We consider time series models in which the conditional mean of the response variable given the past depends on latent covariates. We assume that the covariates can be estimated consistently and use an iterative nonparametric kernel smoothing procedure for estimating the conditional mean...

This paper proposes a new mutual independence test for a large number of high dimensional random vectors. The test statistic is based on the characteristic function of the empirical spectral distribution of the sample covariance matrix. The asymptotic distributions of the test statistic under...

We propose new scoring rules based on partial likelihood for assessing the relative out-of-sample predictive accuracy of competing density forecasts over a specific region of interest, such as the left tail in financial risk management. By construction, existing scoring rules based on weighted...

This paper considers estimation and inference for varying-coefficient models with nonstationary regressors. We propose a nonparametric estimation method using penalized splines, which achieves the same optimal convergence rate as kernel-based methods, but enjoys computation advantages. Utilizing...

Many time series exhibit unconditional heteroskedasticity, often in addition to conditional one. But such time-varying volatility of the data generating process can have rather adverse effects when inferring about its persistence; e.g. unit root and stationarity tests possess null distributions...

Methods of inference based on a unit root assumption in the data are typically not robust to even small deviations from this assumption. In this paper, we propose robust procedures for a residual-based test of cointegration when the data are generated by a near unit root process. A Bonferroni...

This study investigates the asymptotic and finite-sample properties of KPSS-type cointegra-tion tests that use residuals from integrated and modified ordinary least squares estimations.The test statistic, denoted by KPSS^Fb is shown to provide a consistent test against the al-ternative of no...

We conduct a pseudo real-time analysis of the existence and severity of speculative bubbles in eleven US sectors over the period 1973-2015. Based on the real-time bubble signals, a trading strategy is constructed which switches funds between the market index and those industry sectors that...

In the context of predicting the term structure of interest rates, we explore the marginal predictive content of real-time diffusion indexes extracted from a “data rich” real-time dataset, when used in dynamic Nelson-Siegel (NS) models of the variety discussed in Diebold and Li (DNS: 2007)...