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- W2519362464 abstract "We apply heterogeneous autoregressive (HAR) models—including nine univariate, two multivariate and three combination models—to high-frequency data to predict the one-day forward volatilities of two strategically linked commodities, gold and silver. We provide evidence that it is difficult to beat the benchmark HAR model using univariate models and that, a much better strategy is to average the forecasts from many models. In addition, the forecasts are not improved by using volatilities from strategically linked commodities; thus, no volatility spillovers are detected. Interestingly, when the two strategically linked commodities are modelled together using the generalized HAR model, the forecasts are comparable to those of combination forecast models." @default.
- W2519362464 created "2016-09-23" @default.
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- W2519362464 date "2016-09-14" @default.
- W2519362464 modified "2023-10-17" @default.
- W2519362464 title "Volatility forecasting of strategically linked commodity ETFs: gold-silver" @default.
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- W2519362464 doi "https://doi.org/10.1080/14697688.2016.1211799" @default.
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