An Empirical Study on Seasonal Effects in Stock Market
Yaxuan Wang
Co-Presenters: Individual Presentation
College: College of Business and Public Management
Major: Finance
Faculty Research Mentor: Huaibing Yu
Abstract:
This study explores the potential existence of seasonal effects in the stock market, particularly focusing on whether certain months or quarters consistently yield higher returns compared to others. Seasonal effects, such as the "January Effect" or year-end rallies, suggest that stock returns in specific months or periods could be systematically higher. By analyzing historical data from major stock indices, such as the S&P 500, over the past decade, the research will investigate whether stock prices tend to perform better in certain timeframes. The study will employ methods including descriptive statistics, t-tests, and regression analysis to assess the significance of any seasonal patterns. Descriptive statistics will be used to identify trends in returns for different months and seasons, while t-tests will determine if these returns significantly differ across time periods. Additionally, regression analysis will help control for other variables that may influence stock returns, allowing for a clearer understanding of the seasonal effects. The findings could provide valuable insights for investors looking to optimize their strategies by identifying periods of higher expected returns. If seasonal effects are identified, investors could adjust their portfolios to capitalize on these patterns, potentially enhancing overall returns by timing investments according to predictable seasonal trends.