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João Sequeira, Jorge Louçã, António M. Mendes and Pedro G. Lind
We analyze the empirical series of malaria incidence, using the concepts of autocorrelation, Hurst exponent and Shannon entropy with the aim of uncovering hidden variables in those series. From the simulations of an agent model for malaria spreading, we ...
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Oluwasegun B. Adekoya
Pág. 31 - 48
In this paper, long memory behavior of the energy consumption by source of the United States has been examined using the fractional integration technique for the three conventional cases of no regressors, an intercept, and an intercept and a linear trend...
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Rim Ammar Lamouchi
Pág. 29 - 34
This paper examines the market efficiency of Saudi Arabia stock exchange market namely Tadawul All Share Index, TASI, for the period from 1998 to 2020. To test the efficiency of stock market, we analyze the dependence structure of stock market index retu...
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Kristoffer Rypdal
The main features of the instrumental global mean surface temperature (GMST) are reasonably well described by a simple linear response model driven by anthropogenic, volcanic and solar forcing. This model acts as a linear long-memory filter of the forcin...
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Nessrine Hamzaoui,Boutheina Regaieg
Pág. 437 - 443
This paper empirically investigates the contribution of the term structure of the forward premium to explain the long memory behavior that can characterize the forward premium. We apply our empirical study on1-month, 3-month, 6-month, 9-month and 1-year ...
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Shelton Peiris, Manabu Asai and Michael McAleer
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Fernando Antonio Lucena Aiube,Carlos Patrício Samanez,Larissa de Oliveira Resende,Tara Keshar Nanda Baidya
Pág. 511 - 535
We examine the ability of three different GARCH-class models, with four innovation distributions, to capture the volatility properties of natural gas futures contracts traded on the New York Mercantile Exchange. We jointly estimate the long-memory proces...
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M. Shelton Peiris and Manabu Asai
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Alex Sandro Monteiro De Moraes,Antonio Carlos Figueiredo Pinto,Marcelo Cabus Klotzle
Pág. 394?437
This paper compares the performance of long-memory models (FIGARCH) with short-memory models (GARCH) in forecasting volatility for calculating value-at-risk (VaR) and expected shortfall (ES) for multiple periods ahead for six emerging markets stock indic...
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Rafik Nazarian,Esmaeil Naderi,Nadiya Gandali Alikhani,Ashkan Amiri
Pág. 16 - 26
This study is an attempt to review the theory and applications of autoregressive fractionally integrated moving average (ARFIMA) and fractionally integrated generalized autoregressive conditional heteroskedasticity (FIGARCH) models, mainly for the purpos...
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Serpil TURKYILMAZ,Mesut BALIBEY
Pág. 400 - 410
This study examines the weak-form market efficiency of Pakistan Stock Market namely Karachi Stock Exchange for the period 2010-2013. The efficiency of stock market has tested by using ARFIMA-FIGARCH models estimated under different distribution assumptio...
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Samet Günay
Pág. 515 - 522
In this study, the parameters of chaos are analyzed for the leading emerging stock markets: Brazil, Russia, India, China, and Turkey (BRIC-T). As chaos has properties such as nonlinearity, sensitivity to initial conditions, and fractality, we performed d...
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Mesut BALIBEY,Serpil TURKYILMAZ
Pág. 836 - 848
Value-at-Risk (VaR) is a standard tool for measuring potential risk of economic losses in financial markets. In this study, we examine the convenience of the FIGARCH (1, d, 1) and FIAPARCH (1, d, 1) models in evaluating asymmetry features and long memory...
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Talal A. N. M. S. Alotaibi and Lucía Morales
Global stock markets experienced a dual shock in 2020 due to the impact of the global health crisis, parallel to a simultaneous shock derived from the Saudi Arabia and Russia oil price war. The dual shock fueled oil market volatility with lasting effects...
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Leandro dos Santos Maciel,Rosangela Ballini
Pág. 66 - 84
Bitcoin has attracted the attention of investors lately due to its significant market capitalization and high volatility. This work considers the modeling and forecasting of daily high and low Bitcoin prices using a fractionally cointegrated vector autor...
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Samet Günay
In this study, the performance of the Multifractal Model of Asset Returns (MMAR) was examined for stock index returns of four emerging markets. The MMAR, which takes into account stylized facts of financial time series, such as long memory, fat tails and...
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Raúl de Jesús-Gutiérrez,Roberto J. Santillán-Salgado
Pág. 127 - 141
The purpose of this work is to extend McNeil and Frey´s (2000) methodology by combining two component GARCH models and extreme value theory to evaluate the performance of the Value at Risk (VaR) and Expected Shortfall (ES) measures in the Latin American ...
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Guglielmo Maria Caporale, Luis Gil-Alana and Tommaso Trani
This paper applies long-memory techniques (both parametric and semi-parametric) to examine whether Brexit has led to any significant changes in the degree of persistence of the FTSE (Financial Times Stock Index) 100 Implied Volatility Index (IVI) and of ...
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Ivani Bora,Naliniprava Tripathy
Pág. 1716 - 1721
This study investigates the presence of long memory and non-linear dynamics in Indian stock market returns for a period of 19 years from May 1997 to May 2016 by using Rescaled Range (R/S) method and V-statistics. The empirical findings suggest that India...
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Samet Gunay
In this study, we analyzed the multifractality and the source of multifractality of the returns of GBP/USD, EUR/USD, USD/JPY and USD/CHF currencies. In the examination of multifractality we performed the Multifractal Detrended Fluctuation Analysis (MF-DF...
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