STOCHASTIC MODELING OF LIMIT ORDER BOOKS: CONVERGENCE OF THE PRICE PROCESS, SIMULATION AND APPLICATIONS

In the past two decades, electronic limit order books (LOBs) have become the most important mechanism through which securities are traded. A LOB contains the current supply and demand of a security at different prices and it can be modeled as a random, state-dependent, and high-dimensional system since typically a great number of orders are placed at many different prices at a millisecond time scale. These features lead to an inherent mathematical complexity which is extremely hard to describe in a tractable manner. Thus, depending on the purpose, different models have been proposed to capture specific properties of the underlying trading mechanism, making LOB modeling a trending topic in the quantitative and investment finance literature for the past few years. Some of the most important objectives for which a LOB model is designed are to provide algorithmic trading strategies, bottom-up estimates for a variety of parameters, better understanding of asset price formation.

Name thesis:degree_name

Doctor of Philosophy (PhD)

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Mathematics

Year

2015

Author dc:creator

• Chavez Casillas, Jonathan Allan

Contributors dc:contributor

• Jose E Figueroa Lopez
• Frederi Viens
• Jonathon Peterson
• Raghu Pasupathy

• Level I
• Limit Order Book
• Sparsity

Repository record dc:identifier

https://docs.lib.purdue.edu/open_access_dissertations/1342

OAI identifier oai:identifier

oai:docs.lib.purdue.edu:open_access_dissertations-2558