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Forecasting S&P 500 volatility: Long memory, level shifts, leverage effects, day-of-the-week seasonality, and macroeconomic announcements. (2009). van Dijk, Dick ; De Pooter, Michiel ; Martens, Martin .
In: International Journal of Forecasting.
RePEc:eee:intfor:v:25:y:2009:i:2:p:282-303.

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  2. The contribution of jump signs and activity to forecasting stock price volatility. (2023). Murphy, Anthony ; Izzeldin, Marwan ; Hizmeri, Rodrigo ; Bu, Ruijun ; Tsionas, Mike.
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  5. Medium-term and long-term volatility forecasts for EUA futures with country-specific economic policy uncertainty indices. (2022). Umar, Muhammad ; Guo, Xiaozhu ; Luo, Qin ; Zhang, Lixia.
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  9. Economic Value of Modeling the Joint Distribution of Returns and Volatility: Leverage Timing. (2021). Çakmaklı, Cem ; Ozturk, Verda.
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  19. The Contribution of Jump Signs and Activity to Forecasting Stock Price Volatility. (2019). Tsionas, Mike ; Murphy, Anthony ; Izzeldin, Marwan ; Hizmeri, Rodrigo.
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  20. Uncertainty and oil volatility: New evidence. (2019). Cao, Xiang ; Zeng, Qing ; Mei, Dexiang ; Diao, Xiaohua.
    In: Physica A: Statistical Mechanics and its Applications.
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  21. Forecasting the U.S. stock volatility: An aligned jump index from G7 stock markets. (2019). Zhang, Yaojie ; Wahab, M. I. M., ; Ma, Feng.
    In: Pacific-Basin Finance Journal.
    RePEc:eee:pacfin:v:54:y:2019:i:c:p:132-146.

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  22. Good, bad cojumps and volatility forecasting: New evidence from crude oil and the U.S. stock markets. (2019). Ma, Feng ; Chen, Yixiang ; Zhang, Yaojie.
    In: Energy Economics.
    RePEc:eee:eneeco:v:81:y:2019:i:c:p:52-62.

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  23. Forecasting the volatility of crude oil futures using high-frequency data: further evidence. (2018). Ma, Feng ; He, Feng ; Chen, Wang ; Wei, YU.
    In: Empirical Economics.
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    RePEc:ids:injbaf:v:9:y:2018:i:1:p:88-118.

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    In: Physica A: Statistical Mechanics and its Applications.
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    In: Physica A: Statistical Mechanics and its Applications.
    RePEc:eee:phsmap:v:493:y:2018:i:c:p:148-154.

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    In: Physica A: Statistical Mechanics and its Applications.
    RePEc:eee:phsmap:v:492:y:2018:i:c:p:916-922.

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    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:34:y:2018:i:3:p:377-388.

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    In: Energy Economics.
    RePEc:eee:eneeco:v:75:y:2018:i:c:p:400-409.

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    In: Energy Economics.
    RePEc:eee:eneeco:v:72:y:2018:i:c:p:321-330.

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    In: The North American Journal of Economics and Finance.
    RePEc:eee:ecofin:v:44:y:2018:i:c:p:92-108.

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    In: Chaos, Solitons & Fractals.
    RePEc:eee:chsofr:v:113:y:2018:i:c:p:333-344.

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  34. Forecasting the volatility of Nikkei 225 futures. (2017). McAleer, Michael ; Asai, Manabu.
    In: Documentos de Trabajo del ICAE.
    RePEc:ucm:doicae:1707.

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  35. The Memory of Volatility. (2017). Wenger, Kai ; Sibbertsen, Philipp ; Leschinski, Christian.
    In: Hannover Economic Papers (HEP).
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  36. Building News Measures from Textual Data and an Application to Volatility Forecasting. (2017). Caporin, Massimiliano ; Poli, Francesco.
    In: Econometrics.
    RePEc:gam:jecnmx:v:5:y:2017:i:3:p:35-:d:108901.

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  37. Realized volatility forecast of agricultural futures using the HAR models with bagging and combination approaches. (2017). Yang, KE ; Li, Steven ; Chen, Langnan ; Tian, Fengping.
    In: International Review of Economics & Finance.
    RePEc:eee:reveco:v:49:y:2017:i:c:p:276-291.

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    In: Physica A: Statistical Mechanics and its Applications.
    RePEc:eee:phsmap:v:482:y:2017:i:c:p:181-188.

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    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:33:y:2017:i:1:p:132-152.

