"Can the neuro fuzzy model predict stock indexes better than its rivals?"

This paper develops a model of a trading system by using neuro fuzzy framework in order to better predict the stock index. Thirty well-known stock indexes are analyzed with the help of the model developed here. The empirical results show strong evidence of nonlinearity in the stock index by using KD technical indexes. The trading point analysis and the sensitivity analysis of trading costs show the robustness and opportunity for making further profits through using the proposed nonlinear neuro fuzzy system. The scenario analysis also shows that the proposed neuro fuzzy system performs consistently over time.

Numeral Understanding in Financial Tweets for Fine-grained Crowd-based Forecasting

Numerals that contain much information in financial documents are crucial for financial decision making. They play different roles in financial analysis processes. This paper is aimed at understanding the meanings of numerals in financial tweets for fine-grained crowd-based forecasting. We propose a taxonomy that classifies the numerals in financial tweets into 7 categories, and further extend some of these categories into several subcategories. Neural network-based models with word and character-level encoders are proposed for 7-way classification and 17-way classification. We perform backtest to confirm the effectiveness of the numeric opinions made by the crowd. This work is the first attempt to understand numerals in financial social media data, and we provide the first comparison of fine-grained opinion of individual investors and analysts based on their forecast price. The numeral corpus used in our experiments, called FinNum 1.0 , is available for research purposes.Comment: Accepted by the 2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2018), Santiago, Chil

Three Tramp Dacetine Ants in Taiwan

Trabalho de projeto do mestrado em Economia (Economia Financeira), apresentado à Faculdade de Economia da Universidade de Coimbra.Neste trabalho, as taxas forward foram utilizadas para prever os valores futuros da Estrutura de Prazo das Taxas de Juro, em diferentes pontos desta estrutura, e em diferentes contextos do sistema financeiro, e abrange o período que vai do final de 2004 ao final de 2014. As taxas spot e forward foram construidas a partir do modelo de Nelson, Siegel e Svensson (1994), e para a anlisar a relação existente entre estes dois tipos de taxas, recorreu-se o método de cointegração proposto por Johansen (1988, 1991). Para períodos mais curtos, foram construídas taxas forward instantâneas, que antecipam as taxas spot instantâneas a distâncias que vão de 1 a 10 dias. Para períodos mais longos, foram construídas taxas forward com prazo de 1 mês, que antecipam as taxas spot com o mesmo prazo, a distâncias que vão de 1 a 12 meses. Nas taxas instantâneas, verificou-se que existe cointegração entre todas as taxas forward e as taxas spot que antecipam, nas estimações que abrangem a totalidade da amostra, e para alguns casos quando se divide a amostra em sub-períodos. Nas taxas mensais, pelo contrário, apenas em alguns casos foi constatada a existência de cointegração, quer para a totalidade do período quer para os sub-períodos. De seguida, foi estimado o Modelo de Correção dos Erros proposto por Johansen (1988, 1991), e recorreu-se à analise da função impulso-resposta, para as taxas cointegradas. As taxas mensais apresentaram sempre um comportamento mais instável, quando comparadas com as taxas instantâneas. Entretanto, com a divisão do período, as taxas instantâneas apresentaram um comportamento instável, principalmente para o sub-período 2012-2014

The Impact of Timing and Dose of Rehabilitation Delivery on Functional Recovery of Stroke Patients

BackgroundTo investigate the impact of both timing and dose of rehabilitation delivery on the functional recovery of stroke patients.MethodsFrom chart review, we included 76 patients who were admitted to a regional hospital for first-ever stroke, and who had received multidisciplinary rehabilitation programs including physical therapy (PT) and occupational therapy (OT) at the inpatient department, and continuous rehabilitation therapy at the outpatient department for at least 3 months. The collected data included age, sex, type of stroke (hemorrhage/infarction), onset of stroke, initial motor status by Brunnstrom's motor recovery stages, time to rehabilitation intervention (from onset of stroke), length of stay, existence of aphasia, craniotomy (yes/no), and total units of rehabilitation. Main outcome measures were serial Barthel Index (BI) at initial assessment, 1 month, 3 months, 6 months, and 1 year post-stroke.ResultsAge was inversely correlated with BI and BI improvement at 3 months and 6 months post-stroke. Rehabilitation intervention time from onset was negatively correlated with BI improvement at 1 month and 1 year, and with BI at 1 month, 3 months, 6 months, and 1 year post-stroke. The total units of inpatient PT and/or OT were positively correlated with BI improvement at 1 month, 3 months, and 6 months post-stroke. The total units of PT and/or OT were positively correlated with BI improvement at 3 months and 6 months post-stroke. And the initial BI was positively correlated with BI at 1 month, 3 months, and 6 months post-stroke. The total units of OT can significantly predict BI improvement at 3 months and 6 months post-stroke, while the initial BI capacity can significantly predict BI status at 1 month, 3 months, and 6 months post-stroke.ConclusionThere is a dose-dependent effect of rehabilitation on functional improvement of stroke patients for the first 6 months post-stroke, and earlier delivery of rehabilitation has lasting effects on the functional recovery of stroke patients up to 1 year

"An Econometric Analysis of SARS and Avian Flu on International Tourist Arrivals to Asia"

This paper compares the impacts of SARS and human deaths arising from Avian Flu on international tourist arrivals to Asia. The effects of SARS and human deaths from Avian Flu will be compared directly according to human deaths. The nature of the short run and long run relationship is examined empirically by estimating a static line fixed effect model and a difference transformation dynamic model, respectively. Empirical results from the static fixed effect and difference transformation dynamic models are consistent, and indicate that both the short run and long run SARS effect have a more significant impact on international tourist arrivals than does Avian Flu. In addition, the effects of deaths arising from both SARS and Avian Flu suggest that SARS is more important to international tourist arrivals than is Avian Flu. Thus, while Avian Flu is here to stay, its effect is currently not as significant as that of SARS.

NumHG: A Dataset for Number-Focused Headline Generation

Headline generation, a key task in abstractive summarization, strives to condense a full-length article into a succinct, single line of text. Notably, while contemporary encoder-decoder models excel based on the ROUGE metric, they often falter when it comes to the precise generation of numerals in headlines. We identify the lack of datasets providing fine-grained annotations for accurate numeral generation as a major roadblock. To address this, we introduce a new dataset, the NumHG, and provide over 27,000 annotated numeral-rich news articles for detailed investigation. Further, we evaluate five well-performing models from previous headline generation tasks using human evaluation in terms of numerical accuracy, reasonableness, and readability. Our study reveals a need for improvement in numerical accuracy, demonstrating the potential of the NumHG dataset to drive progress in number-focused headline generation and stimulate further discussions in numeral-focused text generation.Comment: NumEval@SemEval-2024 Datase