Relationship between Selic rate and Basel III parameters - A statistics approach and a fuzzy forecasting model

2021 ◽  
pp. 1-14
Author(s):  
Thiago Henrique Barbosa de Carvalho Tavares ◽  
Bruno Pérez Ferreira ◽  
Eduardo Mazoni Andrade Marçal Mendes
Keyword(s):  
Cross Correlation ◽  
Data Distribution ◽  
Forecasting Model ◽  
Basel Iii ◽  
Output Data ◽  
Basel Accords ◽  
Proposed Model ◽  
The Relationship ◽  
The Universe ◽  
Universe Of Discourse

In this work the relationship between the Selic rate and some bank parameters defined by the so-called Basel Accords is studied. The cross-correlation between the Selic rate and the parameters is used to explain how these parameters affect the Selic rate and vice-versa so as to define the predictability of the Selic rate using (some of) these parameters as inputs. A model is then proposed for predicting the Selic rate based on some specific parameters using fuzzy logic ideas, which dealt with a partitioning of the universe of discourse using clusters related to the output data distribution. The proposed model is compared to four other known models in the literature and showed to have better performance in average compared to all other models.

The paradoxical hybridity of words

2017 ◽  
Vol 10 (2) ◽  
pp. 208-233
Author(s):  
ABDOU ELIMAM ◽  
PAUL CHILTON
Keyword(s):  
Cultural Symbols ◽  
Neural Process ◽  
Self Sufficiency ◽  
Meaning Creation ◽  
Under Construction ◽  
The Relationship ◽  
The Universe ◽  
Shed Light ◽  
Universe Of Discourse

abstractWords can be matched with the concept of sign (correspondence of a signifier to a signified) as long as they act as symbol-words endowed with some semantic self-sufficiency. But in discourse, they lose their wholeness as symbol-words and metamorphose into wording-symbols. They, suddenly, appear as mere signifier entities with a more or less loose allusion to their status as cultural symbols. In discourse, words are no longer signs but tools covering ephemeral collections of neurosemes: the link of the sign breaks as soon as discourse takes over. The referential potential is no longer the schematic meaning issued from culture, but the universe of discourse under construction. This is why any attempt to account for meaning in language must integrate the neural process of meaning creation. It is now established that meaning is not the result of language activity but the result of cognition. However, what language does, via discourse, is to make this meaning communicable. For all these reasons, the task of linguistics should be to investigate the relationship between cognition and linguistic output in order to shed light on all the cognitive traces left within the surface strings. The role of morphosyntax thus has to be re-evaluated in this light.

HEURISTIC BIVARIATE FORECASTING MODEL OF MULTI-ATTRIBUTE FUZZY TIME SERIES BASED ON FUZZY CLUSTERING

2012 ◽  
Vol 11 (01) ◽  
pp. 167-195 ◽  
Author(s):  
GUOFANG NAN ◽  
SHUAIYIN ZHOU ◽  
JISONG KOU ◽  
MINQIANG LI
Keyword(s):  
Time Series ◽  
Clustering Algorithm ◽  
Stock Exchange ◽  
Fuzzy Time Series ◽  
Stock Index ◽  
Bivariate Model ◽  
Proposed Model ◽  
Fuzzy C Means Clustering ◽  
The Universe ◽  
Universe Of Discourse

Fuzzy time series has been applied to forecast various domain problems because of its capability to deal with vagueness and incompleteness inherent in data. However, most existing fuzzy time series models cannot cope with multi-attribute time series and remain too subjective in the partition of the universe of discourse. Moreover, these models do not consider the trend factor and the corresponding external time series, which are highly relevant to target series. In the current paper, a heuristic bivariate model is proposed to improve forecasting accuracy, and the proposed model applies fuzzy c-means clustering algorithm to process multi-attribute fuzzy time series and to partition the universe of discourse. Meanwhile, the trend predictors are extracted in the training phase and utilized to select the order of fuzzy relations in the testing phase. Finally, the proper full use of the external series to assist forecasting is discussed. The performance of the proposed model is tested using actual time series including the enrollments at the University of Alabama, the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) and a sensor dataset. The experimental results show that the proposed model can be utilized for multi-attribute time series and significantly improves the average MAER to 1.19% when compared with other forecasting models.