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    In: International Review of Financial Analysis.
    RePEc:eee:finana:v:49:y:2017:i:c:p:176-190.

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    In: Energy Economics.
    RePEc:eee:eneeco:v:67:y:2017:i:c:p:136-145.

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    In: Journal of Econometrics.
    RePEc:eee:econom:v:199:y:2017:i:2:p:202-212.

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    In: Papers.
    RePEc:arx:papers:1712.08057.

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  44. Does the ARFIMA really shift?. (2017). Santucci de Magistris, Paolo ; Grassi, Stefano ; Delle Monache, Davide.
    In: CREATES Research Papers.
    RePEc:aah:create:2017-16.

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  45. Nonlinearity, Breaks, and Long-Range Dependence in Time-Series Models. (2016). Medeiros, Marcelo ; Hillebrand, Eric.
    In: Journal of Business & Economic Statistics.
    RePEc:taf:jnlbes:v:34:y:2016:i:1:p:23-41.

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  46. Forecasting the realized volatility in the Chinese stock market: further evidence. (2016). Pu, Wang ; Ma, Feng ; Chen, Yixiang.
    In: Applied Economics.
    RePEc:taf:applec:v:48:y:2016:i:33:p:3116-3130.

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    In: MPRA Paper.
    RePEc:pra:mprapa:74670.

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  48. Comparing Predictive Accuracy under Long Memory - With an Application to Volatility Forecasting. (2016). Leschinski, Christian ; Kruse, Robinson ; Will, Michael .
    In: Hannover Economic Papers (HEP).
    RePEc:han:dpaper:dp-571.

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  49. Forecasting realized volatility in a changing world: A dynamic model averaging approach. (2016). Wang, Yudong ; Wu, Chongfeng ; Wei, YU ; Ma, Feng.
    In: Journal of Banking & Finance.
    RePEc:eee:jbfina:v:64:y:2016:i:c:p:136-149.

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  50. Combining nearest neighbor predictions and model-based predictions of realized variance: Does it pay?. (2016). Fuertes, Ana-Maria ; Andrada-Felix, Julian ; Fernandez-Rodriguez, Fernando.
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    RePEc:eee:intfor:v:32:y:2016:i:3:p:695-715.

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  51. 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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  52. Comparing Predictive Accuracy under Long Memory - With an Application to Volatility Forecasting. (2016). Leschinski, Christian ; Kruse, Robinson ; Will, Michael .
    In: CREATES Research Papers.
    RePEc:aah:create:2016-17.

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  53. QUANTILE CORRELATIONS: UNCOVERING TEMPORAL DEPENDENCIES IN FINANCIAL TIME SERIES. (2015). Schmitt, Thilo A ; Guhr, Thomas ; Dette, Holger ; Schafer, Rudi .
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  54. Out?of?sample evaluation of macro announcements, linearity, long memory, heterogeneity and jumps in mini?futures markets. (2015). VORTELINOS, DIMITRIOS.
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  55. Testing for Level Shifts in Fractionally Integrated Processes: a State Space Approach. (2015). Grassi, Stefano ; Delle Monache, Davide ; Santucci, Paolo .
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  56. Ex-ante Determinants of Volatility in the Crude Oil Market. (2015). Le, Duong T.
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  57. Out-of-sample evaluation of macro announcements, linearity, long memory, heterogeneity and jumps in mini-futures markets. (2015). Vortelinos, Dimitrios I.
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  58. Realized range volatility forecasting: Dynamic features and predictive variables. (2015). Caporin, Massimiliano ; Velo, Gabriel G.
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  59. Its all about volatility of volatility: Evidence from a two-factor stochastic volatility model. (2015). Santucci de Magistris, Paolo ; Grassi, Stefano.
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    RePEc:eee:empfin:v:30:y:2015:i:c:p:62-78.

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  60. Forecasting co-volatilities via factor models with asymmetry and long memory in realized covariance. (2015). McAleer, Michael ; Asai, Manabu.
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  62. Testing for Level Shifts in Fractionally Integrated Processes: a State Space Approach. (2015). Grassi, Stefano ; Delle Monache, Davide ; de Magistris, Paolo Santucci.
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  71. Forecasting the volatility of crude oil futures using intraday data. (2014). Sévi, Benoît ; Sevi, Benoit.
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    In: CREATES Research Papers.
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  77. Heterogeneous Asymmetric Dynamic Conditional Correlation Model with Stock Return and Range. (2013). Asai, Manabu.
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  79. Common non-linearities in multiple series of stock market volatility. (2013). Vahid, Farshid ; Anderson, Heather.
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