Real option projects with correlated uncertainties

Wrocław

Property developments are inherently uncertain and risky. As a result, several risk management techniques are adopted by property developers in the Australian property development sector to mitigate the impact of potential downside risks. However, uncertainty can create potential upside opportunities for property developers during the property development process which can be explored through flexibility/real options analysis. Several quantitative models and applications have been executed in the literature on flexibility/real options analysis, but practical adoption is still lacking because practitioners are yet to fully understand the theory and its potential benefits. In this paper, a conceptual model is developed to capture flexibilities/real options and linked to the property development process to determine the exact stages within the property development process where real options could be embedded to retain the potential for capturing future upside benefits from uncertainty. Through face to face semi-structured interviews with twelve different stakeholders in the Australian property development industry, thematic analysis and extensive literature review on real options theory, a conceptual model is developed. There are several flexibilities/real options naturally embedded at different stages of the property development process. Other flexibilities can be embedded in the development process deliberately by property developers with the intention of capitalising on upside opportunities in future. These flexibilities embedded at different stages of the development process has the potential to serve as a risk mitigation tool for property developers in Australian property development sector. The model can serve as a practical tool and a visual aid for property development practitioners and stakeholders to determine the exact stages in the property development process where real options are embedded and the specific types of options. It will also aid in deepening the understanding of practitioners regarding real options in property development and further enhance potential acceptance and adoption in the Australian property industry. The linkage to the property development process can enhance easy identification of flexibilities/real options at different stages of the property development process. A model that links real options to the different stages of the property development process is new in the literature.

Exploration geophysicists and geologists are familiar with the process of risk assessment and economic evaluation of oil and gas prospects. Many asset teams are required to conduct individual portfolio management exercises when competing for company resources. In the broader world of finance and economics, real options theory has developed into a sophisticated tool for evaluating and managing large investment portfolios of mixed assets with different risk characteristics. Although examples of option-based analysis have been documented in the oil and gas industry, many applications only address downstream operations. However, the influence and application of real options analysis throughout the entire E&P lifecycle has been limited. Before accepting real options as a common practice in any oil and gas company, a better understanding of this technically demanding process must be achieved. Specifically, in upstream applications of real options, explorationists require a basic understanding of the principles of real option theory before they can add this tool to their arsenal of oil and gas investment evaluation. In the competitive and dynamically changing business environment, success is often measured by management's flexibility and ability to adapt to changes. However, traditional approaches to decision-making assume a static, and rather linear, decision-making process with fixed outcomes. Valuation methods that rely on discounted cash flow (DCF) series, such as net present value (NPV), do not capture all the intrinsic attributes of an investment opportunity. Real options, as its name implies, uses the well-established rules of option theory to evaluate physical or real assets. For years the investment industry has used option theory to analyze financial assets or stocks and bonds. Only in the past decade has real options started to receive more general attention. Unlike the traditional DCF approach, real options assume a dynamic series of future decisions, which provide flexibility to adapt to given changes in …