Text as action, action as text? Ricoeur, λoƔoσ and the affirmative search for meaning in the ‘universe of discourse’

2011 ◽  
Vol 13 (5) ◽  
pp. 593-600
Author(s):  
Alison Scott-Baumann
Keyword(s):  
Common Ground ◽  
Search For Meaning ◽  
Order And Disorder ◽  
The World ◽  
Extended Analysis ◽  
Language Ethics ◽  
The Relationship ◽  
The Universe ◽  
Readable Text ◽  
Universe Of Discourse

Ricoeur placed a great deal of importance upon text and the interpretation of text. Bell accepts this by virtue of his extended analysis of the story of Babel, and I hope to offer ways of extending and developing Bell’s arguments to incorporate the ethical demands that Ricoeur placed upon text, upon our interpretation of text and upon action as a form of readable text. This will not include a commentary on discourse analysis, which I am not qualified to give. Ricoeur differed from the structuralist tradition in that he saw the relationship between language and life as taking a dialectical form: debate that presumes the possibility of altering one’s position by grappling with different views, and often taking inspiration from Hegelian dialectics, with their contrasting polarized views and the eventual attempt at affirmative common ground. The term λoƔoσ ( logos) was first used in a philosophical way by Heraclitus to give us the principle of order and knowledge, and yet for Heraclitus the world was dominated by conflict and change. Ricoeur studied this tension within logos between order and disorder, partly by his writing about language and his work on signs and symbols, partly through metaphor and narrative and also through his insights on translation. For him, all these are facets of the need for both Explaining and Understanding as forms of interpretation of language, ethics and action. Ricoeur’s work on logos provides us with an approach that asks whether ethics controls language or vice versa or both and how this fits in with structuralism and later movements. For Ricoeur, signs (words, texts) are not the centres of our perceptual experience. At the heart of our perception are our motivations and our actions, for which we must take responsibility in a sort of provisional affirmation that we will keep trying. In so doing we must doubt (be suspicious of) our own motives just as much as those of others, and see action as a form of readable text.

The Influence of Cognitive and Affective Reactions to Feedback on Subsequent Goals

2010 ◽  
Vol 15 (2) ◽  
pp. 121-131 ◽  
Author(s):  
Remus Ilies ◽  
Timothy A. Judge ◽  
David T. Wagner
Keyword(s):  
Performance Feedback ◽  
Business School ◽  
Structural Equation ◽  
Emotional Reactions ◽  
Equation Model ◽  
Proposed Model ◽  
And Performance ◽  
Dispositional Measure ◽  
The Relationship ◽  
Reactions To Feedback

This paper focuses on explaining how individuals set goals on multiple performance episodes, in the context of performance feedback comparing their performance on each episode with their respective goal. The proposed model was tested through a longitudinal study of 493 university students’ actual goals and performance on business school exams. Results of a structural equation model supported the proposed conceptual model in which self-efficacy and emotional reactions to feedback mediate the relationship between feedback and subsequent goals. In addition, as expected, participants’ standing on a dispositional measure of behavioral inhibition influenced the strength of their emotional reactions to negative feedback.

scholarly journals A Neutrosophic Forecasting Model for Time Series Based on First-Order State and Information Entropy of High-Order Fluctuation

Entropy ◽  
2019 ◽  
Vol 21 (5) ◽  
pp. 455 ◽  
Author(s):  
Hongjun Guan ◽  
Zongli Dai ◽  
Shuang Guan ◽  
Aiwu Zhao
Keyword(s):  
Time Series ◽  
Information Entropy ◽  
Stock Exchange ◽  
Time Series Forecasting ◽  
High Order ◽  
Stock Index ◽  
Neutrosophic Set ◽  
Forecasting Model ◽  
Forecasting Models ◽  
Proposed Model

