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Volatility Forecasting via MIDAS, HAR and their Combination: An Empirical Comparative Study for IBOVESPA
16 references·13 citing·30 second hop
Volatility Forecasting via MIDAS, HAR and their Combination: An Empirical Comparative Study for IBOVESPA (2014)Volatility Forecasting via MIDAS, HAR and…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…Chapter 4 Forecast Combinations (2006)Chapter 4 Forecast Combinatio…Econometrics of Testing for Jumps in Financial Economics Using Bipower Variation (2005)Econometrics of Testing for J…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…Econometric Analysis of Realized Volatility and its Use in Estimating Stochastic Volatility Models (2002)Econometric Analysis of Reali…The Distribution of Realized Exchange Rate Volatility (2001)The Distribution of Realized …Non-Gaussian Ornstein–Uhlenbeck-based Models and Some of Their Uses in Financial Economics (2001)Non-Gaussian Ornstein–Uhlenbe…Testing the equality of prediction mean squared errors (1997)Testing the equality of predi…Comparing Predictive Accuracy (1994)Comparing Predictive AccuracyCombining forecasts: A review and annotated bibliography (1990)Combining forecasts: A review…Combining forecasts: A review and annotated bibliography (1989)Combining forecasts: A review…Generalized autoregressive conditional heteroskedasticity (1986)Generalized autoregressive co…Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Autoregressive Conditional He…The Combination of Forecasts (1969)The Combination of ForecastsForecasting stock market volatility with a large number of predictors: New evidence from the MS-MIDAS-LASSO model (2022)Forecasting stock market vola…Forecasting crude oil volatility with uncertainty indicators: New evidence (2022)Forecasting crude oil volatil…What effect did the introduction of Bitcoin futures have on the Bitcoin spot market? (2021)What effect did the introduct…The information content of uncertainty indices for natural gas futures volatility forecasting (2021)The information content of un…Forecasting China's crude oil futures volatility: New evidence from the MIDAS-RV model and COVID-19 pandemic (2021)Forecasting China's crude oil…Jumps and oil futures volatility forecasting: a new insight (2020)Jumps and oil futures volatil…Examining the predictive information of CBOE OVX on China’s oil futures volatility: Evidence from MS-MIDAS models (2020)Examining the predictive info…Forecasting the U.S. stock volatility: An aligned jump index from G7 stock markets (2019)Forecasting the U.S. stock vo…Forecasting the Chinese stock volatility across global stock markets (2019)Forecasting the Chinese stock…A novel UMIDAS-SVQR model with mixed frequency investor sentiment for predicting stock market volatility (2019)A novel UMIDAS-SVQR model wit…Forecasting the realized volatility of the Chinese stock market: Do the G7 stock markets help? (2018)Forecasting the realized vola…Are low-frequency data really uninformative? A forecasting combination perspective (2017)Are low-frequency data really…Forecasting the realized range-based volatility using dynamic model averaging approach (2016)Forecasting the realized rang…Expert judgment: Some necessary conditions and an example. (1974)The M3-Competition: results, conclusions and implications (2000)Time Series Analysis: Forecasting and Control (1977)Time Series Analysis: Forecasting and Control (1977)On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks (1993)Multivariate Simultaneous Generalized ARCH (1995)Comparing Predictive Accuracy (1995)Tests of Conditional Predictive Ability (2006)A Comprehensive Look at The Empirical Performance of Equity Premium Prediction (2007)Why Does Stock Market Volatility Change Over Time? (1989)Forecasting, Structural Time Series Models and the Kalman Filter (1990)Answering the Skeptics: Yes, Standard Volatility Models do Provide Accurate Forecasts (1998)Expected Stock Returns and Variance Risk Premia (2009)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)The Cross‐Section of Volatility and Expected Returns (2006)On the network topology of variance decompositions: Measuring the connectedness of financial firms (2014)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)Conditional Heteroskedasticity in Asset Returns: A New Approach (1991)Econometric Analysis of Cross Section and Panel Data (2001)Time series forecasting using a hybrid ARIMA and neural network model (2003)25 years of time series forecasting (2006)Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy (2009)Strictly Proper Scoring Rules, Prediction, and Estimation (2007)
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References

  • 1986Generalized autoregressive conditional heteroskedasticity22,329 cited
  • 1982Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation20,684 cited
  • 1994Comparing Predictive Accuracy5,495 cited
  • 2003Modeling and Forecasting Realized Volatility3,887 cited
  • 1969The Combination of Forecasts3,194 cited
  • 2008A Simple Approximate Long-Memory Model of Realized Volatility2,526 cited
  • 2002Econometric Analysis of Realized Volatility and its Use in Estimating Stochastic Volatility Models2,224 cited
  • 1989Combining forecasts: A review and annotated bibliography2,170 cited
  • 2001The Distribution of Realized Exchange Rate Volatility2,108 cited
  • 1997Testing the equality of prediction mean squared errors2,103 cited
  • 2004Power and Bipower Variation with Stochastic Volatility and Jumps2,033 cited
  • 2001Non-Gaussian Ornstein–Uhlenbeck-based Models and Some of Their Uses in Financial Economics1,801 cited
  • 1990Combining forecasts: A review and annotated bibliography1,465 cited
  • 2007Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility1,448 cited
  • 2005Econometrics of Testing for Jumps in Financial Economics Using Bipower Variation

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1,346 cited
  • 2006Chapter 4 Forecast Combinations1,318 cited
  • Cited by

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    • 2016Forecasting the realized range-based volatility using dynamic model averaging approach51 cited
    • 2019Forecasting the U.S. stock volatility: An aligned jump index from G7 stock markets51 cited
    • 2022Forecasting stock market volatility with a large number of predictors: New evidence from the MS-MIDAS-LASSO model49 cited
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    • 2020Jumps and oil futures volatility forecasting: a new insight43 cited
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    • 2018Forecasting the realized volatility of the Chinese stock market: Do the G7 stock markets help?31 cited
    • 2019A novel UMIDAS-SVQR model with mixed frequency investor sentiment for predicting stock market volatility31 cited
    • 2021Forecasting China's crude oil futures volatility: New evidence from the MIDAS-RV model and COVID-19 pandemic28 cited
    • 2019Forecasting the Chinese stock volatility across global stock markets27 cited