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

Ranjan R. Chakravarty and Sudhanshu Pani ()
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Ranjan R. Chakravarty: NMIMS University
Sudhanshu Pani: NMIMS University

Journal of Quantitative Economics, 2021, vol. 19, issue 4, No 1, 617-652

Abstract: Abstract Ultra High Frequency (UHF) quotes and trades are examined in high resolution and data patterns that do not correspond to plausible market activity as in Brownlees and Gallo (Comput Stat Data Anal 51(4):2232–2245, 2006) are identified. Noise patterns other than microstructure noise are isolated and diagnostic methods are evaluated accordingly. A flexible paradigm of data handling that synthesizes statistical technique and limit order book modelling is presented, extending Barndorff-Nielsen et al. (Econom J 12(3):C1–C32, 2009), which operationalises the use of expanded filtration in empirical microstructure research. Empirical evidence from the NASDAQ 100 is presented, comprehensively demonstrating that removal of non-microstructure noise from the limit order book adds significant robustness to estimation across techniques and levels of market depth.

Keywords: Robustification; Data handling; Limit order book; Model fit; Estimation; Filtration expansion; Ultra High Frequency (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s40953-021-00252-0

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