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.     

Metaheuristic-based simulation optimization approach to network revenue management with an improved self-adjusting bid price function

Making accurate accept/reject decisions on dynamically arriving customer requests for different combinations of resources is a challenging task under uncertainty of competitors' pricing strategies. Because customer demand may be affected by a competitor's pricing action, changes in customer interarrival times should also be considered in capacity control procedures. In this article, a simulation model is developed for a bid price–based capacity control problem of an airline network revenue management system by considering the uncertain nature of booking cancellations and competitors' pricing strategy. An improved bid price function is proposed by considering competitors' different pricing scenarios that occur with different probabilities and their effects on the customers' demands. The classical deterministic linear program (DLP) is reformulated to determine the initial base bid prices that are utilized as control parameters in the proposed self-adjusting bid price function. Furthermore, a simulation optimization approach is applied in order to determine the appropriate values of the coefficients in the bid price function. Different evolutionary computation techniques such as differential evolution (DE), particle swarm optimization (PSO), and seeker optimization algorithm (SOA), are utilized to determine these coefficients along with comparisons. The computational experiments show that promising results can be obtained by making use of the proposed metaheuristic-based simulation optimization approach.     

A Measure of Fundamental Volatility in the Commercial Property Market

The low level of volatility observed in appraisal-based commercial property indices relative to other asset classes has been frequently noted and extensively commented on in the real estate finance literature. However, the volatility of such commercial property indices is only one source of information on the second moment of commercial property returns. The volatility of securitized property returns forms another potential source of information, though there is some uncertainty about how closely the volatility of securitized returns may match the volatility of the underlying asset. Each measure of volatility has a potential source of noise associated with it. This paper proposes a fundamental measure of volatility for the commercial property market by using a stochastic volatility model to filter out the signal in the different sources of volatility information. This allows for different measures of volatility to be decomposed into transitory noise and unobserved fundamental volatility. The suitability of such an approach and the properties of the underlying fundamental volatility series are analyzed using data from the U.K. property market.     

Using mean-Gini and stochastic dominance to choose project portfolios with parameter uncertainty

Although a variety of models have been studied for project portfolio selection, many organizations still struggle to choose a potentially diverse range of projects while ensuring the most beneficial results. The use of the mean-Gini framework and stochastic dominance to select portfolios of research and development (R&D) projects has been gaining attention in the literature despite the fact that such approaches do not consider uncertainty regarding the projects’ parameters. This article discusses, with relation to project portfolio selection through a mean-Gini approach and stochastic dominance, the impact of uncertainty on project parameters. In the process, Monte Carlo simulation is considered in evaluating the impact of parametric uncertainty on project selection. The results show that the influence of uncertainty is significant enough to mislead managers. A more robust selection policy using the mean-Gini approach and Monte Carlo simulation is proposed.     

Evaluation of a mining project under the joint effect of commodity price and exchange rate uncertainties using real options valuation

Cash flows generated by mining projects tend to be volatile and are extensively influenced by exogenous variables, notably commodity prices and exchange rates. The traditional discounted cash flow (DCF) method, which is normally used for economic feasibility studies and mining project evaluations, presents inconsistencies because the method fails to adequately address uncertainties and operational flexibilities and often ignores certain specific market conditions. Numerous studies have been carried out for mining project evaluations using the real options valuation (ROV) technique for assessing commodity price uncertainty, but there is no research on the combined effects of price and exchange rate uncertainties. Therefore, in order to assess the economic viability of a mining project more accurately, the commodity price and its inherent volatility, the exchange rate and its inherent volatility, and the correlation parameters between them have been incorporated into the model and used in the evaluation process. One of the interesting findings revealed in the study is that project values are overestimated if only commodity price uncertainty is considered in evaluating the project value instead of the joint effect of commodity price and exchange rate uncertainties. This new ROV technique will explore the opportunity to utilize an alternative methodology for approximating project values and to identify valuation opportunities to enhance economic gains or to mitigate economic losses, where the DCF valuation method does not.     

An extension to a DEA support system used for assessing R&D projects

This paper describes an extension to the data envelopment analysis (DEA) support system that has been used for the assessment, rating, and ranking of diverse portfolios of research and development (R&D) projects at Lucent Technologies. The approach is illustrated through its application to a large portfolio of R&D projects considered by Lucent's Advanced Technologies Group. The method proceeds by first stratifying the portfolio into comparably efficient groups of projects through the construction of a series of efficient DEA frontiers, and then by lexicographically ranking each project within these groups relative to DEA-based contextual attractiveness measures calculated from the different partitions. The advantages to this approach are provided not only from the perspective of the specific project rankings that are produced but also from the broader managerial insights that can be derived from any resulting differences between officially sanctioned, quantitative decision-making procedures, and the quality of the decisions that have actually been made by managers.     

