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Exponentially Smoothing the Skewed Laplace Distribution for Value‐at‐Risk Forecasting. (2013). Lu, Zudi ; Gerlach, Richard ; Huang, Hai.
In: Journal of Forecasting.
RePEc:wly:jforec:v:32:y:2013:i:6:p:534-550.

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  1. Modality and Limiting Behaviours of Skew Symmetric Distributions. (2025). Nadarajah, Saralees ; Hitchen, Thomas.
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  2. A new Bayesian method for estimation of value at risk and conditional value at risk. (2025). Sanjun, Eva L ; Pizarro, Mario M ; Parra, Isabel M ; Martn, Jacinto.
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  3. Time-varying variance and skewness in realized volatility measures. (2023). Lucas, Andre ; Opschoor, Anne.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:39:y:2023:i:2:p:827-840.

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  4. GAS and GARCH based value-at-risk modeling of precious metals. (2022). Tiwari, Aviral ; Owusu Junior, Peterson ; Tweneboah, George ; Asafo-Adjei, Emmanuel.
    In: Resources Policy.
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  5. A nonparametric copula approach to conditional Value-at-Risk. (2022). Dunn, Richard ; Geenens, Gery.
    In: Econometrics and Statistics.
    RePEc:eee:ecosta:v:21:y:2022:i:c:p:19-37.

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  6. Do realized higher moments have information content? - VaR forecasting based on the realized GARCH-RSRK model. (2022). Wang, Tianyi ; Huang, Zhuo ; Yan, Hong ; Liang, Fang.
    In: Economic Modelling.
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  7. Value‐at‐risk forecasting via dynamic asymmetric exponential power distributions. (2021). Zhao, Zhibiao ; Ou, LU.
    In: Journal of Forecasting.
    RePEc:wly:jforec:v:40:y:2021:i:2:p:291-300.

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  8. Modeling dynamic higher moments of crude oil futures. (2021). Wang, Tianyi ; Huang, Zhuo ; Liang, Fang.
    In: Finance Research Letters.
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  9. Forecasting Value-at-Risk of Cryptocurrencies with RiskMetrics type models. (2020). Lau, Chi Keung ; Gözgör, Giray ; Liu, Wei ; Gozgor, Giray ; Marco, Chi Keung ; Semeyutin, Artur.
    In: Research in International Business and Finance.
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  10. Time-varying tail behavior for realized kernels. (2019). Lucas, Andre ; Opschoor, Anne.
    In: Tinbergen Institute Discussion Papers.
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  11. A nonparametric copula approach to conditional Value-at-Risk. (2019). Dunn, Richard ; Geenens, Gery.
    In: Papers.
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  12. Improving daily Value-at-Risk forecasts: The relevance of short-run volatility for regulatory quality assessment. (2018). Berger, Theo ; Genay, Ramazan.
    In: Journal of Economic Dynamics and Control.
    RePEc:eee:dyncon:v:92:y:2018:i:c:p:30-46.

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  13. Frontiers in VaR forecasting and backtesting. (2016). Ruiz, Esther ; Nieto, Maria Rosa.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:32:y:2016:i:2:p:475-501.

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  14. Score-driven exponentially weighted moving averages and Value-at-Risk forecasting. (2016). Zhang, Xin ; Lucas, Andre.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:32:y:2016:i:2:p:293-302.

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  15. Conditional Value-at-Risk: Semiparametric estimation and inference. (2016). Zhao, Zhibiao ; Wang, Chuan-Sheng .
    In: Journal of Econometrics.
    RePEc:eee:econom:v:195:y:2016:i:1:p:86-103.

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  16. Score Driven exponentially Weighted Moving Average and Value-at-Risk Forecasting. (2015). Zhang, Xin ; Lucas, Andre ; André Lucas, .
    In: Tinbergen Institute Discussion Papers.
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  17. Score Driven Exponentially Weighted Moving Averages and Value-at-Risk Forecasting. (2015). Zhang, Xin ; Lucas, Andre.
    In: Working Paper Series.
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