Modelling Limit Order Book Volume Covariance Structures

Andrija Mihoci

A chapter in Advances in Statistical Methodologies and Their Application to Real Problems from IntechOpen

Abstract: Limit order volume data have been here analysed using key multivariate techniques: principal components, factor and discriminant analysis. The focus lies on understanding of the covariance structure of posted quantities of the asset to be potentially sold or bought at the market. Employing the methods to data of 20 blue chip companies traded at the NASDAQ stock market in June 2016, one observes that two principal components account for approximately 85-95% of order book variation. The most important factor related to order book data variation has furthermore been the demand side (variability). The order book data variation, moreover, successfully classifies stock price movements. Potential applications include improving order execution strategies, designing trading algorithms and understanding price formation.

Keywords: limit order book; multivariate techniques; principal components analysis; factor analysis; discriminant analysis (search for similar items in EconPapers)
JEL-codes: C60 (search for similar items in EconPapers)
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.intechopen.com/chapters/53134 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ito:pchaps:109187

DOI: 10.5772/66152

Access Statistics for this chapter

More chapters in Chapters from IntechOpen
Bibliographic data for series maintained by Slobodan Momcilovic ().