CEO career horizon,corporate governance,and real options: The role of economic short‐termism

Research Summary: Combining studies on real options theory and economic short‐termism, we propose that, depending on CEOs’ career horizons, CEOs have heterogeneous interests in strategic flexibility, and thus, have different incentives to make real options investments. We argue that compared to CEOs with longer career horizons, CEOs with shorter career horizons will be less inclined to make real options investments because they may not fully reap the rewards during their tenure. In addition, we argue that long‐term incentives and institutional ownership will mitigate the relationship between CEOs’ career horizons and real options investments. U.S. public firms as an empirical setting produced consistent evidence for our predictions. Our study is the first to theoretically explain and empirically show that a CEO's self‐seeking behavior will impact real options investments. Managerial Summary: This article helps to explain how a CEO's self seeking‐behavior may shape a firm's real option investment, which could result in different level of strategic flexibility. We argue that CEOs with short career horizons have less time to exercise their firms’ real options, which should lower the investments in the firms’ real options portfolios relative to CEOs with long career horizons. We study a sample of U.S. public firms and find strong evidence that a CEO's expected tenure in the firm is positively related to the real options investments at the firm level. We find that this agency issue can be mitigated by adopting appropriate corporate governance mechanisms such as long‐term incentives and institutional investors.     

Toward a behavioral theory of real options: Noisy signals,bias, and learning

Research Summary: We develop a behavioral theory of real options that relaxes the informational and behavioral assumptions underlying applications of financial options theory to real assets. To do so, we augment real option theory's focus on uncertain future asset values (prospective uncertainty) with feedback learning theory that considers uncertain current asset values (contemporaneous uncertainty). This enables us to incorporate behavioral bias in the feedback learning process underlying the option execution/termination decision. The resulting computational model suggests that firms that inappropriately account for contemporaneous uncertainty and are subject to learning biases may experience substantial downside risk in undertaking real options. Moreover, contrary to the standard option result, greater uncertainty may decrease option value, making commitment to an investment path more effective than remaining flexible. Managerial Summary: Executives recognize the need to make uncertain investments to grow their business while mitigating downside risk. The analogy between financial options and real corporate investments provides an appealing method to consider the practical challenge of such investment decisions. Unfortunately, the “real options” analogy seems to break down in practice. We identify how a second form of uncertainty confounds real options intuition, leading managers to overestimate the value of uncertain investments. We present a behavioral real options model that accounts for both forms of uncertainty and suggest how uncertainty interacts with behavioral bias in the option execution/termination decision. Our model facilitates assessment of the conditions under which investments in uncertain opportunities are usefully considered as real options, and provides a means to evaluate their attractiveness.     

Pricing real growth options when the underlying assets have jump diffusion processes: the case of R&D investments

Numerous previous studies have demonstrated that research and development (R&D) investments can be evaluated by a real growth options approach. However, few studies have constructed evaluating models which consider the important R&D characteristics, including uncertainty regarding the project value, investment cost, and jump diffusion processes. The contribution of this study is not only to derive a model for evaluating R&D investments to conform to these key characteristics of R&D activities but also to build a real option pricing method that is more general than comparative important models, such as the theoretical papers of Black and Scholes (1973), Merton (1976), and Fischer (1978), and the application paper of Brach and Paxson (2001). This study also presents sensitivity analyses which illustrate the dynamic relationship between the real growth option value and the project value, investment cost, and main jump parameters. Hopefully, the results of this study can provide a useful reference for managers, and help them make better evaluations of R&D investments.     

Optimal exploration investments under price and geological‐technical uncertainty: a real options model

This article develops a real options model for valuing natural resource exploration investments (e.g. oil or copper) when there is joint price and geological‐technical uncertainty. After a successful several‐stage exploration phase, there is a development investment and an extraction phase. All phases are optimized contingent on price and geological‐technical uncertainty.
Several real options are considered. There are flexible investment schedules for all exploration stages and a timing option for the development investment. Once the mine is developed, there are closure, opening and abandonment options for the extraction phase. Our model maintains a relatively simple valuation structure by collapsing price and geological‐technical uncertainty into a one‐factor model.
We apply the model to a copper exploration prospect and find that a significant fraction of total project value is due to the operational, development and exploration options available to project managers.     

Flexibility in internationalization: is it valuable during an economic crisis?

