A Stochastic Control Framework for Real Options in Strategic Evaluation


Book Description

The theoretical foundation for real options goes back to the mid 1980s and the development of a model that forms the basis for many current applications of real option theory. Over the last decade the theory has rapidly expanded and become enriched thanks to increasing research activity. Modern real option theory may be used for the valuation of entire companies as well as for particular investment projects in the presence of uncertainty. As such, the theory of real options can serve as a tool for more practically oriented decision making, providing management with strategies maximizing its capital market value. This book is devoted to examining a new framework for classifying real options from a management and a valuation perspective, giving the advantages and disadvantages of the real option approach. Impulse control theory and the theory of optimal stopping combined with methods of mathematical finance are used to construct arbitrarily complex real option models which can be solved numerically and which yield optimal capital market strategies and values. Various examples are given to demonstrate the potential of this framework. This work will benefit the financial community, companies, as well as academics in mathematical finance by providing an important extension of real option research from both a theoretical and practical point of view.




A Stochastic Control Framework for Real Options in Strategic Valuation


Book Description

This text unfolds and examines a new framework for classifying real options from a management as well as a valuation perspective, giving the advantages and disadvantages of the real option approach. Impulse control theory and the theory of optimal stopping combined with methods of mathematical finance are used to construct arbitrarily complex real option models which can be solved numerically and yield optimal capital market strategies and values. Various examples are given, demonstrating the potential of the proposed framework.




Optimisation, Econometric and Financial Analysis


Book Description

This book addresses issues associated with the interface of computing, optimisation, econometrics and financial modeling, emphasizing computational optimisation methods and techniques. The first part addresses optimisation problems and decision modeling, plus applications of supply chain and worst-case modeling and advances in methodological aspects of optimisation techniques. The second part covers optimisation heuristics, filtering, signal extraction and time series models. The final part discusses optimisation in portfolio selection and real option modeling.




Real Options in Engineering Design, Operations, and Management


Book Description

Given that engineering flexibility can potentially provide a competitive advantage, the question then becomes: Precisely how valuable is this flexibility? However, traditional methods often fail to accurately capture the economic value of investments in an environment of widespread uncertainty and rapid change. The real options method represents th




Applications of Stochastic Optimal Control to Economics and Finance


Book Description

In a world dominated by uncertainty, modeling and understanding the optimal behavior of agents is of the utmost importance. Many problems in economics, finance, and actuarial science naturally require decision makers to undertake choices in stochastic environments. Examples include optimal individual consumption and retirement choices, optimal management of portfolios and risk, hedging, optimal timing issues in pricing American options, and investment decisions. Stochastic control theory provides the methods and results to tackle all such problems. This book is a collection of the papers published in the Special Issue "Applications of Stochastic Optimal Control to Economics and Finance", which appeared in the open access journal Risks in 2019. It contains seven peer-reviewed papers dealing with stochastic control models motivated by important questions in economics and finance. Each model is rigorously mathematically funded and treated, and the numerical methods are employed to derive the optimal solution. The topics of the book's chapters range from optimal public debt management to optimal reinsurance, real options in energy markets, and optimal portfolio choice in partial and complete information settings. From a mathematical point of view, techniques and arguments of dynamic programming theory, filtering theory, optimal stopping, one-dimensional diffusions and multi-dimensional jump processes are used.




Real Options Theory


Book Description

Examines the ways in which real options theory can contribute to strategic management. This volume offers conceptual pieces that trace out pathways for the theory to move forward and presents research on the implications of real options for strategic investment, organization, and firm performance.




Real Options Valuation


Book Description

The Author shows that modelling the uncertain cash flow dynamics of an investment project deserves careful attention in real options valuation. Focusing on the case of commodity price uncertainty, a broad empirical study reveals that, contrary to common assumptions, prices are often non-stationary and exhibit non-normally distributed returns. Subsequently, more realistic stochastic volatility, jump diffusion, and Lévy processes are evaluated in the context of a stylised investment project. The valuation results suggest that stochastic process choice can have substantial implications for valuation results and optimal investment rules.




Applications of Stochastic Control in Energy Real Options and Market Illiquidity


Book Description

We present three interesting applications of stochastic control in nance. The rst is a real option model that considers the optimal entry into and subsequent operation of a biofuel production facility. We derive the associated Hamilton Jacobi Bellman (HJB) equation for the entry and operating decisions along with the econometric analysis of the stochastic price inputs. We follow with a Monte Carlo analysis of the risk pro le for the facility. The second application expands on the analysis of the biofuel facility to account for the associated regulatory and taxation uncertainty experienced by players in the renewables and energy industries. A federal biofuel production subsidy per gallon has been available to producers for many years but the subsidy price level has changed repeatedly. We model this uncertain price as a jump process. We present and solve the HJB equations for the associated multidimensional jump di usion problem which also addresses the model uncertainty pervasive in real option problems such as these. The novel real option framework we present has many applications for industry practitioners and policy makers dealing with country risk or regulatory uncertainty which is a very real problem in our current global environment. Our final application (which, although apparently different from the first two applications, uses the same tools) addresses the problem of producing reliable bid-ask spreads for derivatives in illiquid markets. We focus on the hedging of over the counter (OTC) equity derivatives where the underlying assets realistically have transaction costs and possible illiquidity which standard nance models such as Black- Scholes neglect. We present a model for hedging under market impact (such as bid-ask spreads, order book depth, liquidity) using temporary and permanent equity price impact functions and derive the associated HJB equations for the problem. This model transitions from continuous to impulse trading (control) with the introduction of xed trading costs. We then price and hedge via the economically sound framework of utility indi erence pricing. The problem of hedging under liquidity impact is an on-going concern of market makers following the Global Financial Crisis.







The Effect of Capital Controls on Foreign Direct Investment Decisions Under Country Risk with Intangible Assets


Book Description

This paper examines how capital controls affect FDI decisions and how the impact of these restrictive measures varies with different levels of country risk. We construct a model of firms' FDI decisions, broadly in Dunning's "eclectic theory" framework, using "real options" to emphasize economic uncertainty and country risk. Numerical results of the model take the form of "quality statistics" that uncover the underlying dynamics hidden in the aggregate data that is responsible for the low performance of recent empirical studies. We find that increasing levels of capital controls reduce the life-span of FDI investments at each level of country risk and foreign investors' willingness towards risk sharing increases. We reveal a significant interaction between capital control and country risk, resulting in a nonlinear relationship between these and the volatility and volume statistics. We estimate a standard cross-sectional model that provides strong support for our theoretical findings.