While attention is a predictor for digital asset prices, and jumps in Bitcoin prices are well-known, we know little about its alternatives. Studying high frequency crypto data gives us the unique possibility to confirm that cross market digital asset returns are driven by high frequency jumps...

This paper quantifies the amount of noise and bias in analysts' forecast of corporate earnings at various horizons. We first show analyst forecasts outperform statistical forecasts at short-horizons, but underperform at longer horizons. We next decompose the relative accuracy of these forecasts...

We consider the problem of estimating volatility based on high-frequency data when the observed price process is a continuous Itô semimartingale contaminated by microstructure noise. Assuming that the noise process is compatible across different sampling frequencies, we argue that it typically...

We study the interaction of noisy demand and skewed asset payoffs. In our model, price as a function of quantities is convex in a neighborhood around zero if and only if skewness is positive. The combination of convexity and noise produces the idiosyncratic skewness effect--a documented negative...

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...

Both the literature and new empirical evidence show that exchange rate regimes differ primarily by the noisiness of the exchange rate, not be measurable macroeconomic fundamentals. This motivates a theoretical analysis of exchange rate regimes with noise traders. The presence of noise traders...

We study the problem of jump detection for ultra-high-frequency tick-by-tick data. We propose a novel easy-to-implement procedure that can separate the contribution of microstructure noise and that of finite activity price jumps from the price process, which may have interesting implications on...

We introduce the Realized moMents of Disjoint Increments (ReMeDI) paradigm to measure microstructure noise (the deviation of the observed asset prices from the fundamental values caused by market imperfections). We propose consistent estimators of arbitrary moments of the microstructure noise...

This paper develops a strategic trading model in which uninformed orders are allowed to exhibit a general correlation structure that generates autocorrelation in the order flow. Since the order flow is predictable, informed traders and the market maker not only need to infer information about...