This thesis presents research on scheduling in an uncertain environment, which forms a part of the rolling stock life cycle logistics applied research and development program funded by Dutch railway industry companies. The focus therefore lies on scheduling of maintenance operations on rolling stock in the railway industry. The first chapter describes some of the history of the Dutch railways, focusing on the rolling stock used, and it introduces the context in which NedTrain, a major Dutch rolling stock maintenance company, operates. While maintenance of rolling stock is not a new problem, recent changes in the field are identified in this chapter which introduce new challenges: the first is the declining involvement of maintenance experts in the procurement of new rolling stock, the second is the on-going demand for increasing efficiency. Based on this discussion, the goal of this thesis is to devise a method with which schedules can be created based on a flexible process. The schedules resulting from this method are to be both flexible, meaning that they can be adapted easily, and robust, meaning that they are resilient to the effects of uncertain events. Lastly, our goal is to create the schedules in such a way that the effects of disturbances in one team have little or no effect on any other teams in the same workshop. Chapter 2 examines existing research in the context of the formulated research goals. It is shown that the well-known Resource-Constrained Project Scheduling Problem (RCPSP) can be mapped to the problem of scheduling maintenance tasks on trains in the NedTrain workshops. The most important methods to solve the RCPSP are discussed, among which are many exact methods. Both the scale of the problem and the requirement of having a flexible schedule instead of a fixed time assignment for the tasks prohibit using these methods. Among the heuristic methods discussed, the Precedence Constraint Posting method turns out to be an especially good fit: it is able to solve large-sized problems very quickly, and it uses a Simple Temporal Network (STN) as a way of representing many different solutions to the original problem, offering a lot of flexibility. Based on the research discussed, research questions are formulated to answer the research goals. - The first question asks how to define criteria encapsulating the notion of flexibility as posed by our research goals, and how to measure the flexibility of a schedule. - The second question asks how we can make the best use of available flexibility to attain robustness. - The third question asks if there is also a way to extend the concept of temporal flexibility to include a form of sequential flexibility. - The last question asks how we can use our work on robustness to decouple schedules, ensuring that disturbances in the schedule for one agent have no impact on any other agents. The third chapter investigates criteria corresponding to our intuitive notion of flexibility in scheduling. The concept of interval schedules serves as a basis for this investigation: the idea is that each task in the schedule is assigned an interval from which its start time can be picked, and the length of all these intervals serves as a representation for the flexibility of the schedule. We show that flexibility measures in existing research lead to an over-estimation of the total available flexibility, because dependencies between tasks are not taken into account properly: simply adding the interval sizes for two dependent tasks causes over-estimation, because the picked time for one task can reduce the interval size for another task. Our first major contribution is an independence requirement for the creation of these intervals: we state that intervals should be constructed in such a way that any choice in one interval has no impact on the available choices in any of the other intervals. Our second major contribution is a method to actually construct such intervals, which results in a valid interval schedule for an \stn, allowing efficient schedule execution under dynamic circumstances. Additionally, we note that an interval schedule can also serve as a mechanism to decouple a schedule, giving a partial answer to the last research question. In the fourth chapter, we investigate how to make use of the available flexibility to ensure that schedules are robust. We show that having a maximal total amount of flexibility does not imply that the schedule is as robust as possible: maximization might lead to a very skewed distribution of flexibility over the schedule. Different ways of distributing flexibility over a schedule are proposed and analyzed in an experimental setting. From the experiments it can be clearly concluded that sacrificing some of the total flexibility to improve the distribution of flexibility can have a positive influence on the robustness of the schedule. We also propose a different maximization strategy: one which maximizes the minimum of the interval sizes for the schedule. This strategy is shown to work especially well for small delays. So far we only discussed strategies concerning temporal flexibility, i.e., those in which start times remain flexible instead of fixed. Chapter 5 introduces a novel representation of solutions for planning problems in which not all ordering decisions needed to avoid resource contention are made in advance. This is achieved by grouping tasks which need to be executed sequentially together, in such a way that either ordering of the tasks remains feasible during execution time. An analysis using simulation experiments shows that this technique results in higher robustness, at the cost of somewhat lower resource utilization. The proposed algorithm to construct such schedules offers limited control over the size of the grouped tasks. The experiments show a slightly counter-intuitive results: schedules with larger groups offer lower robustness than those with smaller groups. A plausible explanation is the fact that delays can occur at any place in a schedule. Having multiple smaller groups instead of a few very large ones increases the chance that such a delay can be compensated for using a task group.

