A stochastic dynamic programming approach for pricing options on stock-index futures

The aim of this thesis is to price options on equity index futures with an application to standard options on S&P 500 futures traded on the Chicago Mercantile Exchange. Our methodology is based on stochastic dynamic programming, which can accommodate European as well as American options. The model accommodates dividends from the underlying asset. It also captures the optimal exercise strategy and the fair value of the option. This approach is an alternative to available numerical pricing methods such as binomial trees, finite differences, and ad-hoc numerical approximation techniques. Our numerical and empirical investigations demonstrate convergence, robustness, and efficiency. We use this methodology to value exchange-listed options. The European option premiums thus obtained are compared to Black's closed-form formula. They are accurate to four digits. The American option premiums also have a similar level of accuracy compared to premiums obtained using finite differences and binomial trees with a large number of time steps. The proposed model accounts for deterministic, seasonally varying dividend yield. In pricing futures options, we discover that what matters is the sum of the dividend yields over the life of the futures contract and not their distribution.

Quality-optimization algorithm based on stochastic dynamic programming for MPEG DASH video streaming

In contrast to traditional push-based protocols, adaptive streaming techniques like Dynamic Adaptive Streaming over HTTP (DASH) fix attention on the client, who dynamically requests different-quality portions of the content to cope with a limited and variable bandwidth but aiming at maximizing the quality perceived by the user. Since DASH adaptation logic at the client is not covered by the standard, we propose a solution based on Stochastic Dynamic Programming (SDP) techniques to find the optimal request policies that guarantee the users' Quality of Experience (QoE). Our algorithm is evaluated in a simulated streaming session and is compared with other adaptation approaches. The results show that our proposal outperforms them in terms of QoE, requesting higher qualities on average.

Stochastic dynamic programming for election timing: A game theory approach

In this paper, we consider dynamic programming for the election timing in the majoritarian parliamentary system such as in Australia, where the government has a constitutional right to call an early election. This right can give the government an advantage to remain in power for as long as possible by calling an election, when its popularity is high. On the other hand, the opposition's natural objective is to gain power, and it will apply controls termed as "boosts" to reduce the chance of the government being re-elected by introducing policy and economic responses. In this paper, we explore equilibrium solutions to the government, and the opposition strategies in a political game using stochastic dynamic programming. Results are given in terms of the expected remaining life in power, call and boost probabilities at each time at any level of popularity.

Dynamic simulation for closed loops in heating systems with decision-making support

Nowadays utilising the proper HVAC system is essential both in extreme weather conditions and dense buildings design. Hydraulic loops are the most common parts in all air conditioning systems. This article aims to investigate the performance of different hydraulic loop arrangements in variable flow systems. Technical, economic and environmental assessments have been considered in this process. A dynamic system simulation is generated to evaluate the system performance and an economic evaluation is conducted by whole life cost assessment. Moreover, environmental impacts have been studied by considering the whole life energy consumption, CO2 emission, the embodied energy and embodied CO2 of the system components. Finally, decision-making in choosing the most suitable hydraulic system among five well-known alternatives has been proposed.

ESMO Consensus Guidelines for management of patients with colon and rectal cancer. A personalized approach to clinical decision making

Colorectal cancer (CRC) is the most common tumour type in both sexes combined in Western countries. Although screening programmes including the implementation of faecal occult blood test and colonoscopy might be able to reduce mortality by removing precursor lesions and by making diagnosis at an earlier stage, the burden of disease and mortality is still high. Improvement of diagnostic and treatment options increased staging accuracy, functional outcome for early stages as well as survival. Although high quality surgery is still the mainstay of curative treatment, the management of CRC must be a multi-modal approach performed by an experienced multi-disciplinary expert team. Optimal choice of the individual treatment modality according to disease localization and extent, tumour biology and patient factors is able to maintain quality of life, enables long-term survival and even cure in selected patients by a combination of chemotherapy and surgery. Treatment decisions must be based on the available evidence, which has been the basis for this consensus conference-based guideline delivering a clear proposal for diagnostic and treatment measures in each stage of rectal and colon cancer and the individual clinical situations. This ESMO guideline is recommended to be used as the basis for treatment and management decisions.

Optimising weed control by considering disturbance

Mounting scientific evidence suggests newly imposed disturbance and/or alterations to existing disturbances facilitate invasion. Several empirical studies have explored the role of disturbance in invasion, but little work has been done to fit current understanding into a format useful for practical control efforts. We are working towards addressing this shortcoming by developing a metapopulation model couched in a decision theory framework. This approach has allowed us to investigate how incorporating the negative effects of disturbance on native vegetation into decision-making can change optimal control measures. In this paper, we present some preliminary results.

