Mostrando 41 - 60 Resultados de 243 Para Buscar '"The Financial Times"', tiempo de consulta: 0.30s Limitar resultados
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    “…Empirical observations reported in this paper present a new perspective towards the merging of univariate multi scaling and multivariate cross-correlation properties of financial time series.…”
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  3. 43
    “…In this paper a novel application of a particular type of spiking neural network, a Polychronous Spiking Network, was used for financial time series prediction. It is argued that the inherent temporal capabilities of this type of network are suited to non-stationary data such as this. …”
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  4. 44
    “…There are many types of autoregressive patterns in financial time series, and they form a transmission process. …”
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  5. 45
    “…The paper mainly applies the information categorization method to analyze the financial time series. The method is used to examine the similarity of different sequences by calculating the distances between them. …”
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    “…Financial time series forecasting is a crucial measure for improving and making more robust financial decisions throughout the world. …”
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  12. 52
    “…In this paper, we propose an information-theoretic tool, multiscale entropy difference (MED), to evaluate the predictability of nonlinear financial time series on multiple time scales. We discuss the predictability of the isolated system and open systems, respectively. …”
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    “…Machine learning methods have been widely used in financial time series prediction in recent years. How to label financial time series data to determine the prediction accuracy of machine learning models and subsequently determine final investment returns is a hot topic. …”
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    por Olbryś, Joanna, Komar, Natalia
    Publicado 2023
    “…Therefore, we can recommend the use of this STSA method for financial time series analyses.…”
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  17. 57
    por Wang, Jie, Wang, Jun, Fang, Wen, Niu, Hongli
    Publicado 2016
    “…By analyzing the proposed model with the linear regression, complexity invariant distance (CID), and multiscale CID (MCID) analysis methods and taking the model compared with different models such as the backpropagation neural network (BPNN), the stochastic time effective neural network (STNN), and the Elman recurrent neural network (ERNN), the empirical results show that the proposed neural network displays the best performance among these neural networks in financial time series forecasting. Further, the empirical research is performed in testing the predictive effects of SSE, TWSE, KOSPI, and Nikkei225 with the established model, and the corresponding statistical comparisons of the above market indices are also exhibited. …”
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    “…Financial time series are chaotic that, in turn, leads their predictability to be complex and challenging. …”
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  20. 60
    “…This paper presents financial time series forecasting with multistage wavelet transform (WT). …”
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