Results 61 to 70 of about 95 (83)

Forecasting value-at-risk of crude oil futures using a hybrid ARIMA-SVR-POT model. [PDF]

Heliyon
Zhang C, Zhou X.
europepmc   +1 more source

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Modeling and predicting stock returns using the ARFIMA-FIGARCH

2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), 2009
Modeling of real world financial time series such as stock returns are very difficult, because of their inherent characteristics. ARIMA and GARCH models are frequently used in such cases. It is proven of late that, the traditional models may not produce the best results. Lot of recent literature says the successes of hybrid models.
P Bagavathi Sivakumar
exaly   +3 more sources

Comparative Approach to the Backward Elimination and for-ward Selection Methods in Modeling the Systematic Risk Based on the ARFIMA-FIGARCH Model

Advances in mathematical finance and applications, 2017
The present study aims to model systematic risk using financial and accounting variables. Accordingly, the data for 174 companies in Tehran Stock Exchange are extracted for the period of 2006 to 2016. First, the systematic risk index is estimated using the ARFIMA-FIGARCH model.
Rastgoo, Nemat, Panahian, Hossein
exaly   +2 more sources

Arfima-Figarch vs. Arfima-Hygarch: Case Study ETF Returns of Emerging Asian Countries

Asian Journal of Finance and Accounting, 2014
This research investigate the long memory returns for ETF returns index of seven Asian countries in Emerging Markets Equities during 2008-2013 periods. Those ETFs are Wisdom Tree Indian Rupee Fund (ICN), Market Vectors Indonesia Index (IDX), iShares MSCI Malaysia Index Fund (EWM), Market Vectors Russia ETF (RSX), and iShares MSCI Thailand Investable ...
exaly   +2 more sources

Comparing the Intensity of Long-Memory Symmetry in the Returns of the Capital Market Index and Bahar Azadi Coin: An ARFIMA–FIGARCH Approach

Dynamic Management in Business Analysis
Objective: The study aims to compare the structure of long memory in the returns and volatility of the Tehran Stock Exchange Price Index (TEPIX) and the Bahar Azadi gold coin. Methodology: Using daily data from December 2008 to September 2025, the study employs the ARFIMA model to analyze long memory in returns and the FIGARCH model to assess long ...
Mojtaba Abolhasani Pourashkzar, Ahmad Sarlak, Teymor Mohammadi, Gholamali Haji   +3 more
exaly   +2 more sources

Did the Returns and Volatilities in BRIC Countries Follow Long Memory During Global Crisis? Did the Reaction Time Vary Across BRIC Countries During Global Crisis? Evidence from ARFIMA-FIGARCH

SSRN Electronic Journal, 2011
The purpose of this paper is to investigate the effects of financial crisis on the trading behavior of BRIC stock markets. The paper employs the ARFIMA-FIGARCH framework to examine the long memory in equity returns and volatilities and to assess the predictable nature of the financial time series data during the global financial crisis.
Sabur Mollah, Amir Kheirollah, Shahiduzzaman Quoreshi   +2 more
openaire   +1 more source

Reexamining the linkages between inflation and output growth: A bivariate ARFIMA-FIGARCH approach [PDF]

, 2006
In this paper, given recent theoretical developments that inflation can exhibit long memory properties due to the output growth process, we propose a new class of bivariate processes to simultaneously investigate the dual long memory properties in the mean and the conditional variance of inflation and output growth series.
Mustafa Caglayan, Feng Jiang
openaire  

Stock market efficiency beyond the joint hypothesis: Reevaluating the Moroccan stock market Efficiency through ARFIMA-FIGARCH model

Multidisciplinary Science Journal
In the context of an unstable international environment, the assessment of the state of stock market efficiency remains of paramount importance. For this reason, we intend to implement ARFIMA-FIGARCH modeling over the period from 2 January 2013 to 29 December 2023.
Youness Ait Oummou, Driss Omerani, Aomar Ibourk   +2 more
openaire   +1 more source

Testing for long memory in ISE using Arfima-figarch model and structural break test

2009
This study examines long memory in Istanbul Stock Exchange (ISE) by using the structural break test in variance and ARFIMA-FIGARCH model. Our findings indicate that long memory does not exist in the equity return; however, it exits in volatility. Consequently, ISE is found as a weak form inefficient market due to volatility as it has a predictable ...
Korkmaz, Turhan, Çevik, Emrah Ismail, Özataç, Nesrin   +2 more
openaire   +1 more source

A novel time-varying FIGARCH model for improving volatility predictions

Physica A: Statistical Mechanics and Its Applications, 2022
Xuehui Chen
exaly