Innovation and project development: an impossible equation? Lessons from an innovative automobile project development

Product development performance has become a key issue for car manufacturers. But innovation seeks to outperform dominant design, whereas project development targets well-defined areas (costs, lead times, quality, etc.). This article provides an analysis of the extent to which innovation is compatible with recent managerial and technical methods (project and multi-project management, co-development, simulation tools and digital mock-ups, etc.). The analysis is based on a recent development project conducted at Renault in which these various techniques were used in an attempt to achieve highly ambitious targets simultaneously in the areas of lead times, costs and innovation. During the course of the project, unexpected design problems revealed failures in co-ordination, monitoring procedures and expertise. We argue that recent project development methods can induce negative effects on collective learning processes and that these effects have managerial implications for innovative developments.     

Customization of Product Technology and International New Product Success: Mediating Effects of New Product Development and Rollout Timeliness

Offering a standardized product for different country markets may enable companies to accomplish fast product development and multicountry rollout, whereas also enjoying substantial cost benefits. However, not all manufacturers serving multicountry markets can adopt a standardized product strategy. Where technological requirements, standards, and approval procedures vary substantially across countries, manufacturers invariably must adapt the product's technology to fit individual country requirements. Extensive customization may lead to longer new product development and rollout times and increase the likelihood of delays in the entire project, hence adversely affecting overall new product outcome. This study examines the relationships between product technology customization, the timeliness in completion of both the new product development effort and international market launches, and new product success. The study that reports on new product launches across European markets, is based on personal interviews with senior managers in 30 multinational companies. The authors show that timeliness in new product development and timeliness in rolling out the new product into different country markets mediate the link between product technology customization and overall new product success. Customization of product technology increases the likelihood of delays in the completion of new product development projects and multicountry rollout. Additionally, the timeliness in new product development mediates the relationship between product technology customization and timeliness in international new product rollout. This means that if the NPD project runs behind schedule, a fault‐free multicountry rollout program becomes increasingly unlikely, as problems encountered during product development spillover into the rollout program. The results imply that international product managers must assign greater priority to assessing the relative advantages of customizing new product technology and to consider the timing implications for both the NPD effort and subsequent rollout. Managers must set realistic schedules and allocate sufficient resources to ensure both tasks can be accomplished within planned time scales. Finally, managers should not underestimate the complexities and time involved in customizing new product technologies, including the completion of disparate country technical approval procedures.     

T厂2×330MW机组供热改造项目经济评价

伴随环境污染问题滋生的热电联产方案备受关注,本文首先阐述了供热改造项目的背景及其必要性,对该项目进行了技术可行性分析以及经济评价。结合多年的行业经验,创新地提出了热电联产改造项目新增成本费用与收益的界定方法。并通过财务评价,得出该项目经济合理性的结论。最后对该项目投产后的运营风险进行了简要分析,并提出了相应的应对措施。评价结果表明,T厂2×330MW机组供热改造项目不仅符合国家节能减排政策要求,而且具有可观的经济效益,为T厂的可持续发展提供了一条有效的途径,同时也为周边地区带来了良好的环境和社会效益。     

Valuation of projects with minimum revenue guarantees: A Gaussian copula–based simulation approach

This technical note presents a numerical simulation technique to perform valuations of infrastructure projects with minimum revenue guarantees (MRG). It is assumed that the project cash flows—in the absence of the MRG—can be described in a probabilistic fashion by means of a very general multivariate distribution function. Then, the Gaussian copula (a numerical algorithm to generate vectors according to a prespecified probabilistic characterization) is used in combination with the MRG condition to generate a set of plausible cash flow vectors. These vectors form the basis of a Monte Carlo simulation that offers two important advantages: it is easy to implement and it makes no restrictive assumptions regarding the evolution of the cash flows over time. Thus, one can estimate the distribution of a broad set of metrics (net present value, internal rate of return, payback periods, etc.). Additionally, the method does not have any of the typical limitations of real options–based approaches, namely, cash flows that follow a Brownian motion or some specific diffusion process or whose volatility needs to be constant. The usefulness of the proposed approach is demonstrated with a simple example.     

