  In this paper, we build on the analysis of Muni Toke and Yoshida (2020) and
conduct several empirical studies using high-frequency financial data. Muni
Toke and Yoshida (2020) showed the consistency and asymptotic behavior of the
Cox-type model estimators for relative intensities of orders in the limit order
book, and then by using high-frequency trading data for 36 stocks traded on the
Paris Stock Exchange, they carry out model selection and trading sign
prediction. In this study, we add new covariates and carry out model selection
and trading sign prediction using high-frequency trading data for 222 stocks
traded on the Tokyo Stock Exchange. We not only show that the Cox-type model
performs well in the Japanese market as well as in the Euronext Paris market,
but also present the key factors for more accurate estimation. We also suggest
how often the covariates should be calibrated.
