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Volatility forecasting of crude oil futures: The role of investor sentiment and leverage effect
16 references·11 citing·38 second hop
Volatility forecasting of crude oil futures: The role of investor sentiment and leverage effect (2018)Volatility forecasting of crude oil futur…Integración de los mercados financieros Latinoamericanos por medio de MILA (2020)Integración de los mercados f…Forecasting the volatility of crude oil futures using HAR-type models with structural breaks (2016)Forecasting the volatility of…Good Volatility, Bad Volatility: Signed Jumps and The Persistence of Volatility (2015)Good Volatility, Bad Volatili…The Sum of All FEARS Investor Sentiment and Asset Prices (2014)The Sum of All FEARS Investor…Discrete-Time Volatility Forecasting With Persistent Leverage Effect and the Link With Continuous-Time Volatility Modeling (2012)Discrete-Time Volatility Fore…How does oil price volatility affect non-energy commodity markets? (2011)How does oil price volatility…Volatility forecast comparison using imperfect volatility proxies (2010)Volatility forecast compariso…A Simple Approximate Long-Memory Model of Realized Volatility (2008)A Simple Approximate Long-Mem…Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility (2007)Roughing It Up: Including Jum…Power and Bipower Variation with Stochastic Volatility and Jumps (2004)Power and Bipower Variation w…Modeling and Forecasting Realized Volatility (2003)Modeling and Forecasting Real…Comparing Predictive Accuracy (2002)Comparing Predictive AccuracyThe Distribution of Realized Exchange Rate Volatility (2001)The Distribution of Realized …Answering the Skeptics: Yes, Standard Volatility Models do Provide Accurate Forecasts (1998)Answering the Skeptics: Yes, …Volatilities of different time resolutions — Analyzing the dynamics of market components (1997)Volatilities of different tim…Comparing Predictive Accuracy (1994)Comparing Predictive AccuracyInvestor sentiment based on scaled PCA method: A powerful predictor of realized volatility in the Chinese stock market (2022)Investor sentiment based on s…A Decomposition-Ensemble Based Deep Learning Approach for Crude Oil Price Forecasting (2022)A Decomposition-Ensemble Base…Time and frequency dynamics of connectedness and hedging performance in global stock markets: Bitcoin versus conventional hedges (2021)Time and frequency dynamics o…The impact of COVID-19 news, panic and media coverage on the oil and gold prices: An ARDL approach (2021)The impact of COVID-19 news, …The effect of green energy, global environmental indexes, and stock markets in predicting oil price crashes: Evidence from explainable machine learning (2021)The effect of green energy, g…Effects of structural changes on the prediction of downside volatility in futures markets (2021)Effects of structural changes…On realized volatility of crude oil futures markets: Forecasting with exogenous predictors under structural breaks (2020)On realized volatility of cru…Forecast on silver futures linked with structural breaks and day-of-the-week effect (2020)Forecast on silver futures li…Time-varying international market power for the Chinese iron ore markets (2019)Time-varying international ma…Leverage analysis of carbon market price fluctuation in China (2019)Leverage analysis of carbon m…Dynamic impacts of crude oil price on Chinese investor sentiment: Nonlinear causality and time-varying effect (2019)Dynamic impacts of crude oil …Option pricing when underlying stock returns are discontinuous (1976)A Theory of the Term Structure of Interest Rates (1985)A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options (1993)Econometrics of Testing for Jumps in Financial Economics Using Bipower Variation (2005)Realized Variance and Market Microstructure Noise (2006)The Behavior of Stock-Market Prices (1965)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Generalized autoregressive conditional heteroskedasticity (1986)The Cross‐Section of Volatility and Expected Returns (2006)Introductory Econometrics for Finance (2008)A long memory property of stock market returns and a new model (1993)Tails, Fears, and Risk Premia (2011)Quantile Connectedness: Modeling Tail Behavior in the Topology of Financial Networks (2022)Coherent Measures of Risk (1999)On the network topology of variance decompositions: Measuring the connectedness of financial firms (2014)The General Theory of Employment, Interest and Money, by John Maynard Keynes (1936)The General Theory of Employment, Interest and Money. (1936)Noise Trader Risk in Financial Markets (1990)The Asset-Pricing Implications of Government Economic Policy Uncertainty (2015)Manager sentiment and stock returns (2018)Economic policy uncertainty: A literature review (2019)Investor Psychology and Security Market Under‐ and Overreactions (1998)Investor Sentiment and the Cross‐Section of Stock Returns (2006)In Search of Attention (2011)The short of it: Investor sentiment and anomalies (2011)Policy Uncertainty and Corporate Investment (2015)Expected stock returns and volatility (1987)The Pricing of Options on Assets with Stochastic Volatilities (1987)The distribution of realized stock return volatility (2001)No Contagion, Only Interdependence: Measuring Stock Market Comovements (2002)Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards (2004)A Comprehensive Look at The Empirical Performance of Equity Premium Prediction (2007)Strictly Proper Scoring Rules, Prediction, and Estimation (2007)Expected Stock Returns and Variance Risk Premia (2009)The VIX, the variance premium and stock market volatility (2014)Does Anything Beat 5-Minute RV? A Comparison of Realized Measures Across Multiple Asset Classes (2012)Applications of deep learning in stock market prediction: Recent progress (2021)Machine learning in the Chinese stock market (2021)
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References

