Motivated by the need for an unbiased and positive-semidefinite estimator of multivariate realized covariance matrices, we model noisy and asynchronous ultra-high-frequency asset prices in a state-space framework with missing data. We then estimate the covariance matrix of the latent states...

We propose a new methodology to estimate the empirical pricing kernel implied from option data. In contrast to most of the studies in the literature that use an indirect approach, i.e. first estimating the physical and risk-neutral densities and obtaining the pricing kernel in a second step, we...

We provide new empirical evidence on volatility forecasting in relation to asymmetries present in the dynamics of both return and volatility processes. Leverage and volatility feedback effects among continuous and jump components of the S&P500 price and volatility dynamics are examined using...

Building on the results of Ludwig (2012), we propose a method to construct robust time-homogeneous Markov chains that capture the risk-neutral transition of state prices from current snapshots of option prices on the S&P 500 index. Using the recovery theorem of Ross (2013), we then derive the...

Realized volatility computed from high-frequency data is an important measure for many applications in finance. However, its dynamics are not well understood to date. Recent notable advances that perform well include the heterogeneous autoregressive (HAR) model which is economically...

We suggest a joint analysis of ex-post intra-day variability in an option and its associated underlying asset market as a novel means of validating an option pricing model. For this purpose, we introduce the notion of option realized variance, by which we mean the cumulative variance realized by...

We empirically investigate the predictive power of the various components affecting correlations that have been recently introduced in the literature. We focus on models allowing for a flexible specification of the short-run component of correlations as well as the long-run component. Moreover,...

A (conservative) test is constructed to investigate the optimal lag structure for forecasting realized volatility dynamics. The testing procedure relies on the recent theoretical results that show the ability of the adaptive least absolute shrinkage and selection operator (adaptive lasso) to...

We derive new theoretical results on the properties of the adaptive least absolute shrinkage and selection operator (adaptive lasso) for time series regression models. In particular we investigate the question of how to conduct finite sample inference on the parameters given an adaptive lasso...

Using retrospective survey data that covers 1939, 1950, 1960, and 1971, I compare individual-level changes in employment industry and occupational status in Germany from the beginning of World War II to the post-war reconstruction era dubbed the Economic Miracle (Wirtschaftswunder). This...