Date of Award

Spring 5-2017

Author's School

Graduate School of Arts and Sciences

Author's Department

Mathematics

Additional Affiliations

Statistics

Degree Name

Master of Arts (AM/MA)

Degree Type

Thesis

Abstract

The price process in electronic markets is one prototypical example of a stochastic process, and it has historically be fitted and analyzed using different stochastic models such as Levy processes, diffusions, and SDEs (stochastic differential equations). In this thesis, we analyze Microsoft stock data in 2014-11-03 with the goal of studying the presence of jumps based on Limit Order Book (LOB) data. To this end, we divide the whole day’s data into many consecutive intervals and proceed to apply a jump detection method to identify the intervals that could potentially have jumps. After obtaining the intervals with potential jumps, we zoom in these intervals and compare them in order to characterize their features. More specifically, we analyze the price LOB data from both the traditional side and the statistical side, and our aim is that try to identify statistical differences between the intervals with jumps and without any jump, and then give evidence to support this jump detection method and conjecture reasons for the appearance of sharp price changes in small intervals.

Language

English (en)

Chair and Committee

Jose E. Figueroa-Lopes

Committee Members

Jose E. Figueroa-Lopes,Todd Kuffner

Comments

Permanent URL: https://doi.org/10.7936/K70Z71QC

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