Volatility processes and volatility forecast with long memory
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Publication:4647598
DOI10.1088/1469-7688/4/1/007zbMath1409.62219OpenAlexW3123119897MaRDI QIDQ4647598
Publication date: 15 January 2019
Published in: Quantitative Finance (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1088/1469-7688/4/1/007
Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05)
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Cites Work
- Fractionally integrated generalized autoregressive conditional heteroskedasticity
- ARCH modeling in finance. A review of the theory and empirical evidence
- The detection and estimation of long memory in stochastic volatility
- Generalized autoregressive conditional heteroscedasticity
- Varieties of long memory models
- Modeling volatility persistence of speculative returns: a new approach
- Modelling the persistence of conditional variances
- Market heterogeneities and the causal structure of volatility
- STATIONARY ARCH MODELS: DEPENDENCE STRUCTURE AND CENTRAL LIMIT THEOREM
- Heterogeneous volatility cascade in financial markets
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