Improved Integrated Weed Management systems in transgenic farming landscapes

This project will develop and deliver improved integrated weed management strategies for weeds at risk of glyphosate resistance and species shift in transgenic farming landscapes. It will also facilitate the stewarship of glyphosate and transgenic technology, improving the sustainability of both the herbicide and the genes.

Integrated weed management approach to improve weed control efficiencies for sustainable rice production in dry-seeded systems

Weed management is the major challenge to the success of dry-seeded rice (DSR). A field study was conducted during the dry seasons of 2013 and 2014at the International Rice Research Institute to evaluate the performance of herbicides combined with mechanical weeding in DSR. The lowest weed density and biomass were found in the treatment oxadiazon followed by (fb) fenoxaprop+ethoxysulfuron fb 2,4-D fb mechanical weeding (MW) at 42 days after sowing (DAS). However, this treatment had similar weed density and biomass to the treatments oxadiazon fb bispyribac-sodium fb fenoxaprop+ethoxysulfuron fb 2,4-D,oxadiazon fb bispyribac-sodium fb 2,4-D, and oxadiazon fb MW (28 DAS) fb MW (42 DAS). The highest weed density and biomass were recorded in the treatment oxadiazon fb MW (28 DAS) and oxadiazon fb 2,4-D. Higher grain yield (5.3-5.8tha-1) was produced in the plots that received oxadiazon fb fenoxaprop+ethoxysulfuron fb 2,4-D fb MW(42 DAS) and oxadiazon fb bispyribac-sodium fb fenoxaprop+ethoxysulfuron fb 2,4-D. The results of this study provide sustainable weed management options to farmers growing DSR.

Simple rules to contain an invasive species with a complex life cycle and high dispersal capacity

Designing practical rules for controlling invasive species is a challenging task for managers, particularly when species are long-lived, have complex life cycles and high dispersal capacities. Previous findings derived from plant matrix population analyses suggest that effective control of long-lived invaders may be achieved by focusing on killing adult plants. However, the cost-effectiveness of managing different life stages has not been evaluated. We illustrate the benefits of integrating matrix population models with decision theory to undertake this evaluation, using empirical data from the largest infestation of mesquite (Leguminosae: Prosopis spp) within Australia. We include in our model the mesquite life cycle, different dispersal rates and control actions that target individuals at different life stages with varying costs, depending on the intensity of control effort. We then use stochastic dynamic programming to derive cost-effective control strategies that minimize the cost of controlling the core infestation locally below a density threshold and the future cost of control arising from infestation of adjacent areas via seed dispersal. Through sensitivity analysis, we show that four robust management rules guide the allocation of resources between mesquite life stages for this infestation: (i) When there is no seed dispersal, no action is required until density of adults exceeds the control threshold and then only control of adults is needed; (ii) when there is seed dispersal, control strategy is dependent on knowledge of the density of adults and large juveniles (LJ) and broad categories of dispersal rates only; (iii) if density of adults is higher than density of LJ, controlling adults is most cost-effective; (iv) alternatively, if density of LJ is equal or higher than density of adults, management efforts should be spread between adults, large and to a lesser extent small juveniles, but never saplings. Synthesis and applications.In this study, we show that simple rules can be found for managing invasive plants with complex life cycles and high dispersal rates when population models are combined with decision theory. In the case of our mesquite population, focussing effort on controlling adults is not always the most cost-effective way to meet our management objective.

Effect of crop establishment methods and weed control treatments on weed management, and rice yield

Lower water availability coupled with labor shortage has resulted in the increasing inability of growers to cultivate puddled transplanted rice (PTR). A field study was conducted in the wet season of 2012 and dry season of 2013 to evaluate the performance of five rice establishment methods and four weed control treatments on weed management, and rice yield. Grass weeds were higher in dry-seeded rice (DSR) as compared to PTR and nonpuddled transplanted rice (NPTR). The highest total weed density (225-256plantsm-2) and total weed biomass (315-501gm-2) were recorded in DSR while the lowest (102-129plantsm-2 and 75-387gm-2) in PTR. Compared with the weedy plots, the treatment pretilachlor followed by fenoxaprop plus ethoxysulfuron plus 2,4-D provided excellent weed control. This treatment, however, had a poor performance in NPTR. In both seasons, herbicide efficacy was better in DSR and wet-seeded rice. PTR and DSR produced the maximum rice grain yields. The weed-free plots and herbicide treatments produced 84-614% and 58-504% higher rice grain yield, respectively, than the weedy plots in 2012, and a similar trend was observed in 2013.

