Results 71 to 80 of about 7,382 (224)
Forecasting Digital Asset Return: An Application of Machine Learning Model
International Journal of Finance &Economics, Volume 30, Issue 3, Page 3169-3186, July 2025.ABSTRACT In this study, we aim to identify the machine learning model that can overcome the limitations of traditional statistical modelling techniques in forecasting Bitcoin prices. Also, we outline the necessary conditions that make the model suitable.
Vito Ciciretti +4 more
wiley +1 more source
Local Whittle estimation in time‐varying long memory series
Journal of Time Series Analysis, Volume 46, Issue 4, Page 647-673, July 2025.The memory parameter is usually assumed to be constant in traditional long memory time series. We relax this restriction by considering the memory a time‐varying function that depends on a finite number of parameters. A time‐varying Local Whittle estimator of these parameters, and hence of the memory function, is proposed.
Josu Arteche, Luis F. Martins
wiley +1 more source
PREDIKSI HARGA DAGING SAPI DI KABUPATEN BREBES MENGGUNAKAN PEMODELAN ARFIMA DENGAN EFEK GARCH
Jurnal Gaussian: Beef is a source of animal protein which is rich in nutrients and much-loved by the people of Indonesia. Brebes Regency is an area in Indonesia that has local livestock assets, namely Java Brebes cattle or also known as Jabres cattle.
Nanda Diva Lingkar Imani +2 more
semanticscholar +1 more source
Improved Trend Analysis With EOFs and Application to Warming of Polar Regions
International Journal of Climatology, Volume 45, Issue 7, 15 June 2025.Introducing a variation of EOF analysis, we obtain an insignificant Antarctic trend between 1979 and 2023 of (0.13 ± 0.17) K/decade. The first principal component completely captures the trend for land regions of the order of the size of most countries.
Ewan T. Phillips, Holger Kantz
wiley +1 more source
Modeling and Forecasting the Volatility of the Nikkei 225 Realized Volatility Using the ARFIMA-GARCH Model [PDF]
In this paper, we apply the ARFIMA-GARCH model to the realized volatility and the continuous sample path variations constructed from high-frequency Nikkei 225 data.
Isao Ishida, Toshiaki Watanabe
core +3 more sources
Vestnik Volgogradskogo gosudarstvennogo universiteta Ekonomika, 2021 The paper tests the hypothesis that the formation of investment portfolios of two assets based on predicted returns obtained using fractal models with conditional heteroscedasticity (ARFIMA-GARCH) allows to obtain portfolios with better characteristics ...
R. Garafutdinov
semanticscholar +1 more source
Identifying influential individuals and predicting future demand of chronic kidney disease patients
Decision Sciences, Volume 56, Issue 2, Page 123-143, April 2025.ABSTRACT To ensure high service quality, managers need to personalize treatment options and meet their customer demands. Our research is motivated by the need to better anticipate and prepare for that. We develop a generalizable framework that is the first to address two healthcare risk management goals: (1) identifying high risk and stable‐demand ...
Zlatana D. Nenova, Valerie L. Bartelt
wiley +1 more source
Analisis Kejadian Gempa Bumi Tektonik di Wilayah Pulau Sumatera
Jurnal Matematika, 2016 The purpose of this study to get an overview of the earthquakes in Sumatra. The method used is descriptive statistics and models Autoregressive Fractionally Integrated Moving Average (ARFIMA). The result from analysis data yielded a mathematical model to
Jose Rizal +3 more
doaj +1 more source
Computational aspects of Bayesian spectral density estimation
, 2011 Gaussian time-series models are often specified through their spectral density. Such models present several computational challenges, in particular because of the non-sparse nature of the covariance matrix.
Chopin, Nicolas +2 more
core +5 more sources
Detection of DoS Attacks Using ARFIMA Modeling of GOOSE Communication in IEC 61850 Substations
Energies, 2020 Integration of Information and Communication Technology (ICT) in modern smart grids (SGs) offers many advantages including the use of renewables and an effective way to protect, control and monitor the energy transmission and distribution.
Ghada Elbez +4 more
semanticscholar +1 more source