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Do high-frequency stock market data help forecast crude oil prices? Evidence from the MIDAS models
16 references·6 citing·43 second hop
Do high-frequency stock market data help forecast crude oil prices? Evidence from the MIDAS models (2018)Do high-frequency stock market data help …Time-Varying Effects of Oil Supply Shocks on the US Economy (2013)Time-Varying Effects of Oil S…On the links between stock and commodity markets' volatility (2013)On the links between stock an…Oil shocks, policy uncertainty and stock market return (2013)Oil shocks, policy uncertaint…Oil price shocks and stock market activities: Evidence from oil-importing and oil-exporting countries (2013)Oil price shocks and stock ma…Correlations and volatility spillovers across commodity and stock markets: Linking energies, food, and gold (2013)Correlations and volatility s…Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market (2009)Not All Oil Price Shocks Are …The Economic Effects of Energy Price Shocks (2008)The Economic Effects of Energ…Exogenous Oil Supply Shocks: How Big Are They and How Much Do They Matter for the U.S. Economy? (2008)Exogenous Oil Supply Shocks: …A Simple Approximate Long-Memory Model of Realized Volatility (2008)A Simple Approximate Long-Mem…MIDAS Regressions: Further Results and New Directions (2007)MIDAS Regressions: Further Re…Chapter 4 Forecast Combinations (2006)Chapter 4 Forecast Combinatio…There is a risk-return trade-off after all (2005)There is a risk-return trade-…Predicting volatility: getting the most out of return data sampled at different frequencies (2005)Predicting volatility: gettin…The MIDAS Touch: Mixed Data Sampling Regression Models (2004)The MIDAS Touch: Mixed Data S…Combination forecasts of output growth in a seven‐country data set (2004)Combination forecasts of outp…Comparing Predictive Accuracy (1994)Comparing Predictive AccuracyCan multi-source heterogeneous data improve the forecasting performance of tourist arrivals amid COVID-19? Mixed-data sampling approach (2023)Can multi-source heterogeneou…Oil futures volatility predictability: New evidence based on machine learning models (2022)Oil futures volatility predic…Forecasting stock market volatility with a large number of predictors: New evidence from the MS-MIDAS-LASSO model (2022)Forecasting stock market vola…High frequency multiscale relationships among major cryptocurrencies: portfolio management implications (2021)High frequency multiscale rel…Improving Adaptive Neuro-Fuzzy Inference System Based on a Modified Salp Swarm Algorithm Using Genetic Algorithm to Forecast Crude Oil Price (2019)Improving Adaptive Neuro-Fuzz…Forecasting Crude Oil Price Using Kalman Filter Based on the Reconstruction of Modes of Decomposition Ensemble Model (2019)Forecasting Crude Oil Price U…The Combination of Forecasts (1969)Combining forecasts: A review and annotated bibliography (1989)The M3-Competition: results, conclusions and implications (2000)Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy (2009)Investor Sentiment Aligned: A Powerful Predictor of Stock Returns (2014)Forecasting: theory and practice (2022)Oil and the Macroeconomy since World War II (1983)This is what happened to the oil price-macroeconomy relationship (1996)What is an Oil Shock? (2000)What do we learn from the price of crude oil futures? (2010)Dynamic correlation between stock market and oil prices: The case of oil-importing and oil-exporting countries (2011)Financialization of Commodity Markets (2013)Investigating Causal Relations by Econometric Models and Cross-spectral Methods (1969)Conditional Heteroskedasticity in Asset Returns: A New Approach (1991)On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks (1993)New Eurocoin: Tracking Economic Growth in Real Time (2010)Now-Casting and the Real-Time Data Flow (2013)Atheoretical macroeconometrics: A critique (1985)Systematic Monetary Policy and the Effects of Oil Price Shocks (1997)THE IMPACT OF OIL PRICE SHOCKS ON THE U.S. STOCK MARKET* (2009)THE ROLE OF INVENTORIES AND SPECULATIVE TRADING IN THE GLOBAL MARKET FOR CRUDE OIL (2013)Oil prices, US stock return, and the dependence between their quantiles (2015)Forecasting Using Principal Components From a Large Number of Predictors (2002)Macroeconomic Forecasting Using Diffusion Indexes (2002)Forecasting Stock Returns (2013)Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500 (2016)A long memory property of stock market returns and a new model (1993)Answering the Skeptics: Yes, Standard Volatility Models do Provide Accurate Forecasts (1998)Modeling and Forecasting Realized Volatility (2003)Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility (2007)Tails, Fears, and Risk Premia (2011)Quantile Connectedness: Modeling Tail Behavior in the Topology of Financial Networks (2022)An Intertemporal Capital Asset Pricing Model (1973)The conditional CAPM does not explain asset-pricing anomalies☆ (2006)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Generalized autoregressive conditional heteroskedasticity (1986)Parametric and Nonparametric Volatility Measurement (2010)Threshold bipower variation and the impact of jumps on volatility forecasting (2010)Good Volatility, Bad Volatility: Signed Jumps and The Persistence of Volatility (2015)Oil price shocks and stock markets in the U.S. and 13 European countries (2008)Causes and Consequences of the Oil Shock of 2007-08 (2009)A Comprehensive Look at The Empirical Performance of Equity Premium Prediction (2007)Strictly Proper Scoring Rules, Prediction, and Estimation (2007)
this work references cited by second hop

References

  • 1994Comparing Predictive Accuracy5,495 cited
  • 2009Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market4,637 cited
  • 2008A Simple Approximate Long-Memory Model of Realized Volatility2,526 cited
  • 2006Chapter 4 Forecast Combinations1,318 cited
  • 2008The Economic Effects of Energy Price Shocks1,299 cited
  • 2004Combination forecasts of output growth in a seven‐country data set1,138 cited
  • 2005There is a risk-return trade-off after all1,019 cited
  • 2007MIDAS Regressions: Further Results and New Directions1,003 cited
  • 2008Exogenous Oil Supply Shocks: How Big Are They and How Much Do They Matter for the U.S. Economy?926 cited
  • 2005Predicting volatility: getting the most out of return data sampled at different frequencies813 cited
  • 2013Oil price shocks and stock market activities: Evidence from oil-importing and oil-exporting countries573 cited
  • 2004The MIDAS Touch: Mixed Data Sampling Regression Models563 cited
  • 2013On the links between stock and commodity markets' volatility559 cited
  • 2013Correlations and volatility spillovers across commodity and stock markets: Linking energies, food, and gold556 cited
  • 2013Time-Varying Effects of Oil Supply Shocks on the US Economy

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530 cited
  • 2013Oil shocks, policy uncertainty and stock market return505 cited
  • Cited by

    • 2019Improving Adaptive Neuro-Fuzzy Inference System Based on a Modified Salp Swarm Algorithm Using Genetic Algorithm to Forecast Crude Oil Price62 cited
    • 2023Can multi-source heterogeneous data improve the forecasting performance of tourist arrivals amid COVID-19? Mixed-data sampling approach58 cited
    • 2022Oil futures volatility predictability: New evidence based on machine learning models51 cited
    • 2019Forecasting Crude Oil Price Using Kalman Filter Based on the Reconstruction of Modes of Decomposition Ensemble Model50 cited
    • 2022Forecasting stock market volatility with a large number of predictors: New evidence from the MS-MIDAS-LASSO model49 cited
    • 2021High frequency multiscale relationships among major cryptocurrencies: portfolio management implications29 cited