Investment Risk Appraisal

Standard financial techniques neglect extreme situations and regards large market shifts as too unlikely to matter. This approach may account for what occurs most of the time in the market, but the picture it presents does not reflect the reality, as the major events happen in the rest of the time and investors are ‘surprised’ by ‘unexpected’ market movements. An alternative fuzzy approach permits fluctuations well beyond the probability type of uncertainty and allows one to make fewer assumptions about the data distribution and market behaviour. Fuzzifying the present value criteria, we suggest a measure of the risk associated with each investment opportunity and estimate the project’s robustness towards market uncertainty. The procedure is applied to thirty-five UK companies and a neural network solution to the fuzzy criterion is provided to facilitate the decision-making process. Finally, we discuss the grounds for classical asset pricing model revision and argue that the demand for relaxed assumptions appeals for another approach to modelling the market environment

Orbiting deep space relay station. Volume 3: Implementation plan

An implementation plan for the Orbiting Deep Space Relay Station (ODSRS) is described. A comparison of ODSRS life cycle costs to other configuration options meeting future communication requirements is presented

Orbiting Deep Space Relay Station (ODSRS). Volume 1: Requirement determination

The deep space communications requirements of the post-1985 time frame are described and the orbiting deep space relay station (ODSRS) is presented as an option for meeting these requirements. Under current conditions, the ODSRS is not yet cost competitive with Earth based stations to increase DSN telemetry performance, but has significant advantages over a ground station, and these are sufficient to maintain it as a future option. These advantages include: the ability to track a spacecraft 24 hours per day with ground stations located only in the USA; the ability to operate at higher frequencies that would be attenuated by Earth's atmosphere; and the potential for building very large structures without the constraints of Earth's gravity

Mariner Mars 1964 telecommunication system

Radio, telemetry, and command subsystems of Mariner IV telecommunication syste

Local versus Global Search in Channel Graphs

Previous studies of search in channel graphs has assumed that the search is global; that is, that the status of any link can be probed by the search algorithm at any time. We consider for the first time local search, for which only links to which an idle path from the source has already been established may be probed. We show that some well known channel graphs may require exponentially more probes, on the average, when search must be local than when it may be global.Comment: i+13 pages, 2 figure

Soft computing in investment appraisal

Standard financial techniques neglect extreme situations and regards large market shifts as too unlikely to matter. Such approach accounts for what occurs most of the time in the market, but does not reflect the reality, as major events happen in the rest of the time and investors are ‘surprised’ by ‘unexpected’ market movements. An alternative fuzzy approach permits fluctuations well beyond the probability type of uncertainty and allows one to make fewer assumptions about the data distribution and market behaviour. Fuzzifying the present value criteria, we suggest a measure of the risk associated with each investment opportunity and estimate the project’s robustness towards market uncertainty. The procedure is applied to thirty-five UK companies traded on the London Stock Exchange and a neural network solution to the fuzzy criterion is provided to facilitate the decision-making process. Finally, we suggest a specific evolutionary algorithm to train a fuzzy neural net - the bidirectional incremental evolution will automatically identify the complexity of the problem and correspondingly adapt the parameters of the fuzzy network

Interoperable services based on activity monitoring in ambient assisted living environments

Ambient Assisted Living (AAL) is considered as the main technological solution that will enable the aged and people in recovery to maintain their independence and a consequent high quality of life for a longer period of time than would otherwise be the case. This goal is achieved by monitoring human’s activities and deploying the appropriate collection of services to set environmental features and satisfy user preferences in a given context. However, both human monitoring and services deployment are particularly hard to accomplish due to the uncertainty and ambiguity characterising human actions, and heterogeneity of hardware devices composed in an AAL system. This research addresses both the aforementioned challenges by introducing 1) an innovative system, based on Self Organising Feature Map (SOFM), for automatically classifying the resting location of a moving object in an indoor environment and 2) a strategy able to generate context-aware based Fuzzy Markup Language (FML) services in order to maximize the users’ comfort and hardware interoperability level. The overall system runs on a distributed embedded platform with a specialised ceiling- mounted video sensor for intelligent activity monitoring. The system has the ability to learn resting locations, to measure overall activity levels, to detect specific events such as potential falls and to deploy the right sequence of fuzzy services modelled through FML for supporting people in that particular context. Experimental results show less than 20% classification error in monitoring human activities and providing the right set of services, showing the robustness of our approach over others in literature with minimal power consumption

An empirical investigation of the relationship between the real economy and stock returns for the United States

This paper tests for the relationship between excess returns and economic growth rates in the U.S., using a Seemingly Unrelated Regression (SUR) approach. The system includes monthly data for inflation, consumption, narrow money supply and personal disposable income and each equation has up to 24-lagged Autoregressive terms. After removing the four major shocks associated with Black Monday, the Asian Crisis, “9·11” and its anniversary, we cannot find any ARCH behaviour in either the excess returns or the money series. The models are reduced to their parsimonious forms and the inflation and real consumption equations are corrected for ARCH. To make the result more robust we reduce our system to four equations by conditioning on income and testing the remaining equations for stability. The SUR model suggests strong long-run feedback between the financial sector and the real economy firstly through inflation, then consumption while the influence of real money supply appears transitory. Consumption is more sensitive to the economic variables in short and long run as compared with stock market windfalls