A Boosting Approach to Forecasting the Volatility of Gold-Price Fluctuations Under Flexible Loss
A Boosting Approach to Forecasting the Volatility of Gold-Price Fluctuations Under Flexible Loss
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DOI：
10.2139/ssrn.2513830
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发表时间：
2015-11
期刊：
影响因子：
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通讯作者：
Christian Pierdzioch;M. Risse;Sebastian Rohloff
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文献类型：
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作者：
Christian Pierdzioch;M. Risse;Sebastian Rohloff
我们使用boosting方法来研究各种金融和宏观经济变量的随时间变化的样本外信息含量，以预测黄金价格波动的波动性。我们使用样本外R2统计量来评估预测，作为预测者损失函数形状的函数。我们表明，与自回归基准预测相比，那些预测者往往受益于使用提振方法隐含的预测，当低估而不是高估黄金价格波动的未来波动性时，他们会遇到更大的损失。我们用模拟实验来研究这一效益的意义。
We use a boosting approach to study the time-varying out-of-sample informational content of various financial and macroeconomic variables for forecasting the volatility of gold-price fluctuations. We use an out-of-sample R2 statistic to evaluate forecasts as a function of the shape of a forecaster’s loss function. We show that, when compared to an autoregressive benchmark forecast, those forecasters tend to benefit from using predictions implied by the boosting approach who encounter a larger loss when underestimating rather than overestimating the future volatility of gold-price fluctuations. We use a simulation experiment to study the significance of this benefit.