This study investigates the value of the strategic flexibility provided by firms' international investments during an economic crisis, defined here as an unanticipated significant downturn in the economy. To avoid below‐par performance, firms need to adapt quickly to this significant change in their environment, making real options very valuable to them. Although firms' international investments can potentially provide such flexibility, this issue has not been empirically examined in a context of such dramatic negative change. We consider two types of international investments by firms in this regard, foreign direct investments and export‐related international investments, developing two measures that directly assess the flexibility derived from each that are new to the literature. Based on these measures, we find evidence that both types of international investments provided valuable flexibility for Korean firms during the economic crisis conditions. This study contributes to the literature by showing that firms with real options investments in place have a greater ability to flexibly adapt their overall operations in line with unforeseen negative environmental change, in contrast to firms without such investments. Copyright © 2009 John Wiley & Sons, Ltd.     

商业地产投资的实物期权特性及应用框架研究

商业地产开发投资中存在投资的不可逆性、外部环境的不确定性和决策的灵活性,因而具有实物期权特性。从确定要解决的问题、分析不确定性的来源、鉴别关键的不确定性因素、识别实物期权类型、构建期权定价模型、计算项目价值、检查计算结果和重新设计8个方面,构建了商业地产投资决策的实物期权分析框架。     

Project valuation in the pharmaceutical industry: a comparison of least‐squares Monte Carlo real option valuation and conventional approaches

Least‐squares Monte Carlo simulation (LSM) is a promising new technique for valuing real options that has received little or no attention in the pharmaceutical industry. This study demonstrates that LSM can handle complex valuation situations with multiple uncertainties and compounded American‐type options. The limited application of real option valuation (ROV) in the pharmaceutical industry is remarkable, given the importance of accurate project valuation in an industry that requires large investments in high‐risk projects with long pay‐back periods, which is furthermore suffering from ever‐increasing development costs and shrinking profit margins. The LSM model developed in this study is constructed as an extension of a discounted cash flow model that should be familiar to economists active in the pharmaceutical industry. A number of pharmaceutical projects have been evaluated using LSM ROV, binominal real option valuation and expected net present value techniques. The different results yielded by these methods are explained in terms of differences in risking assumptions and ability to capture the value of flexibility. The analysis provides a framework to introduce the basic concepts of real option pricing to a non‐specialist audience. The LSM model illustrates the potential for real‐life commercial assessment as the versatility of the technique allows for an easy customisation to specific business problems.     

Making real options work for practitioners: a generic model for valuing R&D projects

We propose a generic valuation framework for the appraisal of R&D projects based on real option theory. The added value of this approach is the presentation of a model that was implemented in a manner that allows corporate decision makers to use real options in an intuitive and standardized way. The project valuation procedure is separated into three main phases: project modeling, data and input collection, and result generation and analysis. The project model represents the structure of the real world R&D project with its investments, expected results, and decisions that need to be taken conditionally on the outcomes of research activities. The project model is represented in the form of a decision tree, where different research results or taken decisions lead to new branches. In this way, every possible situation the project can pass through can be represented. Uncertainties are separated into market uncertainties (e.g., market prices) and project specific, private uncertainties (e.g. uncertainty of research results). For both uncertainties, event trees are constructed which are then combined and merged with the above mentioned decision tree in order to represent the value evolution of the R&D project under given decisions and uncertainties. For every possible state of the project the real option value is calculated. By creating multidimensional trees, a multitude of decision steps and various kinds of real options (e.g., continue, expansion, switch, abandonment) can be modeled. The calculation complexity for the decision trees is given. From the tree structure we can calculate the real option value of starting an R&D project, i.e., the value of undertaking the first investment and thus acquiring the subsequent decision opportunities given by the completion of the first research effort. Furthermore, the optimal exercise strategy is derived from the decision tree. The exercise strategy gives the manager the possibility to have an a priori overview of where an R&D project may lead to, which decisions need to be taken in which circumstances, and when the project needs to be stopped in order not to generate losses. In an in‐depth case study we use an illustrative R&D project to set up and discuss the three phases of project modeling in the real options framework: building the multidimensional decision tree, input generation, and calculation of the real option value as well as the optimal strategy for the R&D project.     

Human capital matters: Market valuation of firm investments in training and the role of complementary assets

Research summary: This article empirically examines the economic value to firms of investing in the training of their employees and firm‐level factors that influence how much the firms benefit. Event study methodology is used to obtain a measure of the economic impact of information regarding a firm's human capital management investments and policies. Subsequent regression analyses are then used to test hypotheses regarding possible complementary relationships between firm‐level factors and human capital investments. Results provide robust support for the proposition that effective investments in human capital and training matter, and that these human capital investments are more impactful when combined with complementary assets of R&D, physical capital, and advertising investments . Managerial summary: Do firm investments in training and the development of employee human capital matter with regard to financial performance? We find that, yes, these investments do matter. Our results show that managers who view employee human capital as an asset to be invested in and developed can expect to outperform those who view it as a cost to be minimized. In addition, we find that these human capital investments will be of even greater economic value to firms when they have made complementary investments in R&D, physical capital, and advertising . Copyright © 2016 John Wiley & Sons, Ltd.     