Integrated vector management for malaria control in Uganda: knowledge, perceptions and policy development.

BACKGROUND: Integrated vector management (IVM) is increasingly being recommended as an option for sustainable malaria control. However, many malaria-endemic countries lack a policy framework to guide and promote the approach. The objective of the study was to assess knowledge and perceptions in relation to current malaria vector control policy and IVM in Uganda, and to make recommendations for consideration during future development of a specific IVM policy. METHODS: The study used a structured questionnaire to interview 34 individuals working at technical or policy-making levels in health, environment, agriculture and fisheries sectors. Specific questions on IVM focused on the following key elements of the approach: integration of chemical and non-chemical interventions of vector control; evidence-based decision making; inter-sectoral collaboration; capacity building; legislation; advocacy and community mobilization. RESULTS: All participants were familiar with the term IVM and knew various conventional malaria vector control (MVC) methods. Only 75% thought that Uganda had a MVC policy. Eighty percent (80%) felt there was inter-sectoral collaboration towards IVM, but that it was poor due to financial constraints, difficulties in involving all possible sectors and political differences. The health, environment and agricultural sectors were cited as key areas requiring cooperation in order for IVM to succeed. Sixty-seven percent (67%) of participants responded that communities were actively being involved in MVC, while 48% felt that the use of research results for evidence-based decision making was inadequate or poor. A majority of the participants felt that malaria research in Uganda was rarely used to facilitate policy changes. Suggestions by participants for formulation of specific and effective IVM policy included: revising the MVC policy and IVM-related policies in other sectors into a single, unified IVM policy and, using legislation to enforce IVM in development projects. CONCLUSION: Integrated management of malaria vectors in Uganda remains an underdeveloped component of malaria control policy. Cooperation between the health and other sectors needs strengthening and funding for MVC increased in order to develop and effectively implement an appropriate IVM policy. Continuous engagement of communities by government as well as monitoring and evaluation of vector control programmes will be crucial for sustaining IVM in the country.

Participatory modelling to support decision making in water management under uncertainty: Two comparative case studies in the Guadiana river basin, Spain.

A participatory modelling process has been conducted in two areas of the Guadiana river (the upper and the middle sub-basins), in Spain, with the aim of providing support for decision making in the water management field. The area has a semi-arid climate where irrigated agriculture plays a key role in the economic development of the region and accounts for around 90% of water use. Following the guidelines of the European Water Framework Directive, we promote stakeholder involvement in water management with the aim to achieve an improved understanding of the water system and to encourage the exchange of knowledge and views between stakeholders in order to help building a shared vision of the system. At the same time, the resulting models, which integrate the different sectors and views, provide some insight of the impacts that different management options and possible future scenarios could have. The methodology is based on a Bayesian network combined with an economic model and, in the middle Guadiana sub-basin, with a crop model. The resulting integrated modelling framework is used to simulate possible water policy, market and climate scenarios to find out the impacts of those scenarios on farm income and on the environment. At the end of the modelling process, an evaluation questionnaire was filled by participants in both sub-basins. Results show that this type of processes are found very helpful by stakeholders to improve the system understanding, to understand each others views and to reduce conflict when it exists. In addition, they found the model an extremely useful tool to support management. The graphical interface, the quantitative output and the explicit representation of uncertainty helped stakeholders to better understand the implications of the scenario tested. Finally, the combination of different types of models was also found very useful, as it allowed exploring in detail specific aspects of the water management problems.

The effects of job demands and low job control on work-family conflict: The role of fairness in decision making and management

The present study examined whether Perceptions of organizational fairness (the procedural and interactional components) were able to diminish the negative effects of high job demands and low job control on the balance between work and family. The study participants were 713 women working in long-term care for elderly people in Finland. The results showed that high job demands, low job control, and unfair decision making were associated with high levels of time-based work interference with family (WIF). Perceptions of organizational fairness were found to partially mediate the association between Job control and WIF In addition, fair treatment and management protected against WIF when demands were low but were unable to bluffer against the negative effects of high job demands. (C) 2008 Wiley Periodicals, Inc.