This thesis attempts to model the returns on Regional Greenhouse Gas Initiative (RGGI) allowances using logged monthly returns from 2011-2018. This asset, shown to be a useful diversifier in portfolios, has been identified by previous literature to behave similarly to commodities. I used auto-regressive, GARCH, and Markov regime switching models to analyze the returns because the returns displayed changing volatility. These models were comparatively analyzed both in and out-of-sample. In this limited data analysis, the Markov model outperformed both alternatives in-sample. The Markov and Garch models displayed similar predictive power out-of-sample, however neither were particularly effective.
Identifer | oai:union.ndltd.org:CLAREMONT/oai:scholarship.claremont.edu:cmc_theses-3058 |
Date | 01 January 2019 |
Creators | Keneally, James |
Publisher | Scholarship @ Claremont |
Source Sets | Claremont Colleges |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | CMC Senior Theses |
Rights | @ 2018 James F Keneally, default |
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