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市场摩擦的多期限检验AI 解读

We test for the presence of market frictions that induce transitory deviations of observed asset prices from the underlying efficient prices. Our test is based on the joint inference of return covariances across multiple horizons. We demonstrate that a small set of horizons suffices to identify a broad spectrum of frictions, both theoretically and practically. Our method works for high- and low-frequency data under different asymptotic regimes. Extensive simulations show our…

注意你的语言：市场对央行讲话的反应AI 解读

Central bank communication between meetings often moves markets, but researchers have traditionally paid less attention to it. Using a dataset of U.S. Federal Reserve speeches, we develop supervised multimodal natural language processing methods to identify how monetary policy news affect bond and stock market volatility and tail risk through implied changes in forecasts of GDP, inflation, and unemployment. We find that forecast revisions derived from FOMC-member speech can…

含特征驱动与特异 beta 的因子模型统一预测推断AI 解读

This paper investigates the impact of allowing for characteristic-based time-varying factor betas on the diffusion-index type forecasts. The factor beta consists of two distinct components: the “instrumental beta” is a function of some observable characteristics, while the “idiosyncratic beta” captures more volatile residual movements. To estimate these characteristic-based time-varying betas and the corresponding factors, we apply the projected principal component analysis…

杠杆效应估计：核函数与效率AI 解读

This article proposes more efficient estimators for the leverage effect than the existing ones. The idea is to allow for nonuniform kernel functions in the spot volatility estimates or the aggregated returns. This finding highlights a critical difference between the leverage effect and integrated volatility functionals, where the uniform kernel is optimal. Another distinction between these two cases is that the overlapping estimators of the leverage effect are more efficient…

基于相关矩阵的主成分分析的渐近性质AI 解读

It is a common practice to conduct principal component analysis (PCA) using standardized data, which is equivalent to applying PCA to the correlation matrix rather than the covariance matrix. Yet little research has been done about such differences in the context of high frequency data. This paper bridges this gap. We derive the analytical forms of the asymptotic biases and variances for the estimators of the integrated eigenvalues and eigenvectors. Furthermore, we propose a…

连续时间半参数估计：小带宽与大带宽下积分波动率泛函的渐近理论AI 解读

This article studies the estimation of integrated volatility functionals, which is a semiparametric two-step estimation problem in the nonstationary continuous-time setting. We generalize the asymptotic normality results of Jacod and Rosenbaum to a wider range of bandwidths. Moreover, we employ matrix calculus to obtain a new analytical bias correction and variance estimation method. The proposed method gives more succinct expressions than the element-by-element analytical…

用收缩方法、实时扩散指数与模型组合预测利率AI 解读

Summary In the context of predicting the term structure of interest rates, we explore the marginal predictive content of real‐time macroeconomic diffusion indexes extracted from a “data rich” real‐time data set, when used in dynamic Nelson–Siegel (NS) models of the variety discussed in Svensson (NBER technical report, 1994; NSS) and Diebold and Li ( Journal of Econometrics , 2006, 130 , 337–364; DNS). Our diffusion indexes are constructed using principal component analysis…

波动率泛函的时不变限制：有效估计与设定检验AI 解读

This paper studies the estimation and inference problems of time-invariant restrictions on certain known functions of the stochastic volatility process. We first develop a more efficient GMM estimator and derive the efficiency bound under such restrictions. Then we construct an integrated Hausman-type test by summing up the squared differences between this more efficient estimator and the unrestricted estimator computed at different time points. Although less efficient under…

跳跃自激性的检验AI 解读

This paper extends the notion of self-excitation in jumps to a rich class of continuous time semimartingale models, proposes statistical tests to detect its presence in a discretely observed sample path at high frequency, and derives the tests’ asymptotic properties. Our statistical setting is semiparametric: except for necessary parametric assumptions on the jump size measure, the other components of the semimartingale model are left essentially unrestricted. We analyze the…

高频数据中的相互激发跳跃与金融避险迁移检验AI 解读

We propose a new nonparametric test to identify mutually exciting jumps in high frequency data. We derive the asymptotic properties of the test statistics and show that the tests have good size and reasonable power in finite sample cases. Using our mutual excitation tests, we empirically characterize the dynamics of financial flights in forms of flight-to-safety and flight-to-quality. The results indicate that mutually exciting jumps and risk-off trades mostly occur in…

连续与不连续杠杆效应的估计AI 解读

This paper examines the leverage effect, or the generally negative covariation between asset returns and their changes in volatility, under a general setup that allows the log-price and volatility processes to be Itô semimartingales. We decompose the leverage effect into continuous and discontinuous parts and develop statistical methods to estimate them. We establish the asymptotic properties of these estimators. We also extend our methods and results (for the continuous…