Results 31 to 40 of about 20,295,200 (307)
Fractional integration and cointegration in US financial time series data [PDF]
, 2011 This paper examines several US monthly financial time series data using fractional integration and cointegration techniques. The univariate analysis based on fractional integration aims to determine whether the series are I(1) (in which case markets ...
Gil-Alana, Luis A. +5 more
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The 8th International Conference on Time Series and Forecasting, 2022 Este artículo forma parte de las actas del "The 8th International Conference on Time Series and Forecasting."
Florian Combes +2 more
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Information theoretic results for stationary time series and the Gaussian-generalized von Mises time series [PDF]
, 2021 This chapter presents some novel information theoretic results for the analysis of stationary time series in frequency domain. In particular, the spectral distribution that corresponds to the most uncertain or unpredictable time series with some values ...
Gatto, Riccardo
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Essays on Time Series Momentum
, 2023 The three essays in this dissertation are all related to the topic of time series momentum. In the first essay, my co-authors and I introduce a cross-asset extension of time series momentum that we call cross-asset time series momentum.
Pitkäjärvi, Aleksi
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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 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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Intuitionistic fuzzy time series functions approach for time series forecasting [PDF]
Granular Computing, 2020 AbstractFuzzy inference systems have been commonly used for time series forecasting in the literature. Adaptive network fuzzy inference system, fuzzy time series approaches and fuzzy regression functions approaches are popular among fuzzy inference systems.
Egrioglu, Erol, Bas, Eren, Yolcu, Ufuk
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PTB-M4D/time-series-metadata: v0.2.0
, 2023 v0.2.0 (2023-08-01) Documentation <ul> <li><p>docs(Python version): upgrade Python versions from greater or equal 3.5 to greater or equal 3.7 (<a href="https://github.com/PTB-M4D/time-series-metadata/commit ...
Ludwig, Björn, Gruber, Maximilian
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CoRR, 2019 Multivariate time series is a very active topic in the research community and many machine learning tasks are being used in order to extract information from this type of data. However, in real-world problems data has missing values, which may difficult the application of machine learning techniques to extract information. In this paper we focus on the
Samuel Arcadinho, Paulo Mateus
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A Three-Stage Nonparametric Kernel-Based Time Series Model Based on Fuzzy Data
Mathematics, 2023 In this paper, a nonlinear time series model is developed for the case when the underlying time series data are reported by LR fuzzy numbers. To this end, we present a three-stage nonparametric kernel-based estimation procedure for the center as well as ...
Gholamreza Hesamian +2 more
doaj +1 more source