Imperial College London


Faculty of EngineeringDepartment of Civil and Environmental Engineering

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Publication Type

5 results found

Maier S, Polak J, Gann D, 2020, Valuing portfolios of interdependent real options using influence diagrams and simulation-and-regression: A multi-stage stochastic integer programming approach, Computers and Operations Research, Vol: 115, ISSN: 0305-0548

Although real options generally occur within portfolios, most valuation approaches based on either option pricing or decision analysis alone focus on single well-defined options. In this paper we present a new approach for modelling and approximating the value of portfolios of interdependent real options using both influence diagrams and simulation-and-regression. The key feature of this approach is that it translates the interdependencies between real options into a set of constraints and then directly models the dynamics of all underlying uncertainties using (Markovian) stochastic processes. These are then integrated in a portfolio optimisation problem which is formulated as a multi-stage stochastic integer program. Applying a simulation and parametric regression approach to approximate the value of this optimisation problem, we present a transparent valuation algorithm that explicitly takes into account vector-valued exercise decisions and the state variable’s multidimensional resource component. The approach is therefore applicable to a wide range of complex investment projects with both inherent interdependent flexibilities and many underlying uncertainties. The approach is illustrated by evaluating a complex natural resource investment that features both a large portfolio of interdependent real options and four stochastic factors. We analyse the way in which the approximated value of the portfolio and its individual options are affected by the initial copper price as well as by the degrees of production cost and copper price uncertainty.

Journal article

Maier S, Pflug G, Polak J, 2019, Valuing portfolios of interdependent real options under exogenous and endogenous uncertainties, European Journal of Operational Research, ISSN: 0377-2217

Although the value of portfolios of real options is often affected by both exogenous and endogenous sources of uncertainty, most existing valuation approaches consider only the former and neglect the latter. In this paper we introduce an approach for valuing portfolios of interdependent real options under both types of uncertainty. In particular, we study a large portfolio of options (deferment, staging, mothballing, abandonment) under conditions of four underlying uncertainties. Two of the uncertainties, decision-dependent cost to completion and state-dependent salvage value, are endogenous, the other two, operating revenues and their growth rate, are exogenous. Assuming that endogenous uncertainties can be exogenised, we formulate the valuation problem as a discrete stochastic dynamic program. To approximate the value of this optimisation problem, we apply a simulation-and-regression-based approach and present an efficient valuation algorithm. The key feature of our algorithm is that it exploits the problem structure to explicitly account for reachability – that is the sample paths in which resource states can be reached. The applicability of the approach is illustrated by valuing an urban infrastructure investment. We conduct a reachability analysis and show that the presence of the decision-dependent uncertainty has adverse computational effects as it increases algorithmic complexity and reduces simulation efficiency. We investigatethe way in which the value of the portfolio and its individual options are affected by the initial operating revenues, and by the degrees of exogenous and endogenous uncertainty. The results demonstrate that ignoring endogenous, decision- and state-dependent uncertainty can lead to substantial over- and under-valuation, respectively.

Journal article

Maier S, 2017, An Approach for Valuing Portfolios of Interdependent Real Options under both Exogenous and Endogenous Uncertainties, 21st Annual International Conference on Real Options

Conference paper

Lambert RSC, Polak JW, Maier S, Shah Net al., 2016, Optimal phasing of district heating network investments using multi-stage stochastic programming, International journal of sustainable energy planning and management, Vol: 09, Pages: 57-57

Journal article

Maier S, Polak J, Gann D, 2015, Appraising a Portfolio of Interdependent Physical and Digital Urban Infrastructure Investments: A Real Options Approach, 19th Annual International Real Options Conference

Conference paper

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