Results 171 to 180 of about 2,061 (206)
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Applied Financial Economics, 2002
This paper, estimates figarch models introduced by baillie et al. (1996a) for the four major daily exchange rates against the usd (dem, frf, yen and the gbp). The former contributions are extended by accounting for the observed kurtosis through a student- t based maximum likelihood estimation and by including variables capturing the effect of closing ...
Beine, Michel +2 more
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This paper, estimates figarch models introduced by baillie et al. (1996a) for the four major daily exchange rates against the usd (dem, frf, yen and the gbp). The former contributions are extended by accounting for the observed kurtosis through a student- t based maximum likelihood estimation and by including variables capturing the effect of closing ...
Beine, Michel +2 more
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Long memory and FIGARCH models for daily and high frequency commodity prices [PDF]
, 2007 Daily futures returns on six important commodities are found to be well described as FIGARCH fractionally integrated volatility processes, with small departures from the martingale in mean property. The paper also analyzes several years of high frequency intra day commodity futures returns and finds very similar long memory in volatility features at ...
Richard T. Baillie +3 more
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Development of out-of-sample forecast formulae for the FIGARCH model
Model Assisted Statistics and ApplicationsVolatility 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)
Rakshit, Debopam, Paul, Ranjit Kumar
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Long memory behavior in the returns of Pakistan stock market: Arfima-Figarch models [PDF]
International Journal of Economics and Financial Issues, 2014 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 assumptions as Normal, Student-t, Skewed Student-t and GED distribution.
TURKYILMAZ, Serpil, BALIBEY, Mesut
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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, 2014In 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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Integrated ARCH, FIGARCH and AR models: Origins of long memory
2015Although the properties of the ARCH(∞) model are well investigated, the existence of long memory FIGARCH and IARCH solution was not established in the literature. These two popular ARCH type models which are widely used in applied literature, were causing theoretical controversy because of the suspicion that other solutions besides the trivial zero one,
Giraitis, Liudas +2 more
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Studies in Nonlinear Dynamics & Econometrics, 2007
This paper extends the Fractionally integrated GARCH (FIGARCH) model by incorporating Normal Inverse Gaussian Distribution (NIG). The proposed model is flexible and allows one to model time-variation, long memory, fat tails as well as asymmetry and skewness in the distribution of financial returns.
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This paper extends the Fractionally integrated GARCH (FIGARCH) model by incorporating Normal Inverse Gaussian Distribution (NIG). The proposed model is flexible and allows one to model time-variation, long memory, fat tails as well as asymmetry and skewness in the distribution of financial returns.
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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 ...
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Bivariate Error Correction FIGARCH and FIAPARCH Models on the Australian All Ordinaries Index and Its SPI Futures. [PDF]
, 2004 In this paper we extend the univariate FIGARCH and FIAPARCH models to a bivariate framework. We estimate bivariate error correction FIGARCH and FIAPARCH models between the All Ordinaries Index and its SPI futures using constant correlation and diagonal parameterisations.
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An improved FIGARCH model with the fractional differencing operator (1-νL)
Finance Research Letters, 2023Qunxing Pan, Peng Li, Xiuli Du
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