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Efficient volatility estimation in a two-factor model

机译:两个因子模型中有效的波动性估计

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We statistically analyze a multivariate Heath-Jarrow-Morton diffusion model with stochastic volatility. The volatility process of the first factor is left totally unspecified while the volatility of the second factor is the product of an unknown process and an exponential function of time to maturity. This exponential term includes some real parameter measuring the rate of increase of the second factor as time goes to maturity. From historical data, we efficiently estimate the time to maturity parameter in the sense of constructing an estimator that achieves an optimal information bound in a semiparametric setting. We also nonparametrically identify the paths of the volatility processes and achieve minimax bounds. We address the problem of degeneracy that occurs when the dimension of the process is greater than two, and give in particular optimal limit theorems under suitable regularity assumptions on the drift process. We consistently analyze the numerical behavior of our estimators on simulated and real datasets of prices of forward contracts on electricity markets.
机译:我们在统计上分析了具有随机挥发性的多变量Heath-Jarrow-Morton扩散模型。第一因素的波动率过程完全未指定,而第二因素的波动性是未知过程的产物和成熟时间的指数函数。随着时间的推移,这种指数术语包括一些测量第二因素的增加率的真实参数。从历史数据中,我们有效地估计了在构建估计器的估计的意义上估计成熟时间的时间,该估计器实现了在半甲型设置中绑定的最佳信息。我们还非分解地识别波动率过程的路径并实现Minimax界限。我们解决了当过程的维度大于两个时发生的退化问题,并且在漂移过程上的合适规律性假设下给出特定的最佳限制定理。我们一直分析了我们对电力市场上向前合同价格的模拟和实际数据集的估算数的数值行为。

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