| Autor: |
Dr. DAVID R. BOWES, Dr. JAY JOHNSON, Dr. MATTHEW ALFORD |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
International Journal of Social Sciences and Management Review. :60-69 |
| ISSN: |
2582-0176 |
| DOI: |
10.37602/ijssmr.2022.5405 |
| Popis: |
This paper uses a Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) model to estimate the effect of uncertainty surrounding U.S. congressional elections on the level and volatility of U.S. stock market returns from 2000-2008. Uncertainty in these elections is measured using asset prices from the Iowa Electronic Market (IEM), online, real money, and online futures market where payoffs are based on real-world events including U.S. elections. This research model uses IEM futures contracts based on the control of the U.S. Senate and/or House of Representatives by either of the two major political parties in the United States. The election futures market prices are used to measure the “closeness” of upcoming election outcomes. The model results indicate that the volatility of U.S. stock market returns in the S&P 500 index is increased by uncertainty regarding which political party will control the U.S. Congress after the results of upcoming elections. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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