Abstract
We study whether investors’ fear can predict oil price volatility. The proxies used for investors’ fear are the CBOE Crude Oil Volatility Index (OVX), Google searches for “oil price”, and United States Oil Fund (USO) trading volume. In the in-sample analysis, we find that increased OVX, increased Google searches, and increased trading volume predict increased oil price volatility. Additionally, we find bidirectional Granger-causalities between volatility and OVX, volatility and Google searches, and volatility and trading volume. However, results are very different for the out-of-sample forecasts. We incorporate OVX, Google searches for “oil price”, trading volume, and their combinations into commonly used volatility models but find that these variables or their combinations improve none of the models in terms of out-of-sample forecasting.
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