the learning rate on the level of investment (the "signal-to-noise" ratio), the optimal strategy is to invest gradually in the project so that a two-dimensional sufficient statistic reflects below a monotone boundary. Moreover, this boundary is characterised as the solution of a differential problem. Finally, we also formulate and solve a discrete version of the problem, which mirrors and complements the continuous version.
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Taxonomy
TopicsReservoir Engineering and Simulation Methods · Stochastic processes and financial applications · Optimization and Variational Analysis
