Model specification and forecasting foreign exchange rates with vector autoregressions

This study examines the forecasting accuracy of alternative vector autoregressive models each in a seven-variable system that comprises in turn of daily, weekly and monthly foreign exchange (FX) spot rates. The vector autoregressions (VARs) are in non-stationary, stationary and error-correction forms and are estimated using OLS. The imposition of Bayesian priors in the OLS estimations also allowed us to obtain another set of results. We find that there is some tendency for the Bayesian estimation method to generate superior forecast measures relatively to the OLS method. This result holds whether or not the data sets contain outliers. Also, the best forecasts under the non-stationary specification outperformed those of the stationary and error-correction specifications, particularly at long forecast horizons, while the best forecasts under the stationary and error-correction specifications are generally similar. The findings for the OLS forecasts are consistent with recent simulation results. The predictive ability of the VARs is very weak.

The design of a real-time nowcasting system for localised weather

National meteorological offices are largely concerned with synoptic-scale forecasting where weather predictions are produced for a whole country for 24 hours ahead. In practice, many local organisations (such as emergency services, construction industries, forestry, farming, and sports) require only local short-term, bespoke, weather predictions and warnings. This thesis shows that the less-demanding requirements do not require exceptional computing power and can be met by a modern, desk-top system which monitors site-specific ground conditions (such as temperature, pressure, wind speed and direction, etc) augmented with above ground information from satellite images to produce `nowcasts'. The emphasis in this thesis has been towards the design of such a real-time system for nowcasting. Local site-specific conditions are monitored using a custom-built, stand alone, Motorola 6809 based sub-system. Above ground information is received from the METEOSAT 4 geo-stationary satellite using a sub-system based on a commercially available equipment. The information is ephemeral and must be captured in real-time. The real-time nowcasting system for localised weather handles the data as a transparent task using the limited capabilities of the PC system. Ground data produces a time series of measurements at a specific location which represents the past-to-present atmospheric conditions of the particular site from which much information can be extracted. The novel approach adopted in this thesis is one of constructing stochastic models based on the AutoRegressive Integrated Moving Average (ARIMA) technique. The satellite images contain features (such as cloud formations) which evolve dynamically and may be subject to movement, growth, distortion, bifurcation, superposition, or elimination between images. The process of extracting a weather feature, following its motion and predicting its future evolution involves algorithms for normalisation, partitioning, filtering, image enhancement, and correlation of multi-dimensional signals in different domains. To limit the processing requirements, the analysis in this thesis concentrates on an `area of interest'. By this rationale, only a small fraction of the total image needs to be processed, leading to a major saving in time. The thesis also proposes an extention to an existing manual cloud classification technique for its implementation in automatically classifying a cloud feature over the `area of interest' for nowcasting using the multi-dimensional signals.

The Application of Geographic Information Systems to climate change & land evaluation : a study of the effects of climate change upon crop productivity in a sub-tropical environment

This research investigates the contribution that Geographic Information Systems (GIS) can make to the land suitability process used to determine the effects of a climate change scenario. The research is intended to redress the severe under representation of Developing countries within the literature examining the impacts of climatic change upon crop productivity. The methodology adopts some of the Intergovernmental Panel on Climate Change (IPCC) estimates for regional climate variations, based upon General Circulation Model predictions (GCMs) and applies them to a baseline climate for Bangladesh. Utilising the United Nations Food & Agricultural Organisation's Agro-ecological Zones land suitability methodology and crop yield model, the effects of the scenario upon agricultural productivity on 14 crops are determined. A Geographic Information System (IDRISI) is adopted in order to facilitate the methodology, in conjunction with a specially designed spreadsheet, used to determine the yield and suitability rating for each crop. A simple optimisation routine using the GIS is incorporated to provide an indication of the 'maximum theoretical' yield available to the country, should the most calorifically significant crops be cultivated on each land unit both before and after the climate change scenario. This routine will provide an estimate of the theoretical population supporting capacity of the country, both now and in the future, to assist with planning strategies and research. The research evaluates the utility of this alternative GIS based methodology for the land evaluation process and determines the relative changes in crop yields that may result from changes in temperature, photosynthesis and flooding hazard frequency. In summary, the combination of a GIS and a spreadsheet was successful, the yield prediction model indicates that the application of the climate change scenario will have a deleterious effect upon the yields of the study crops. Any yield reductions will have severe implications for agricultural practices. The optimisation routine suggests that the 'theoretical maximum' population supporting capacity is well in excess of current and future population figures. If this agricultural potential could be realised however, it may provide some amelioration from the effects of climate change.

