Results 41 to 50 of about 3,433,600 (309)
Time series momentum: Is it there?
Journal of Financial Economics, 2018 Time series momentum (TSM) refers to the predictability of the past 12-month return on the next one-month return and is the focus of several recent influential studies. This paper shows that asset-by-asset time series regressions reveal little evidence of TSM, both in- and out-of-sample. While the t-statistic in a pooled regression appears large, it is
HUANG, Dashan +3 more
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Time-series clustering via quasi U-statistics [PDF]
, 2015 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)The problem of time-series discrimination and classification is discussed. We propose a novel clustering algorithm based on a
Pinheiro, A, Valk, M
core +1 more source
Time Alignment Measurement for Time Series
Pattern Recognition, 2018 Abstract When a comparison between time series is required, measurement functions provide meaningful scores to characterize similarity between sequences. Quite often, time series appear warped in time, i.e, although they may exhibit amplitude and shape similarity, they appear dephased in time.
Duarte Folgado +5 more
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On predictability of time series [PDF]
Physica A: Statistical Mechanics and its Applications, 2019 The method to estimate the predictability of human mobility was proposed in [C. Song \emph{et al.}, Science {\bf 327}, 1018 (2010)], which is extensively followed in exploring the predictability of disparate time series. However, the ambiguous description in the original paper leads to some misunderstandings, including the inconsistent logarithm bases ...
Xu, Paiheng +3 more
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Time Series Compression Survey
ACM Computing Surveys, 2023 Smart objects are increasingly widespread and their ecosystem, also known as the Internet of Things (IoT), is relevant in many application scenarios. The huge amount of temporally annotated data produced by these smart devices demands efficient techniques for the transfer and storage of time series data.
Chiarot, Giacomo, Silvestri, Claudio
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Polynomial Regressions and Nonsense Inference
Econometrics, 2013 Polynomial specifications are widely used, not only in applied economics, but also in epidemiology, physics, political analysis and psychology, just to mention a few examples.
Daniel Ventosa-Santaulària +1 more
doaj +1 more source
Clustering of Time Series Data for Enhanced Forecasting: A Comparative Study and Practical Applications [PDF]
, 2023 reservedTime series forecasting plays a pivotal role in various domains, such as finance, healthcare, and supply chain management. Traditional forecasting methods often assume that all time series follow a similar pattern, which may not hold true in real-
SARTORI, FRANCESCO
core
Hybrid Time Series Method for Long-Time Temperature Series Analysis
Discrete Dynamics in Nature and Society, 2021 This paper combines discrete wavelet transform (DWT), autoregressive moving average (ARMA), and XGBoost algorithm to propose a weighted hybrid algorithm named DWTs-ARMA-XGBoost (DAX) on long-time temperature series analysis.
Guangdong Huang, Jiahong Li
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Children with sickle cell disease (SCD) face multiple acute and chronic medical complications that may impact their quality of life as reported by patients themselves. Health‐related social needs (HRSNs), such as food and housing insecurity, are common in people with SCD, but the association between HRSNs and patient‐reported ...
Sarah J. Marks +5 more
wiley +1 more source
A Family of Correlated Observations: From Independent to Strongly Interrelated Ones
Stats, 2020 This paper proposes a new classification of correlated data types based upon the relative number of direct connections among observations, producing a family of correlated observations embracing seven categories, one whose empirical counterpart currently
Daniel A. Griffith
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