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 study high-frequency exchange rate movements over the sample 1993-2006. We document that the (Swiss) franc, euro, Japanese yen and the pound tend to appreciate against the U.S. dollar when (a) S&P has negative returns; (b) U.S. bond prices increase; and (c) when currency markets become more...

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...

Rapach et al. (2013) have recently shown that U.S. equity market returns carry valuable information to improve return forecasts in a large cross-section of international equity markets. In this study, we extend the work of Rapach et al. (2013) and examine if U.S. based equity market information...

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...

A very general stochastic volatility (SV) model specification with leverage, heavy tails, skew and switching regimes is proposed, using realized volatility (RV) as an auxiliary time series to improve inference on latent volatility. The information content of the range and of implied volatility...