A production planning system for plastic footwear in a seasonal market

Modern injection-moulding machinery which produces several, pairs of plastic footwear at a time brought increased production planning problems to a factory. The demand for its footwear is seasonal but the company's manning policy keeps a fairly constant production level thus determining the aggregate stock. Production planning must therefore be done within the limitations of a specified total stock. The thesis proposes a new production planning system with four subsystems. These are sales forecasting, resource planning, and two levels of production scheduling: (a) aggregate decisions concerning the 'manufacturing group' (group of products) to be produced in each machine each week, and (b) detailed decisions concerning the products within a manufacturing group to be scheduled into each mould-place. The detailed scheduling is least dependent on improvements elsewhere so the sub-systems were tackled in reverse order. The thesis concentrates on the production scheduling sub-systems which will provide most. of the benefits. The aggregate scheduling solution depends principally on the aggregate stocks of each manufacturing group and their division into 'safety stocks' (to prevent shortages) and 'freestocks' (to permit batch production). The problem is too complex for exact solution but a good heuristic solution, which has yet to be implemented, is provided by minimising graphically immediate plus expected future costs. The detailed problem splits into determining the optimal safety stocks and batch quantities given the appropriate aggregate stocks. It.is found that the optimal safety stocks are proportional to the demand. The ideal batch quantities are based on a modified, formula for the Economic Batch Quantity and the product schedule is created week by week using a priority system which schedules to minimise expected future costs. This algorithm performs almost optimally. The detailed scheduling solution was implemented and achieved the target savings for the whole project in favourable circumstances. Future plans include full implementation.

Cationic ring opening polymerisation (CROP) of oxetane and its derivatives using oxonium derived initiators

Several cationic initiator systems were developed and used to polymerise oxetane with two oxonium ion initiator systems being investigated in depth. The first initiator system was generated by the elimination of a chloride group from a chloro methyl ethyl ether. Adding a carbonyl co-catalyst to a carbocationic centre generated the second initiator system. It was found that the anion used to stabilise the initiator was critical to the initial rate of polymerisation of oxetane with hexafluoroantimonate resulting in the fastest polymerisations. Both initiator systems could be used at varying monomer to initiator concentrations to control the molecular number average, Mn, of the resultant polymer. Both initiator systems showed living characteristics and were used to polymerise further monomers and generate higher molecular weight material and block copolymers. Oxetane and 3,3-dimethyl oxetane can both be polymerised using either oxonium ion initiator system in a variety of DCM or DCM/1,4-dioxane solvent mixtures. The level of 1,4-dioxane does have an impact on the initial rate of polymerisation with higher levels resulting in lower initial rates of polymerisation but do tend to result in higher polydispersities. The level of oligomer formation is also reduced as the level of 1,4-dioxane is increased. 3,3-bis-bromomethyl oxetane was also polymerised but a large amount of hyperbranching was seen at the bromide site resulting in a difficult to solvate polymer system. Multifunctional initiator systems were also generated using the halide elimination reactions with some success being achieved with 1,3,5-tris-bromomethyl-2,4,6-tris-methyl-benzene derived initiator system. This offered some control over the molecular number average of the resultant polymer system.

A solar powered liquid-desiccant cooling system for greenhouses

Liquid desiccant systems are of potential interest as a means of cooling greenhouses to temperatures below those achieved by conventional means. However, only very little work has been done on this technology with previous workers focussing on the cooling of human dwellings using expensive desiccants such as lithium salts. In this study we are designing a system for greenhouse cooling based on magnesium chloride desiccant which is an abundant and non-toxic substance. Magnesium chloride is found in seawater, for example, and is a by-product from solar salt works. We have carried out a detailed experimental study of the relevant properties of magnesium rich solutions. In addition we have constructed a test rig that includes the main components of the cooling system, namely a dehumidifier and solar regenerator. The dehumidifier is a cross-flow device that consists of a structured packing made of corrugated cellulose paper sheets with different flute angles and embedded cooling tubes. The regenerator is of the open type with insulated backing and fabric covering to spread the flow of desiccant solution. Alongside these experiments we are developing a mathematical model in gPROMS® that combines and simulates the heat and mass transfer processes in these components. The model can be applied to various geographical locations. Here we report predictions for Havana (Cuba) and Manila (Philippines), where we find that average wet-bulb temperatures can be lowered by 2.2 and 3°C, respectively, during the month of May.