An Econophysics Approach to Short Time-Scale Dynamics of the Equities Markets

Abstract

Financial markets have evolved drastically over the last decade due to the advent of high frequency trading and ubiquitous influence of algorithmic trading. Analyzing the equities markets has become an extremely data intensive and noisy undertaking. This work explores the information content of equity order book data outside of the inside price. First, an object-oriented library is presented to efficiently construct and maintain the order books of individual securities, by parsing and processing NASDAQ TotalView-ITCH data files. This library is part of the NASDAQ Order Processing software suite developed through this research effort. A framework for forecasting the returns of stock symbols that combines vector autoregression and principal component analysis is presented to determine if additional order book data, such as the volume of canceled orders and deleted orders, affects the price dynamics of stocks. Although the resulting model did not provide an adequate methodology for reliably forecasting prices, it was determined that information in the order book beyond returns and order volume should be included in market dynamics. This research also presents a novel visualization technique for viewing market dynamics and limit order book structure.