Rare Events Analysis of High-Frequency Equity Data

Wilmott Journal, pp. 74-81, 2011

13 Pages Posted: 29 Feb 2012 Last revised: 2 Mar 2012

Dragos Bozdog

Stevens Institute of Technology

Ionut Florescu

Stevens Institute of Technology

Khaldoun Khashanah

Stevens Institute of Technology

Jim Wang

Stevens Institute of Technology

Date Written: July 1, 2011

Abstract

In this work we present a methodology to detect rare events which are defined as large price movements relative to the volume traded. We analyze the behavior of equity after the detection of these rare events. We provide methods to calibrate trading rules based on the detection of these events and illustrate for a particular trading rule. We apply the methodology to tick data for thousands of equities over a period of five days. In order to draw comprehensive conclusions, we group the equities into classes and calculate probabilities of price recovery after these rare events for each class. The methodology that we have developed is based on non-parametric statistics and makes no assumption about the distribution of the random variables in the study.

Keywords: high-frequency trading, average daily volume, trading strategy

JEL Classification: C61

Suggested Citation

Bozdog, Dragos and Florescu, Ionut and Khashanah, Khaldoun and Wang, Jim, Rare Events Analysis of High-Frequency Equity Data (July 1, 2011). Wilmott Journal, pp. 74-81, 2011. Available at SSRN: https://ssrn.com/abstract=2013355

Dragos Bozdog (Contact Author)

Stevens Institute of Technology ( email )

Castle Point on Hudson
Hoboken, NJ 07030
United States

HOME PAGE: http://personal.stevens.edu/~dbozdog/

Ionut Florescu

Stevens Institute of Technology ( email )

Castle Point on the Hudson
Hoboken, NJ 07030
United States

Khaldoun Khashanah

Stevens Institute of Technology ( email )

Hoboken, NJ 07030
United States

Jim Wang

Stevens Institute of Technology ( email )

Hoboken, NJ 07030
United States

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