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- Corpus ID: 59584867
@article{Huang2012PriceVF, title={Price Volatility Forecast for Agricultural Commodity Futures： The Role of High Frequency Data}, author={Wen Huang and Zhuo Huang and Marius Matei and Tianyi Wang}, journal={Romanian Journal of Economic Forecasting}, year={2012}, volume={15}, pages={83-103}, url={https://api.semanticscholar.org/CorpusID:59584867}}- Wen Huang, Zhuo Huang, Tianyi Wang
- Published 2012
- Agricultural and Food Sciences, Economics
- Romanian Journal of Economic Forecasting
Realized measures of volatility based on high frequency data contain valuable information about the unobserved conditional volatility. In this paper, we use the Realized GARCH model developed by Hansen, Huang and Shek (2012) to estimate and forecast price volatility for four agricultural commodity futures. Empirical evidences, both in-sample and out-of-sample, show that the Realized GARCH model and its variants outperform the conventional volatility models that only use daily price data, such…
11 Citations
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11 Citations
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- Dr. Tejaskumar R. GhadiyaliDr. Kalpesh B. Lad
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Agricultural and Food Sciences, Economics
In this paper we compare the incremental information content of lagged implied volatility to GARCH models of conditional volatility for a collection of agricultural commodities traded on the New York…
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Agricultural and Food Sciences, Economics
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Agricultural and Food Sciences, Economics
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This article applies the realized GARCH model, which incorporates the GARCH model with realized volatility (RV), to quantile forecasts of financial returns such as Value-at-Risk and expected…
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