Hemantha S. B. Herath

MULTI-STAGE CAPITAL INVESTMENT OPPORTUNITIES AS COMPOUND REAL Options

Abstract Real options provide a new and productive way to view corporate investment decisions as options. Multi-stage or sequential-investment decisions are an important class of real options with embedded managerial flexibility. These multi-stage real options involve a bundle of interrelated investment opportunities, with the early upstream opportunities creating potentially valuable discretionary downstream opportunities. We investigate a multi-stage project setting where each investment opportunity derives revenues from different markets but share common technological resources. In such a setting, one should consider the underlying asset volatility of each investment opportunity in a compound-options framework. In this paper, we extend the binomial lattice framework to model a multi-stage investment as a compound real option when several uncorrected underlying variables exist. Volatility estimation is important for implementing real option models. Therefore, we develop the theoretical framework for estimating the volatility parameter of an underlying variable using Monte Carlo simulation technique.

ECONOMIC ANALYSIS OF R&D PROJECTS: AN OPTIONS APPROACH

ABSTRACT An emerging trend in research and development (R&D) project valuation is the use of options approach, which permits a more flexible assessment of the future growth opportunities in the entire process. The traditional DCF method when naively applied fails to capture all the future opportunities that create value, thereby resulting in an under investment in R&D. The options approach is more appropriate in a world of uncertainty because it views an R&D project as an initial investment that creates future follow-on commercial opportunities that are undertaken only if the initial R&D project is successful. Valuation of R&D projects is usually complex due to substantial uncertainties at different project phases, including the R&D phase and commercialization phases. Several recent papers on real options indicate that valuations of R&D projects based upon an options approach have been neglected by the finance community. To help correct this deficiency, we develop a valuation model that incorporates the r...

EXPLOITING UNCERTAINTY—INVESTMENT OPPORTUNITIES AS REAL OPTIONS: A NEW WAY OF THINKING IN ENGINEERING ECONOMICS

Abstract A new trend in corporate planning is to exploit uncertainty by taking investment opportunities as real options. This options approach is to complement the conventional net present value (NPV) criterion in evaluating risky investments. In this paper, we take a broad look at the real options approach to various engineering economic decision problems, laying out how it provides an immediate and important perspective on value creation in an uncertain world. Unlike financial options, real options analysisdeals with investments in real assets, which is one of the primary interest areas in engineering economics. For that reason, we believe that any advancement in the real options decision framework will benefit the field of engineering economics.

Investments in Information Security: A Real Options Perspective with Bayesian Postaudit

The application of real options techniques to information security is significantly different than in the case of general information technology investments due to characteristics unique to information security. Emerging research in the economics of information security has suggested real options analysis (ROA) as a potential technique for assessing the value of information security assets, but has focused primarily on the most effective level of investment and the configuration of intrusion prevention/detection systems. In this paper, we attempt to address significant gaps in the literature by developing an integrated real options model for information security investments using Bayesian statistics that incorporates learning and postauditing in the analysis. By using the proposed model with actual data on e-mail and spam, we demonstrate that ROA with Bayesian postauditing offers a systematic valuation and risk management framework for evaluating information security spending by firms. We also discuss the managerial implications.

REAL OPTIONS VALUATION AND ITS RELATIONSHIP TO BAYESIAN DECISION-MAKING METHODS

ABSTRACT It is well accepted that conventional NPV criterion fails to capture investment flexibility, and the market approach using riskless-arbitrage-pricing is ideally suited to price real options. However, when valuing complex real options, it is difficult to satisfy the restrictive assumptions required for risk-free arbitrage pricing. Using two-action linear payoff analysis, we show that when it is possible to delay and obtain additional information, an irreversible capital investment decision should be valued as an option taking into considering the value of flexibility. This option value is not based on risk-less arbitrage, but on a more fundamental concept in decision theory - the opportunity loss criterion. Our approach relates to the Quasi-Option concept of Arrow and Fisher (1974) and Henry (1974) that considers the value of gaining more information before making irreversible environment decisions. Lund (1991) provides an excellent analysis of the relationship between the Arrow and Fishers [1] Quasi-Option Value and Black and Scholes Market based Model [4], and suggests using both ideas for valuing real options. Conrad (1980), Fisher and Hanemann (1987) and Hanemann (1989) discuss the relationship between Quasi-Option Value and Expected Value of Perfect Information (EVPI) with respect to environmental decisions. We extend the opportunity loss concept to value real options and analyze its relationship to EVPL We show that the value of a quasi-real option is equal to value of information. In the special case where a lognormal terminal distribution is assumed, we show that the EVPI is equivalent to the Black and Scholes model. We demonstrate how EVPI can be used to make investment decisions under uncertainty within an options framework. The suggested approach allows revision of option values sequentially using Bayesian methods at each decision point within the well-known decision theory framework. Financial economists have not considered the intersection between Bayesian decision framework and value of investment flexibility, that allow for a less restrictive set of assumptions.

