This paper considers the problem of estimating spot volatility in the simultaneous presence of Lévy jumps and market microstructure noise. We propose to use the pre-averaging approach and the threshold kernel-based method to construct a spot volatility estimator, which is robust to both...

This paper constructs unbiased and model-free measures of daily and hourly volatility of the overnight interest rate negotiated on the Italian interbank deposits market (e-MID) using high-frequency transaction data. We find that the largest increases in volatility and the most notable variations...

For decades, the academic literature has focused on three survey measures of expected inflation: the Livingston Survey, the Survey of Professional Forecasters, and the Michigan Survey. While these measures have been useful in developing models of forecasting inflation, the data are low frequency...

We study nonparametric estimation of the volatility function of a diffusion process from discrete data, when the data are blurred by additional noise. This noise can be white or correlated, and serves as a model for microstructure effects in financial modeling, when the data are given on an...

We study whether the accuracy of news announcements matters for the impact of news on exchange rate volatility. We use high-frequency EUR/USD returns and releases of 20 US macroeconomic indicators, and measure the precision of news in three different ways. When the precision is defined by the...

This paper decomposes volatility proxies according to upward and downward price movements in high-frequency financial data, and uses this decomposition for forecasting volatility. The paper introduces a simple Garch-type discrete time model that incorporates such high-frequency based statistics...