Results 11 to 20 of about 4,943 (215)
Fractional Neuro-Sequential ARFIMA-LSTM for Financial Market Forecasting
IEEE Access, 2020 Forecasting of fast fluctuated and high-frequency financial data is always a challenging problem in the field of economics and modelling. In this study, a novel hybrid model with the strength of fractional order derivative is presented with their ...
Ayaz Hussain Bukhari +5 more
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Data & Policy, 2022 The aim of the present article is to evaluate the use of the Autoregressive Fractionally Integrated Moving Average (ARFIMA) model in predicting spatially and temporally localized political violent events using the Integrated Crisis Early Warning System ...
Tamir Libel
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Mathematics, 2021 The peaks-over-threshold (POT) method has a long tradition in modelling extremes in environmental variables. However, it has originally been introduced under the assumption of independently and identically distributed (iid) data. Since environmental data
Pushpa Dissanayake +3 more
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Combining long memory and level shifts in modeling and forecasting the volatility of asset returns [PDF]
, 2017 We propose a parametric state space model of asset return volatility with an accompanying estimation and forecasting framework that allows for ARFIMA dynamics, random level shifts and measurement errors.
Perron, Pierre, Varneskov, Rasmus T.
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Kubik, 2015 Model ARFIMA (Autoregressive Fractionally Integrated Moving Average) merupakan pengembangan dari model ARIMA yang pertama kali dikenalkan oleh Granger dan Joyeux (1980). Sedangkan Hosking (1981) memperkenalkan sifat jangka panjang (long memory) pada data
Rini Cahyandari, Rima Erviana
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Long-Range Dependence in Financial Markets: a Moving Average Cluster Entropy Approach [PDF]
, 2020 A perspective is taken on the intangible complexity of economic and social systems by investigating the underlying dynamical processes that produce, store and transmit information in financial time series in terms of the \textit{moving average cluster ...
Carbone, Anna +2 more
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MODELLING FOR THE WAVELET COEFFICIENTS OF ARFIMA PROCESSES [PDF]
Journal of Time Series Analysis, 2014 AbstractWe consider a model for the discrete nonboundary wavelet coefficients of autoregressive fractionally integrated moving average (ARFIMA) processes in each scale. Because the utility of the wavelet transform for the long‐range dependent processes, which many authors have explained in semi‐parametrical literature, is approximating the transformed ...
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InPrime, 2019 Wind speed is one of the most important weather factors in the landing and takeoff process of airplane because it can affect the airplane's lift. Therefore, we need a model to predict the wind speed in an area.
Devi Ila Octaviyani +2 more
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Predicting BRICS stock returns using ARFIMA models [PDF]
Applied Financial Economics, 2014 This article examines the existence of long memory in daily stock market returns from Brazil, Russia, India, China and South Africa (BRICS) countries and also attempts to shed light on the efficacy of autoregressive fractionally integrated moving average (ARFIMA) models in predicting stock returns.
Aye, Goodness Chioma +5 more
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Journal of Hydrology and Hydromechanics, 2014 Short term streamflow forecasting is important for operational control and risk management in hydrology. Despite a wide range of models available, the impact of long range dependence is often neglected when considering short term forecasting.
Szolgayová Elena +3 more
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