In time series forecasting, information presentation directly affects prediction efficiency. Most existing time series forecasting models follow logical rules according to the relationships between neighboring states, without considering the inconsistency of fluctuations for a related period. In this paper, we propose a new perspective to study the problem of prediction, in which inconsistency is quantified and regarded as a key characteristic of prediction rules. First, a time series is converted to a fluctuation time series by comparing each of the current data with corresponding previous data. Then, the upward trend of each of fluctuation data is mapped to the truth-membership of a neutrosophic set, while a falsity-membership is used for the downward trend. Information entropy of high-order fluctuation time series is introduced to describe the inconsistency of historical fluctuations and is mapped to the indeterminacy-membership of the neutrosophic set. Finally, an existing similarity measurement method for the neutrosophic set is introduced to find similar states during the forecasting stage. Then, a weighted arithmetic averaging (WAA) aggregation operator is introduced to obtain the forecasting result according to the corresponding similarity. Compared to existing forecasting models, the neutrosophic forecasting model based on information entropy (NFM-IE) can represent both fluctuation trend and fluctuation consistency information. In order to test its performance, we used the proposed model to forecast some realistic time series, such as the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX), the Shanghai Stock Exchange Composite Index (SHSECI), and the Hang Seng Index (HSI). The experimental results show that the proposed model can stably predict for different datasets. Simultaneously, comparing the prediction error to other approaches proves that the model has outstanding prediction accuracy and universality.

scholarly journals Usage of the Pareto Fronts as a Tool to Select Data in the Forecasting Process—A Short-Term Electric Energy Demand Forecasting Case

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3204
Author(s):  
Michał Sabat ◽  
Dariusz Baczyński
Keyword(s):  
Energy Demand ◽  
Demand Forecasting ◽  
Electric Energy ◽  
Forecasting Model ◽  
Short Term ◽  
Complex Evaluation ◽  
Proposed Model ◽  
Energy Demand Forecasting ◽  
Pareto Fronts ◽  
Naive Approach

Transmission, distribution, and micro-grid system operators are struggling with the increasing number of renewables and the changing nature of energy demand. This necessitates the use of prognostic methods based on ever shorter time series. This study depicted an attempt to develop an appropriate method by introducing a novel forecasting model based on the idea to use the Pareto fronts as a tool to select data in the forecasting process. The proposed model was implemented to forecast short-term electric energy demand in Poland using historical hourly demand values from Polish TSO. The study rather intended on implementing the range of different approaches—scenarios of Pareto fronts usage than on a complex evaluation of the obtained results. However, performance of proposed models was compared with a few benchmark forecasting models, including naïve approach, SARIMAX, kNN, and regression. For two scenarios, it has outperformed all other models by minimum 7.7%.

scholarly journals Context-Aware Neural Machine Translation for Korean Honorific Expressions

Electronics ◽  
2021 ◽  
Vol 10 (13) ◽  
pp. 1589
Author(s):  
Yongkeun Hwang ◽  
Yanghoon Kim ◽  
Kyomin Jung
Keyword(s):  
Machine Translation ◽  
Deep Neural Networks ◽  
Contextual Information ◽  
Context Aware ◽  
Neural Machine Translation ◽  
Translation Quality ◽  
Sentence Level ◽  
Proposed Model ◽  
The Given ◽  
The Relationship

Neural machine translation (NMT) is one of the text generation tasks which has achieved significant improvement with the rise of deep neural networks. However, language-specific problems such as handling the translation of honorifics received little attention. In this paper, we propose a context-aware NMT to promote translation improvements of Korean honorifics. By exploiting the information such as the relationship between speakers from the surrounding sentences, our proposed model effectively manages the use of honorific expressions. Specifically, we utilize a novel encoder architecture that can represent the contextual information of the given input sentences. Furthermore, a context-aware post-editing (CAPE) technique is adopted to refine a set of inconsistent sentence-level honorific translations. To demonstrate the efficacy of the proposed method, honorific-labeled test data is required. Thus, we also design a heuristic that labels Korean sentences to distinguish between honorific and non-honorific styles. Experimental results show that our proposed method outperforms sentence-level NMT baselines both in overall translation quality and honorific translations.

scholarly journals Openbaring as principium theologiae

1993 ◽  
Vol 27 (1) ◽  
Author(s):  
M. A. Kruger
Keyword(s):  
South Africa ◽  
Contextual Theology ◽  
World Religions ◽  
General Revelation ◽  
Reformed Churches ◽  
The Relationship ◽  
Point Of Departure ◽  
The Universe

