ERA

Download the full-sized PDF of Algorithmic Trading: Implementing PVol in Discrete TimeDownload the full-sized PDF

Analytics

Share

Permanent link (DOI): https://doi.org/10.7939/R3D795K22

Download

Export to: EndNote  |  Zotero  |  Mendeley

Communities

This file is in the following communities:

Graduate Studies and Research, Faculty of

Collections

This file is in the following collections:

Theses and Dissertations

Algorithmic Trading: Implementing PVol in Discrete Time Open Access

Descriptions

Other title
Subject/Keyword
Finance
Percentage Volume
Discrete Time
Algorithmic Trading
Mathematics
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Yang, Zhuolin
Supervisor and department
Frei, Christoph (Mathematical and Statistical Sciences)
Examining committee member and department
Melnikov, Alexander (Mathematical and Statistical Sciences)
Frei, Christoph (Mathematical and Statistical Sciences)
Schmuland, Byron (Mathematical and Statistical Sciences)
Cadenillas, Abel (Mathematical and Statistical Sciences)
Choulli, Tahir (Mathematical and Statistical Sciences)
Department
Department of Mathematical and Statistical Sciences
Specialization
Mathematical Finance
Date accepted
2013-09-24T14:30:29Z
Graduation date
2013-11
Degree
Master of Science
Degree level
Master's
Abstract
This thesis considers PVol (Percentage of Volume) strategies, which are an often used type of algorithmic trading strategies. In a PVol strategy, the broker aims to bring the order execution speed in line with a percentage of the market volume. This target percentage and the total order size are typically given by the client. In a discrete-time setting, we analyze the optimization problem of minimizing the expected deviations between the realized portion of trading and the target percentage. Under different assumptions, we either solve the problem explicitly or implement a numerical solution in MATLAB.
Language
English
DOI
doi:10.7939/R3D795K22
Rights
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
Citation for previous publication
[1] R. Almgren and N. Chriss (2000): Optimal Execution of Portfolio Transactions, Journal of Risk 3, 5–59[2] S. Berkowitz, D. Logue and E. Noser (1988): The Total Cost of Transactions on the NYSE. Journal of Finance 43, 97–112.[3] O. Guéant (2013): Execution and Block Trade Pricing with Optimal Constant Rate of Participation. Preprint available at arXiv:1210.7608.[4] O. Kallenberg (2002): Foundations of Modern Probability, second Edition. Springer, New York.

File Details

Date Uploaded
Date Modified
2014-05-01T17:30:16.917+00:00
Audit Status
Audits have not yet been run on this file.
Characterization
File format: pdf (Portable Document Format)
Mime type: application/pdf
File size: 269427
Last modified: 2015:10:12 14:37:25-06:00
Filename: Yang_Zhuolin_Fall 2013.pdf
Original checksum: 5c1f470816745ea13cf512a228f19a9b
Well formed: true
Valid: true
Page count: 72
Activity of users you follow
User Activity Date