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Effects of structural changes on the prediction of downside volatility in futures markets
Author(s) -
Gong Xu,
Lin Boqiang
Publication year - 2021
Publication title -
journal of futures markets
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.88
H-Index - 55
eISSN - 1096-9934
pISSN - 0270-7314
DOI - 10.1002/fut.22207
Subject(s) - downside risk , volatility (finance) , economics , futures contract , econometrics , autoregressive model , realized variance , financial economics , portfolio
We develop a heterogeneous autoregressive model of downside volatility (HAR‐DV) model with structural changes (HAR‐DV‐SC) model to investigate the effects of structural changes on predicting downside volatility. Then we employ HAR‐DV and HAR‐DV‐SC models to forecast downside volatilities in S&P 500 index, crude oil, gold, copper, and soybean futures markets. The in‐sample analysis shows that structural changes contain in‐sample information for predicting downside volatility. The out‐of‐sample analysis indicates that the HAR‐DV‐SC model outperforms the HAR‐DV model, suggesting that structural changes contain incremental out‐of‐sample information on future downside volatility. These results are robust and have important implications for risk management of stakeholders.