Investigating Intertrade Durations using Copulas: An Experiment with NASDAQ Data

Autor:	Ranjan R. Chakravarty, Sudhanshu Pani
Rok vydání:	2022
Předmět:	Computational Mathematics Computer Vision and Pattern Recognition Finance Computer Science Applications
Zdroj:	Algorithmic Finance. 9:81-102
ISSN:	2157-6203 2158-5571
Popis:	The pattern of dependence between liquidity, durations (orders and trades) and bid-ask spreads in a limit order market are examined in high resolution invoking copulas and graph theory. Using intraday data from a sample of NASDAQ 100 stocks and an experimental design, we study the information pathways in markets in the presence of algorithmic traders. Our results confirm that multivariate analysis is more appropriate to investigate these information pathways. We observe that the strength and nature of the dependence between variables vary through the trading day. We confirm the existence of stylised aspects of algorithmic trading, such as tail dependence in trade durations, a balance between buy and sell side in order durations, liquidity and bid-ask spreads, and the bid-ask spread and liquidity trade-off in the dependence structure.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::ed4b92c95fe180584058fc4942830fd7 https://doi.org/10.3233/af-200362 Zobrazit plný text záznamu