Results 51 to 60 of about 13,793,172 (210)
Environmetrics, Volume 37, Issue 3, April 2026.ABSTRACT We propose a new time series model for continuous data supported on the open unit interval (0,1)$$ \left(0,1\right) $$, motivated by applications in environmental and energy systems. The Matsuoka autoregressive moving average (MARMA) model combines the Matsuoka distribution‐a uniparametric member of the canonical exponential family‐as the ...
Guilherme Pumi +3 more
wiley +1 more source
PM10 AIR QUALITY INDEX MODELING USING ARFIMA-GARCH METHOD: BUNDARAN HI AREA OF DKI JAKARTA PROVINCE
BarekengAir quality is an essential factor in urban life, and its’ assessment often relies on the concentration of measurable air pollution parameters. One critical parameter is Particulate Matter (PM), particularly PM10, which comprises solid or liquid ...
Susilo Hariyanto +2 more
doaj +1 more source
A Fuzzy Framework for Realized Volatility Prediction: Empirical Evidence From Equity Markets
Journal of Forecasting, Volume 45, Issue 3, Page 1261-1291, April 2026.ABSTRACT This study introduces a realized volatility fuzzy time series (RV‐FTS) model that applies a fuzzy c‐means clustering algorithm to estimate time‐varying c latent volatility states and their corresponding membership degrees. These memberships are used to construct a fuzzified volatility estimate as a weighted average of cluster centroids.
Shafqat Iqbal, Štefan Lyócsa
wiley +1 more source
Jurnal LebesgueOil price movements are highly volatile and tend to be influenced over extended periods, often displaying long memory effect. This study utilizes the Autoregressive Fractionally Integrated Moving Average (ARFIMA) model, a long memory model, to analyze ...
Eza Syafri Ramadhani +2 more
doaj +1 more source
International Journal of Finance &Economics, Volume 31, Issue 2, Page 2845-2862, April 2026.ABSTRACT One of the critical risks associated with cryptocurrency assets is the so‐called downside risk, or tail risk. Conditional Value‐at‐Risk (CVaR) is a measure of tail risks that is not normally considered in the construction of a cryptocurrency portfolio.
Xinran Huang +3 more
wiley +1 more source
PENERAPAN MODEL ARFIMA-FIAPARCH UNTUK PERAMALAN HARGA SAHAM (Studi Kasus Harga Saham PT Bank Rakyat Indonesia Tbk.) [PDF]
, 2021 Berinvestasi saham dihadapkan dengan risiko tinggi karena harga saham yang cenderung fluktuatif menyebabkan adanya ketidakkonsistenan pada volatilitas dan heteroskedastisitas pada data.
Delyana Meilawati Krismonia, -
core
Discrete Dynamics in Nature and Society, Volume 2026, Issue 1, 2026.Today, the astonishing growth of digital currency has attracted many bold investors. This has caused digital currencies to be gradually introduced as a new asset class with its own criteria. However, the relationship between traditional assets and new assets is not yet deeply understood. This study’s objective is to investigate the dynamic relationship
Farzaneh Shams Tarnabi, Fabio Tramontana
wiley +1 more source
FORECASTING FRESH WATER AND MARINE FISH PRODUCTION IN MALAYSIA USING ARIMA AND ARFIMA MODELS
Malaysian Journal of Computing, 2018 Malaysia is surrounded by sea, rivers and lakes which provide natural sources of fish for human consumption. Hence, fish is one source of protein supply to the country and fishery is a sub-sector that contribute to the national gross domestic product ...
P.J.W. Mah, N.N.M. Zali, N.A.M. Ihwal, N.Z. Azizan
doaj +1 more source
Journal of Applied Mathematics, Volume 2026, Issue 1, 2026.In this paper, we model edge traffic with a conformable fractional partial differential equation that keeps memory in time and space. The solution represents a unit‐free attack pressure, built from a z‐scored edge series, a quiet period baseline, and a partially absorbing boundary that reflects scrubbing and rate limits.
Ahmad Alshanty +3 more
wiley +1 more source
Fractional Gaussian Noise: Spectral Density and Estimation Methods
Journal of Time Series Analysis, Volume 46, Issue 6, Page 1146-1174, November 2025.The fractional Brownian motion (fBm) process, governed by a fractional parameter H∈(0,1)$$ H\in \left(0,1\right) $$, is a continuous‐time Gaussian process with its increment being the fractional Gaussian noise (fGn). This article first provides a computationally feasible expression for the spectral density of fGn.
Shuping Shi, Jun Yu, Chen Zhang
wiley +1 more source