Abstract
In this study, we estimate the order execution probability of a limit-order book (LOB) and analyze its determinants using high-frequency LOB data from the National Stock Exchange (NSE) of India. For this purpose, we propose an algorithm that estimates the LOB execution time. Using a survival function with log-normal distribution, this study analyzes the significant determinants of the limit-order execution times. The average execution probability is found to be higher for stocks belonging to the information technology and telecom sectors. The limit-order execution probability increases with a larger bid–ask spread, lower limit-order size, and deeper opposite order book. On the other hand, multiple factors, including price aggressiveness, inferior price, limit-order size, and spread, have a direct impact on execution times. The findings could help traders understand various factors influencing the probability of execution and execution time of LOBs. This study is unique in that it models limit-order execution using high-frequency tick-by-tick trading data for emerging markets, such as the NSE of India.
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Recommended Citation
Pan, Aritra and Misra, Arun Kumar
(2022)
"Carry Forward Modeling for High-Frequency Limit-Order Executions: An Emerging Market Perspective,"
American Business Review: Vol. 25:
No.
1, Article 7.
DOI: 10.37625/abr.25.1.92-119
Available at:
https://digitalcommons.newhaven.edu/americanbusinessreview/vol25/iss1/7
DOI
10.37625/abr.25.1.92-119
