Results 11 to 20 of about 4,516 (208)
Evaluation of Combined ARMA-ARCH and BL-ARCH models in Modeling Lake Urmia water level [PDF]
علوم و مهندسی آبیاری, 2017 Many nonlinear models have been developed based on the mean errors modeling. However, the non-linear models with Autoregressive conditional heteoscedasticity are based on variance modeling. These models are combined with linear models, partly to increase
Mohammad Nazeri Tahrudi +3 more
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Pendugaan Imbal Hasil Saham dengan Model Autoregressive Moving Average
Jambura Journal of Mathematics, 2021 ABSTRAK Seorang investor pada umumnya berharap untuk membeli suatu saham dengan harga yang rendah dan menjual saham tersebut dengan harga yang lebih tinggi untuk memperoleh imbal hasil yang tinggi.
Grifin Ryandi Egeten +2 more
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SchWARMA: A model-based approach for time-correlated noise in quantum circuits
Physical Review Research, 2021 Temporal noise correlations are ubiquitous in quantum systems, yet often neglected in the analysis of quantum circuits due to the complexity required to accurately characterize and model them.
Kevin Schultz +3 more
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Groundwater Depth Forecasting Using a Coupled Model
Discrete Dynamics in Nature and Society, 2021 Accurate and reliable prediction of groundwater depth is a critical component in water resources management. In this paper, a new method based on coupling wavelet decomposition method (WA), autoregressive moving average (ARMA) model, and BP neural ...
Manfei Zhang +3 more
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Mathematics, 2020 In this paper, we compare the predictions on the market liquidity in crypto and fiat currencies between two traditional time series methods, the autoregressive moving average (ARMA) and the generalized autoregressive conditional heteroskedasticity (GARCH)
Klender Cortez +2 more
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Implied Volatility Prediction Based on Different Term Structures: An Empirical Study of the SSE 50 ETF Options Market from High-Frequency Data [PDF]
E3S Web of Conferences, 2021 This article focuses on the implied volatility forecast of the SSE 50 ETF options market from June 1, 2017, to August 30, 2019, and constructs AR (1) model and ARMA-GARCH model based on liquidity characteristics to compare and analyze the prediction ...
Yang Wenqi, Ma Jingkun
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Modelling The Volatility of Frankfurt Stock Exchange (DAX) Returns Using hybrid Models [PDF]
Financial Markets, Institutions and RisksRecently, the interest of researchers in the use of hybrid models in the process of analyzing model time series with fluctuations and forecasting fluctuations in financial time series has increased significantly. Hybrid ARMA-GARCH models were created for
Hadj Khelifa +2 more
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Estimation of ARMA Model Order via Artificial Neural Network for Modeling Physiological Systems
IEEE Access, 2020 Model order estimation is the most important but challenging step for system identification using an autoregressive moving average (ARMA) model. In this paper, we propose an artificial neural network (ANN) structure to estimate the best model order for ...
Md-Billal Hossain +2 more
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PLoS ONE, 2022 SVR-ARMA-GARCH models provide flexible model fitting and good predictive powers for nonlinear heteroscedastic time series datasets. In this study, we explore the change point detection problem in the SVR-ARMA-GARCH model using the residual-based CUSUM ...
HsinKai Wang +3 more
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MOTION ARTIFACT REDUCTION IN FUNCTIONAL NEAR INFRARED SPECTROSCOPY SIGNALS BY AUTOREGRESSIVE MOVING AVERAGE MODELING BASED KALMAN FILTERING [PDF]
Journal of Innovative Optical Health Sciences, 2013 Functional near infrared spectroscopy (fNIRS) is a technique that is used for noninvasive measurement of the oxyhemoglobin (HbO2) and deoxyhemoglobin (HHb) concentrations in the brain tissue.
MEHDI AMIAN, S. KAMALEDIN SETAREHDAN
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