Improving trading saystems using the RSI financial indicator and neural networks.

Proceedings of: 11th International Workshop on Knowledge Management and Acquisition for Smart Systems and Services (PKAW 2010), 20 August-3 September 2010, Daegu (Korea)Trading and Stock Behavioral Analysis Systems require efficient Artificial Intelligence techniques for analyzing Large Financial Datasets (LFD) and have become in the current economic landscape a significant challenge for multi-disciplinary research. Particularly, Trading-oriented Decision Support Systems based on the Chartist or Technical Analysis Relative Strength Indicator (RSI) have been published and used worldwide. However, its combination with Neural Networks as a branch of computational intelligence which can outperform previous results remain a relevant approach which has not deserved enough attention. In this paper, we present the Chartist Analysis Platform for Trading (CAST, in short) platform, a proof-of-concept architecture and implementation of a Trading Decision Support System based on the RSI and Feed-Forward Neural Networks (FFNN). CAST provides a set of relatively more accurate financial decisions yielded by the combination of Artificial Intelligence techniques to the RSI calculation and a more precise and improved upshot obtained from feed-forward algorithms application to stock value datasets.This work is supported by the Spanish Ministry of Industry, Tourism, and Commerce under the EUREKA project SITIO (TSI-020400-2009-148), SONAR2 (TSI-020100-2008-665 and GO2 (TSI-020400-2009-127). Furthermore, this work is supported by the General Council of Superior Technological Education of Mexico (DGEST). Additionally, this work is sponsored by the National Council of Science and Technology (CONACYT) and the Public Education Secretary (SEP) through PROMEP.Publicad

Temporal changes in total and size-fractioned chlorophyll-a in surface waters of three provinces in the Atlantic Ocean (September to November) between 2003 and 2010

Phytoplankton total chlorophyll concentration (TCHLa) and phytoplankton size structure are two important ecological indicators in biological oceanography. Using high performance liquid chromatography (HPLC) pigment data, collected from surface waters along the Atlantic Meridional Transect (AMT), we examine temporal changes in TCHLa and phytoplankton size class (PSC: micro-, nano- and pico-phytoplankton) between 2003 and 2010 (September to November cruises only), in three ecological provinces of the Atlantic Ocean. The HPLC data indicate no significant change in TCHLa in northern and equatorial provinces, and an increase in the southern province. These changes were not significantly different to changes in TCHLa derived using satellite ocean-colour data over the same study period. Despite no change in AMT TCHLa in northern and equatorial provinces, significant differences in PSC were observed, related to changes in key diagnostic pigments (fucoxanthin, peridinin, 19’-hexanoyloxyfucoxanthin and zeaxanthin), with an increase in small cells (nano- and pico-phytoplankton) and a decrease in larger cells (micro-phytoplankton). When fitting a three-component model of phytoplankton size structure ̶ designed to quantify the relationship between PSC and TCHLa ̶ to each AMT cruise, model parameters varied over the study period. Changes in the relationship between PSC and TCHLa have wide implications in ecology and marine biogeochemistry, and provide key information for the development and use of empirical ocean-colour algorithms. Results illustrate the importance of maintaining a time-series of in-situ observations in remote regions of the ocean, such as that acquired in the AMT programme

Keeping secrets from parents: Advantages and disadvantages of secrecy in adolescence.

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Biomass offsets little or none of permafrost carbon release from soils, streams, and wildfire: an expert assessment

As the permafrost region warms, its large organic carbon pool will be increasingly vulnerable to decomposition, combustion, and hydrologic export. Models predict that some portion of this release will be offset by increased production of Arctic and boreal biomass; however, the lack of robust estimates of net carbon balance increases the risk of further overshooting international emissions targets. Precise empirical or model-based assessments of the critical factors driving carbon balance are unlikely in the near future, so to address this gap, we present estimates from 98 permafrost-region experts of the response of biomass, wildfire, and hydrologic carbon flux to climate change. Results suggest that contrary to model projections, total permafrost-region biomass could decrease due to water stress and disturbance, factors that are not adequately incorporated in current models. Assessments indicate that end-of-the-century organic carbon release from Arctic rivers and collapsing coastlines could increase by 75% while carbon loss via burning could increase four-fold. Experts identified water balance, shifts in vegetation community, and permafrost degradation as the key sources of uncertainty in predicting future system response. In combination with previous findings, results suggest the permafrost region will become a carbon source to the atmosphere by 2100 regardless of warming scenario but that 65%–85% of permafrost carbon release can still be avoided if human emissions are actively reduced

Mode Analysis Domains for Typed Logic Programs

Precise mode information is important for compiler optimisations and in program development tools. Within the framework of abstract compilation, the precision of a mode analysis depends, in part, on the expressiveness of the abstract domain and its associated abstraction function. This paper considers abstract domains for polymorphically typed logic programs and shows how specialised domains may be constructed for each type in the program. These domains capture the degree of instantiation to a high level of precision. By providing a generic definition of abstract unification, the abstraction of a program using these domains is formalised. The domain construction procedure is fully implemented using the Godel language and tested on a number of example programs to demonstrate the viability of the approach

Do Applicants' Perceptions Matter? Investigating Reapplication Behavior Using Fairness Theory

This study used a fairness theory approach to examine a link between applicants\u27 perceptions and their actual reapplication behavior. We suggested that applicants who do not receive job offers form ‘Would’ counterfactuals based on perceived performance and ‘Should’ counterfactuals based on two procedural justice rules (job relatedness and opportunity to perform). Participants ( N=542) were applicants for a United States federal government position. After not being hired in the initial selection process, 9% of the applicants reapplied for the job the following year. We found some support for the hypothesized interactions. The job relatedness–perceived performance interaction was not significant, but the opportunity to perform–perceived performance interaction was. Opportunity to perform had a stronger influence when perceived performance was higher

Predicting the paths of peripherals: The interaction of identification and future possibilities

Two studies investigated how both degree of identification and the individual's position within the group influence aspects of group loyalty. The authors considered ingroup position in terms of both the individual's current position within a group and expectations concerning the likelihood that one's position might change in the future. Peripheral group members learned that their acceptance by other group members would improve in the future or that they could expect rejection by other group members. Various indices of group loyalty (ingroup homogeneity, motivation to work for the group, and evaluation of a motivated group member) showed that when group members anticipated future rejection, the lower the identification the less loyal they were. In contrast, those who expected future acceptance were more loyal (more motivated to work for the group) the lower their identification. Current group behavior depends on both intragroup future expectations and level of identification