Christian Brownlees, Eulalia Nualart and Yucheng Sun, "Realized
Networks", Journal of Applied Econometrics, Vol. 33, No. 7, 2018,
pp. 986-1006.

The proprietary data used in this work come from the New York Stock
Exchange Trade and Quote (NYSE-TAQ) database. The NYSE-TAQ database
contains intraday transactions data (trades and quotes) for all
securities listed on the New York Stock Exchange (NYSE) and American
Stock Exchange (AMEX), as well as Nasdaq National Market System (NMS)
and SmallCap issues. The data can be accessed either directly at
http://www.nyxdata.com/ or through 
https://wrds-www.wharton.upenn.edu/.

The analysis of this work is based on the transaction price data in
the trades table of the TAQ database. We follow closely Brownlees and
Gallo (2006) and Barndorff-Nielsen, Hansen, Lunde, and Shephard (2009)
for the construction of the raw data series that is then used in the
paper. In particular, for each ticker analysed in the paper, we
extract all transaction prices that occurred between 9:30 and 16:05
with a correction indicator (CORR field) different from zero. When
multiple transaction prices are available at the same timestamp we 
pick the median price. Intraday high-frequency trading prices are
known to be contaminated by wrong observations, and we apply the
algorithm proposed in Brownlees and Gallo (2006) to identify such
observations and to delete them.  The resulting time series are then
used as inputs for the computation of the realized volatility series
used in the paper. We provide details on the exact construction of the
measures in the main body of the paper.

References

Brownlees, C. T. and Gallo, G. M. (2006). Financial econometric
analysis at ultra–high frequency: Data handling concerns.
Computational Statistics and Data Analysis, 51, 2232-2245.

Barndorff-Nielsen, O. E., Hansen, P. R., Lunde, A., and Shephard, N.
(2009).  Realised kernels in practice: Trades and quotes. Econometrics
Journal , 12, 1-32.

Christian Brownlees
christian.brownlees [AT] upf.edu