Date of Award
2010
Publisher
North Dakota State University
Document Type
Master's Paper
Degree Awarded
Master of Science (MS)
Program
Statistics
Department
Statistics
College
Science and Mathematics
Faculty Advisor
Magel, Rhonda
Description
This study proposes two new cointegration tests that employ rank-based and least absolute deviation techniques to create a robust version of the Engle-Granger cointegration test. Critical values are generated through a Monte Carlo simulation over a range of error distributions, and the performance of the tests is then compared against the Engle-Granger and Johansen tests. The robust procedures underperform slightly for normally distributed error terms but outperform for fatter-tailed distributions. This characteristic suggests the robust tests are more appropriate for many applications where departures from normality are common. One particular example discussed here is statistical arbitrage, a stock trading strategy based on cointegration and mean reversion. In a simple example, the rank-based procedure produces additional profits over the Engle-Granger procedure.
Recommended Citation
Hanson, Thomas Alan, "Robust Tests for Cointegration with Application to Statistical Arbitrage Trading Strategies" (2010). Statistics. 102.
https://digitalcommons.ndsu.edu/stats/102
Rights
NDSU policy 190.6.2
Rights Link
https://www.ndsu.edu/fileadmin/policy/190.pdf
Handle Identifier
https://hdl.handle.net/10365/33719