Health is characterized by the ability to continuously adapt in varying circumstances where multiple mechanisms of system flexibility are involved. Their ability to adapt can act as an indicator for maintenance or improvement of physiological function. The term ‘phenotypic flexibility` expresses the cumulative ability of overarching physiological processes (e.g. metabolism, inflammation, oxidation) to return to homeostatic levels after short-term perturbations. The EU NutriTech project aimed to demonstrate and validate that phenotypic flexibility is a sensitive biomarker of metabolic resilience and that it can serve as a measure of health. A key factor is determining the physiological relevance of specific changes in phenotypic flexibility in a healthy (sub)population, for example in response to a dietary intervention. Ideally, this is pursued by validation against established markers of health, but these do not exist. Alternatively, modifications in challenge responses can be correlated to established markers of disease or to long-term health outcomes (disease risk, longevity) in cohort studies for validation purposes which is not easy. Therefore, new data integration methodology was introduced based on network-biology with the objective to allow for validation of biomarkers across studies to enhance scientific evidence for effects of dietary interventions on identified markers of phenotypic flexibility. Network analysis enables integration and visualization of multi-layered experimental datasets and prior knowledge. Data from 4 human studies focusing on phenotypic flexibility were available in the phenotype database and used for a multi-study analysis providing a metabolic syndrome reference network. When this reference network is combined with the NutriTech human study data, the resulting visualization shows how the caloric restriction diet has impacted biomarkers of phenotypic flexibility related to metabolic syndrome. The NutriTech data integration pipeline offers a sustainable knowledge resource and toolbox for assessment of health effects of nutritional interventions. Acknowledgements : Financed by the European Commission in the 7th Framework Programme FP7, Grant agreement no: 289511

Distributed Video Coding (DVC) is a new paradigm for video compression based on the information theoretical results of Slepian and Wolf (SW), and Wyner and Ziv (WZ). While conventional coding has a rigid complexity allocation as most of the complex tasks are performed at the encoder side, DVC enables a flexible complexity allocation between the encoder and the decoder. The most novel and interesting case is low complexity encoding and complex decoding, which is the opposite of conventional coding. While the latter is suitable for applications where the cost of the decoder is more critical than the encoder's one, DVC opens the door for a new range of applications where low complexity encoding is required and the decoder's complexity is not critical. This is interesting with the deployment of small and battery-powered multimedia mobile devices all around in our daily life. Further, since DVC operates as a reversed-complexity scheme when compared to conventional coding, DVC also enables the interesting scenario of low complexity encoding and decoding between two ends by transcoding between DVC and conventional coding. More specifically, low complexity encoding is possible by DVC at one end. Then, the resulting stream is decoded and conventionally re-encoded to enable low complexity decoding at the other end. Multiview video is attractive for a wide range of applications such as free viewpoint television, which is a system that allows viewing the scene from a viewpoint chosen by the viewer. Moreover, multiview can be beneficial for monitoring purposes in video surveillance. The increased use of multiview video systems is mainly due to the improvements in video technology and the reduced cost of cameras. While a multiview conventional codec will try to exploit the correlation among the different cameras at the encoder side, DVC allows for separate encoding of correlated video sources. Therefore, DVC requires no communication between the cameras in a multiview scenario. This is an advantage since communication is time consuming (i.e. more delay) and requires complex networking. Another appealing feature of DVC is the fact that it is based on a statistical framework. Moreover, DVC behaves as a natural joint source-channel coding solution. This results in an improved error resilience performance when compared to conventional coding. Further, DVC-based scalable codecs do not require a deterministic knowledge of the lower layers. In other words, the enhancement layers are completely independent from the base layer codec. This is called the codec-independent scalability feature, which offers a high flexibility in the way the various layers are distributed in a network. This thesis addresses the following topics: First, the theoretical foundations of DVC as well as the practical DVC scheme used in this research are presented. The potential applications for DVC are also outlined. DVC-based schemes use conventional coding to compress parts of the data, while the rest is compressed in a distributed fashion. Thus, different conventional codecs are studied in this research as they are compared in terms of compression efficiency for a rich set of sequences. This includes fine tuning the compression parameters such that the best performance is achieved for each codec. Further, DVC tools for improved Side Information (SI) and Error Concealment (EC) are introduced for monoview DVC using a partially decoded frame. The improved SI results in a significant gain in reconstruction quality for video with high activity and motion. This is done by re-estimating the erroneous motion vectors using the partially decoded frame to improve the SI quality. The latter is then used to enhance the reconstruction of the finally decoded frame. Further, the introduced spatio-temporal EC improves the quality of decoded video in the case of erroneously received packets, outperforming both spatial and temporal EC. Moreover, it also outperforms error-concealed conventional coding in different modes. Then, multiview DVC is studied in terms of SI generation, which differentiates it from the monoview case. More specifically, different multiview prediction techniques for SI generation are described and compared in terms of prediction quality, complexity and compression efficiency. Further, a technique for iterative multiview SI is introduced, where the final SI is used in an enhanced reconstruction process. The iterative SI outperforms the other SI generation techniques, especially for high motion video content. Finally, fusion techniques of temporal and inter-view side informations are introduced as well, which improves the performance of multiview DVC over monoview coding. DVC is also used to enable scalability for image and video coding. Since DVC is based on a statistical framework, the base and enhancement layers are completely independent, which is an interesting property called codec-independent scalability. Moreover, the introduced DVC scalable schemes show a good robustness to errors as the quality of decoded video steadily decreases with error rate increase. On the other hand, conventional coding exhibits a cliff effect as the performance drops dramatically after a certain error rate value. Further, the issue of privacy protection is addressed for DVC by transform domain scrambling, which is used to alter regions of interest in video such that the scene is still understood and privacy is preserved as well. The proposed scrambling techniques are shown to provide a good level of security without impairing the performance of the DVC scheme when compared to the one without scrambling. This is particularly attractive for video surveillance scenarios, which is one of the most promising applications for DVC. Finally, a practical DVC demonstrator built during this research is described, where the main requirements as well as the observed limitations are presented. Furthermore, it is defined in a setup being as close as possible to a complete real application scenario. This shows that it is actually possible to implement a complete end-to-end practical DVC system relying only on realistic assumptions. Even though DVC is inferior in terms of compression efficiency to the state of the art conventional coding for the moment, strengths of DVC reside in its good error resilience properties and the codec-independent scalability feature. Therefore, DVC offers promising possibilities for video compression with transmission over error-prone environments requirement as it significantly outperforms conventional coding in this case.

