Results 21 to 30 of about 21,636,733 (224)
In this survey paper we present a systematic methodology of how to identify origins of fractional dynamics. We consider three models leading to it, namely fractional Brownian motion (FBM), fractional Lévy stable motion (FLSM) and autoregressive ...
Weron Aleksander
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Growth enterprise market in Hong Kong: Efficiency evolution and long memory in return and volatility [PDF]
Purpose – Growth enterprise market (GEM) in Hong Kong is acknowledged as one of the world’s most successful examples of small and medium enterprise (SME) stock market.
Trang Nguyen +3 more
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Combining long memory and level shifts in modeling and forecasting the volatility of asset returns [PDF]
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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For modeling in time series, models with fractional differences are widely used. The best known model is the ARFIMA (autoregressive fractionally integrated moving average) model.
Dmitriy V. Ivanov
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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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MODELLING FOR THE WAVELET COEFFICIENTS OF ARFIMA PROCESSES [PDF]
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 ...
openaire +1 more source
Diabetes has become a concern in the developed and developing countries with its growing number of patients reported to the ministry of health records.
S. Zahrani +3 more
semanticscholar +1 more source
Forecasting energy futures volatility based on the unbiased extreme value volatility estimator
This paper uses the opening, high, low, and closing prices of five energy futures to estimate and model volatility based on the unbiased extreme value volatility estimator (the Add RS estimator).
Dilip Kumar
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ARFIMA Model for Short Term Forecasting of New Death Cases COVID-19 [PDF]
COVID-19 is an infectious disease that can spread from one person to another and has a high potential for death. The infection of COVID-19 is spreading massive and fast that causes the extreme fluctuating data spread and long memory effects.
Kartikasari Puspita +2 more
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Modelling exchange rate volatility with random level shifts [PDF]
Recent literature has shown that the volatility of exchange rate returns displays long memory features. It has also been shown that if a short memory process is contaminated by level shifts, the estimate of the long memory parameter tends to be upward ...
Li, Ye, Perron, Pierre, Xu, Jiawen
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