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Oil futures volatility predictability: New evidence based on machine learning models · Study

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ArticleOil futures volatility predictability: New evidence based on machine learning models

Xinjie Lu2022

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Articlegreen2022

Oil futures volatility predictability: New evidence based on machine learning models

Xinjie Lu · Feng Ma · Jin Xu · Zehui Zhang

51 citations·0/0 files stored·International Review of Financial Analysis

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Stock Market Forecasting Methods Financial Risk and Volatility Modeling Market Dynamics and Volatility

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References

2020Empirical Asset Pricing via Machine Learning 2006Approximately normal tests for equal predictive accuracy in nested models 1989Combining forecasts: A review and annotated bibliography 2009THE IMPACT OF OIL PRICE SHOCKS ON THE U.S. STOCK MARKET*2009Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy 2006Chapter 4 Forecast Combinations 2010Volatility forecast comparison using imperfect volatility proxies 2004Combination forecasts of output growth in a seven‐country data set

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Year2022

Typearticle

Published2022-07-13

VenueInternational Review of Financial Analysis

ISSN-L1057-5219

Languageen

Citations51

Files0 public / 0

ShelfStock Market Forecasting Methods

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doi10.1016/j.irfa.2022.102299

openalex_workW4285401607

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