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The Estimation of the Order of an ARMA Process
Annals of Statistics, 1980 Under general conditions strong consistency of certain estimates of the maximum lags of an autoregressive moving average process is established. A theorem on weak consistency is also proved and in certain cases where consistency does not hold the probability of over-estimation of a maximum lag is evaluated.
E J Hannan
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The distribution of the maximum of an ARMA(1, 1) process [PDF]
Comptes Rendus. Mathématique, 2020 We give the cumulative distribution function of $M_n=\max \left(X_1, \ldots , X_n \right)$, the maximum of a sequence of $n$ observations from an ARMA(1, 1) process.
Withers, Christopher S. +1 more
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Enhanced separation of long-term memory from short-term memory on top of LSTM: Neural network-based stock index forecasting. [PDF]
PLoS ONELSTM (Long Short-Term Memory Network) is currently extensively utilized for forecasting financial time series, primarily due to its distinct advantages in separating the long-term from the short-term memory information within a sequence.
Hongfei Xiao
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AcMNPV, a viral insecticide of Lepidoptera pests, stimulates the immune response of the natural enemy Arma chinensis Fallou [PDF]
Applied and Environmental MicrobiologyAutographa Californica multiple nucleopolyhedrovirus (AcMNPV) is the most widely studied baculovirus currently used as a biopesticide application for crop pest control.
Ximei Yuan +7 more
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Can crude oil prices predict world tuna prices? [PDF]
Songklanakarin Journal of Science and Technology (SJST), 2020 World tuna prices exhibit substantial fluctuations over time. We studied monthly tuna and preceding crude oil prices from 1986 to 2018, using linear regression models with autoregressive and moving average (ARMA) errors.
Boonmee Lee +3 more
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Modelling International Tourist Arrivals Volatility in Zimbabwe Using a GARCH Process [PDF]
African Journal of Hospitality, Tourism and Leisure, 2021 The aim of the paper was to develop bootstrap prediction intervals for international tourism demand and volatility in Zimbabwe after modelling with an ARMA-GARCH process.
Tendi Makoni, Delson Chikobvu
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Scaled Muth–ARMA Process Applied to Finance Market
Mathematics, 2023 The analysis of financial market time series is an important source for understanding the economic reality of a country. We introduce a new autoregressive moving average (ARMA) process, the sMuth–ARMA model, which has the sMuth law as the marginal ...
Abraão D. C. Nascimento +3 more
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ARMA–GARCH model with fractional generalized hyperbolic innovations
Financial Innovation, 2022 In this study, a multivariate ARMA–GARCH model with fractional generalized hyperbolic innovations exhibiting fat-tail, volatility clustering, and long-range dependence properties is introduced. To define the fractional generalized hyperbolic process, the
Sung Ik Kim
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Applied Sciences, 2022 This article presents a hybrid method of structural modal parameter identification, based on improved empirical mode decomposition (EMD) and autoregressive and moving average (ARMA).
Chun Fu, Shao-Fei Jiang
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Functional clustering of periodic transcriptional profiles through ARMA(p,q). [PDF]
PLoS ONE, 2010 BackgroundGene clustering of periodic transcriptional profiles provides an opportunity to shed light on a variety of biological processes, but this technique relies critically upon the robust modeling of longitudinal covariance structure over time ...
Ning Li +5 more
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