Date of Award

Spring 5-18-2018

Author's School

Graduate School of Arts and Sciences

Author's Department

Mathematics

Degree Name

Master of Arts (AM/MA)

Degree Type

Thesis

Abstract

Traders utilize strategies by using a mix of market and limit orders to generate profits. There are different types of traders in the market, some have prior information and can learn from changes in prices to tweak her trading strategy continuously(Informed Traders), some have no prior information but can learn(Uninformed Learners), and some have no prior information and cannot learn(Uninformed Traders). In this thesis. Alvaro C, Sebastian J and Damir K \cite{AL} proposed a model for algorithmic traders to access the impact of dynamic learning in profit and loss in 2014. The traders can employ the model to decide which strategies to use. The model considered the distribution of the prices in the future using prior information, the spread of the bid and ask prices and also the capital appreciation of inventories. I implemented the model for the case when the trader can only learn from and take positions in one asset. Compared to the uninformed traders, the informed trader using the proposed model can change the strategies along time and make higher profits.

Language

English (en)

Chair and Committee

Prof. José E. Figueroa-López

Committee Members

Prof. Nan Lin

Comments

Permanent URL: https://doi.org/10.7936/K7668CN8

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