Upper management control of new product development projects and project performance

While some degree of freedom and flexibility is an essential ingredient to productive cross‐functional NPD teams, upper‐managers are faced with the challenge of instituting effective control mechanisms which head projects in the right strategic direction, monitor progress toward organizational and project goals, and allow for adjustments in the project if necessary. But too much or the wrong type of control may constrain the team's creativity, impede their progress, and injure their ultimate performance. Therefore, this study examines formal and interactive control mechanisms available to upper‐managers in controlling new product development (NPD) projects, and the relationship between these mechanisms and NPD project performance. Formal output and process controls are examined which consist of the setting and monitoring of outcomes, such as goals, schedule and budgets, and of processes and procedures, respectively. This study also looks at how the effectiveness of these control mechanisms may be contingent upon the degree of innovativeness in the project and the degree to which the project is part of a broad product program. In addition, the use of formal rewards for achieving team performance as opposed to rewards for individual achievement is investigated. Lastly, interactive controls are examined which consist of upper‐managers interacting directly with project members in the development of strategy and operational goals and procedures prior to the start of the project, and upper‐managers intervening in project decision‐making. Questionnaire data are collected on 95 projects across a variety of industries. The findings suggest that while NPD projects teams need some level of strategic direction concerning the objectives to be accomplished and the procedures to be followed, upper‐level managers can exert too much control. In particular, the findings showed a negative association between the use of upper manager‐imposed process controls and project performance. The findings also indicated that the degree to which upper‐managers intervened in project‐level decisions during the project was negatively related to project performance. However, the results showed support for the notion that early and interactive decision‐making on control mechanisms is important for effective projects. In particular, early team member and upper‐management involvement in the setting of operational controls, such as goals and procedures for monitoring and evaluating the project, was positively associated with project performance. This study provides additional insight into our understanding of upper‐management support in new product development. The study suggests that upper‐managers can over control with the wrong type of controls, and suggests effective ways of implementing participative and interactive control mechanisms.     

On the Effects of Uncertainty on Investment Timing and Option Value

This article demonstrates that when the relationship between systematic risk and project value is taken into account, the sensitivity of investments with respect to volatility changes dramatically. By taking cash flows as a fundamental variable, the article shows that the value of an option to invest can be decreasing in volatility, contradicting the conventional wisdom. Second, the recent proposition, according to which the expected time to invest is U-shaped, does not generally hold; the expected time and the cash flow trigger are likely to be always increasing in volatility.     

ECONOMIC APPRAISAL OF TRANSPORT PROJECTS: A Manual With Case Studies by Hans A. Adler

A challenge to developing data-driven approaches in finance and trading is the limited availability of data because periods of instability, such as during financial market crises, are relatively rare. This study applies a stability-oriented approach (SOA) based on statistical tests to compare data for the current period to a past set of data for a stable period, providing higher reliability due to a more abundant source of data. Based on an SOA, this study uses an artificial neural network (ANN), which is one of the commonly applied machine learning algorithms, for simultaneously forecasting the volatility and classifying the level of market stability. In addition, this study develops a dynamic target volatility strategy for asset allocation using an ANN to enhance the ability of a target volatility strategy that is established for automatically allocating capital between a risky asset and a risk-free cash position. In order to examine the impact of the proposed strategy, the results are compared to the buy-and-hold strategy, the static asset allocation strategy, and the conventional target volatility strategy using different volatility forecasting methodologies. An empirical case study of the proposed strategy is simulated in both the Korean and U.S. stock markets.     

PDMA Success Measurement Project: Recommended Measures for Product Development Success and Failure

Success is not just elusive; it is also multifaceted and difficult to measure. A firm can assess the success or failure of a development project in any (or all) of many terms, including customer satisfaction, financial return, and technical advantage. To complicate matters, success may be measured not only at the level of the individual project, but also at the program level. With so many variables to consider and so many stakeholders involved, managers face a difficult challenge just deciding which measures are useful for measuring product development success. Recognizing that no single measure suffices for gauging the success of every product development project, Abbie Griffin and Albert L. Page hypothesize that the most appropriate set of measures for assessing project-level success depends on the project strategy. For example, the objectives (and thus, the success criteria) for a new product that creates an entirely new market will differ from those of a project that extends an existing product line. Similarly, they hypothesize that the appropriate measures of a product development program's overall success depend on the firm's innovation strategy. For example, a firm that values being first to market will measure success in different terms from those used by a firm that focuses on maintaining a secure market niche. To test these hypotheses, product development professionals were presented with six project strategy scenarios and four business strategy scenarios. For each project strategy scenario, participants were asked to select the four most useful measures of project success. For each business strategy scenario, participants were asked to choose the set of four measures that would provide the most useful overall assessment of product development success. The responses strongly support the idea that the most appropriate measures of project-level and program-level success depend on the firm's project strategy and business strategy, respectively. For example, customer satisfaction and customer acceptance were among the most useful customer-based measures of success for several project strategies, but market share was cited as the most useful customer-based measure for projects involving new-to-the-company products or line extensions. At the program level, firms with a business strategy that places little emphasis on innovation need to focus on measuring the efficiency of their product development program, while innovative firms need to assess the program's contribution to company growth.     

