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Modelling Limit Order Book Volume Covariance Structures

In: Advances in Statistical Methodologies and Their Application to Real Problems

Author

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  • Andrija Mihoci

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.

Suggested Citation

  • Andrija Mihoci, 2017. "Modelling Limit Order Book Volume Covariance Structures," Chapters, in: Tsukasa Hokimoto (ed.), Advances in Statistical Methodologies and Their Application to Real Problems, IntechOpen.
    • Handle: RePEc:ito:pchaps:109187
    DOI: 10.5772/66152
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    Cited by:

    1. repec:hum:wpaper:sfb649dp2017-026 is not listed on IDEAS
    2. Chen, Likai & Wang, Weining & Wu, Wei Biao, 2017. "Dynamic semiparametric factor model with a common break," SFB 649 Discussion Papers 2017-026, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    More about this item

    Keywords

    limit order book; multivariate techniques; principal components analysis; factor analysis; discriminant analysis;
    All these keywords.

    JEL classification:

    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General

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