Results 41 to 50 of about 772 (205)
Modeling and Forecasting the Volatility of Eastern European Emerging Markets
This study has attempted to seek a volatility forecasting model that can reflect sufficiently the long memory characteristic in the volatility of four Eastern European emerging stock markets, naThis study has attempted to seek a volatility forecasting ...
Sang Hoon Kang , Seong-Min Yoon
doaj +1 more source
Neste trabalho foram avaliados os ajustes de cinco modelos para previsão da variância, utilizando-se uma série de preços de soja, uma commodity negociada na bolsa de mercadorias de Chicago (CBOT), com dados de alta frequência. Os modelos utilizados foram
Mario Domingues Simões +3 more
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Functional central limit theorems for augmented GARCH(p, q) and FIGARCH processes [PDF]
Augmented GARCH; FIGARCH; Fractional FCLT; Functional central limit ...
이외숙
core +1 more source
Evaluation of Dual Long Memory Properties with Emphasizing the Skewed and Fat-Tail Distribution: Evidence from Tehran Stock Exchange [PDF]
This paper investigates the presence of long memory in the Tehran stock market, using the ARFIMA, GPH, GSP and FIGARCH models. The data set consists of daily returns, and long memory tests are carried out both for the returns and volatilities of TEPIX ...
Mohammad Javad Mohagheghnia +3 more
doaj
A note on asymptotic inference for FIGARCH($p, d, q$) models [PDF]
Parameters estimation for a FIGARCH(p, d, q )m odel is studied in this paper. By constructing a compact parameter space Θ satisfying the non-negativity constraints for the FI- GARCH model, it is shown that the results of Robinson and Zaffaroni (2006) can be applied to establish the strong con- sistency and asymptotic normality of the quasi-maximum ...
Ngai Hang Chan, Chi Tim Ng
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The research delved into analysing the stochastic characteristics of Nigeria's Real GDP, the exchange rate of the Naira to US Dollar, and the inflation rate employing Autoregressive fractionally integrated moving average (ARFIMA) and the Autoregressive ...
Ayoade Adewole
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This study addresses the limitations of the Kalman Filter (KF) by extending the application of the Unscented Kalman Filter (UKF) and the variational Bayes method (VBM) for estimating long-memory (LM) volatility models.
Kisswell Basira +2 more
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Stochastic equilibrium of free trade under a FIGARCH volatility
Abstract Free trade for some economists gains so much attention, the horrible thing is though when a nation doesn't knit relations with other countries because this would harm the future gains almost if land or property is rare: what i had tried to mention is the importance of free trade as far as consumption is concerned, if the national ...
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A Hybrid LSTM Neural Network Approach for Modeling Periodical Long-Memory Characteristics in Financial Energy Index Time Series [PDF]
Forecasting financial market volatility has always been a major challenge in economics and financial engineering. In this study, a hybrid approach based on FIGARCH and PLM-GARCH models combined with Long Short-Term Memory (LSTM) neural networks is ...
Minou Yari +2 more
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Parametric Time‐Variation in the Unconditional Volatility: Estimation and Inference
ABSTRACT We propose modeling time‐variation in the unconditional volatility by augmenting the standard GARCH model by a deterministic time‐varying intercept. The model, called the additive time‐varying (ATV‐)GARCH model, can be interpreted as a reduced form of a model including covariates and can be derived from a multiplicative decomposition of ...
Niklas Ahlgren +2 more
wiley +1 more source