Finance: Longevity Risk Management for Individual Investors Optimal SP-Based Personal Financial Planning with Intermediate and Long Term Goals Intertemporal Surplus Management with Jump Risks Jump-Diffusion Risk-Sensitive Benchmarked Asset Management Dynamic Portfolio Optimization Under Regime-Based Firm Strength Options Portfolio Management as a Chance Constrained Problem Stochastic Models for Optimizing Immunization Strategies in Fixed-Income Security Portfolios Under Some Sources of Uncertainty Stochastic Programming and Optimization in Horserace Betting Production Planning and Logistics: Multi-Stage Stochastic Programming for Natural Gas Infrastructure Design with a Production Perspective Stochastic Programming Model for Optimizing the Production of Farmed Atlantic Salmon Prioritizing Network Interdiction of Nuclear Smuggling Sawmill Production Planning Under Uncertainty: Modelling and Solution Approaches Energy: An Electricity Procurement Model with Energy and Peak Charges Value of Flexibility in Hydroelectric Reservoir Operations Multi-Lag Benders Decomposition for Power Generation Planning with Nonanticipativity Constraints on the Dispatch of LNG Thermal Plants Theory Papers: Stochastic Second-Order Cone Programming in Mobile Ad-Hoc Networks Stochastic Frequency Assignment Problem.