Hedging in currency futures: A Singapore dollar case study

In recent months the volatility of currency values, especially the changing value of the US Dollar against the Swiss Franc. Deutsche Mark, Japanese Yen and the Singapore Dollar has significantly increased the foreign exchange risk exposure of multinational corporations. This article looks at several different strategies which a corporate treasurer can consider for minimizing his risk exposure. Finally, two different borrowing strategies in the forward market which are based upon local currency (Singapore Dollar) and foreign currency (US Dollar) borrowing are compared. The results show that substantial cost savings can be obtained by selective borrowing.     

REAL OPTIONS VOLATILITY ESTIMATION WITH CORRELATED INPUTS

Real Options Analysis (ROA) provides a framework for valuing reactive and proactive managerial flexibility in investment decisions. Estimating the volatility parameter for a real options model is challenging because there are typically no historical returns for the underlying asset and no current market prices. A previously developed method of using simulation to estimate the volatility parameter for a real investment is demonstrated. The effects of serial price correlation and price-demand cross-correlation on volatility parameters developed with this method are explained. Finally, managerial implications of these findings are discussed.     

Statistical dependence in risk analysis for project networks using Monte Carlo methods

Monte Carlo simulation of project networks is increasingly used by engineering firms to analyze schedule/cost risk for bidding purposes. However, one serious methodological flaw of most Monte Carlo simulations is the assumption of statistical independence of activity durations in the network. In this paper, a method is proposed to model and quantify positive dependence between uncertainty distributions of activities. This method inherits the theoretically sound foundations of the rank correlation method, but provides a less cumbersome method to elicit dependency information from project engineers. Details of the methodology are described along with an example of project risk analysis in a manufacturing domain (shipbuilding).     

基于项目治理的城市轨道交通项目BT模式选择与运行效果

现有工程项目交易方式的选择通常考虑项目管理层面的因素,而忽略了项目治理层面相关因素的影响,这导致BT模式下工程项目交易效率较低,成为制约BT模式在我国城市轨道交通项目中推行的关键因素之一。为此,本文引入项目治理理论,提出应根据BT项目契约中的项目控制权强弱及与之匹配的风险分担的有效性划分出强BT、标准BT、弱BT三种项目交易模式,给出了按照项目控制权与风险分担相匹配的BT模式选择过程,并通过案例研究分析了这三种模式的运行效果,为城市轨道交通项目BT模式创新和优化提供了依据。     

Market Efficiency and Return Statistics: Evidence from Real Estate and Stock Markets Using a Present-Value Approach

This paper develops a methodology to identify asset price response to news in the framework of the Campbell–Shiller log-linear present-value equation. We further show that a slow price adjustment in real estate markets not only induces a high serial autocorrelation in excess returns, but also dampens the return volatility and the correlation with excess returns in other asset markets. Using Hong Kong real estate and stock market data, we find that the quarterly real estate price assimilates only about half the effect of market news, whereas the quarterly stock price incorporates the news fully. Our analysis identifies a cumulative price adjustment that recovers lost information in real estate returns due to market inefficiency and thereby restores the real estate return volatility and the correlation between real estate and stock markets.     

Evaluating Product Plans Using Real Options

Product planning helps a company to strategically plan its current and future product platforms and offer product variants in the marketplace. Product platforming is widely touted as a successful strategy for mass customization. However, due diligence should be exercised before implementing any product platform strategy. The product planning exercise should account for future uncertainties. Traditional financial tools such as the net present value (NPV) are static since they do not compensate for any exogenous and endogenous uncertainties during the course of the project. The crux of the problem lies in the evaluation model that is used for evaluating the product planning projects. While many view uncertainties in a product planning project as problematic, it can also be viewed as a source of new opportunities. We argue that uncertainties should be an integral part of the evaluation model. If the future possibilities (or strategic options) are not considered in the evaluation model, a corporation may face a “myopic syndrome”.

In this article, we consider two important product planning decisions—platform decisions and product variant decisions. The platform decision involves strategic selection of a concept product platform from various possible alternative concept product platforms. The product variant decision involves deciding how long a company should continue to offer its current product variant in the marketplace and whether the existing product variant should be discontinued, scaled down, or scaled up with additional product features. To address the two aforementioned decisions, we developed a real options–based methodology that considers technical, project implementation, and market-related uncertainties. The proposed methodology uses a binomial and quadranomial lattice approach to build a decision tree. Product planning decisions at various decision tree nodes are evaluated using a risk-neutral option valuation methodology. We demonstrate the working of the proposed methodology using an illustrative example.