Theological renewal regarding different theological disciplines as well as the complete theological encyclopedia has lately been debated worldwide. Likewise, the Reformed Churches in South Africa are in a process of reconsidering the traditional reformed theological encyclopedia. This task can, however, not be fulfilled unless the basic issues are not also reconsidered. This article focuses on revelation as the principium theologiae. The line of argumentation centres round the fundamental confession in article 2 of the Belgian Confession. The truth implicit in this article, and accepted by the Reformed Churches, stresses that God can be known through his creation, sustenance and government of the universe, but He can be known more convincingly by studying holy Scripture. To prove this point of departure, Romans 1-4 and Romans 10 are discussed. The distinction between special and general revelation, contextual theology and the relationship to world religions and H. Bavinck's concept of the principium theologiae are also considered.

scholarly journals An Attention-Based Model Using Character Composition of Entities in Chinese Relation Extraction

Information ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 79 ◽  
Author(s):  
Xiaoyu Han ◽  
Yue Zhang ◽  
Wenkai Zhang ◽  
Tinglei Huang
Keyword(s):  
Language Processing ◽  
Large Scale ◽  
Named Entity Recognition ◽  
Relation Extraction ◽  
Entity Recognition ◽  
Additional Information ◽  
Named Entity ◽  
Proposed Model ◽  
The Relationship ◽  
Crucial Part

Relation extraction is a vital task in natural language processing. It aims to identify the relationship between two specified entities in a sentence. Besides information contained in the sentence, additional information about the entities is verified to be helpful in relation extraction. Additional information such as entity type getting by NER (Named Entity Recognition) and description provided by knowledge base both have their limitations. Nevertheless, there exists another way to provide additional information which can overcome these limitations in Chinese relation extraction. As Chinese characters usually have explicit meanings and can carry more information than English letters. We suggest that characters that constitute the entities can provide additional information which is helpful for the relation extraction task, especially in large scale datasets. This assumption has never been verified before. The main obstacle is the lack of large-scale Chinese relation datasets. In this paper, first, we generate a large scale Chinese relation extraction dataset based on a Chinese encyclopedia. Second, we propose an attention-based model using the characters that compose the entities. The result on the generated dataset shows that these characters can provide useful information for the Chinese relation extraction task. By using this information, the attention mechanism we used can recognize the crucial part of the sentence that can express the relation. The proposed model outperforms other baseline models on our Chinese relation extraction dataset.

Loyalty program in Africa: risk-seeking and risk-averse adventurers

2014 ◽  
Vol 69 (2) ◽  
pp. 137-157 ◽  
Author(s):  
Shogo Mlozi
Keyword(s):  
Consumer Behavior ◽  
Consumer Products ◽  
Loyalty Programs ◽  
Risk Averse ◽  
Loyalty Program ◽  
Content Type ◽  
Risk Seeking ◽  
Proposed Model ◽  
First Time ◽  
The Relationship

Purpose – This article aims to test the relationship between expected attractiveness-satisfaction-loyalty for international adventure tourists visiting Tanzania. The proposed model is based on travel consumer behavior theoretical constructs extracted from the literature. Design/methodology/approach – This article aims to test the relationship between expected attractiveness-satisfaction-loyalty for international adventure tourists visiting Tanzania. The proposed model is based on travel consumer behavior theoretical constructs extracted from the literature. Findings – The findings for overall model differed from the moderating factors of high risk, low risk, first-time visit and repeat visit. Also, the results are interesting when satisfaction is tested as a mediator. Practical implications – Practitioners could consider the fact that repeat visits may change tourists’ perceptions toward destination and may even increase their inclination to take on risks. This may impact innovation of consumer products in tourism. Also, policy makers could benefit on how loyalty programs can be developed to increase performance. Originality/value – The study offers specific strategic recommendations toward different groups of tourists (i.e. first-time, repeat visitors, risk averse, risk seeking) and proposes logic for setting up a loyalty program as a long-term strategy for success.

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