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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
Evaluation of Dual Long Memory Properties with Emphasizing the Skewed and Fat-Tail Distribution: Evidence from Tehran Stock Exchange [PDF]
Muṭāli̒āt-i Mudīriyyat-i Ṣan̒atī, 2014 This paper investigates the presence of long memory in the Tehran stock market, using the ARFIMA, GPH, GSP and FIGARCH models. The data set consists of daily returns, and long memory tests are carried out both for the returns and volatilities of TEPIX ...
Mohammad Javad Mohagheghnia +3 more
doaj
Lecturas de Economía, 2011 Sesgos en estimación, tamaño y potencia de una prueba sobre el parámetro de memoria larga en modelos ARFIMA Resumen: Castaño et al. (2008) proponen una prueba para investigar la existencia de memoria larga, basada en el parámetro de diferenciación ...
Elkin Castaño Vélez +2 more
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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
doaj +1 more source
Nonfractional Memory: Filtering, Antipersistence, and Forecasting
, 2018 The fractional difference operator remains to be the most popular mechanism to generate long memory due to the existence of efficient algorithms for their simulation and forecasting.
Vera-Valdés, J. Eduardo
core +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
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
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
Physical Review Research, 2022 We introduce a method for reconstructing macroscopic models of one-dimensional stochastic processes with long-range correlations from sparsely sampled time series by combining fractional calculus and discrete-time Langevin equations.
Johannes A. Kassel, Holger Kantz
doaj +1 more source
Nelson And Plosser Revisited: Evidence From Fractional Arima Models [PDF]
, 2004 In this paper fractionally integrated ARIMA (ARFIMA) models are estimated using an extended version of Nelson and Plosser’s (1982) dataset. The analysis employs Sowell’s (1992) maximum likelihood procedure.
Caporale, GM, Gil-Alana, LA
core