A Data Paradigm to Operationalise Expanded Filtration: Realized Volatilities and Kernels from Non-Synchronous NASDAQ Quotes and Trades

Abstract

Ultra High Frequency (UHF) quotes and trades are examined in high resolution. Patterns which do not correspond to plausible market activity as in Brownlees and Gallo (2006) are observed. Noise other than microstructure noise is identified and diagnostic methods are evaluated. Extending Barndorff-Nielsen et al. (2009), a paradigm of data handling that synthesizes statistical technique and limit order book modeling is developed. The data paradigm operationalises the use of expanded filtration in empirical research. Empirical evidence from the NASDAQ 100 demonstrates that removal of non microstructure noise from the limit order book robustifies estimation across techniques and levels of market depth.

Keywords: Robustification, Data Handling, Limit Order Book, Model Fit, Estimation, Filtration expansion, Ultra High Frequency

JEL Classification: G1