In this paper we discuss the real options valuation of investments in flexible power plants. After the energy supply crisis lived in 2001, new investments in gas fired power plants were made to increase electricity generation in the short term, due to the reduced maturity time of these investments. More recently, the nationalization of the Bolivian natural gas reserves raised uncertainties over the prices and supply of this commodity. First we analyze an operating power plant which can switch fuels among natural gas and oil. Second, we study the option to temporarily shut down the plant. Finally, we assess the interaction between these two flexibilities. Valuation involves the use of two quadranomial trees, supporting co rrelated GBM for the fuel prices.

This paper compares two well-known approaches for valuing a risky investment using real options theory: contingent claims (CC) with risk neutral valuation and dynamic programming (DP) using a constant risk adjusted discount rate. Both approaches have been used in valuing forest assets. A proof is presented which shows that, except under certain restrictive assumptions, DP using a constant discount rate and CC will not yield the same answers for investment value. A few special cases are considered for which CC and DP with a constant discount rate are consistent with each other. An optimal tree harvesting example is presented to illustrate that the values obtained using the two approaches can differ when we depart from these special cases to a more realistic scenario. We conclude that for real options problems the CC approach is preferred when data exists (such as futures prices) that allow the estimation of the market price of risk or convenience yield. Even when such data do not exist we argue that the CC approach is preferred as it has the advantage of allowing the individual specification of the prices of different sources of risk.

Firms have developed climate change strategies over the last decade in response to rising regulatory, social and competitive pressures. Increasingly, these strategies include the development of new products and services (P&S) to reducing the environmental impact of the firm and its customers. In this paper, I explore how managerial interpretation of climate change has evolved over time and how these changes in interpretation are associated with innovation outcomes. The existing literature suggests that interpreting environmental challenges as opportunities is more likely to lead to open and innovative strategies. Using qualitative survey data on 99 Global 500 firms over the period 2003 to 2009, I find that threat-based interpretation can in fact lead to positive innovation outcomes at early stages of new P&S development. I identify three main mechanisms through which the detailed identification of threats encourages innovation in response to climate change. Furthermore, I develop a temporal dimension to the relationship between interpretation and stages of P&S development. I find that at advanced stages of P&S development, a balanced and opportunity-focused interpretation becomes more important. The results imply that managerial interpretation can provide firms with added flexibility to provide innovative responses to social and environmental challenges. But the relationship between interpretation and innovation is not static, nor is it a question of threat or opportunity interpretation but a combination of the two at different times that provides flexibility.

Education has an important role in influencing the advancement of a nation's civilization. A nation that has good education tends to be an advanced nation in civilization, science and technology, social economy, as well as culture. One of the educational problems is the need for adjustment and improvement of educational program material so that it can flexibly move along with the demands of the workforce and the changing demands of people's lives. The implementation of School-Based Management (SBM) is essentially the granting of greater autonomy to schools with the ultimate goal of improving the quality of the results of the implementation of education so that it can produce actual achievements through a well established managerial process. School-based management is the granting of broad autonomy at the level of the education unit in order to be able to manage resources and sources of funds and allocate according to the level of need. The aim of school-based management is to improve the efficiency of education quality by independence and flexibility in managing existing resources. Components in school-based management include management of curriculum and teaching programs, management of teaching staff, management of students, financial management and financing, management of educational facilities and infrastructure, public relations management and special service management. Supporting factors for the success of the first school-based management, the demands of a considerable democratic life from the people in the reform era. Second, the application of Law No. 22 of 1999 concerning Regional Government which emphasizes the autonomy of government at the district / city level. Third, there is a school committee that functions to help implement the Social Safety Net (JPS) program in many schools. Fourth, there is a desire by the government to increase community participation in education by increasing the duties, functions and roles of the Education Provider Assistance Agency (BP3). Factors that become obstacles in running school-based management come from students, educators, infrastructure and community participation.