  • 1994Comparing Predictive Accuracy5,495 cited
  • 2003Modeling and Forecasting Realized Volatility3,887 cited
  • 2020Integración de los mercados financieros Latinoamericanos por medio de MILA3,764 cited
  • 1998Answering the Skeptics: Yes, Standard Volatility Models do Provide Accurate Forecasts3,380 cited
  • 2008A Simple Approximate Long-Memory Model of Realized Volatility2,526 cited
  • 2001The Distribution of Realized Exchange Rate Volatility2,108 cited
  • 2004Power and Bipower Variation with Stochastic Volatility and Jumps2,033 cited
  • 2002Comparing Predictive Accuracy1,745 cited
  • 2007Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility1,448 cited
  • 2014The Sum of All FEARS Investor Sentiment and Asset Prices1,384 cited
  • 2010Volatility forecast comparison using imperfect volatility proxies1,281 cited
  • 2015Good Volatility, Bad Volatility: Signed Jumps and The Persistence of Volatility772 cited
  • 1997Volatilities of different time resolutions — Analyzing the dynamics of market components745 cited
  • 2012Discrete-Time Volatility Forecasting With Persistent Leverage Effect and the Link With Continuous-Time Volatility Modeling337 cited
  • 2011

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How does oil price volatility affect non-energy commodity markets?
330 cited
  • 2016Forecasting the volatility of crude oil futures using HAR-type models with structural breaks269 cited
  • Cited by

    • 2021The effect of green energy, global environmental indexes, and stock markets in predicting oil price crashes: Evidence from explainable machine learning148 cited
    • 2021The impact of COVID-19 news, panic and media coverage on the oil and gold prices: An ARDL approach129 cited
    • 2019Dynamic impacts of crude oil price on Chinese investor sentiment: Nonlinear causality and time-varying effect90 cited
    • 2021Time and frequency dynamics of connectedness and hedging performance in global stock markets: Bitcoin versus conventional hedges81 cited
    • 2021Effects of structural changes on the prediction of downside volatility in futures markets65 cited
    • 2020On realized volatility of crude oil futures markets: Forecasting with exogenous predictors under structural breaks62 cited
    • 2022A Decomposition-Ensemble Based Deep Learning Approach for Crude Oil Price Forecasting55 cited
    • 2019Leverage analysis of carbon market price fluctuation in China48 cited
    • 2020Forecast on silver futures linked with structural breaks and day-of-the-week effect37 cited
    • 2022Investor sentiment based on scaled PCA method: A powerful predictor of realized volatility in the Chinese stock market37 cited
    • 2019Time-varying international market power for the Chinese iron ore markets15 cited