Integrating Real Options with Managerial Cash Flow Estimates

This article presents a real options model that fits managerial cash flow estimates (optimistic, likely, and pessimistic projections) to a continuous geometric Brownian motion (GBM) cash flow process with changing growth and volatility parameters. The cash flows and the value of a project are correlated to a traded asset, so the real option is priced under the risk-neutral measure with a closed-form solution. The analysis is extended to a sequential compound call option for investments over multiple periods. If the project is correlated to the market, then some of the risk may be mitigated by a delta-hedging strategy. A numerical example shows that the effect of the correlated asset on the real option value is significant, and the relationship between the volatility of the project and the real option value is not analogous to the typical relationship found in financial option pricing. Integrating the expertise and industry knowledge of management, this approach makes possible a more rigorous estimation of model inputs for real option pricing.     

Flexibility planning for managing R&D projects under risk

Incorporating managerial flexibility in an innovative R&D project is important, because managers face greater uncertainty in today's competitive and dynamic changing environment. It is essential to bring managerial flexibility into R&D project planning to decrease technical and market risks, while increasing potential market value. The objective of this paper is to develop a flexibility planning methodology based on real option analysis to improve managerial flexibility for R&D projects. The proposed methodology identifies potential risks that may occur during every R&D stage. It also recognizes a cascading option structure to resolve the identified risks, and evaluates and selects adequate options that maximize the potential value of the project. Instead of using a traditional option pricing method, a dynamic programming model that considers multidimensional product performance and market payoff is used to evaluate the R&D project value. Using the proposed methodology, managers can identify future scenarios as a function of their management actions. The proposed flexibility planning methodology can help managers improve managerial flexibility of R&D project and increase the success rate of product launch. A drug development project is used to illustrate the proposed methodology.     

Technology search investments: evolutionary,option reasoning,and option pricing approaches

How do firms allocate limited search resources among substituting technologies with uncertain prospects? This paper contrasts three different approaches. The first follows evolutionary theorists' portrayals of decision‐making processes under bounded rationality. The second approach—real option reasoning—fosters flexibility by investing in more than one technology and postponing the decision to specialize. Following the third approach—real option pricing—firms base their search investments on forward‐looking calculations of technology option prices. We lay out the contrasting theoretical assumptions behind each of these three approaches and construct a simulation model to compare their implications. Copyright © 2004 John Wiley & Sons, Ltd.     

Firm heterogeneity in growth option value: The role of managerial incentives

Growth option value varies widely across firms. This research explores managerial incentives as a source of firm heterogeneity in growth option value. We argue that when the payoff structure of managerial incentives corresponds to that of growth options, managers will be motivated to pursue actions that increase firms' growth option value, particularly when greater growth opportunities are available in an industry. Results indicate that stock option holdings and managerial stock ownership have a positive effect on growth option value, while short‐term pay has a negative effect. We also find support for a positive interaction effect between equity‐based managerial incentives and industry growth opportunities on growth option value. These findings highlight the critical role of managerial incentives in affecting firms' realization of growth option value. Copyright © 2012 John Wiley & Sons, Ltd.     

实物期权定量分析方法在风险投资决策中的应用

在风险投资项目中，不确定性对风险项目投资评价、决策起到了决定性的作用。运用实物期权原理分析了不确定性对风险投资项目评价和决策的影响，通过风险中性概率方法将这些影响予以定量化，并进一步对实际投资行为作出解释。     

Investment decisions in the wireless industry applying real options

The wireless industry is one of the most capital intensive high-technology industries. This paper applies real options techniques to estimate investments under uncertainty in two new ventures: (a) deferral of the expansion from 2.5G to 3G networks; and (b) expansion of a 2.5G network using Wi-Fi as an alternative technology. The cases are examined and analyzed both qualitatively and quantitatively, using realistic assumptions and parameters. Investment cost, number of subscribers, pricing of services, and risk are at the core of investment decision processing. In both cases, sensitivity analysis of the value of the (real) option considering the above key parameters was conducted, to extrapolate useful findings that should be taken into consideration by the decision makers in wireless companies.     

