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低频污染下分数协整的中频带最小二乘估计AI 解读

This paper introduces a new estimator of the fractional cointegrating vector between stationary long memory processes that is robust to low-frequency contamination such as random level shifts, outliers, Markov switching means, and certain deterministic trends. In particular, the proposed medium band least squares (MBLS) estimator uses sample-size-dependent trimming of frequencies in the vicinity of the origin to account for such contamination. Consistency and asymptotic…

SR 方法：非线性非高斯动态期限结构模型的新估计程序AI 解读

This paper suggests a new approach for estimating linear and non-linear dynamic term structure models with latent factors. We impose no distributional assumptions on the factors which therefore may be non-Gaussian. The novelty of our approach is to use many observables (yields or bond prices) in the cross-section dimension. This implies that the latent factors can be determined quite accurately by a sequence of cross-section regressions. We also show how output from these…

GARCH 均值模型中的半参数推断AI 解读

A new semiparametric estimator for an empirical asset pricing model with general nonparametric risk-return tradeoff and GARCH-type underlying volatility is introduced. Based on the profile likelihood approach, it does not rely on any initial parametric estimator of the conditional mean function, and it is under stated conditions consistent, asymptotically normal, and efficient, i.e., it achieves the semiparametric lower bound. A sampling experiment provides finite sample…

隐含波动率对外汇、股票与债券波动率及跳跃预测的作用AI 解读

We study the forecasting of future realized volatility in the foreign exchange, stock, and bond markets from variables in our information set, including implied volatility backed out from option prices. Realized volatility is separated into its continuous and jump components, and the heterogeneous autoregressive (HAR) model is applied with implied volatility as an additional forecasting variable. A vector HAR (VecHAR) model for the resulting simultaneous system is…