48,624 research outputs found
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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
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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
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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
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