Balanced Scorecard Implementation of Security Strategies: A Framework for IT Security Performance Management

The article develops a conceptual framework for strategic implementation of IT security using a balanced scorecard (BSC) approach. Current research has mostly looked at economics of IT security, technical considerations, and behavioral aspects of what counter measures are available to firms instead of how successful or cost effective the investments or counter measures are. More specifically, our article provides a framework for building and implementing scorecards for information security performance management.

IT security auditing: A performance evaluation decision model

Compliance with ever-increasing privacy laws, accounting and banking regulations, and standards is a top priority for most organizations. Information security and systems audits for assessing the effectiveness of IT controls are important for proving compliance. Information security and systems audits, however, are not mandatory to all organizations. Given the various costs, including opportunity costs, the problem of deciding when to undertake a security audit and the design of managerial incentives becomes an important part of an organizations control process. In view of these considerations, this paper develops an IT security performance evaluation decision model for whether or not to conduct an IT security audit. A Bayesian extension investigates the impact of new information regarding the security environment on the decision. Since security managers may act in an opportunistic manner, the model also incorporates agency costs to determine the incentive payments for managers to conduct an audit. Cases in which the agency model suggests that it is optimal not to conduct an IT security audit are also discussed.

New Research Directions in Engineering Economics—Modeling Dependencies with Copulas

Understanding and quantifying dependencies among variables often arises in stochastic capital investment and real option analysis. In such modeling situations, Pearson product moment linear correlation is widely used as a dependence measure. Linear correlation has several limitations. More recently, copulas have been used in financial economics and insurance to model dependencies. We contribute to the engineering economy literature by introducing copulas to model dependent risks that will enhance research and practice. We demonstrate the usefulness of copula-based sampling in simulation of project risk and regression analysis for forecasting. We also discuss potential copula research in engineering economic analysis.

Monitoring Projects Using Cash Flow Control Charts

ABSTRACT Post Completion Audits (PCA). an important area in capital budgeting have not received much attention in the past. In a competitive environment, however, PCA plays an important role. Uncertain initial forecasts and current estimates can be revised using post audit information under a Bayesian approach at virtually no additional cost, thus enhancing future decisions. Prueitt and Park [2]. developed the Cash Flow Control Chart (CFCC) model for a special class of investment problems with multiple identical units with uncertain cash flows, typically found in Advanced Manufacturing Systems (AMS) and fleet replacement. This paper provides meaningful interpretations to modified Cash Row Control Chart (M-CFCC) patterns.

Facilitating a Team Culture: A Collaborative Balanced Scorecard as an Open Reporting System

The balanced scorecard (BSC) allows firms to place importance on both financial and nonfinancial performance measures in four perspectives for developing and implementing corporate strategy and performance evaluation. The BSC literature however provides minimal insight on how to set targets, how to weigh measures when evaluating managers and the firm, and how to resolve conflicts that arise in the BSC process. Researchers have attempted to fill these gaps using two contending approaches. In particular, Datar et al. (2001) uses an agency model to select the optimal set of weights and more recently Herath et al. (2009) develop a mathematical programming–based collaborative decision model to find the optimal (or approximately optimal) set of target and weights considering inputs from two parties. In this article, we apply the Herath et al. (2009) model to a detailed BSC example. We demonstrate how the collaborative BSC model can be implemented in Microsoft Excel by practitioners to minimize BSC conflicts. Finally, we discuss how the model facilitates alignment and a culture of open reporting (information sharing) around the BSC that is necessary for its effective implementation.