This study describes the systematic creation, application and evaluation of a comprehensive framework for the design of distance graduate programmes, the goal of which is to inform decision-making for sustainable curricula that suit the growing demand for flexible learning options. A wide range of challenges face educators, and existing models appear to be insufficient to guide such endeavours. Successful distance learning is rooted in the values of the institution and requires a significant amount of organizational support, needs assessment of stakeholders, strategic planning, implementation and evaluation. This first international study of distance masters degree programmes in Tourism and Hospitality Management (TH triangulating data by adding the perspective of traditional instructors transitioning into a blended learning format. This study provides a robust curriculum model linking new findings and rich eclectic sources that can assist distance programme planners in the selection of technologyenhanced approaches to meet the unique needs and interests of learners while balancing change. Extending the academic plan of Stark and Lattuca (1997, 2009), this timely study offers a design framework to formatively stimulate quality interaction, foster high-level thinking and motivate both learners and instructors in a student-centred paradigm. Holistic design, not technology alone, opens the way to enhancing flexibility and programme competitiveness and resilience in a borderless academic community.

Objective To explore the application and effect of flexible management in emergency nursing management. Methods Emergency department began to implement comprehensive flexible management as the core of nursing management measures since September 2012. We aimed to create a People-oriented culture, an autonomous management platform and a flexible motivational mechanism. Results After implemented flexible nursing management, the rate of good performance of emergency nurses in theory knowledge, skills assessment and their job satisfaction were 82. 14% , 89.29% and 92.86% , respectively, which were higher than 57.69% , 61.54% and 65.38% before the implementation. The differences were statistically significant （ X2 = 3. 865,4. 262,4. 693, respectively ; P 〈 0. 05 ）. Conclusions Implemented comprehensive flexible nursing management can meet nurses＇ physiological, psychosocial and social needs. It embodies the concept of a human-being-oriented management and can improve the nurses＇ working enthusiasm and creativity. It also makes nurses to provide the patients with better care, and moderate the relationship between nurses and patients, as well as improving the management effect. Key words: Emergency Room, hospital; Nursing administration research; Flexible management

The belief-desire-intention (BDI) model is one of the most widely used for developing agents. One of its benefits is the flexibility of choosing among different plans to achieve a goal and, to leverage this benefit, a particular algorithm that makes this choice must be selected. Although many techniques have been proposed addressing the plan selection process -- as well as other aspects of BDI agents -- they require many customisations and adaptations to be used in particular applications, thus requiring expert knowledge to be adopted, which is a real barrier to the large-scale adoption of this kind of agent technology. We thus in this paper propose a model-driven approach that allows modelling agents based on an extended BDI model (inspired by the Tropos meta-model) and automatically generating source code that implements agents with the ability of selecting plans. As this plan selection process typically involves analysing plan side effects, e.g. cost of execution, in the context of current agent preferences, our approach uses a preference-based plan selection process over what we refer to as softgoals. This process relies on the multi-attribute utility theory, taking into account the uncertainty of plan outcomes. We evaluate our approach experimentally.

This paper investigates the problem of controlling a team of quadrotors that cooperatively transport a common payload. The main contribution of this study is to propose a cooperative control algorithm based on a decentralized algorithm. This strategy is comprised of two main steps: the first one is calculating the basic control vectors for each quadrotor using Moore–Penrose theory aiming at cooperative transport of an object and the second one is combining these vectors with individual control vectors, which are obtained from a closed-loop non-linear robust controller. In this regard, a nonlinear robust controller is designed based on Second Order Sliding Mode (SOSMC) approach using Extended Kalman-Bucy Filter (EKBF) to estimate the unmeasured states which is capable of facing external disturbances. The distinctive features of this approach include robustness against model uncertainties along with high flexibility in designing the control parameters to have an optimal solution for the nonlinear dynamics of the system. Design of the controller is based on Lyapunov method which can provide the stability of the end-effecter during the tracking of the desired trajectory. Finally, simulation results are given to illustrate the effectiveness of the proposed method for the cooperative quadrotors to transport a common payload in various maneuvers.