Time changes of Brownian motion impose restrictive jump structures in the motion of asset prices. Quadratic variations also depart from time changes. Joint Laplace Fourier transforms for quadratic variation and the stock are developed. They are used to study the multiple of the cap strike over...

This paper develops a novel method to correct small-sample bias in autoregressive roots of AR(p) models. We evaluate median-bias properties and variability of the bias-adjusted parameters by examining the accuracy of bias-adjusted impulse responses. Our simulation results show that bias...

This paper proposes efficient estimation of risk measures by fully exploring the first and second moment information in a GARCH framework. We propose a quantile estimator based on inverting an empirical likelihood weighted distribution estimator. It is found that the new quantile estimator is...

This paper develops and compares nonnested hypothesis tests for linear regression models with first-order serially correlated errors. It extends the nonnested testing procedures of Pesaran, Fisher and McAleer, and Davidson and MacKinnon, and compares their performance on four conventional models...

This paper develops the asymptotic theory of the threshold pre-averaged multi-power variation estimation in the simultaneous presence of jumps and market microstructure noise and then proposes an improved estimator for integrated volatility of an Itô semi-martingale based on the obtained...

I present a peer effects model for count data using a static game of incomplete information. I provide sufficient conditions under which the game equilibrium is unique. I estimate the model's parameters using the Nested Partial Likelihood approach and establish asymptotic properties of the...

We propose a dynamic factor state-space model for the prediction of high-dimensional realized covariance matrices of asset returns. Using a block LDL decomposition of the joint covariance matrix of assets and factors, we express the realized covariance matrix of the individual assets similar to...

We adopt a flexible filtering procedure to extract information from high-frequency data. Specifically, we provide a parsimonious framework to integrate realized measures from high frequency index and derivative prices. In a simulation study, we document the incremental information offered by...

We estimate the latent factors in high-dimensional panel non-Gaussian data using Higher-order multi-cumulant Factor Analysis (HFA). HFA consists of an eigenvalue ratio test to select the number of non-Gaussian factors and uses alternating regressions to estimate both Gaussian and non-Gaussian...