Intraday order transition dynamics in high, medium, and low market cap stocks: A Markov chain approach
S. R. Luwang (1), A. Rai (1, 2), Md. Nurujjaman (1), F. Petroni (3), ((1) National Institute of Technology Sikkim, India, (2) Algolabs, Chennai, Mathematical Institute, India, (3) University of Chieti-Pescara, Italy)

TL;DR
This paper uses a Markov chain model to analyze intraday order transition dynamics across stocks of different market caps, revealing patterns in order types, modifications, and timing that vary throughout the trading day.
Contribution
It introduces a first-order Markov chain approach to compare order transition dynamics across market cap categories and time zones within high-frequency NASDAQ data.
Findings
Limit orders show higher inertia during opening hours.
Order transition behaviors differ across market cap categories.
Order transition patterns cluster except during opening and closing hours.
Abstract
An empirical stochastic analysis of high-frequency, tick-by-tick order data of NASDAQ100 listed stocks is conducted using a first-order discrete-time Markov chain model to explore intraday order transition dynamics. This analysis focuses on three market cap categories: High, Medium, and Low. Time-homogeneous transition probability matrices are estimated and compared across time-zones and market cap categories, and we found that limit orders exhibit higher degree of inertia (DoI), i.e., the probability of placing consecutive limit order is higher, during the opening hour. However, in the subsequent hour, the DoI of limit order decreases, while that of market order increases. Limit order adjustments via additions and deletions of limit orders increases significantly after the opening hour. All the order transitions then stabilize during mid-hours. As the closing hour approaches,…
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Taxonomy
TopicsFinancial Risk and Volatility Modeling · Complex Systems and Time Series Analysis · Stochastic processes and financial applications
