Proceedings of the 2014 International Conference on Mechatronics, Electronic, Industrial and Control Engineering

An Dynamic Statistical Arbitrage Trading System

Authors
Yang Liu, Guibin Lu
Corresponding Author
Yang Liu
Available Online November 2014.
DOI
10.2991/meic-14.2014.287How to use a DOI?
Keywords
component;Statistical arbitrage; Mispricing; Quantile; Normal Distribution; Dynamic-GARCH;
Abstract

Objective – The paper’s aim is to explore an efficient statistical arbitrage system. Methods – The paper use moving-window and Regression model to identify the volatility of the relation between two assets. When the relation move beyond normal range which defined by quantile, arbitrage opportunities occur. Result –Residuals from moving-window regression model is very close to normal distribution. Generally the arbitrage system is profitable under different parameters. An instance show the system’s total rate of return is 18.9%. Conclusion –The profit curve tend to be flat in recent years. Parameters used in the framework should be changed intelligently, because misprice may be corrected in shorter or longer term than history.

Copyright
© 2014, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2014 International Conference on Mechatronics, Electronic, Industrial and Control Engineering
Series
Advances in Engineering Research
Publication Date
November 2014
ISBN
978-94-62520-42-4
ISSN
2352-5401
DOI
10.2991/meic-14.2014.287How to use a DOI?
Copyright
© 2014, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Yang Liu
AU  - Guibin Lu
PY  - 2014/11
DA  - 2014/11
TI  - An Dynamic Statistical Arbitrage Trading System
BT  - Proceedings of the 2014 International Conference on Mechatronics, Electronic, Industrial and Control Engineering
PB  - Atlantis Press
SP  - 1276
EP  - 1280
SN  - 2352-5401
UR  - https://doi.org/10.2991/meic-14.2014.287
DO  - 10.2991/meic-14.2014.287
ID  - Liu2014/11
ER  -