Considerations for Applying Entropy Methods to Temporally Correlated Stochastic Datasets [PDF]
Entropy, 2023 The goal of this paper is to highlight considerations and provide recommendations for analytical issues that arise when applying entropy methods, specifically Sample Entropy (SampEn), to temporally correlated stochastic datasets, which are representative
Joshua Liddy, Michael Busa
doaj +2 more sources
Hybridization of long short-term memory neural network in fractional time series modeling of inflation [PDF]
Frontiers in Big Data, 2023 Inflation is capable of significantly impacting monetary policy, thereby emphasizing the need for accurate forecasts to guide decisions aimed at stabilizing inflation rates.
Erman Arif +4 more
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Long-Range Dependence in Financial Markets: a Moving Average Cluster Entropy Approach [PDF]
Entropy (Basel), 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
core +4 more sources
Evaluating the long-term impact of COVID-19-associated public health interventions on zoonotic and vector-borne diseases in China: an interrupted time series analysis [PDF]
Journal of Translational MedicineBackground The long-term impact of COVID-19-associated public health interventions on zoonotic and vector-borne infectious diseases (ZVBs) remains uncertain.
Yongbin Wang +8 more
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Fractional and fractal processes applied to cryptocurrencies price series [PDF]
Journal of Advanced Research, 2021 Introduction: Cryptocurrencies have been attracting the attention from media, investors, regulators and academia during the last years. In spite of some scepticism in the financial area, cryptocurrencies are a relevant subject of academic research ...
S.A. David +3 more
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medRxiv, 2020 In this research, an ARFIMA model is proposed to forecast new COVID-19 cases in Algeria two weeks ahead. In the present study, public health database from Algeria health ministry has been used to build an ARFIMA model and used to forecast COVID-19 new ...
B. Balah, M. Djeddou
semanticscholar +2 more sources
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
semanticscholar +1 more source
Fractional differencing in stock market price and online presence of global tourist corporations [PDF]
Journal of Economics Finance and Administrative Science, 2019 Purpose - This work aims to explore the behavior of stock market prices according to the autoregressive fractional differencing integrated moving average model.
Francisco Flores-Muñoz +2 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.
core +1 more source
Lecturas de Economía, 2013 Prueba de hipótesis sobre la existencia de una raíz fraccional en una serie de tiempo no estacionaria Resumen: En este trabajo se propone una modificación de la prueba de hipótesis propuesta por Castaño, Gómez y Gallón (2008) para determinar la ...
Diego Lemus, Elkin Castaño
doaj +5 more sources