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VIX forecasting and variance risk premium: A new GARCH approach

机译:VIX预测和方差风险溢价:一种新的GARCH方法

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This paper proposes to forecast VIX under GARCH(1,1), GJR, and Heston-Nandi models, and to assess variance risk premium innovatively. The one-day out-of-sample VIXs, computed with traditional empirical GARCH parameters, turn out to be below the market VIXs by roughly 20-30% (10-13%) on average before (after) 22 September 2003. The underestimation is interpreted as a kind of variance risk premium, which for the later part of the data turns out to be significantly smaller. On the other hand, risk-neutral GARCH models can be obtained by calibration against the prior-day market VIX. For the same dataset, the risk-neutral parameters forecast the one-day out-of-sample VIXs with errors within -0.30 to 0.03% on average. (C) 2015 Elsevier Inc. All rights reserved.
机译:本文建议在GARCH(1,1),GJR和Heston-Nandi模型下预测VIX,并创新地评估方差风险溢价。使用传统的经验GARCH参数计算的一日样本VIX低于2003年9月22日之后的市场VIX平均约20-30%(10-13%)。被解释为一种方差风险溢价,对于数据的后半部分,事实证明该溢价明显较小。另一方面,可以通过根据前一天的市场VIX进行校准来获得风险中性的GARCH模型。对于同一数据集,风险中性参数预测了一天的样本外VIX,平均误差在-0.30到0.03%之间。 (C)2015 Elsevier Inc.保留所有权利。

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