A Study of Information Regimes in the Limit Order Book
In this dissertation I examine the existence and the identification of information regimes in the limit order book as defined by Lehmann (2008). The importance of identifying information regimes is that they explain the formation of the prices and the best quotes process. According to the theory, the best quotes process is comprised of three elements: movement along the same limit order book within a regime, moving from one regime to another and the mapping between the price schedule and the underlying value, which also accounts for moving from one regime to another. Simply putted, in the price process there is movement along a curve and moving from one curve to the other. The current market microstructure models do not account for these two distinct phenomena and in that respect are incomplete. Once, the existence of the information regimes is established, I investigate how the best quotes, the underlying value and the depth of the limit order book series interact with each other and how they change trough time. Based on these interactions, I propose that the regimes can be categorized in different groups. Further, I attempt to forecast the depth of the book, which as demonstrated, is more reliable of capturing all information events than the best quotes. In this study I am also interested in finding what triggers the changes from one regime to the other, how long the regimes are, is there transition period between the regimes and how long these periods are. One attempt to explain the changes of regimes is by estimation of Volume-Synchronized Probability of Informed Trading (VPIN) metric proposed by Easley et al. (2011). A major topic in the study is the use of wavelet analysis of limit order book. I propose the use of wavelet multi-resolution analysis in order to identify information regimes. In relation to wavelet theory I apply the use fractional Brownian motion (fBm) simulation of the depth of the book and compare the results to a more traditional vector autoregression model (VAR).
Trendafilov, Rossen, "A Study of Information Regimes in the Limit Order Book" (2012). ETD Collection for Fordham University. AAI3543393.