Date of Award
Doctor of Philosophy (PhD)
This dissertation is to examine the impact of the El Niño phenomenon on the international stock market, both at the aggregate level and the portfolio level.
In first essay, I study the predictive relation between the El Niño phenomenon and international stock market aggregate returns. I find that the El Niño anomaly can predict all 14 countries’ stock returns. Specifically, the El Niño unconditional effect can predict stock return negatively in Japan, Malaysia, and South Africa, while the El Niño conditional on winter season can predict positively stock returns in 13 countries’ stock markets except for Japan. This conditional effect is stronger in January and February than in December. These results are robust after controlling for investor sentiment, weather, and seasonal affective disorder effects. The implication of this study suggests that current asset pricing models are incomplete and need to incorporate a prominent role for the El Niño phenomenon.
In second essay, I study the predictive effects of the El Niño anomaly on returns of forty-nine US industries and portfolios formed based on many common strategies. I also examine the predictive effects of the El Niño anomaly on portfolio returns in ten other countries besides the US. For forty-nine US industries, the unconditional El Niño anomaly can predict eight industries’ portfolio returns; conditional on winter month, the El Niño anomaly can predict twenty-two industries’ portfolio returns. Overall, twenty-seven industries’ returns can be affected by the El Niño anomaly. For ten countries’ value premiums, the unconditional El Niño anomaly can predict three of them. Conditional on winter season (winter month), the El Niño anomaly can predict four (five) of them. Overall, seven countries’ value premiums can be affected by the El Niño anomaly. For ten US portfolio returns, unconditionally the El Niño anomaly can negatively predict return of portfolio formed based on cash flow/price ratio. Conditional on winter month, the El Niño anomaly can predict four portfolios’ returns. For six Japanese portfolios, conditional on winter month, the El Niño anomaly can predict five returns. Those findings remain robust using various different GARCH models.
Yang, Zhijun. "Essays on the El Niño Anomaly and Stock Return Predictability" (2017). Doctor of Philosophy (PhD), dissertation, Finance, Old Dominion University, https://digitalcommons.odu.edu/finance_etds/10
Available for download on Wednesday, March 25, 2020