Results 161 to 170 of about 13,792,513 (203)

Asymmetric volatility in asset prices: An explanation with mental framing. [PDF]

Heliyon
Ormos M, Timotity D.
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Comparative Analysis Between GARCH And FIGARCH Models For The Prediction Of Volatility In Financial Time Series Models

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A novel time-varying FIGARCH model for improving volatility predictions

Physica A: Statistical Mechanics and Its Applications, 2022
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Xuehui Chen, Xinru Zhang
exaly   +2 more sources

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
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FIGARCH model on Chinese securities market based on the genetic algorithms

2010 3rd International Congress on Image and Signal Processing, 2010
In this paper, a new method of Fractionally Integrated Generalized Autoregressive Conditionally Heteroskedasticity (FIGARCH) model for characterizing financial market volatility is introduced to test the long memory property. We also introduce a new method to establish FIGARCH model — Genetic Algorithms (GA).
Lei Wu
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Development of out-of-sample forecast formulae for the FIGARCH model

Model Assisted Statistics and Applications
Volatility is a matter of concern for time series modeling. It provides valuable insights into the fluctuation and stability of concerning variables over time. Volatility patterns in historical data can provide valuable information for predicting future behaviour. Nonlinear time series models such as the autoregressive conditional heteroscedastic (ARCH)
Ranjit Kumar Paul
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Sectoral stock return sensitivity to oil price changes: a double-threshold FIGARCH model

Quantitative Finance, 2013
We investigate the association between the stock return distributions of 10 major U.S. sectors and oil returns within a double-threshold FIGARCH model. This model nests GARCH, IGARCH and Fama–French specifications as its special cases and allows a test of their validity. This model also has the advantage of capturing not only the short-run dynamics (as
Elyas Elyasiani
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Testing for long memory volatility of Chinese stock markets with FIGARCH model

2014 International Conference on Management Science & Engineering 21th Annual Conference Proceedings, 2014
In this study, the long memory property in the volatility of Chinese stock markets is examined. For this purpose, we applied two semi-parametric tests (GPH and LW) and the FIGARCH model, to four Chinese market indices: Shanghai A, Shanghai B, Shenzhen A and Shenzhen B.
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Long Term Hedging of the Australian All Ordinaries Index Using a Bivariate Error Correction FIGARCH Model [PDF]

, 2004
This article compares the performance of bivariate error correction GARCH and FIGARCH models when estimating long term dynamic minimum variance hedge ratios (MVHRs) on the Australian All Ordinaries Index. The paper therefore introduces the bivariate error correction FIGARCH model into the hedging literature, which to date has only employed the GARCH ...
Dark, Jonathan
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