We propose a novel way to assess information processing in a complex environment of market fragmentation. We take a different angle from the price discovery literature, and investigate information processing in the stochastic process driving stock's volatility (volatility discovery). We show...

We show that the standard econometric framework typically yields inconsistent estimates of price discovery measures in the presence of richer market microstructure noise dynamics. We address this errors-in-variable issue using instrumental variables. We devise valid instruments for two...

We formulate a price discovery model in which the price discovery measures vary either locally, say, for instance, at intervals of 30 minutes or at a daily frequency. Given the empirical and theoretical evidence that price discovery measures relate to highly persistent fundamentals, we adopt a...

We formulate a continuous-time price discovery model and investigate how the standard price discovery measures vary with respect to the sampling interval. We find that the component share measure is invariant to the sampling interval, and hence discrete-sampled prices suffice to identify the...

A new type of momentum based on the signs of past returns is introduced. This momentum is driven primarily by sign dependence, which is positively related to average return and negatively related to return volatility. An empirical application using a universe of commodity and financial futures...