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

45 Pages Posted: 26 Oct 2020

See all articles by Ranjan R. Chakravarty

Ranjan R. Chakravarty

School of Business Management, NMIMS

Sudhanshu Sekhar Pani

School of Business Management, NMIMS

Multiple version iconThere are 2 versions of this paper

Date Written: May 2, 2020

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

Suggested Citation

Chakravarty, Ranjan and Pani, Sudhanshu Sekhar, A Data Paradigm to Operationalise Expanded Filtration: Realized Volatilities and Kernels from Non-Synchronous NASDAQ Quotes and Trades (May 2, 2020). Available at SSRN: https://ssrn.com/abstract=3691669 or http://dx.doi.org/10.2139/ssrn.3691669

Ranjan Chakravarty

School of Business Management, NMIMS ( email )

V. L. Mehta Road,
Vile Parle (W),
Mumbai, 400 056
India

Sudhanshu Sekhar Pani (Contact Author)

School of Business Management, NMIMS ( email )

V. L. Mehta Road,
Vile Parle (W),
Mumbai, 400 056
India

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