Aggregating sentiment in Europe: the relationship with volatility and returns

This paper presents several proposals for creating an aggregate sentiment index for the European stock market. We achieve this objective by using the OWA and WOWA operators, which have been successful in finance and have a strong financial interpretation. We compute ten different aggregate sentiment indices for the 2007-2021 period and evaluate their ability to provide information about current and future market volatility and returns. We find several results of interest for both investors and policymakers. Sentiment indices have a strong negative relationship with market volatility. Extreme values of sentiment can predict future market returns, with low values indicating positive returns and high values suggesting negative returns. Finally, using stock market capitalisation as an input of the WOWA operator enhances explanatory power of the indices on future market returns compared to the OWA operator

The problem of collective identity in a fuzzy environment

Producción CientíficaWe define the problem of group identication in a fuzzy environment. We concentrate on the case where the society is required to self-determine the belongingness of each member to a speci_c group, characterized by a single attribute. In general terms, this case consists of a collective identity issue that can be regarded as an aggregation problem of individual assessments within a group. Here we introduce the possibility that both the original assessments and the resulting output attach partial memberships to the collectivity, for each potential member. We propose relevant classes of rules, and some are axiomatically characterized. Our new approach provides a way to circumvent classical impossibility results like Kasher and Rubinstein's.Ministerio de Economía, Industria y Competitividad (Project ECO2012-32178

Fusion of Text and Image in Multimedia Information Retrieval System

Multimedia Information Retrieval is very useful for any application in our daily work. Most of the applications consist of Multimedia data that are images, text, audio and video. Multimedia information retrieval system is used to search an image. There are same meanings for different data which is also known as semantic gap. This problem is solved by fusion of text based image retrieval and content based image retrieval. Weighted Mean, OWA and WOWA are aggregation operators used in this system for the fusion of text and image numeric values. The Scale invariant feature transforms and speeded up robust feature are two algorithms for feature extraction. To increase the speed of system, the speeded up robust feature algorithm is used. Bag of Words and Bag of Visual Word approaches are used in this system for retrieving images. DOI: 10.17762/ijritcc2321-8169.15066

A WOWA-based aggregation technique on trust values connected to metadata

Metadata produced by members of a diverse community of peers tend to contain low-quality or even mutually inconsistent assertions. Trust values computed on the basis of users' feedback can improve metadata quality and reduce inconsistency, eliminating untrustworthy assertions. In this paper, we describe an approach to metadata creation and improvement, where community members express their opinions on the trustworthiness of each assertion. Our technique aggregates individual trustworthiness values to obtain a community-wide assessment of each assertion. We then apply a global trustworthiness threshold to eliminate some assertions to reduce the metadatabase's overall inconsistency

Decision Support under Risk by Optimization of Scenario Importance Weighted OWA Aggregations, Journal of Telecommunications and Information Technology, 2009, nr 3

The problem of evaluation outcomes under several scenarios to form overall objective functions is of considerable importance in decision support under uncertainty. The fuzzy operator defined as the so-called weighted OWA (WOWA) aggregation offers a well-suited approach to this problem. TheWOWA aggregation, similar to the classical ordered weighted averaging (OWA), uses the preferential weights assigned to the ordered values (i.e., to the worst value, the second worst and so on) rather than to the specific criteria. This allows one to model various preferences with respect to the risk. Simultaneously, importance weighting of scenarios can be introduced. In this paper we analyze solution procedures for optimization problems with the WOWA objective functions related to decisions under risk. Linear programming formulations are introduced for optimization of the WOWA objective representing risk averse preferences. Their computational efficiency is demonstrated

Information fusion for norm consensus in virtual communities

Treballs Finals de Grau de Matemàtiques, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2016, Director: Maite López Sánchez i Juan Antonio Rodríguez-AguilarLegislation in virtual communities should not be a private privilege, as well as the application of norms. In this project a new way of deliberating about norms is formalized, with the norm argument map, people will be able to argue and decide the norms that rule their virtual community. Also, we will see a method to fuse all the data introduced by participants into a single score or opinion about a given norm, from this the decision of wether to establish the norm or not will be taken. All of these decisions have to be taken in the most human way possible, to evaluate the results of the method, a Java project has been coded and by comparing it with other methods we will reason why this project’s method is better

Overview of Methods Implemented in MCA: Multiple Criteria Analysis of Discrete Alternatives with a Simple Preference Specification

Many methods have been developed for multiple criteria analysis and/or ranking of discrete alternatives. Most of them require complex specification of preferences. Therefore, they are not applicable for problems with numerous alternatives and/or criteria, where preference specification by the decisin makers can hardly be done in a way acceptable for small problems, e.g., for pair-wise comparisons. In this paper we describe several new methods implemented for a real-life application dealing with multi-criteria analysis of future energy technologies. This analysis involves large numbers of both alternatives and criteria. Moreover, the analysis was made by a large number of stakeholders without expeience in analytical methods. Therefore a simple method for interactive preference specification was condition for the analysis. The paper provides overview of several of new methods based on diverse concepts developed for multicriteria analysis, and summarizes a comparison of methods and experence of using them

Journal of Telecommunications and Information Technology, 2009, nr 3

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hi_class: Horndeski in the Cosmic Linear Anisotropy Solving System

We present the public version of hi_class (www.hiclass-code.net), an extension of the Boltzmann code CLASS to a broad ensemble of modifications to general relativity. In particular, hi_class can calculate predictions for models based on Horndeski's theory, which is the most general scalar-tensor theory described by second-order equations of motion and encompasses any perfect-fluid dark energy, quintessence, Brans-Dicke, $f(R)$ and covariant Galileon models. hi_class has been thoroughly tested and can be readily used to understand the impact of alternative theories of gravity on linear structure formation as well as for cosmological parameter extraction.Comment: 17 pages + appendices, 4 figures, code available on https://github.com/miguelzuma/hi_class_publi