10,130 research outputs found

    An Evaluation of Overseas Oil Investment Projects under Uncertainty Using a Real Options Based Simulation Model

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    This paper applies real options theory to establish an overseas oil investment evaluation model that is based on Monte Carlo simulation and is solved by the Least Squares Monte-Carlo method. To better reflect the reality of overseas oil investment, our model has incorporated not only the uncertainties of oil price and investment cost but also the uncertainties of exchange rate and investment environment. These unique features have enabled our model to be best equipped to evaluate the value of oil overseas investment projects of three oil field sizes (large, medium, small) and under different resource tax systems (royalty tax and production sharing contracts). In our empirical setting, we have selected China as an investor country and Indonesia as an investee country as a case study. Our results show that the investment risks and project values of small sized oil fields are more sensitive to changes in the uncertainty factors than the large and medium sized oil fields. Furthermore, among the uncertainty factors considered in the model, the investment risk of overseas oil investment may be underestimated if no consideration is given of the impacts of exchange rate and investment environment. Finally, as there is an important trade-off between oil resource investee country and overseas oil investor, in medium and small sized oil investment negotiation the oil company should try to increase the cost oil limit in production sharing contract and avoid the term of a windfall profits tax to reduce the investment risk of overseas oil fields.Overseas Oil Investment, Project Value, Real Options, Least Squares Monte-Carlo

    Price Variations in a Stock Market With Many Agents

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    Large variations in stock prices happen with sufficient frequency to raise doubts about existing models, which all fail to account for non-Gaussian statistics. We construct simple models of a stock market, and argue that the large variations may be due to a crowd effect, where agents imitate each other's behavior. The variations over different time scales can be related to each other in a systematic way, similar to the Levy stable distribution proposed by Mandelbrot to describe real market indices. In the simplest, least realistic case, exact results for the statistics of the variations are derived by mapping onto a model of diffusing and annihilating particles, which has been solved by quantum field theory methods. When the agents imitate each other and respond to recent market volatility, different scaling behavior is obtained. In this case the statistics of price variations is consistent with empirical observations. The interplay between ``rational'' traders whose behavior is derived from fundamental analysis of the stock, including dividends, and ``noise traders'', whose behavior is governed solely by studying the market dynamics, is investigated. When the relative number of rational traders is small, ``bubbles'' often occur, where the market price moves outside the range justified by fundamental market analysis. When the number of rational traders is larger, the market price is generally locked within the price range they define.Comment: 39 pages (Latex) + 20 Figures and missing Figure 1 (sorry), submitted to J. Math. Eco

    Inventory drivers in a pharmaceutical supply chain

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    In recent years, inventory reduction has been a key objective of pharmaceutical companies, especially within cost optimization initiatives. Pharmaceutical supply chains are characterized by volatile and unpredictable demands –especially in emergent markets-, high service levels, and complex, perishable finished-good portfolios, which makes keeping reasonable amounts of stock a true challenge. However, a one-way strategy towards zero-inventory is in reality inapplicable, due to the strategic nature and importance of the products being commercialised. Therefore, pharmaceutical supply chains are in need of new inventory strategies in order to remain competitive. Finished-goods inventory management in the pharmaceutical industry is closely related to the manufacturing systems and supply chain configurations that companies adopt. The factors considered in inventory management policies, however, do not always cover the full supply chain spectrum in which companies operate. This paper works under the pre-assumption that, in fact, there is a complex relationship between the inventory configurations that companies adopt and the factors behind them. The intention of this paper is to understand the factors driving high finished-goods inventory levels in pharmaceutical supply chains and assist supply chain managers in determining which of them can be influenced in order to reduce inventories to an optimal degree. Reasons for reducing inventory levels are found in high inventory holding and scrap related costs; in addition to lost sales for not being able to serve the customers with the adequate shelf life requirements. The thesis conducts a single case study research in a multi-national pharmaceutical company, which is used to examine typical inventory configurations and the factors affecting these configurations. This paper presents a framework that can assist supply chain managers in determining the most important inventory drivers in pharmaceutical supply chains. The findings in this study suggest that while external and downstream supply chain factors are recognized as being critical to pursue inventory optimization initiatives, pharmaceutical companies are oriented towards optimizing production processes and meeting regulatory requirements while still complying with high service levels, being internal factors the ones prevailing when making inventory management decisions. Furthermore, this paper investigates, through predictive modelling techniques, how various intrinsic and extrinsic factors influence the inventory configurations of the case study company. The study shows that inventory configurations are relatively unstable over time, especially in configurations that present high safety stock levels; and that production features and product characteristics are important explanatory factors behind high inventory levels. Regulatory requirements also play an important role in explaining the high strategic inventory levels that pharmaceutical companies hold

    Stress Testing the Corporate Loans Portfolio of the Canadian Banking Sector

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    Stress testing, at its most general level, is an investigation of the performance of an entity under abnormal operating conditions. The authors focus on one set of entities--the Canadian banking sector--and investigate losses in the loans portfolio of this sector as a function of changing circumstances in the different industries in which these loans reside. These circumstances are characterized by means of one summary measure--sectoral probabilities of default--and this measure is modelled as a function of macroeconomic variables. Using this model, the authors assess the interrelationship between the macroeconomic environment and sectoral defaults, and perform a series of stress tests under different scenarios that are thought to be most pertinent to Canada. The tools underlying the authors' analysis are general and can be applied to other countries, as well as to other macroeconomic scenarios.Financial stability, Financial institutions

    The Value and Costs of Modularity: A Cognitive Perspective

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    This paper discusses the issue of modularity from a problem-solving perspective. Modularity is in fact a decomposition heuristic, through which a complex problem is decomposed into independent or quasi-independent sub-problems. By means of a model of problem decomposition, this paper studies the trade-offs of modularity: on the one hand finer modules increase the speed of search, but on the other hand they usually determine lock-in into sub-optimal solutions. How effectively to balance this trade-off depends upon the problem environment and its complexity and volatility: we show that in stationary and complex environments there exists an evolutionary advantage to over-modularization, while in highly volatile – though “simple” – en- vironments, contrary to usual wisdom, modular search is inefficient. The empirical relevance of our findings is discussed, especially with reference to the literature on system integration.modularity, problem solving, complex systems

    A Consumer-Centric Open Innovation Framework for Food and Packaging Manufacturing

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    This article has been archived following written permission from IGI Global.Closed innovation approaches have been employed for many years in the food industry. But, this sector recently perceives its end-user to be wary of radically new products and changes in consumption patterns. However, new product development involves not only the product itself but also the entire manufacturing and distribution network. In this paper, we present a new ICT based framework that embraces open innovation to place customers in the product development loop but at the same time assesses and eventually coordinates the entire manufacturing and supply chain. The aim is to design new food products that consumers will buy and at the same time ensure that these products will reach the consumer in time and at adequate quantity. On the product development side, our framework enables new food products that offer an integrated sensory experience of food and packaging, which encompass customization, healthy eating, and sustainability
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