Analyzing operational real options in metal mining investments with a system dynamic model

This article presents a detailed system dynamic (SD) model of a metal mining investment that is usable in ex-ante profitability and operations management analysis. We show how the SD model can be used to analyze the profitability effect of three operational real options: the option to temporarily close production, the option to abandon production, and the option to increase production through cutoff grade change. The SD model allows for intuitive modeling of the multiple interactive real options and arriving at results that are difficult, or impossible, to reach with commonly used spreadsheet software. We also analyze the effect of mining project debt ratio to the project value and show that correctly choosing the debt ratio affects project profitability. The effect on the project value of using three different future metal price scenarios with two different stochastic processes is illustrated to highlight the importance of correct process selection in modeling future metal price paths. A realistic case of a high-cost nickel (Ni) metal mine is used as a basis for the presented numerical illustration of the model.     

Property Investment and Rental Rate under Housing Price Uncertainty: A Real Options Approach

The conventional wisdom that housing prices are the present value of future rents ignores the fact that unlike dividends on stocks, rent is not discretionary. Housing price uncertainty can affect household property investments, which in turn affect rent. By extending the theory of investment under uncertainty, we model the renter's decision to buy a house and the landlord's decision to sell as the exercising of real options of waiting and examine real options effects on rent. Using data from Hong Kong and mainland China, we find a significant effect of housing price on rent and draw important policy implications.     

An Options Approach to Valuing Expansion Flexibility in Flexible Manufacturing System Investments

Flexibility in manufacturing processes provides an ability to change or even reverse the decisions made in earlier periods. The traditional economic evaluation methods of investments in flexible manufacturing systems ignore the value of flexibility, which should be one of the key issues in the justification process. Options approach appears as a means of overcoming the limitations of conventional discounted cash flow methods. In this work, a methodology for valuing expansion flexibility of flexible manufacturing systems is presented. Expansion flexibility in a phased manufacturing investment can be valued by viewing an initial investment as being analogous to purchasing an option to exchange one risky asset for another risky asset within a time period from the initial investment. While keeping the option to expand is of value, a thorough analysis requires that the opportunity cost of delaying expansion be taken into account. In this paper, an analytic approximation methodology for valuing sequential American exchange options on dividend paying stocks is employed for valuing expansion flexibility. A comprehensive numerical example is presented to illustrate the approach, and sensitivity analyses are performed.     

The Determinants of Stock Option Compensation: Evidence from Finland

A new, long, and rich panel data set consisting of all Finnish publicly traded firms is used to study how firm characteristics and stock market developments influence the adoption and targeting of stock option compensation. Stock option adoption is found to be a procyclical phenomenon. Findings from firm‐level econometric analysis often corroborate those based on U.S. data, but important differences also emerge. Findings include: (i) firms with higher market value per employee are more likely to use stock option compensation; (ii) share returns from the past year affect the adoption of targeted stock options, but not broad‐based plans; (iii) our results are consistent with the hypothesis that selective and broad‐based plans arise as solutions to differing monitoring difficulties. Broad‐based schemes are observed when production is human capital‐intensive and employee performance is hard to monitor, while selective schemes are adopted when ownership is dispersed and therefore owners may have weak incentives to monitor management.     

Evaluating growth options as sources of value for pharmaceutical research projects

The financial value of research projects is difficult to assess because they are highly uncertain. Often, the result is either an overly conservative approach to strategic innovation, based on net present value analyses, or an overly aggressive approach based on optimistic qualitative portfolios. R&D project evaluation requires recognizing threats as well as opportunities from uncertain events, and incorporating flexibility in managerial action in response to them. Real options pricing analysis is a widely discussed tool for evaluating such managerial flexibility. The limitation of options pricing lies in its requirement for complete financial markets, in which a replicating asset can be found that reproduces (or, at least, is correlated with) the project’s payoffs in all possible states of the world. However, the major risks of research projects are typically project specific and cannot be replicated in external markets. In this situation, a decision tree is a better tool to represent managerial options during execution of the project, and to evaluate its value. A decision tree is equivalent to options pricing for risks that can be priced in the financial markets (if trading of securities is explicitly included), and moreover, it can incorporate risks and flexibility that are not traded in financial markets. Using decision trees, we demonstrate a quantitative evaluation of compound growth options from research at BestPharma, a large international pharmaceutical company. A growth option is a future opportunity that may arise from a current R&D investment. The growth option may not be related to the primary purpose of the R&D project, or not even be directly foreseeable. Kester (1984) has argued that growth options may account for a large part of project value. BestPharma faced the problem of choosing among several strategic research initiatives. They developed a decision tree representation of the projects, which helped to provide transparency about project value and strategic options. Most importantly, carefully thinking through the tree helped to identify growth options, represented by additional branches in the tree, and to quantify that they represented major sources of value.