Bayesian learning provides the core concept of information processing in financial markets. Typically, it is assumed that market participants know perfectly the quality of released news. However, in practice, news' precision is rarely disclosed. Therefore, we extend standard Bayesian learning,...

We introduce a regularization and blocking estimator for well-conditioned high-dimensional daily covariances using high-frequency data. Using the Barndorff-Nielsen, Hansen, Lunde, and Shephard (2008a) kernel estimator, we estimate the covariance matrix block-wise and regularize it. A data-driven...

We analyze how markets adjust to new information when the reliability of news is uncertain and has to be estimated itself. We propose a Bayesian learning model where market participants receive fundamental information along with noisy estimates of news' precision. It is shown that the efficiency...

This paper is an investigation into the determinants of asymmetries in stock returns. We develop a series of cross-sectional regression specifications which attempt to forecast skewness in the daily returns of individual stocks. Negative skewness is most pronounced in stocks that have...

We assume that the instantaneous riskless rate reverts towards a central tendency which in turn, is changing stochastically over time. As a result, current short-term rates are not" sufficient to predict future short-term rates movements, as would be the case if the central" tendency was...

This paper is an investigation into the determinants of asymmetries in stock returns. We develop a series of cross-sectional regression specifications which attempt to forecast skewness in the daily returns of individual stocks. Negative skewness is most pronounced in stocks that have...

We study the implications of learning in an environment where the true model of the world is a multivariate one, but where agents update only over the class of simple univariate models. If a particular simple model does a poor job of forecasting over a period of time, it is eventually discarded...

This paper provides a guide to high frequency option trade and quote data disseminated by theOptions Price Reporting Authority (OPRA). We present a comprehensive overview of the U.S. option market, including details on market regulation and the trading processes for all 16 constituent option...

We study the implications of learning in an environment where the true model of the world is a multivariate one, but where agents update only over the class of simple univariate models. If a particular simple model does a poor job of forecasting over a period of time, it is eventually discarded...

We develop a model of monetary policy with two key features: (i) the central bank has private information about its long-run target for the policy rate; and (ii) the central bank is averse to bond-market volatility. In this setting, discretionary monetary policy is gradualist, or inertial, in the...