The wide availability of high-frequency data for many financial instruments stimulates an upsurge interest in statistical research on the estimation of volatility. Jump-diffusion processes observed with market microstructure noise are frequently used to model high-frequency financial data. Yet, existing methods are developed for either noisy data from a continuous diffusion price model or data ...

This study analyzes the relationship between information asymmetry and dividend policy in an emerging market, Korea. We adopt several proxies for asymmetry, such as Glosten–Harris Hasbrouk–Foster–Viswanathan models, drawn from market microstructure literature. finds a negative yields, which appears to be particularly strong when firms have difficulty raising external capital because they high s...

In this paper we extend the series of our studies on the properties of an interacting particle model for market microstructure. In our earlier work we defined a Markov process on the majority opinion of the agents, obtained the transition probabilities and analyzed the martingale properties of the ensuing wealth process. Here we relax the assumption on the choices of individual agents by allowi...

Asset prices observed in financial markets combine equilibrium prices and market microstructure noise. In this paper, we study how to tell apart large shifts in equilibrium prices from noise using high frequency data. We propose a new nonparametric test which allows us to asymptotically remove the noise from observable price data and to discover jumps in fundamental asset values. We provide its...

Currency trading is a vast and highly profitable business. This review examines the profitability of two popular currency trading strategies in light of currency-market microstructure research. The carry-trade strategy involves borrowing a low-interest currency and investing the proceeds in a high-interest currency. Technical trading strategies are determined exclusively on the basis of past as...

Real-time market microstructure analysis: online transaction cost analysis R. Azencott, A. Beri, Y. Gadhyan, N. Joseph, C.-A. Lehalle & M. Rowley a Department of Mathematics, University of Houston, Houton, TX, USA b Ecole Normale Supérieure Cachan, Cachan, France c Mathematical Biosciences Institute, The Ohio State University, Columbus, OH, USA d Cluster Innovation Center, University of Delhi, ...

An Autoregressive Conditional Marked Duration (ACMD) model for the analysis of irregularly spaced transactions data is proposed. Based on the Autoregressive Conditional Duration (ACD) model of Engle and Russell (1998), the ACMD model assigns marks to characterize events such as price movements, order arrivals, or quote revisions. By marking tick movements, we study the influence of trade freque...